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Journal ofCompetitiveness

A Comparative Analysis of the Competitiveness of the Readymade Garment Industry Clusters in Delhi, Dhaka and ColomboChoe, KyeongAe; Nazem, Nurul Islam; Roberts, Brian H.; Samarappuli, Nihal; Singh, Rajveer

Determinants of Competitiveness: A Study of the Indian Auto-component IndustryJoshi, Deepikaa; Rathore, Ajay Pal Singh; Sharma, Dipti

Multidimensional Networks: The Changing Character and Framework of Inter-firm CollaborationPloder, Michael; Steiner, Michael

When Policy Goes Cluster: Reflecting the European way(s)Rehfeld, Dieter

From Industrial Clusters to Global Knowledge HubsReve, Torger

Also featuringArticles from the IFC India City Competitiveness Report 2010

Papers and ideas presented at the 13th TCI Global Competitiveness Conference 2010

January 2011, Volume 1, Issue 1

Arturo, CondoProfessor of Competitiveness and StrategyINCAE, Costa Rica

Dharwadkar, RaviProfessor of ManagementMartin J. Whitman School of Manage-ment, USA

Doyle, EleanorSenior Lecturer in EconomicsUniversity College Cork, Ireland

Duffill, DavidDeputy DeanRobert Kennedy College, Switzerland

Elazar, BerkovitchDeanArison School of Business, Israel

Hergnyan, ManukProfessor, Strategic ManagementYerevan State University, Armenia

Kapoor, AmitProfessor of Strategy and Industrial EconomicsManagement Development Institute, India

Kini, RameshProfessor of Automation and Com-puter Science DepartmentKazakh British Technical University, Kazakhstan

Lall, AshishAssociate ProfessorLee Kuan Yew School of Public Policy, Singapore

Mishra, AbhishekProfessor of Business Policy and StrategyIndian Institute of Management-Ahmedabad, India

Prasad, AjitProfessor of StrategyInternational Management Institute, India

Rolfe, RobertProfessor of International BusinessMoore School of Business, USA

Steinbock, DanResearch Director of International ResearchIndia, China & America Institute, USA

Unger, Michael Associate professor of management and international businessSellinger School of Business and Management

Balaji, G.Senior Director, Fidelity Business Services India

Batra, AnuragMD and Editor-in-Chief, Exchange4-Media Group

Doyle, ChristopherMD, Dynamic Results IndiaFormer Country Manager, India, Economist Intelligence Unit

Ffowcs-Williams, IforCEO, Cluster Navigators

Jakhu, Ram S.Associate Professor, Institute of Air and Space Law, McGill University

Kapoor, AmitHonorary Chairman, Institute for CompetitivenessProfessor of Strategy and Industrial Economics, MDI

Ketels, ChristianPrincipal Associate, Institute for Strat-egy and Competitiveness, Harvard Business School

Muneer, M.Leading management consultant and author

Verma, SanjayExecutive Managing Director, South Asia, Cushman & Wakefield

Editorial Board Advisory Board, Institute for Competitiveness

enhancingprosperity

January 2011 Journal of Competitiveness 1

Journal of Competitiveness

January 2011Journal of Competitiveness2


Dear Readers,Competitiveness is a very important word, especially for countries like India that are transforming

rapidly and have the immense opportunity to prioritize productivity and inclusiveness in their growth strategy.

But the truth is that it’s not a very well-known word. Outside of the lecture halls and academic journals and perhaps select boardrooms, it’s an alien term for—not just the ‘lay’ person—but even entrepreneurs, policy makers and senior executives.

The Journal of Competitiveness brought out by the Institute for Competitiveness is an attempt to ad-dress various aspects of the subject, from both academic and non-academic perspectives.

This issue gives you the best of the 13th TCI Global Competitiveness Conference 2010, presenting five papers in their entirety. The papers, from researchers and cluster experts across the world, focus on the scenario in South Asia and the priorities for India’s clusters—particularly in the readymade garment and automobile industry. Additionally, the papers look at developing knowledge hubs, the framework of inter-firm collaboration, and lessons for shaping policies for clusters. Excerpts from the papers and ideas presented at the 13th TCI Global Competitiveness Conference 2010 are also included.

The journal also includes articles from the India City Competitiveness Report 2010, which is being released by the Institute for Competitiveness during this conference. These articles look at various aspects of how cities in India could improve their competitiveness in areas like governance, transportation, brand-ing and attracting investment.

It is our sincere hope that the ideas presented in the Journal of Competitiveness reach a wide and relevant audience of decision makers in corporations, as well as policy makers.

To submit your papers for double-blind review, email [email protected].

Editor’s notE


A CompArAtivE AnAlysis of thE CompEtitivEnEss of thE rEAdymAdE GArmEnt industry ClustErs in dElhi, dhAkA And Colombo1

Choe, KyeongAe2

Nazem, Nurul Islam3

Roberts, Brian H.4 Samarappuli, Nihal5

Singh, Rajveer6

The Asian Development Bank has recently com-pleted a project on City Cluster Economic Devel-opment (CCED) in South Asia, which examined the competitiveness of cities and industry clusters in Bangladesh, India and Sri Lanka. Part of the research involved an analysis of readymade gar-ment industry clusters in Delhi, Dhaka and Co-lombo. This paper describes new methodology techniques for analyzing the competitiveness of clusters, using a modification of the Porter Dia-mond Model. The study measures 39 attributes of competitiveness affecting the performance and development of three RMG industry clusters. The

1 The views expressed in this paper are those of the authors and do not reflect a position or are binding on the ADB and AusAID that supported the CCED project in South Asia

2 Urban Development Division, South Asia Department Asian Development Bank, Manila3 Centre for Urban Studies, Dhaka, Bangladesh4 University of Canberra, Australia 5 Board of Investment of Sri Lanka, Colombo6 Apex Clusters, Delhi, India

paper, which is a part of the CCED research proj-ect, has involved one of the most in-depth analyses conducted in the competitiveness industry clusters in South Asia. The analytical methodology proved to be useful for strategizing identified strategic opportunities for interventions by the government and cluster stakeholders to enhance the competi-tiveness of the readymade garment industries in the three countries.

Keywords: Readymade garment industry, Competi-tiveness, Industry clusters, Bangladesh, India, Sri Lanka

ABSTRACT


introduCtionThe readymade garment (RMG) industry is one of the world’s largest industries. Global production of garments in 2009 exceeded 17 million tons, with exports worth more than US$ 300 billion. The RMG industry is labor-intensive and a very large generator of employment globally. Most of the la-bor force is women, who work in large factories or micro enterprises for very low wages. Asian countries dominate the production of textiles and RMGs. The industry is a major source of export income for countries like Bangladesh, China, India, Indonesia and Sri Lanka. It is a highly competitive industry, driven by keeping labor, transportation, materials and utility costs low. Industry margins at the factory floor production level are low; so that firms engaged in manufacturing and retail of cloth-ing and apparel products are constantly seeking ways to keep costs down to maintain a competitive business edge.

The high dependence countries like Bangladesh and Sri Lanka have on textile and RMG exports makes them especially vulnerable to changes in ex-change rates, raw material costs, technology im-provements and buyer markets. The recent global financial crisis has had a significant impact on the RMG industry, causing cut backs in production and the loss of a large number of jobs in many coun-tries. There is growing concern by western con-sumers also about the environmental impacts and labor conditions in footwear, clothing and textile factories in developing countries. These factors are putting pressure on manufacturers of garments and textiles to change the way RMG products are pro-duced to tailor for the changing demands of export markets in the future.

The growing pressure on firms and small busi-nesses in the RMG industry to enhance their Com-petitiveness to maintain market share is leading many countries to explore ways that governments and business can work more closely together to re-duce transaction costs. Business, in particular, is looking constantly for ways to reduce transactions costs. Most do this by focusing on achieving greater efficiencies within internal production and distri-bution systems—especially along internal supply

chains. However, firms are less able to reduce ex-ternal transaction costs of commonly-shared fa-cilities and services, such as water and transport facilities.

For more than two decades governments and business have been focused on ways to improve competitive advantage in cities and regions. Much of Michael Porter’s work since the Competitive-ness of Nations (Porter, 1990) was published has focused on ways to enhance the competitiveness of business in cities and regions (Porter, 2000). This has led to a growing interest by governments and business on ways to foster the development of industry clusters, which are seen as a way to en-hance the Competitiveness of local economies and increase production. Clusters developed by rival firms and suppliers collocating and collaborating on ways to reduce external transaction costs, in-novate and develop new business opportunities and markets that support the development of new busi-ness and investment in local economies and the growth of exports.

The initial focus on the development of clusters sought to examine ways firms can pursue and cre-ate competitive advantage. However, over time, there has been a significant shift from the initial focus on competitive advantage (which focused on improving organizational efficiencies) to collabora-tive advantage (Tapscott and Williams, 2006). This development of industry clusters as a way to en-hance the competitiveness of local economies lead to an interest and new ideas on how to use clus-tering as a means of reducing external transaction costs to business and government. The new focus on clusters involves rival firms and suppliers and gov-ernments cooperating and collaborating on ways to reduce external rather than internal transaction costs, innovate, and develop new business opportu-nities and markets.

The Asian Development Bank has recently com-pleted a project on City Cluster Economic Devel-opment (CCED) in South Asia (Roberts and Choe, (forthcoming 2010)). CCED involves a seven step process that is used to evaluate the competitiveness of cities and industry clusters, and to develop plans for investment in projects and programs to develop


a plan to build-up strategic architecture (Hamel and Prahalad, 1994, Roberts and Stimson, 1998), which is used to support the development and more efficient operation of local economies. Part of the CCED research project involved an analysis of the RMG industry clusters in Delhi, Dhaka and Co-lombo. Strategic architecture includes endowed resources, human capital, business dynamics and enabling environments. The competitiveness of these things is important to the development of lo-cal economies and clusters.

An important element of strategic architecture is the creation of catalysts. These take different forms including networks, civic entrepreneurs, fa-cilities and incentives. Catalysts are responsible for driving business effort, innovation and investment attraction in local economies and clusters. Once projects and programs needed to develop strategic architecture to support clusters have been identi-fied, there is need to establish a cluster develop-ment pathway and mechanisms to build critical elements of strategic architecture. This includes the financial mechanisms and organizational gov-ernance arrangements to deliver on these.

The paper commences with a brief description of the methodology used for cluster analysis de-veloped by the CCED project, and provides some insights on the policy implications this has had on the development of clusters. A comparative analy-sis of 13 key Competitiveness indicators derived from a measure of the 39 competitiveness attri-butes in the RMG industry clusters in Colombo, Delhi and Dhaka is presented. The results show significant differences between the competitive at-tributes for each cluster. An explanation is given for some of these differences. The findings have enabled the identification of strategic opportuni-ties for interventions by government and cluster stakeholders to improve the competitiveness and performance of the readymade garment industries in each country. The research has involved one of the most in-depth analyses ever undertaken to compare the competitiveness of three RMG indus-try clusters in South Asia. Some of the insights gained from the comparison study are presented in the conclusion to the paper.

mEthodoloGy usEd to EvAl-uAtE thE CompEtitivEnEss of rGm ClustErsMany techniques have been developed to study and analyze the structure of clusters. Marshall (1929, 1920) and Weber (1929) studied spatial agglom-eration of economic activities in national econo-mies during the early 20th century. One of the ear-liest studies on clusters was of the New York hotel industry in the 1890s, which demonstrated the benefits and spin-offs of competitive businesses co-locating (Baum and Haveman, 1997, Weber, 1929). Co-location of hotels led to the local devel-opment of smaller service businesses, restaurants, bars and shops that serviced hotel customers. The synergy created by the mix of land-use activities enhanced competition between suppliers, and ex-panded the range and choice of accommodation services.

Porter Model of Cluster AnalysisMichael Porter (1980) began to explore techniques to map and analyze industrial structures and com-petitors, and using the information derived from his research on strategies firms use to achieve a competitive advantage. This research revealed four forces driving industrial competitiveness—potential entrants, buyers, suppliers and industry competitors. This resulted in the concept of inter-nal and external environmental analysis. In Por-ter’s model, environment dealt exclusively with the economic and business environment given his realization that the study of firms and industries was insufficient to explain competitive advantage. This led to further research on the competitiveness of global industries (Porter 1985) and of nations (Porter 1990).

Porter’s Competitive Advantage of Nations (1990) introduces his diamond model of competi-tiveness. The model has the following four broad drivers that shape the environment in which firms and regions compete for business: n factor conditions, which include the skills, re-sources, technology, and infrastructure necessary to create competition in a given industry or cluster;


n demand conditions, which include the nature of local and overseas demand for industry products and services;n related and supporting industries, where the presence or absence of suppliers and distributors in support of industry sectors or clusters will deter-mine competitiveness;n firm strategy, structure, and rivalry, which re-late to conditions in a nation governing how com-panies are created, organized, and managed and the nature of domestic rivalry.

Porter identified two other important factors that affect competitive advantage of firms: chance and the role of government. Chance relates to events or occurrences that have little to do with a country’s circumstances, but can be influenced by individuals, such as the decision by Bill gates to locate Microsoft’s in Seattle. Governments can have significant role in aiding competitive advan-tage, especially through public policies which are favorable to investment and profit performance. Porter identifies the importance of clustering com-petitive industries to create rivalry and stimulate innovation.

Porter (1990) has had an important influence on strategic thinking for business and economic development. While his early work was extensive-ly concerned with the competitiveness of nations, many of the case studies provide an insight into the competitiveness of regions. Other researchers have used Porter’s model to analyze the competitive advantage of regions for manufacturing (O’malley and Egeraa, 2000), trade services (Daly and Rob-erts, 1998), film (Assmo, 2005), food (Neven and Dröge, 2001), and education (Curran, 2001). Still other researchers have developed new qualitative and quantitative methods for exploring and evalu-ating the competitiveness of clusters in cities and regions (Enright et al, 1996, Brown, 1996). In-deed, the study of industry clusters has become a discipline in itself.

Cluster Structure and Supply Chain MappingCluster mapping, seeks to translate statistical data and information gained from the above types of analysis into a map the structure and supply chains

of a cluster. These cluster maps can be very com-plex. The intent of cluster mapping is to identify significant spatial concentrations of employment and business activities, financial and related trans-actions that occur between businesses and support industries in the same locality. The process begins by assessing the spatial concentration of industries by SIC category input-output (I/O) analysis. A good example of this technique was used by Feser and Bergman’s (2000) to study clusters in the North Carolina economy. Cluster mapping also uses loca-tion quotient (LQ) analysis to identify the level of concentration or intensity of business activities in a location. I/O tables help define the transaction relationships between different types of industries in a cluster supply chain.

Certain types of firms make up the core of a cluster. Core industries might include several food processing factories which form the core of a food cluster or a steel mill for a metals cluster. LQs for these industries are likely to be high. Other firms lo-cate close to and service the cluster’s core firms. In Porter’s (1990) model, these are the suppliers or re-lated supporting industries. Where LQs for non-core industries are relatively high, greater than 5, this could indicate a relatively mature and large cluster.

Cluster maps also provide useful spatial plan-ning information about the scale and the mag-nitude of agglomeration occurring in a cluster. Spatial plans can be designed to encourage the co-location of supporting industries and improve logistics facilities needed to transport goods and services and other products to and from the cluster, or within a metropolitan region where a cluster is poly-centered; that is, not confined to one area of the city. The mapping provides important informa-tion for more detailed analysis of how the cluster functions, and the competitiveness of the different factors that support its operation and development. Once analysts have mapped a cluster, the next step is to analyze the competitiveness of pertinent clus-ter elements.

Cluster Attribute Competitive AnalysisPorter’s (1990) Diamond Model is one of the most widely used techniques for cluster analysis. It in-


volves analysts working with industry focus groups to score the relative strengths of the attributes of competitiveness within a cluster. The Diamond Model has its weaknesses in that it does not provide a spatial dimension to cluster analysis, but it has provided a useful framework for strategic thinking about local economic development and has been widely applied in many countries to analyze clus-ters. The model can be used to identify and analyze the interaction of factors that underlie local com-petitiveness and to formulate strategy for regional economic and industry cluster development based on identified elements of competitive advantage.

The CCED methodology used to conduct the cluster analysis of the RMG industry in Colombo, Delhi and Dhaka, seeks to measure 39 attributes of competitiveness that are grouped under the five driving factors in the Porter model: factor condi-tions; demand conditions; related and supporting industries; firm strategy, structure, and rivalry; and the role of government. The chance factor is removed as it is not easy to measure as a factor of competitiveness. Table 1 shows 13 primary attri-butes of cluster competitiveness related to the five driver factors measured as part of the research. These are an aggregation of the 39 indicators un-dertaken for simplicity of presentation in the pa-per. The 39 attributes of competitiveness are as-sociated with six elements of strategic architecture explained earlier that support the development of regional economies and clusters. Using an ordinal ranking semi-qualitative scoring method based on numeral scale of 0–5 (see Table 1) it is possible to measure the relative competitiveness of each at-tribute. The scoring of attributes is done using a modified Delhi technique (Bordecki, 1984) where an industry focus group comprising 10-15 business leaders and other knowledgeable experts (all to-gether known as a cluster working group) score the current and estimated future level of competitive-ness needed for each of the 39 attributes to make a cluster competitive.

The scores recorded for each attribute by the industry cluster focus group assessors are summed and averaged. Following discussion by the group members, scores may be adjusted until a final

agreed score for the Competitiveness attribute is agreed upon. The scores for all the attributes are averaged to arrive at an overall Competitiveness score for the cluster. An average attribute competi-tiveness score greater than 3.75 suggests combined attributes supporting the cluster are very strong, well-developed and internationally competitive; a score around 3.00 suggests a relatively strong, na-tionally competitive cluster; while a score between 2.5 indicates a small, emerging, sub-national strength cluster. A score of 2 or less suggests that the cluster is relatively weak and only competing for business in local markets or is a newly emerg-ing cluster.

Cluster Competitiveness Deficiency (Gap) AnalysisThe second part of the competitiveness analysis is to assess competitiveness gaps of attributes; that is, the difference between the current and future level of competitiveness attributes necessary to develop the elements of strategic architecture sup-porting the development of the cluster competitive. Where there are significant differences or gaps, for

Competitiveness Elements Of Cluster Indicators Competitiveness

Score 0-5Factor ConditionsLabor 4 3.1Infrastructure 4 3.75Resources 3 2Social Environment 2 2.75Demand ConditionsMarkets 2 3.2New Products 2 3.8Business Environment 4 2.3Firm Strategy Structure And RivalryStructure 2 4Collaboration 5 4.1Technology Orientation 1 4Related Supporting IndustriesSupply Chains 3 3.5Value Adding 2 3.8GovernmentEnabling Environment 5 3.9Source: Roberts And Choe, (Forthcoming 2010)

Table 1: Attributes Of Competitiveness Related To Five Factors In The Porter Diamond Model


Table 2 Sample of Competitive Attributes of Clusters Using Porter’s Diamond Model

Demand Conditions Current Status Future Competitiveness Requirements Gap Actions

Markets

Expanding Domestic And Local Markets 2.75 3.75 - 1 Sufficient Market Intelligence

Expanding Export Markets 2 4 - 2 Collaborative Marketing

New Products

Demand Expansion Capacity For New Products 2 4 - 2 New Technologies

Responsiveness To Change And Innovativeness 2 3 - 1 Change Anagement

Source: Roberts And Choe, (Forthcoming 2010)

example a factor of 2, this suggests there may be need for strong intervention by government and in-dustry stakeholders to lift the level of the selected attributes of competitiveness to raise the overall competitiveness and economic performance of the cluster.

Table 2 shows an example of how two primary competitive attributes of the cluster might be as-sessed. For example, a growing cluster seeking to expand into national or international markets might score 2.75 on overall current competitive-ness, but it would need to lift its overall index score to 3.00 to succeed nationally and 3.75 internation-ally. The cluster’s competitiveness index would need to improve by 0.25, or 9%, to become a successful national cluster, and 1 or 36% to be internationally competitive. Actions to strengthen weak competi-tiveness attributes would need to be identified. Pos-sible actions for enhancing the competitiveness of marketing and new products attributes are shown in the final column of the table. The analysis may also include references to other sources of informa-tion that may be relevant to the analysis.

The competitiveness deficiency-gap analysis provides a qualitative measure of the strengths and weaknesses of attributes of strategic architecture, as well as potential threats and opportunities fac-ing the development of a cluster. The value of the analysis is that it enables a cluster working group responsible for preparing a plan to develop a clus-

ter to identify possible projects and programs that should be considered in a cluster development busi-ness plan and action plan.

AnAlysis of rmG industriEs in Colombo, dElhi And dhAkAUsing the above techniques, the CCED investiga-tion teams in each country began a detailed analy-sis of nine industry clusters in Colombo, Delhi and Dhaka. The RMG industry was a common cluster investigated in each country. The following pres-ents a summary of the competitiveness analysis conducted for the three RMG clusters.

Colombo RMG Clusters RMG and textiles is Sri Lanka’s largest export sector generating US$3.2 billion in exports in 2009, equiv-alent to 46% of the country’s total export earnings. Most RMG are exported to Europe and the United States. The Colombo Metropolitan Region (CMR) is the centre of the RMG industry in Sri Lanka and is a world-class RMG manufacturing cluster. The cluster provides direct employment for more than 300,000 people (33% of manufacturing sector employment) and indirect employment for a 1 million people. Di-rect foreign investment in the RMG industry at the end of 2007 exceeded US$ 700 million, of which the CMR accounted for US$ 280 million.


Current Conditions The RMG cluster in the CMR has a significant presence of manufacturing units engaged in core industries. The core of the cluster has more than 500 apparel manufacturers. The cluster is backed by a proactive industry association, the Joint Ap-parel Association Forum, made up of representa-tives from key stakeholders in the industry. The CMR also has a good network of transportation in-frastructure supported by export and logistics com-panies. The CMR RMG cluster has well established forward and horizontal supplier firms producing textiles and garment accessories such as buttons, elastic, labels and packaging materials. However, the highest value-added components, including equipment suppliers, designers and retailers, are largely absent. Figure 1 presents the apparel clus-ter map constructed by the RMG industry focus group for the CCED project.

Mapping the RMG supply chain was undertak-en and provide an important understanding of the clusters production systems, the value-adding ele-ments associated with this and the linkages to other supporting industries and services. The textile and apparel industry’s supply chain shows that the in-dustry cluster has extensive backward linkages that have a strong multiplier effect on employment and production. Figure 2 presents the apparel cluster

map constructed by the RMG industry focus group for the CCED project.

The emerging IT cluster in the CMR has im-proved the supply chain management and local financial institutional capacity supporting the clus-ter. Much of the equipment necessary for produc-ing garments is imported mostly from Germany and Italy. The demand for this equipment is not sufficient to encourage manufacturing of machin-ery under license to replace the need for imports of machinery. The cluster is supported by a small number of exporting and logistics companies along with relatively good supporting infrastructure such as transportation and utility firms. Universities and vocational schools with design and production cur-ricula support the cluster, but as foreign retailers design most products, and more than 85% of out-put is exported, Sri Lanka has few designers and retailers. As a result, the cluster has not been able to gain access to international media, promotion and advertising, including fashion shows. This has a significant negative impact on the cluster’s abil-ity to move toward higher value-added activities.

Competitiveness Analysis of the Apparel Clus-ter in ColomboFigure 2 shows the analysis of the competitive-ness factors in the apparel industry cluster using the Porter Diamond Model and scaling systems

described above. These factors were identified by a cluster focus group for the five driving fac-tors (See Figure 3). The cluster is positioned in the right market, including high-end products, but many of the activities associated with the cluster are low value-added activities such as cut-and-make garments. Thus, the cluster effectively participates in only 10% of the value chain process. The challenge is to shift into high value-added activities such as design, marketing and sales. This is difficult because of the global structure of the RMG industry

IndustryA i ti

Fig 1 Apparel Industry Cluster Map, CMR

Source: (ADB, 2010) IT = information technology.


Highly competent workforce

Good quality telecommunication services

Good Quality of raw materials

Good workplace conditions

High cost of Electricity Poor quality of

infrastructure logistics Poor education/training

facilities Poor quality of living

conditions for workforce

International repute as a reliable supplier of quality products

High level of business ethics (‘Garments without Guilt’)

Emphasis on change

Small domestic market Narrow Export base Undue competition due to lack

of preferential market access Slow responsiveness and

innovativeness to change Lack of demand expansion

capacity for new products Lack of readiness to face risks Less emphasis/success on

product branding (brand management)

350 + existing firms competing without Government protection

Presence of reputed international firms Presence of strong business associations (JAAF)

Proactive at National / International level Involvement in CSR activities

Low level of knowledge sharing Low level of Technology application in firms

Usage of automated design / software Emerging accessories cluster

Lack of business development

services Low response time and low quality of local support services

Firms inability to exploit value adding potential

Government – Policy & Support

Lack of long-term plans for apparel industry development

Lack of government support for industry development (eg. R&D)

Lack of enforcement of business regulations (VAT refunds)

Relatively rigid labour regulations Not enough marketing of the

industry

Fig 2 Apparel Industry Cluster Analyses

R&D = research and development.

Source: ADB, 2010

where these activities tend to be dominated by de-sign houses and global corporation.

Figure 3 shows the assessment of the five driv-ers of competitiveness in the Colombo RMG clus-ter. Factor and demand conditions are relatively strong, as is firm strategy and rivalry and related supporting industries; however, government support is weak. The overall competitiveness of the cluster is 2.68, which is below 3.25 considered necessary to remain competitive in international markets. While the RMG industry is growing, it appears to be los-ing market share to its competitors especially from China and other SE Asian countries.

Delhi RMG ClusterMore than 600,000 people are employed in the Delhi garment and textile industries. The New Delhi National Capital Region (NCR) has one of the larg-est concentrations of RMG industry employment in India. The NCR produces 40% of India’s ready-made garment exports and is the leading RMG cluster in the country. Most of the garment firms in the NCR are located in the Okhla Industrial Area, in the southeast part of New Delhi. The industrial area is responsible for 40% of RMG manufactured

goods in the NCR. More than 4,000 factories are located in this industrial area, which is one of the largest in the country. The other major production center in NCR is in Gurgaon, in the southwest.

Current Conditions The RMG cluster is very dependent on export or-ders for its development. The cluster accounts for 16% of total apparel exports from India. There are about 50 large export houses situated in Okhla that are responsible for most of the clusters exports. With the presence of international brands, exports go primarily to the European Union countries, Can-ada and the United States. Exports are mainly fo-cused on clothing and discount chain markets, and not high-priced garments. The key features of the cluster include the following: (i) firms face difficul-ties in accessing supplier services, education and training facilities, and product improvement ser-vices and in building brands; (ii) stakeholders have low levels of awareness of policy matters, govern-ment issues, and export procedures; and (iii) firms tend to use traditional, outdated practices and have low social capital and a lack of expertise that could help units solve production-related problems.


Competitiveness Analysis of the Delhi RMG ClusterAn assessment of the competi-tiveness of the cluster was under-taken by an industry focus group using the CCED techniques de-scribed earlier. The following briefly describes the analysis of the drivers of competitiveness us-ing the Porter model. The results of the analysis are shown in fig-ure 4. The strengths of the clus-ter include a trained workforce, good supporting clusters and preferential access to the Euro-pean Union market. Weaknesses include the low levels of branding and marketing. Significant entre-preneurial activity is apparent in this small but rap-idly growing sector, but moving the whole cluster in this direction will require higher levels of coor-dination between education institutions, firms and the government. The conditions prevailing in this cluster are poor and their competitiveness scores range from 1.25 to 3.66. Of the 39 competitiveness attributes, 72% have an average score of less than 2.5 (scores of 3 are necessary for a driver or at-tribute to be considered nationally competitive). To compete at the international level, the conditions in RMG cluster needs to be improved to at least 3.75 to make the cluster more competitive.

The following describes briefly the analysis of the drivers of Competitiveness using the Porter model.

Factor Conditions Production resources for the RMG industry include raw materials suppliers, machinery tools suppliers, fabric processors, and packing materials suppliers. Suppliers in the cluster are close to their markets and the SMEs in the cluster have easy and cost-effective access to a wide range of services. Criti-cal to the growth and development of the cluster has been the availability of cheap labor due to the migrant population from Bihar and Uttar Pradesh. These workers gain entry to the trade by working in factories with little formal training. The NCR

has a number of established education and ICT in-stitutions that act as a catalyst for enriching the cluster’s human capital base. This has had a posi-tive spin-off to the region, but the impact on the RMG industry has been less than other sectors of the economy.

The cluster firms have access to railways, roads and airports, including an international container at the Okhla industrial area; however, the condition of infrastructure and reliability of utility services is poor. Internal public transport facilities are not available, which makes it difficult for workers to get to and from places of work. The condition of water supply, solid waste management and electric-ity supply is poor, but the latter has improved some-what, but further improvement is needed to ensure an uninterrupted 24-hour power supply to firms in the cluster. This has a disruptive impact on produc-tion costs and efficiencies. In many cases, factories are duplicating public services in order to maintain production. This represents significant sunk costs to businesses for the provision of services that are used when supply of water or electricity is disrupt-ed or not available.

Demand Conditions The RMG cluster is solely dependent on orders for manufacturing. The cluster accounts for 16% of to-

Fig 3: Analysis of the Competitiveness of the RMG Cluster, Colombo

Source: ADB, 2010


Fig 4: Analysis of the Competitiveness of the RMG Cluster, Okhla, Delhi

Source: NIUA, 2010

tal apparel exports from India. There are about 50 large export houses situated in Okhla, which are responsible for most of the clusters exports. With the presence of international brands, exports go primarily to the European Union countries, Canada and the United States. Exports are mainly focused on clothing and discount chain markets, and not high-priced garments.

Related and Supporting IndustriesSupplementary industries and activities that sup-port the RMG cluster include: merchants; traders; manufacturers of fabric, thread, buttons, and fit-tings; processing units; buying houses; exporters; fabricators; machine embroiderers; and machin-ery suppliers. The supply chain structure is well developed, with a very large number of micro en-terprises. The industry experiences a problem of high rejection rates, indicating a quality assurance problem within the supply chain network. The cur-rent situation in the RMG cluster is that few of the competitiveness attributes are good or excellent.

Firm Strategy and RivalryMost garment manufacturing units in the clus-ter are small and family-owned, with the owner and other family members taking on the roles of manager, purchaser, marketer, negotiator, qual-ity controller and finance controller. As a result, few professionally-qualified people are recruited to those roles with the exception of a few people with diplomas holders in merchandising. However,

large firms and export houses do recruit technically- and com-mercially-qualified employees for production, inventory control and design work. There is need for a wide range of support programs involving education and training.

The key features of the cluster that emerged from the evalua-tion included the following: (i) firms face difficulties in access-ing supplier services, education and training facilities, and prod-uct improvement services and in

building brands; (ii) stakeholders have low levels of awareness of policy matters, government issues and export procedures; and (iii) firms tend to use traditional, outdated practices and have low social capital and a lack of expertise that could help units solve production-related problems.

The cluster’s strength lies in production flexibil-ity, opportunities to expand the domestic market and capacity to expand into new products. Low in-vestment, entry barrier requirements, easy and cost effective access to a wide range of services, abun-dant availability of raw materials and easy avail-ability of cheap labor need to be harnessed in the right manner to open up markets at all levels, and give a fair share of reward to all the stakeholders.

Dhaka RMG IndustryThe RMG industry in Dhaka has been the lead-ing export sector industry in Bangladesh for more than 15 years. In 2007 there were almost 4,500 registered (and many unregistered) garment fac-tories in Bangladesh, employing about 2.4 million people. More than 1.2 million people are employed in the industry in Dhaka. More than 60% of fac-tories were located in Dhaka, 8% in Narayanganj and 17% in Gajipur (BGMEA 2008). The gar-ments industry in Bangladesh is mostly export-oriented. The geographical concentration of fac-tories in these districts gave them advantages in terms of access to skilled labor, lower transpor-tation and other business transaction costs. This sector has gained comparative advantage due to


the large pool of low cost labor and low transpor-tation costs due to co-location of industrial estab-lishments and some supporting government poli-cies. The government of Bangladesh has identified this sector as one of the ‘thrust sectors’ of growth of the economy and has provided significant sup-port to its development.

Current Conditions The development of the RMG industry in Bangla-desh is encouraged and supported by the govern-ment since the mid-1980s. The backward link-age supply industries grew rapidly in response to a demand for material and fabricated products. Many of this lower order supply chain industries became scattered around the region because sup-pliers could not afford rents on properties close to the main producers and the very low profit margins in micro or family-run enterprises. As a result, the supply chain distribution structure became widely dispersed, and this resulted in inefficiencies and high local transaction costs in the industry sector.

Many of the factory buildings in the city centre are multi-storey and not well designed to accom-modate expansion or ensure efficient production. Many of the supporting industries are located close to the main production houses; however, the inten-sity of development in these areas has added to the traffic congestion problem and over taxed many of the utility services. It is for this reason that many factories that have undergone expansion have re-located to areas where there is more land for ex-pansion and vertical (same level) integration into production systems. Despite these disadvantages, many have well-established family businesses that have expanded operations elsewhere in the region, and continue to maintain premises in the inner city, partly because of the availability of skilled work-force that continues to reside in this area.

Cluster Structure MapFigure 5 is a map showing the structure of the RMG industry cluster in DCR. The five core industries that make up the cluster are textiles, knitwear, woolen

Fig 5: Forward-Backward Linkage Map Showing the Structure of the Dhaka RMG Cluster

Source: (CUS, 2010)


textiles, jute textiles and handlooms. The backward and forward linkages supporting the industry clus-ter are government on policy and strategy matters, as well as utility services, industry association and interest groups, education establishments, labor unions, national market and international R&D/design linkages. Many components of the clusters are poorly developed, inefficient or missing. As a result, the cluster is not functioning efficiently and this will continue to undermine its competitiveness in the face of competition from other Asian RMG centers especially China.

There are many problems associated with the operations of the RMG industry cluster. Most large firms have purchased backup utility systems (power generation, water supply, steam supply and ETP) to overcome continuous disruptions to public agency provision of services. The large labor force and mid-level technical/management staff are often not sufficiently skilled to take on greater responsibili-ties or are technologically literate. There is a heavy reliance upon foreign skilled man power to do tasks that could easily be done by trained Bangladeshis, provided there were facilities to do so. While tele-communication have improved, transport services, congestion and logistics management are becom-ing worse, thereby adding to the transaction costs of business. Quality assurance on many projects is weak, leading to high rejection rates on export products.

Supply Chain MappingFigure 6 shows the nature of the vertical supply chain for the textile and RMG Industry in DCR. There are over nine stages in the supply chain for some products produced by firms in the cluster. Each stage offers opportunity to add value to products, especially by horizontal integration of design and marketing services. Mapping the RMG supply chain was important in aiding industry un-derstanding of the production systems operating within the cluster, the value-adding elements of the cluster and the linkages to supporting supply industries and services. The textile and apparel industry’s supply chain has extensive backward linkages that have a strong multiplier effect on employment and raw material supply.

Overall Competitiveness Figure 7 shows the overall completeness of the five driving factors affecting the competitiveness of the cluster. Overall, the competitiveness of the cluster is weak and in need of improvement. Demand condi-tions are most favorable in the cluster, as most of the products are low-priced exports destined for dis-count or lower-priced stores in developed economies. The weakest position is government support. Much of this has to do with the need for industry reforms and removal of many unnecessary restrictions on the operations of the industry, and in the provision of essential infrastructure and services. Factor condi-

Fiber

Natural Fibers:1 .Cotton2.Jute Fibers

ManMadeFibers

SyntheticFibers

1 .Wool2.Silk

Ginning

Spinning

Dyeing

Y arn

Knitting

Weaving

Cloth

ReadymadeGarments

Export

LocalMarket

Lining, Button,Zip and otheraccessories

Fig 6: Nine Stages of Supply Chain for Textile and Readymade Garments Industry, Dhaka

Source: Authors (forthcoming 2010)


tions, firm strategy and rivalry and supporting in-dustries are not internationally competitive.

Factor ConditionsParticipants in the initial industry stakeholder meet-ing for the RMG industry cluster identified a number of labor problems that were affecting the effective-ness and efficiency of the sector. There is lack of adequate education and training facilities and insuf-ficient skilled manpower to improve the competitive-ness and performance of the RMG sector. The only specialized education institution serving the sector is the College of Textile Engineering and Technology. Some educational institutions offer degree courses for fashion technology, merchandising, supply chain management, etc., but the greatest need is for edu-cation and training facilities to upgrade technical skills and quality enhancement programs. This is a significant factor affecting the poor floor quality of finished goods and high rejection rates in the RMG industry in DCR.

Utility services supporting the RMG industry were identified as being poor and unreliable. The DCR LGUs also need to improve the delivery and quality of utility services, especially in areas where the concentration of industrial units is high. Indus-try focus group participants also identified problems with proximity and access to raw materials. This indicates the need for government and industry to

work together to make a greater effort to improve the quantity and quality of raw materials supply and delivery systems to support the bottom-end of the supply chain.

Conditions for employees working in RMG facto-ries are generally poor, due to low wages, high rents and overcrowded housing, along with poor access to basic health and social services. Work place safety and health conditions in factories are poor and, in some cases, dangerous. These factors impact on workplace productivity and stoppages due to acci-dents. Many of these costs are considered externali-ties and not the responsibility of business; however, they have a significant impact on the overall produc-tivity of the sector.

Demand ConditionsMarket conditions for the RMG industry are highly competitive for exporting firms, but the domestic market is very weak. There is the realization by many companies that international markets are go-ing to become more difficult to access and that ex-pansion into the domestic markets will be important if the industry is to grow. However, the capacity of the domestic market to expand is constrained, as most of the population has little excess disposable income to spend on clothing. However, demand elas-ticity for cheap cloth is low, thus, making the sector less vulnerable to international business risk associ-

Fig 7: Analysis of the Competitiveness Drivers of the RMG Cluster, Dhaka



ated with raw material prices. The market will have to be developed for budget and a few niche product lines of clothes and dress wear. The capacity of the sector to develop new products is relatively weak, as is the capacity to respond to change and innovate. The ability to develop new products and change pro-duction line processes will be important if the cluster is to maintain and develop its export market share and develop domestic market opportunities.

The dynamics of the business environment is rela-tively strong and quality and reliability of product is high, because firms have to compete in international markets. Entrepreneurs in this sector are generally across the need for post sales and product support, as this is important for quality assurance and prod-uct reputation in dealing with foreign buyers. The RMG sector in Bangladesh seems capable of dealing with international business risks, but still needs to improve the level of business ethics and risk man-agement. Despite the current global recession, the RMG sector in Bangladesh shows a moderate level of growth, which suggests they are experienced enough to deal with the problems this has created globally for the industry. Demand elasticity for cheap cloth is low, thus, making the cluster less vulnerable to inter-national business risk associated with rapid fluctua-tions in raw material prices. A significant demand factor that will affect the industry in future will be the pressure place upon the industries to be more carbon neutral. This will be a major challenge for the RMG industry, as it will significantly affect costs, and likely put a downward pressure on wages.

Firm Strategy and Rivalry The RMG industry is dominated by local firms. There are few joint ventures or foreign firms engaged in the in the Dhaka RGM cluster. Foreign firm inter-ests tend to Taiwanese and Korean. There is need for the industry to expand its engagement with foreign firms to speed up the rate of technology transfer, to adopt more modern management practices and to use the purchasing power of foreign firms to gain access to new and expanded markets. There is need also to improve the flexibility and integration of production systems. While many firms are entre-preneurial, there is rigidity to change and most do

not have the capital to invest in new technologies or way to respond to rapidly changing market de-mands. Investment in the textile and clothing sector could generate more wealth for the country, but the government will need to take steps to reform foreign investment policy and tariffs if it wants to attract foreign investment and modernize productions sys-tems in the sector.

The practice of knowledge sharing and collabora-tion within the firms is new for most businesses op-erating in the RMG industry sector in Bangladesh. So is the level of technological diffusion along supply chains. The industry, as a whole, has not realized that collaboration is necessary to take advantage of economies of scale, and to overcome the treats from more capital-intensive production systems that are driving down production costs in other parts of Asia. Firms could share the experience of knowledge on market condition or new technology. Initiatives to encourage the practice of knowledge sharing will be an important step in enhancing a more collabora-tive approach to competition and production in the sector.

Finally, the uptake of modern technology in the RMG sector is not high. Bangladesh has an abun-dance of unskilled labor, and many firms are pre-pared to force down labor costs in order to remain competitive. Many firms don’t realize that forcing down labor costs often leads to lower productiv-ity. Higher salaries, up-skilling of workers and the introduction of more modern technologies lead to increased productivity and higher returns on capi-tal. The application of new technologies has been frustrated by labor laws and practices that prevent the adoption of new technologies. The slow uptake in new technology is a significant constraint on the development and competitiveness of the sector.

Related and Supporting Industries The research found many firms were not satisfied with the performance of supporting services, espe-cially government services that are very slow and prone to rent seeking. Modern industries are in-creasingly dependent on high quality information, regulation, financial and legal services to maintain competitiveness. These support services are weak or


are lacking in the cluster, and it is one of the most significant constraints on its development.

The value adding potential in the sector is high, but opportunities to expand and develop supply chain industries are undermined by poor knowledge, lack of government policy and support for innovation, research and development. Most firms do not know how to value add, sticking to traditional production systems and practices that are rapidly becoming out-dated. Education programs to encourage innovation and risk management of product development are necessary.

GovernmentFirms in the clothing & textile sector expect a lot of support from the government. This is partly be-cause industrialization in Bangladesh began under socialist policies that tended to protect and support firms from competition. There is no coherent policy for supporting the development of the RMG cluster at this time. Private sector investment in R&D is negligible. The RMG industry is the ‘thrust sector’ for the economy, and they do get some tax benefit support from the government; however, there is the need for long-term business development policy, in-stitutional reforms, tax breaks for R&D and venture capital formation and low interest loans that are necessary to enhance the performance of the sector. The government must also take a leading role in the development of strategic public infrastructure, such industrial estate and infrastructure development, and land banking to ensure the industry can grow and develop sustainably.

CompArison of thE Com-pEtitivEnEss of rmG Clus-tErs in dhAkA, Colombo And dElhiAn analysis of the attributes and drivers of com-petitiveness for the three RMG clusters was under-taken to identify differences between the industries in the three countries. The results of the data col-lected are shown in table 3 and analysis of the re-sults summarized in the following discussion.

Competitive Analysis of RMG ClustersTable 3 shows the scores for 39 current and future attributes of competitiveness for the RMG indus-try clusters in Colombo, Delhi and Dhaka. Figure 8 shows the 39 competitive attributes for the five drivers aggregated to 13 key or primary attributes. There are significant differences between the com-petitiveness of attributes in the three clusters. The comparative analysis suggests that the Colombo cluster overall is the most competitive of the three clusters. This is because it is more specialized and targets the higher value end of the global consum-er market. However, the cluster has a number of weaknesses that need support if it is to enhance its competitive position and develop. All three clus-ters are facing strong competition from Southeast Asian producers and will not be in a position to strengthen their competitive position by relying on advantage through economies of scale in the future. To develop, it will have to identify how to add value along the supply chains.

Several weak competitiveness attributes are common to all the clusters studied. Overall support from government is weak, compared to other Asian countries. Value adding, development of markets, access to resources and access to skilled labor are common factors undermining the competitiveness of the cluster. The condition in Colombo in the social and business environments, collaboration, technology orientation, infrastructure and supply chains is much stronger than in the other clusters. The Colombo cluster appears to have a much stron-ger willingness of firms to collaborate, although this might be because the firms in the clusters is having to pitch themselves.

The market focus of all the clusters is exports, primarily to generate foreign exchange earnings. While leading firms in the clusters are aware of the potential of developing domestic markets, inefficien-cies in the production chain process of the cluster mean that profit margins and the potential to add value and expand demand in the domestic market have not been attractive. Firms in Dhaka, especially, are reluctant to share information and knowledge to improve cross-industry learning that could support innovation. Social capital in the cluster is strong be-


cause of the long history and associations between local producers and suppliers in areas with a strong physical concentration of similar types of businesses. As a result, opportunities for the clusters to support endogenous growth is being hampered.

Government support for cluster development in all three countries is generally weak, especially the unwillingness of governments to streamline business approval processes, increase resources for educa-tion and training, and incentives to upgrade tech-nologies that will enhance business performance and lead to more sustainable industry development. Governments are also reluctant to address the seri-ous environmental problems associated with many of these clusters. Most clusters enjoy some strategic advantage by being located close to sources of raw materials that are reliable in terms of supply and of reasonably good quality; however, there is still a high import component, especially for synthetic gar-ments, which weakens the competitiveness of the re-source attribute. Competition in global markets has raised awareness of the need for improved quality assurance, production sustainability and business ethics. Without such improvements, cluster firms find securing international contracts difficult.

Two sets of competitive attributes require the most support. The first set is related to support-ing industries, especially strengthening the delivery and quality of local business support services, iden-tifying opportunities to add value to supply chains, and sharing this knowledge with other businesses in the cluster. Enhancing the competitiveness of these attributes associated with factor conditions will require formal and informal dissemination of knowledge though the development of training facilities, networks and partnerships and industry associations.

The second significant set of attributes re-quiring support relates to government services. Government support for clusters is limited in all three countries. Approval systems for business development are bureaucratic, which deters in-vestors and new entrants into the cluster. Busi-ness and environmental regulations are complex and not enforced. Governments’ failure to address environmental problems affects public health and employees’ productivity. Government support for R&D is limited, undermining clusters’ capacity to raise productivity and production along supply chain systems.

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00Labour

Infrastructure

Resources

Social Environment

Markets

NewProducts

BusinessEnvironment

Structure

Collaboration

TechnologyOrientation

Supply Chains

Value Adding

Government

ApparelCluster Colombo

Okhla& Noida ReadymadeGarmentsDelhi

RMG IndustryDhaka

FIRMSTRATEGYSTRUCTUREANDRIVALRY

RELATEDSUPPORTINGINDUSTRIES

DEMANDCONDITIONS

FACTORCONDITIONS

Fig 8: Comparison of the 13 Primary Competitive Attributes for the Three RMG Clusters



App

arelCluster

Colombo

Okhla&Noida

Readym

adeGarments

Delhi

RMGIndu

stry

Dhaka

App

arealCluster

Colombo

Okhla&Noida

Readym

adeGarments

Delhi

RMGIndu

stry

Dhaka

App

arelCluster

Colombo

Okhla&Noida

Readym

adeGarments

Delhi

RMGIndu

stry

Dhaka

FACTOR CONDITIONS 3.02 2.13 2.10 4.71 4.51 3.82 1.69 2.38 1.72LabourAvailability of Skilled Labour 3.20 2.11 2.10 4.80 4.22 4.00 1.60 2.11 1.90Management Skills 3.20 2.50 1.80 5.00 4.72 3.90 1.80 2.22 2.10Efficiency and Productivity of Labour 3.00 2.22 2.40 4.80 4.44 3.80 1.80 2.22 1.40Education and Training facilities 2.80 3.11 1.00 5.00 4.66 3.60 2.20 1.55 2.60InfrastructureQuality of Infrastructure Services (logistics) 2.80 2.11 2.20 4.80 4.61 4.10 2.00 2.50 1.90Quality of Infrastructure Services (utilities) 3.00 2.34 1.80 4.40 4.61 3.80 1.40 2.27 2.00Cost of Services 3.20 1.50 2.20 4.80 4.50 3.40 1.60 3.00 1.20Quality of Telecommunication Services 3.80 1.11 2.70 4.60 4.77 3.90 0.80 3.66 1.20ResourcesProximity to raw material 2.20 2.14 2.20 4.20 4.42 4.10 2.00 2.28 1.90Cost of local raw materials vis imports 2.40 1.93 2.40 5.00 4.57 3.70 2.60 2.64 1.30Quality of raw materials 3.40 2.50 3.10 4.60 4.62 4.30 1.20 2.12 1.20Social EnvironmentQuality of living environment for workforce 2.40 2.28 1.10 4.40 4.05 3.10 2.00 1.77 2.00Workplace conditions 3.80 1.83 2.30 4.80 4.38 4.00 1.00 2.55 1.70DEMAND CONDITIONS 2.71 2.40 2.31 4.29 5.18 3.53 1.57 2.78 1.21MarketsExpanding domestic and local markets 1.40 1.37 1.00 3.20 4.31 3.00 1.80 2.94 2.00Expanding export markets 2.20 2.28 3.20 4.40 4.66 4.20 2.20 2.38 1.00New Productsdemand expansion capacity for new products 2.00 1.56 2.00 3.80 4.33 3.60 1.80 2.77 1.60Responsiveness and innovativeness to change 2.80 1.94 2.00 4.80 4.44 3.40 2.00 2.50 1.40Business EnvironmentQuality & reliability of product or service 3.60 2.38 2.80 4.80 4.88 3.10 1.20 2.50 0.30Product sustainably awareness and support 3.20 2.37 2.70 4.40 4.37 3.60 1.20 2.00 0.90Strong business ethics 3.80 2.55 2.50 4.60 4.77 3.80 0.80 2.22 1.30Readiness to face risk 2.33 4.50 2.17FIRM STRATEGY STRUCTURE AND RIVALRY 3.00 2.26 1.81 4.48 4.26 3.46 1.48 2.00 1.65StructureExtent of foreign and joint venture firm presence 2.80 2.32 1.60 3.80 3.75 3.30 1.00 1.43 1.70Flexibility of production systems 2.60 1.29 1.90 4.40 4.12 3.50 1.80 2.83 1.60CollaborationStrong industry firm collaboration 2.80 2.62 1.40 4.20 4.12 3.20 1.40 1.50 1.80Shared industry knowledge capital development 2.40 2.65 1.60 5.00 4.31 3.40 2.60 1.66 1.80Strong social capital and business networks 3.60 2.45 2.30 5.00 4.33 3.80 1.40 1.88 1.50National or international leadership 3.40 2.55 2.30 4.80 4.38 3.70 1.40 1.83 1.40Civic entrepreneurship and community engagement 3.60 2.05 1.30 4.40 4.27 3.30 0.80 2.22 2.00Technology OrientationHigh level of technology application in firms 2.80 2.16 2.10 4.20 4.77 3.50 1.40 2.61 1.40RELATED SUPPORTING INDUSTRIES 2.80 2.43 1.98 4.92 4.63 3.98 2.12 2.20 2.00Supply ChainsStrength of local business support services 2.80 2.41 1.80 4.80 4.66 3.90 2.00 2.25 2.10Responsiveness of local support services 2.80 2.20 1.80 5.00 4.62 4.00 2.20 2.42 2.20Quality of local support services 3.20 2.61 1.90 5.00 4.75 4.00 1.80 2.14 2.10Value AddingPotential to add value to supply chains 2.80 2.50 2.40 5.00 4.62 3.80 2.20 2.12 1.40Business awareness of value adding potential 2.40 2.44 2.00 4.80 4.50 4.20 2.40 2.06 2.20GOVERNMENT 1.72 2.71 1.44 5.00 4.50 3.66 3.28 1.80 2.22Government support for cluster development 2.20 2.82 0.90 5.00 4.50 3.80 2.80 1.68 2.90Streamlined business approval systems 1.40 2.37 1.50 5.00 4.37 3.50 3.60 2.00 2.00Support for sustainable industry development 1.80 2.12 1.60 5.00 4.43 4.00 3.20 2.31 2.40Enforcement of business regulations 2.00 2.81 2.20 5.00 4.56 3.60 3.00 1.75 1.40Support for R&D 1.20 3.41 1.00 5.00 4.66 3.40 3.80 1.25 2.40

Average 2.68 2.21 1.92 4.52 4.36 3.59 1.84 2.15 1.67

Current Competitive Position Necessary CompetitivePosition

Gap Analysis

Table 3 Competitiveness Attributes for RMG Industry Clusters in Colombo, Delhi and Dhaka


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2.50

3.00

3.50Labour

Infrastructure

Resources

Social Environment

Markets

NewProducts

BusinessEnvironment

Structure

Collaboration

TechnologyOrientation

Supply Chains

ValueAdding

Government

Apparel Cluster Colombo

Okhla & Noida Readymade GarmentsDelhi

RMG Industry Dhaka

DEMANDCONDITIONS

FACTORCONDITIONS

FIRMSTRATEGYSTRUCTUREANDRIVALRY

RELATEDSUPPORTINGINDUSTRIES

Fig 9 Competitive Gap Analysis 13 Primary Competitive Attributes in the Three Clusters


Competitiveness Gap Analysis in the Three ClustersFigures 9 show the competitive gap for conditions for the 13 primary attributes of competitiveness in the three clusters using aggregated data de-rived from table 3. There are significant differ-ences between the competitiveness gaps for the 13 primary attributes in each cluster. The gap analysis measures the difference between the per-ceived actual and necessary level of competitive-ness considered necessary to a level or national or international competitiveness. For the three clusters, 18 attributes have an average competi-

tive deficiency score gap of 2 or more considered necessary to support the desired level of competi-tiveness. Nineteen attributes had scores between 2 and 1.5 for the desired level of competitiveness improvement. The deficiency gap analysis is a use-ful means of identifying priorities for strengthen-ing the competitiveness attributes supporting the development of a cluster.

The gaps in the competitive attributes for fac-tor conditions occur mainly in the area of human resource development. The clusters have an abun-dant supply of unskilled labor, but all were expe-riencing a high level of skills loss through migra-

tion. Currently, the clusters do not have enough capacity to meet the demand for skilled labor and management, which are essential to improve overall productivity and performance. Education and training facilities to meet the ongoing and expanding demand for professional and technical skills and competencies needed to support the nine clusters are in short supply. Foreign enterprises in some clusters are recruiting international staff because of the shortage of local skills. Skill shortages are undermining firms’ ability to build strong, competitive management and production capabilities.

The lack of government support and infrastruc-ture is a problem for the development of all the industry clusters studied, although the situation is not as bad as for the prior issues, as a significant proportion of leading firms in the clusters are lo-cated in planned industrial areas and districts, and infrastructure and utility services are generally better in these locations than in inner city areas. The costs of services, especially water, electricity and telecommunications, are high because of sys-tem losses and theft that affect production costs, and hence the competitiveness, of many firms. Poor telecommunications services combined with low


levels of computer literacy often mean that con-tracts are lost, many to clusters in Southeast Asian countries where these services are much more reli-able. The proximity to materials used in production is a competitive advantage for the clusters studied, but poor logistics are causing delivery delays and damage, affecting just-in-time and perishable food businesses in particular.

Many larger firms in the RMG clusters realize that appropriate residential accommodation is es-sential to attract and maintain skilled workers. It is also important to ensure healthy and productive workforces. When planning and developing special enterprise zones and industrial estates, govern-ments have failed to provide for workers’ housing needs.

Demand condition deficiencies were the lack of capacity to expand export markets and develop domestic markets, firms’ slow responsiveness to changes in market demand, and lack of innovation to respond to demand for new products. The clus-ters tend to suffer from inertia, which reduces the overall dynamics of business in the cluster.

prioritiEs for fostErinG ClustEr dEvElopmEnt in rmG industriEsThe goal of the CCED approach seeks to identify bankable projects that are attractive to investors and prioritize investment areas to maximize the economic impact of development in cities in Asia. Government support is important for the develop-ment of clusters, because many projects involving major infrastructure, facilities and capacity-build-ing programs entail high initial risks, which private investors find unacceptable. For many projects the economic returns to the community and business are high, but the financial returns to investors are not acceptable. In such cases, CCED analysis can provide better information of “where to invest first” to have clusters develop more efficiently and to generate job opportunities for the local residents. Governments have a key role to play in sharing risks or guaranteeing cash flow during the initial stages

of a project intended to support the development of a cluster. This is common for public–private part-nership projects, where governments need to take a leading role in supporting cluster development projects to overcome risks before private sector partner(s) become engaged.

Many of the investments in the action plans for clusters developed for the three clusters are tar-geted at enhancing government support and indus-try services, as these were shown to be particularly weak in all three countries. Most priority projects selected are needed to reduce the external transac-tion costs associated with the operations of firms involved in the cluster. Many projects involve pub-lic sector investment, as engaging businesses in investment projects helps to improve municipal in-frastructure and services, the capacity of logistics support systems, R&D, education and training, and reforming business regulations. These are matters best undertaken by governments, but stakeholders’ interests must be considered when addressing these issues. In many cases, business can offer solutions and be engaged in the delivery of public services, provided it is profitable and expedient for them to do so.

Priority areas to support the development of RMG clusters in the three countries include:n improving knowledge management and interna-tional marketing intelligencen applying ICT technologies to improve efficien-cies in the clustersn providing training facilities and programs to enhance the knowledge and skills of cluster work-forcesn improving the delivery of utilities, especially water supply, waste management, electricity, and telecommunications servicesn enhancing support for R&D, particularly to fos-ter innovation and the development of new products and servicesn streamlining approval and permitting processes by providing one-stop shop facilities and e-gover-nance systemsn developing business networks and associations to foster the dissemination of knowledge and for-mal and informal (tacit) learning


n Developing special initiatives such as an ap-parel city in Colombo, regional garment centers in Dhaka, and national garment institutes in Delhi and Dhaka

ConClusionThe CCED analysis of the RMG industries in Co-lombo, Delhi and Dhaka has added a new dimen-sion to analyzing the competitiveness of clusters in Asian cities. There is growing interest in Bangla-desh, India and Sri Lanka on the role clusters could play in supporting local economic development and attracting foreign investment. The development and testing of CCED analytical methodology in the three countries has involved a significant learning process, along with experimentation not commonly associated with this type of research undertaken by development banks. The process has provided in-sights into improved project design of development bank projects, but it took much longer than antici-pated to achieve results, the data collection proved problematic, and the facilitating of industry focus groups to share information and collaborating in the qualitative research involved a great deal of trust building and education before good coopera-tion between industry stakeholders and the govern-ment was achieved.

CCED analytical methodology uses many techniques well -established in regional econom-ics research and practices to analyze and pre-pare strategies for local economic development. The CCED is one of the first kinds of research in competitiveness and cluster areas where it com-bines spatial agglomeration for practical urban development perspectives. The process has dem-onstrated that when combined with limited quali-tative data, qualitative techniques can generate information and insights that provide valuable understanding insights into what shapes the de-velopment of local economies and identifies the competitive strengths as well as weaknesses in existing strategic architecture.

The RMG industry is a highly competitive in-dustry. In Asia it is a labor-intensive industry, which employs millions of mainly low-skilled and low-paid female workers. In most cases the indus-

tries are only engaged in the primary production stage of manufacturing and export, which provides few opportunities for RMG clusters to significantly climb up the supply chain and add value to local production systems. With the expansion of domes-tic markets, there is significant potential of the RMG industry clusters to expand both the horizon-tal and vertical supply chains in the industry. To do this they must create much more competitive strategic architecture.

Factor conditions of competitiveness in all three RMG clusters are relatively weak, especially govern-ment support. The enabling environments to support cluster development in all three cities need to be sub-stantially improved. The unnecessary high levels of bureaucracy in governance and regulations systems, rent seeking and the lack of government support and know-how to develop the RMG industries in Colom-bo, Delhi and Dhaka is holding back the development of the industry and undermining its competitiveness. Greater support for clustering by local and national government could help to overcome some the prob-lems in infrastructure and skills shortages through a range of partnerships with the private sectors and the fostering of strong industry cluster organiza-tions. By fostering a more collaborative approach to cluster development to overcome some of these problems, it should be possible to reduce transac-tions cost to business and make these cities more attractive places for investors in the future.

The investigation into the RMG clusters has led to important discoveries that could help policy de-cision making by governments, businesses, and in-vestors to facilitate opportunities to support the de-velopment of clusters. CCED analysis has enhanced well-established research techniques by enabling a more detailed exploration into the competitiveness of cities and industry clusters than has been pos-sible before. Finally, the CCED study of the RMG clusters has led to a better understanding of the nature and economic importance of the three RMG clusters in the three cities in which the studies were conducted, and how industry and government can work collaboratively to develop pathways that can lead to the achievement of more sustainable devel-opment outcomes for these clusters in the future.


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2 Assmo, P. (2005) Creative Clusters - Ideas And Realities For Cluster Growth: The Example Of Film In Vast In The Region Of Vastra, Gota-land, Sweden. In Karlsson, C., Johansson, B. & Stough, R. G. (Eds.) Industrial Clusters And Inter-Firm Networks. Cheltenham, Edward El-gar Publishing Ltd.

3 Baum, J. A. C. & Haveman, H. A. (1997) Love Thy Neighbor? Differentiation And Agglomera-tion In The Manhattan Hotel IndUstry: 1898-1990. Administrative Science Quarterly, 42.

4 Bordecki, M. J. (1984) A Delphi Approach, New York, N.Y. University.

5 Brown, R. F. (1996) Industry Clusters: A New Approach To Economic Development In Re-gional Australia, Canberra, Agps.

6 Curran, P. J. (2001) Competition In Uk Higher Education: Applying Porter’s Diamond Model To Geography Departments. Studies In Higher Education, 26, 223 - 251.

7 Cus (2010) City Cluster Economic Develop-ment: Bangladesh Case Study, Manila, Asian Development Bank.

8 Daly, M. T. & Roberts, B. H. (1998) Applica-tion Of Porter’s Diamond Model To Evaluate The Competitiveness Of Tradeable Services In A Regional Economy: A Case Study Of Tropical North Queensland, Australia. Western Regional Science Association: Thirty-Seventh Annual Meeting. Monterey, California.

9 Enright, M., Scott, E. & West, J. (1996) Hong Kong’s Competitiveness, Hong Kong, Oxford University Press.

10 Feser, E. J. & Bergman, E. M. (2000) National Industry Cluster Templates: A Framework For Applied RegionaL Clusters. Regional Studies, 34, 1-19.

11 Hamel, G. & Prahalad, C. (1994) Competing For The Future: Breakthrough Strategies For Seizing Control Of Your Industry And Creating

The Markets Of Tomorrow, New York, Har-vard University Press.

12 Marshall, A. (1920) Industry And Trade, Lon-don, Mcmillian.

13 Neven, D. & Dröge, C. L. M. (2001) A Diamond For The Poor? Assessing Porter’s Diamond Model For The Analysis Of Agro-Food Clusters In The Developing Countries. Michigan State University.

14 Niua (2010) City Cluster Economic Develop-ment: Innovative Interventions South Asia New Delhi, Institute For Urban Affairs.

15 O’malley, E. & Egeraa, C. V. (2000) Industry Clusters And Irish Indigenous Manufacturing: Limits Of The Porter View. The Economic And Social Review, 31, 55-79.

16 Porter, M. E. (1980) Competitive Strategy: Techniques For Analyzing Industries And Com-petitors, New York, Free Press.

17 Porter, M. E. (1985) Competitive Advantage: Creating And Sustaining Superior Performance, New York, Free Press.

18 Porter, M. E. (1990) The Competitive Advan-tage Of Nations, New York, Macmillian Inc.

19 Porter, M. E. (2000) Location, Competition, And Economic Development: Local Clusters In A Global Economy Economic Development Quarterly, 14, 15-34.

20 Roberts, B. H. & Choe, K.-A. (Eds.) ((Forthcom-ing 2010)) City Economic Economic Develop-ment In South Asia, Manila, Asain Development Bank.

21 Roberts, B. H. & Stimson, R. J. (1998) Multi-Sectoral Qualitative Analysis: A Tool For As-sessing The Competitiveness Of Regions And DevelopIng Strategies For Economic Develop-ment. The Annals Of Regional Science, 32, 1-25.

22 Tapscott, D. & Williams, A. D. (2006) Wikinom-ics: How Mass Collaboration Changes Every-thing, New York, Portfolio.

23 Weber, A. (1929) Theory Of The Location Of Industries. Chicago, Il, University Of Chicago Press.


dEtErminAnts of CompEtitivEnEss: A study of thE indiAn Auto-ComponEnt industry

Joshi, Deepikaa1

Rathore, Ajay Pal Singh2

Sharma, Dipti3

In the present era of global competition, competi-tiveness is the key word to success. Industries are competing in their respective domains to establish the global benchmarking standards. Here deter-mining the critical success factors is an important task. In the context of the Indian auto-component industry, this paper is an attempt to identify, in-tegrate and analyze the factors responsible for

1 Department of Management Studies, Malaviya National Institute of Technology Jaipur, India2 Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, India3 Department of Humanities & Social Science, Malaviya National Institute of Technology Jaipur, India

its competitiveness. Further, this evaluation will assist in recognizing the critical factors of suc-cess to win a place in the global auto-component industry.

Keywords: Competitiveness, Determinants of com-petitiveness, Automotive industry, Auto-component industry

ABSTRACT


introduCtionUnparalleled intensification of the worldwide market has created a fierce competition amongst various sectors and nations across the globe. Pres-ently, when most of the nations are facing turbulent growth rates, the focus is shifted to those sectors of economy that promise accelerated growth. The Indian automotive industry is one such sector hav-ing tremendous potential for future growth. Today, domestic firms have already realized the market opportunities and are trying hard to excel within their domains. In this scenario, competitiveness is the universally-accepted formula for growth [29]. However, leapfrogging of the Indian automotive in-dustry has made it a part of the global supply chain activity. To become competitive, firms or industries need to find and act upon critical factors to success. This not only helps in mitigating local competition, but also builds up national competitiveness.

The Indian auto-component sector that initially started with the development of small and medium scale enterprises is now gaining recognition as a ‘global quality player’. The global attractiveness and success of this sector depends on some signifi-cant factors. These factors directly or indirectly af-fect the performance of a firm or an industry. Thus, it merits extraordinary attention of practitioners and researchers. The present study is primarily fo-cused on analyzing the competitiveness of the In-dian automotive industry. Secondly, it identifies the critical success factors for profitable development of the Indian auto-component sector.

rEviEW of litErAturEIn the present era of globalization and industrial-ization, competitiveness is achieving a positive ap-preciation. Over a period of time, it has become the name of game i.e. “be competitive and win”. This has made competitiveness synonymous with success. Various researchers have expressed it in different ways; for K. Momaya [22] it is a useful indicator of the long-term socio-economic health of a country. For scholars with a resource-based viewpoint, it is distinctive competence available in any given organization [5] [6] [11] [14] [16]

[19] [31] [33]; for scholars having a knowledge-based viewpoint, competence is creation of orga-nizational knowledge that is proprietary to firm (Nonaka and Spender, 1992); and for scholars with a competence-based viewpoint, it is resources and capabilities that are difficult to imitate [17]. Thus, productivity comes from capability, which in turn comes from resources and knowledge.

The wide-ranging concept of competitiveness is built across three different levels of competitive-ness i.e. firm, industry and nation. At the national level, competitiveness is synonymous to productiv-ity of the nation [15] [21] [27] thus augmenting its trade and export performance [30] to achieve high and rising standard of living [20] [34]. Essen-tially, it is not the nations that directly compete in the global marketplace, competition actually arises at the industry and firm level [22] [28]. More precisely, firms of an industry struggle to build up industrial competitiveness that ultimately aug-ments national competitiveness. For this reason, national competitiveness is often considered as the macro factor while the individual competitiveness of various industries and firms is counted as micro-factors.

The study of various models and frameworks related with ascertaining competitiveness has un-veiled the important fact that competitiveness is a collection of discrete variables that are often iden-tified as determinants of competitiveness or indica-tors of competitiveness. The diamond approach to international competitiveness [27] has identified four factors for national competitiveness: (a) fac-tor conditions, (b) demand conditions, (c) related and supporting industries, and (d) firms’ strategy, structure and rivalry. Caves [9] has identified five factors responsible for inter-industry differences: (a) competitive conditions, (b) organizational fac-tors, (c) structural heterogeneity, (d) dynamic dis-turbances and (e) regulation. K. Momaya and A. Ambastha [4] [22] have discussed different aspects of industry level competitiveness: (a) assets, (b) processes and (c) performance. Thus, competitive-ness is a multidimensional concept [24]. However, the determinants of competitiveness at all three different levels are not exclusively separated. This


can be attributed to the mutual impact they have on each other. The factors affecting national competi-tiveness are also considered as determinants of the performance of industries and firms. On the other hand, the ability of firms and industries is often translated into the position that a nation’s economy holds on a global platform.

Assessing national competitiveness is a complex task. Nevertheless, it can always be measured with reference to the competitiveness of the nation’s in-dustries [7] [8] [22]. The dimensions of any given sector’s/nation’s performance often depend upon a large number of variables and sub-variables at-tached to it. Even the most authenticated reports like Global Competitiveness Report and World Competitiveness Yearbook have ranked the coun-tries on the basis of various pillars and indicators. These pillars and indicators are basically variables or units used for measuring competitiveness. How-ever, the factors (variables) governing competitive-ness at the industry level are highly sector-specific, and vary from sector to sector.

Various public policies adopted by the govern-ment are aimed at restructuring the present posi-tion of industry sectors [22]. This initiates open border practices and creates a single platform for exchange of goods and services. Thus, competitive-ness for the trade sector depends on open trade or no protection or subsidies [8] and international trade agreements [7] [22]. This increases exports from a country thereby allowing increased inflow of foreign currency. Government-protected poli-cies specify the level of FDI and FII received by the industry as a whole [7]. This however requires a developed infrastructure in the form of industrial clusters [7] [28]. Thereby it brings in subsidies, incentives and SEZs by government and industry-specific agencies. Moreover, the never-ending R&D activities are central to technological innovations [7] [13] [22], though it can also be achieved by in-house automation, design knowledge and skills [10] [23]. For heavy-technology-oriented business-es like manufacturing, investment in R&D activities is the major source of positive cash flows. These activities affects new product development, short-ens lead time as well as cycle time [32] and finally

results in the realization of profits, revenue growth, and market capitalization. It is also supported by the concept of quality, which is highly subjective in nature. But quality standards and accreditations are universal performance indicators. Following these standards usually indicates the firm-specific degree of product quality [7] [10] [22] [23]. For sectors that are involved in mass production like the auto-component industry, labor productivity is the key indicator of efficiency [7]. Simultaneously it requires effectiveness too. Failure to attain labor productivity renders production a costly affair. This may increase the overall cost of doing business. Fi-nally it can increase the price of products or ser-vices [10] [22]. For labor-intensive industries, the world’s best economies are competing on unit labor cost [3] [12].

According to the supply chain research commu-nity, any given firm is a set of management pro-cesses. These processes are interlinked with each other. Any uncertainty at the first stage of forecast-ing the demand and supply situation can distort the subsequent processes [10]. Moreover, satisfying the customer is the ultimate aim of any business activity. In business-to-business (B2B) markets it often depends upon satisfying the other’s business needs. Proper scheduling techniques and reducing the frequency of machine breakdowns leads to per-fect delivery [10]. Here information always plays a very important role [10]. If shared properly and wholly among suppliers, buyers and the ultimate consumers, it can be a good source of competitive-ness for the industry as a whole.

rEsEArCh mEthodoloGy/ApproAChThe review of literature presented in the previous section is aimed at highlighting the importance of competitiveness. Factors that decide the com-petitiveness of the manufacturing sector are also put forth. Further, in the next section a secondary method of data collection is used for collecting the required information. Statistical data from various organizations of national repute like CRISIL, So-ciety of Indian Automobile Manufacturers (SIAM),


Automotive Component Manufacturers Association of India (ACMA), and India Brand Equity Founda-tion (IBEF) is used for the current study. Informa-tion so obtained is analyzed properly and compari-son made among the data of the past five to seven years. This unveiled the current status of the Indian automotive industry and its future prospects. In-sights from various firms have helped in determining the factors responsible for the success of the Indian auto component industry. The Auto Policy 2002 and Auto Mission Plan 2006-2016 are used to validate the identified factors of competitiveness.

indiAn AutomotivE indus-try: A hiGh potEntiAl for GroWthIf auto manufacturing were a country, it would be the fifth largest economy.

International Organization of Motor Vehicle Manufacturers, 2009

Automobile IndustryThe Indian automotive industry emerged in the 1940s. After independence in 1945, this sector has struggled very hard to become the core sector of the economy. However, the recent global downturn has trimmed down automobile manufacturing in India, but due to the competence associated with the country’s automotive sector, it has succeeded in maintaining its position in the global market place. Presently, India enjoys the ninth position in auto-mobile manufacturing worldwide. Figure 1 depicts the recent trend in automobile production from

2002-03 to 2008-09. Nevertheless, with continu-ous improvements in the production system and the escalating demand conditions, the Indian automo-bile sector is growing at a very high pace.

It’s no wonder that presently India is among the most favored destination for foreign automobile manufacturers. This has strengthened the country’s exports portfolio as well. Figure 2 shows the trend in Indian automobile exports from 2002-03 to 2008-09. Analysis shows that passenger vehicle exports have grown five times and two-wheeler exports have more than doubled in 2008-09 compared to 2002-03. Presently, the Indian automotive sector is grow-ing at the CAGR of 9.08% since 2003-04.

Fig 1: Trends in Indian Automobile Production

Data source: CRISIL Research and SIAM(Refer Table 1)

0

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(nos) 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09

Amount (Percentage of total)



Amount (Percentage

of total)

Amount (Percentage

of total)

Amount (Percentage

of total)


Commercial vehicles 202,852 3.1 275,098 3.7 350,202 4.1 391,078 3.9 520,000 4.6 545,104 4.9 417,272 3.6

Two-wheelers 5,109,239 79.0 5,624,950 75.8 6,454,765 74.8 7,601,801 76.0 8,436,186 73.9 8,024,804 71.8 8,385,128 73.1

Three-wheelers 270,483 4.2 340,729 4.6 371,208 4.3 410,788 4.1 555,887 4.9 500,592 4.5 496,832 4.3

Tractors 166,889 2.6 190,687 2.6 245,546 2.8 296,080 3.0 352,835 3.1 345,172 3.1 335,011 2.9

Cars and multi-utility

vehicles721,220 11.1 990,032 13.3 1,209,654 14.0 1,308,913 13.1 1,544,850 13.5 1,767,867 15.8 1,825,748 16.1

TOTAL 6,470,683 100.0 7,421,496 100.0 8,631,375 100.0 10,008,660 100.0 11,409,758 100.0 11,183,539 100.0 11,459,991 100

Table 1: Trends in Automobile Production in India (2002-03 to 2008-09)

Data source: CRISIL Research for data from 2002-2003 to 2007-2008, SIAM for data of 2008-2009


The consistent increase in automobile manufac-turing and its export has created opportunities for both domestic as well as international firms. The in-dustry is expected to increase its turnover to $145 billion by 2016 from the present $35 billion. This will increase the export revenues to $35 billion by 2016. Moreover, it will generate additional em-ployment for 25 million people and is expected to contribute 10% to the country’s GDP. Owing to its growth status, today the country has the world’s best car manufacturer’s right from the ‘people’s car’ seg-ment to ‘most luxurious car’ manufacturers.

Auto-component Industry‘When an industry grows in a country, it also brings in the growth of its related and supporting indus-tries [27]. So is the case with the Indian auto-com-ponent industry. The high growth rate of the au-tomobile sector and supportive public and private

investment in India have highly favored the growth of the Indian auto-component industry. Because of its upstream and downstream linkages with various other sectors like machine tool, steel, aluminum, electronics, forgings, intermediate products, etc., this sector has a huge potential for growth.

The Indian auto-component industry reported a size of $19 billion for the financial year 2008-09 and growing at CAGR of 23 per cent over the last five years (IBEF). Figure 3 shows the trend of auto

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Fig 2: Trends in Indian Automobile Exports

Data source: SIAM, (Refer Table 2

(Number of Vehicles)

Category 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09

Passenger Vehicles 72,005 129,291 166,402 175,572 198,452 218,401 335739

Commercial Vehicles 12,255 17,432 29,940 40,600 49,537 58,994 42673

ThreeWheelers 43,366 68,144 66,795 76,881 143,896 141,225 148074

Two Wheelers 179,682 265,052 366,407 513,169 619,644 819,713 1004174

Grand Total 307,308 479,919 629,544 806,222 1,011,529 1,238,333 1,530,660

Table 2: Trends in Automobile Exports in India (2002-03 To 2008-09)

Data source: SIAM

ancillary and parts produced in India. Presently country has approximately 500 organized and 10, 000 unorganized units involved in component manufacturing. Total auto component produced in country is the contribution of both organized and unorganized units. Figure 4 shows the individual contribution of small scale industries (SSIs) and the organized sector.

Study indicates that the contribution of the or-ganized sector has been far more than that of SSIs.


However, the combined efforts of SSIs and the orga-nized sector have improved the position of clusters involved in component manufacturing. Of the total auto-components produced in the country, the major portion is utilized by cars, two-wheeler and three-wheeler manufacturers. In spite of a huge turmoil in the global economy, the Indian component sector exported $3.82 billion in 2008-09 (IMaCS).

There are certainly a large number of factors responsible for this growing trend; one of the most important among them being the decision of In-dian manufacturers to diversify their business portfolios and to tap newer regions for exports. In spite of having the world’s best manufactur-ing practices in these regions, 58-60% of Indian auto component exports go towards the US and Europe. Today, the Indian auto-component sector is considered as the fastest-growing sector among Asian countries. Analysis given in Table 3 clearly shows that investment in the component industry

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Fig 3: Month-wise Industrial Production of Auto Ancillary and Parts in India

Data Source: Data as per Central Statistical Organization Com-piled by Indiastat. (Refer Table 4)

Value in US $ Billion 2003-04 2004-05 2005-06 2006-07 2007-08 2008-09

Turnover 6,730 8,700 12.0 15.0 18.0 19.1

Export 1.274 1.692 2.469 2.873 3.615 3.800

Import 1.428 1.902 2.482 3.600 5.220 6.80

Investment 3.100 3.750 4.400 5.400 7.200 7.700

Table 3: Analysis of Auto-Component Industry

(Rs. Million)

Year Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

2003-04 10075 9216 10282 10018 10108 9054 8920 9038 9648 9325 9157 9752

2004-05 9275 8772 9423 9851 9453 9472 9627 9618 10055 9763 10710 10168

2005-06 9944 10264 9939 10398 10362 10668 11094 10473 11136 10899 10797 11101

2006-07 11637 11797 11903 12122 11536 12377 11955 12343 12721 12581 12602 13356

2007-08 12381 12627 12550 12433 12706 12652 13288 12818 13538 14365 14337 16042

2008-09 14808 15366 15363 15720 16770 17107 13929 12812 10775 10047 11172 13328

Table 4: Month-wise Industrial Production of Auto Ancillary and Parts in India (2003-04 To 2008-09)

Data Source: Data as per Central Statistical Organization, Compiled by Indiastat


has increased more than two times in the past five years. This has supported the increase in produc-tion and exports of components in India. Both, production and exports have shown a growth of nearly 6% in 2009, whereas imports have shown a growth of 31%. This is an indicator of the huge requirement of auto-components for India-based manufacturers. It is a matter of concern for the locally-producing firms as they are losing domes-tic opportunities to foreign-based manufacturers and hence increasing the outflow of Indian cur-rency to the global market.

As of today, the growth in the auto-component sector has reached such a position that various multinational companies like Mercedes, General Motors, Ford, Daewoo, Honda and Volkswagen have already set up their international purchasing offices (IPOs) in India to source for their global op-erations. This has further complemented the growth rate of the Indian auto-component industry. Today, the Indian auto-component industry has become a part of the global supply chain activity and hence requires special attention of practitioners and re-searchers for its further development.

drivErs of CompEtitivE-nEssThe accelerated growth of the Indian automotive sector is determined by some critical success fac-tors. These factors are the entities and variables involved throughout the business process, i.e. right

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Fig 4: Individual Contribution of Small Scale In-dustries (SSIs) & Organized Sector

Data Source: CRISIL Research, ACMA (Refer Table 5)

Table 5: Individual Contribution Of Small Scale Industries (Ssis) And Organized Sector

(Rs. Million)

Type 2002-03 2003-04 2004-05 2005-06 2006-07 2007-08

Total organized sector 196,425.9 235,928.0 298,105.5 409,054.8 522,637.5 558,142.2

SSI sector 58,927.8 70,472.0 89,044.5 122,185.2 156,112.5 166,717.8

Total 255,353.6 306,400.0 387,150.0 531,240.0 678,750.0 724,860.0

Data Source: CRISIL Research, Automotive Component Manufacturers Association (ACMA)

from procurement of raw materials to delivery of finished goods. The degree of effectiveness and ef-ficiency of these factors truly determines the per-formance of the Indian automotive industry as a whole. For the ease of study, they are classified as direct and indirect factors.

The elements of competitiveness actually form a paradigm. The directly-involved entities are a mem-ber of the auto-component supply chain activity and the indirectly-involved entities carry out supportive functions. Moreover, the directly-involved variables are the firms’ strategies on which an organization


has direct control to achieve competence. Indirect-ly-involved variables are mainly industry-specific factors. A graphical depiction of the interrelation-ship among these factors is presented in figure 5. The combined effect of these factors actually deter-mines competitiveness. For the auto-component in-dustry, which has mass production and supply, cost competitiveness and perfect delivery are the major criteria for success, which in turn comes from these entities and variables. Here, 1 and 2 represent the directly-involved variables.

Customers drive competition in the industry by creating demand. Stipulated demand for robust and reliable auto parts by automobile manufacturers has forced OEMs to compete considering technol-ogy as a success factor. Today, Indian manufactur-ers are fully capable enough of producing hi-tech components like electronic fuel injectors and metal intensive components used in forging, stamping and casting, etc. For example, Bharat Forge Limited from India has a leading position in steel and alu-minum forging across the world. However, with the growing trend of alliances and ventures, the status of technology as a factor is now that of an order qualifier instead of an order winner. In this context, success stories of Maruti Udyod Limited and Suzu-

ki of Japan, and that of Steering Systems and Sona Koyo of Japan are of utmost significance. Both these ventures were made for technology acquisi-tion for continuous production improvement. To-day, large numbers of companies are building their product consortia and competitiveness because of easy mode to technology transfer. Though India is still on its learning curve as far as technology and R&D are concerned, it has helped developing in-house R&D and design and development (D&D) facilities. Scorpio from Mahindra and Mahindra, Indica and Indigo from Tata Motors and Pulsar from Bajaj Auto’s are all indigenously-designed vehicles. Today, Indian firms are designing after receiving orders from manufacturers. Firms like Sundram Fasteners have well equipped CAD/CAM labs for testing and designing of auto components. The developed Indian software industry is a great source of help to the industry’s R&D activities. As the cost of component designing in India is one-twelfth of that in the US and UK, the manufactur-ers like Volkswagen, Mercedes, Nissan and many more are starting their component production in India. Undoubtedly, intensification of the global automotive industry has created competitive rival-ry, but simultaneously it has forced firms to design

OEMs Tier 1 Tier 2

Automobile Assemblers Customer

Cost

Delivery12

12

12

Competitive Rivalry

Demand pattern

Financial Institutions

Third Party Logistics

Research Firms

Agencies

Fig 5: Entities and Variables Involved in Auto-component Business Activity

Directly-involved entities Tier 1& Tier 2 suppliers, OEMs, auto assemblers, ultimate customersIndirectly-involved entities Banks and financial institutions, third-party logistics, research firms, government and non-government agenciesDirectly-involved variables Technology, human skills, resources, flexibility, qualityIndirectly-involved variables Competitive rivalry, demand pattern


globally competitive business strategies to leverage market opportunities.

Government initiatives and policies always act as facilitators for industrial development. In India, The Department of Heavy Industry is the main agency for promoting the growth and de-velopment of the automotive sector. In order to push advancement in the auto sector, the depart-ment has undertaken several measures, like the Auto Policy in 2002, time-bound implementation of the Auto Mission Plan 2006-16, setting up the National Manufacturing Competitiveness Council and Investment Commission for enhancing the manufacturing competitiveness, and the National Automotive Testing and R&D Infrastructure Proj-ect (NATRiP) at a total cost of $388.5 between central and state governments to aid world-class automotive safety, emission and performance standards. Moreover, the government has allowed 100% foreign equity investment and reduced the duties and taxes on raw material purchase to 5-7.5% from the earlier 10%. This has also given an opportunity to multinationals to start their production units in India. Apart from setting up SEZs, the government is fostering cluster forma-tion at the regional level, whereby manufactur-ers located in proximity to OEMs synergize each others profit. Major clusters of in the country are present in Delhi, Gurgaon, Faridabad, Manesar (North), Mumbai, Pune, Nashik, Aurangabad (West), Chennai, Bangalore, Hosur (South) In-dore (Central India) and Jamshedpur (East). This allows easy sharing of commonalities and comple-mentariness. The formation of nodal associations like ACMA and SIAM has structured the industry for its long-term profitable development. Current-ly, ACMA represents 479 component manufactur-ers and SIAM represents 39 leading vehicle and vehicular manufacturers in India. These agencies act as a catalyst and interact with international experts for the development of the sector.

The auto-component sector is a mass produc-tion industry. The advantageous position of the country with regards to low cost skilled workforce with multilingual capability is promoting exports of labor-intensive work. For example, Indian firms

are incurring just $6 per day as compared to 33.6 in Brazil. This accounts for 9.3% of the total cost of component production in India. Even after com-paratively lower productivity, a components manu-facturer enjoys a cost advantage of 2-30%. More-over, the decreasing cost of raw materials is one of the key factors responsible for development of the component and ancillary industry. Raw material ac-counts for 57% of the total cost of auto-component production compared to 61% in 2007 (IMaCS). The huge popularity of cost advantage has made India a global auto-component manufacturing hub. German automaker Volkswagen is initiating com-ponent sourcing from India for its Russian and Eu-ropean plants. Carlos Ghosn of Nissan said that “If I have to fight the battle on low cost, I am going to do it (with a base) in India.” Thus, cost competence is amplifying the potential gains of the Indian auto-component manufacturing industry.

Driven by the need of export markets, quality awareness has increased since the last decade. In-dian firms have improved product quality by imbib-ing world-class quality standards like TS 16949, GS 9000, ISO 9000 and OHSAS 18001. The de-fects have been reduced to 100 parts per million (ppm) in 2009 from 500 ppm in 2007. Eleven In-dian auto-component manufacturers have won the prestigious Deming Award and fifteen have won the Total Productive Maintenance (TPM) Awards in 2009. To attain high operational efficiency, In-dian suppliers are embracing modern shop floor practices like Six-Sigma, Kaizen, TQM, TPM, lean manufacturing, etc. Moreover, the adoption of world-class manufacturing practices, educating managers and shop floor workers has made Indian component manufacturing a quality-oriented indus-try. It has also facilitated the flexible production system thereby making the perfect delivery system for firms.

The growth of rubber, aluminum and steel produc-tion as well as development of the power sector and business infrastructure facilities within the country has also strengthened the ancillary and component production. However, the linkage between universi-ties and manufacturers is still missing. These link-ages, if developed properly with IITs, NITs and IIMs


can help in technical as well as business planning ac-tivities for the enhancement of the auto-component sector as a whole.

Various socio-economic factors that contribute towards high growth in the Indian automobile sec-tor are rising per capita income, falling age of first-car users, shorter replacement cycles, rising duel income families, new technology (which is lowering cost of ownership), low car penetration in the coun-try and easily-available financing options. This is surging the demand of components and ancillaries too. Various initiatives at the national and industry level have made this sector a rising sector in the Indian economy.

Besides, the strategic handling of competitive pressure has also helped national and multinational firms to overcome local as well as global challeng-es. Building industry competitiveness ultimately paves the way towards development of nation as a whole.

ConClusionIndian is one among the fastest-growing economies of the world. Herein, the country’s developing auto-component industry plays a vital role. Nevertheless, there are some factors critical to the success of de-veloping the Indian auto-component industry. De-tailed review of literature is done to identify these factors and named them determinants of competi-tiveness. Findings revealed that technology, R&D capabilities, D&D capabilities, developing status of allied industries, low cost advantage associated with the country, following global quality norms and developing the socio-economic status of the country’s population are some of the critical suc-cess factors to the Indian auto-component indus-try. However, government policies, nodal agencies, escalating demand condition, intensifying competi-tive rivalry and large number of choices available to the ultimate customer derive the industry com-petition as a whole. The study also discovered one fact that cost and delivery are the core competence of the auto component and ancillary industry. Any improvement in the effectiveness of the aforesaid factors will have a strong multiplier effect on the auto-parts sector. Moreover, the well-implemented

national strategies will advocate the growth of in-dividual auto-component manufacturers and finally the country as a whole.

The current research paper is entirely limited to secondary data obtained from various publica-tions of authorized sources. The above cited success factors are required to be tested and validated in auto component firms for generalizing the research studies. This leaves scope for further research too.

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multidimEnsionAl nEtWorks: thE ChAnGinG ChArACtEr And frAmEWork of intEr-firm CollAborAtion

Ploder, Michael1

Steiner, Michael2

The paper explores the form and content of eco-nomic interaction of firms based on various con-cepts of agglomeration and social networks. It uses a case study of the machinery sector in the region of Styria as empirical background.

Starting with types of clustering—the model of pure agglomeration, the industrial-complex model and the social-network model—the paper argues that given geographical agglomerations allow dif-ferent types of networks and different patterns of behavior, and thus different forms of learning, knowledge sharing and knowledge creation.

Some “stylized facts” in support of this perspec-tive are derived from an analysis of a regional net-work. This network comprises more-or-less individu-

1 Joanneum Research2 University Of Graz

alistic open systems consisting of several areas of overlap. Physical linkages between these networks are rather weak, but intersections based on coopera-tive R&D and R&D infrastructure, qualification and informal exchanges are clearly evident, and seem to dominate from a regional perspective. Despite evi-dent sectoral concentrations, direct links to the pre-vailing science base appear more significant as bind-ing factors than long-term supplier networks. These relationships are interpreted in terms of their need for proximity, their durability and above all their di-rection of knowledge dependency.

Keywords: Agglomeration, Knowledge Transfer, Social Networks, Evolutionary Economics

ABSTRACT


introduCtionWhile we are well aware that it is probably im-possible to provide one single theory of clusters and their networks, there is nevertheless a certain consensus that several elements of specific theories may help us understand their forms and functions. They, thus, offer a certain unity of approach in identifying the important elements that are needed for explaining the changing character of the inno-vation process.

Recent debate has begun to focus more on how far, and in which ways, clusters foster knowledge creation and organizational learning, and has em-phasized the organic-evolutionary dimension of cluster-based industrial agglomerations. Knowl-edge has been recognized as a major source of competitive advantage in an increasingly integrat-ed world economy (Dosi and Malerba 1996, Grant 1996, Foss 1999, Nonaka et al 2000).

The most successful regions are perceived to be those where firms display innovative capacity, i.e. firms are able to adapt to a rapidly-changing mar-ketplace and stay one step ahead of competitors.

The emphasis of cluster interpretation has changed from an analysis of forces of agglomera-tion to the various forms and contents of organiza-tional learning and knowledge exchange—the orig-inal concentration on clusters as mere geographic concentrations of sectors and firms has been trans-formed into a search for institutions for knowledge management and organizational learning empha-sizing the organic-evolutionary dimension.

Growth of the knowledge base depends on in-tended and unintended individual processing of experiences, i.e. ‘learning’, while the interpreta-tion, transfer and use of experiences is influenced by interaction between individuals and between organizations (Cohen/Levinthal 1989, Ander-sen 1995, Hartmann 2006). These insights have shifted the emphasis from material links to the immaterial knowledge flows within clusters, and have pointed to the need for connectivity between different agents concerning knowledge creation and diffusion.

This has then led to further questions concern-ing the degree to which clusters are to be regarded

as non-market devices by which firms may seek to coordinate their activities with other firms and knowledge-generating institutions. Ongoing learn-ing processes between firms and within clusters stress the importance of institutional arrangements for the generation of knowledge and learning net-works that are not available in markets (Maskell/Malmberg 1999). As the necessary knowledge may lie outside a firm’s traditional core competence, inter-firm alliances and networks are widely recog-nized as an important organization form of innova-tive activity (Gay/Dousset 2005).

In this paper, we again emphasize the ideas of agglomeration and knowledge exchange, and dis-cuss to what extent this approach has specific re-gional or spatial dimensions, while focusing on the necessity and forms of proximity, especially with respect to knowledge exchange.

By means of network analysis we then develop some “stylized facts” for the various dimensions of interaction within a given network of medium-tech firms in Styria, one of the nine provinces (regions) of Austria. The final section is used to interpret the findings.

GEoGrAphiCAl AGGlomErA-tion And loCAl nEtWorksSince Marshall (1890/1920), Weber (1929) and Hoover (1948), many authors have dealt with the phenomenon of geographical agglomeration. In the discussions of clusters, networks and agglomera-tions, and particularly in those relating to indus-trial districts and agglomerations, there are cer-tain common traits, and frequently terms are only weakly differentiated.

The basic idea of geographical agglomeration was brought up by Marshall (1890/1920) and the three sources of economies of agglomeration he mentions—input sharing, labor market pooling and knowledge spillovers—correspond with the core-elements of the current cluster-concept, at least in that form in which it has been discussed since the early nineties in industrial countries. A more re-cent attempt to distinguish various cluster forms has been made by Belussi (2006) by contrasting


geographical agglomeration and active clustering (as policy- or firm-driven strategy).

While implicitly focusing on geographical ag-glomeration and economies of agglomeration, we stress here a dimension of externalities beyond the tangible dimension of direct co-operation. On extending the basic idea of economies of agglom-eration, we see that externalities are widely en-forced by informal and non-economic dimensions. Amin and Thrift (1995) use the term “institutional thickness” to address the existence of a support-ing environment beyond firms (institutionalized co-operations and networks). Geographic agglom-eration (and concentrated versus dispersed location patterns) set a framework for economic interaction and (material and immaterial) linkages between economic actors.

The existence of a cluster doesn’t necessarily imply the coexistence of all defining characteris-tics of a geographical agglomeration. On the other hand, a geographical agglomeration may also exist in the absence of a cluster or network.

While the existence of a pure geographical ag-glomeration (e.g. a city) favors the development of clusters; growing networks and clusters can also cause the emergence of a geographical agglom-eration, as was the case perhaps in Silicon Valley in California. Myrdal’s (1957) idea of cumulative causation corresponds with a dynamic view of a co-evolutionary development of economies of agglom-eration and growing clusters (without yet formal-izing interdependency as was done by Kaldor, 1972 and Dixon and Thirlwall, 1975).

In other words, additional local linkages and re-lations strengthen tendencies of concentration and agglomeration. Networks and clusters are possible means of overcoming constraints of exchange with-in and between geographical agglomerations, and also facilitate the definition and defense of rules of exclusion, as already pointed out by Marshall.

Yet, what is still an open question is the micro-perspective. Economies of agglomeration and di-mensions of interaction could be selective in re-spect of the actors, since they regulate the extent to which the latter are able to participate or gain from externalities: e.g. with respect to exchange of

physical goods versus R&D, or labor market pools for blue collar workers or engineers.

In addition to direct physical exchange, input sharing and common labor market pools, system-atic knowledge exchange and knowledge spillovers have gained considerably importance as an argu-ment for geographical concentrations of activities. A frequently used argument is that the collabora-tive nature of innovation processes has reinforced tendencies toward geographical clustering because of the advantages of locating in close proximity to other firms in specialized and related industries (Storper, 1995, 1997). Transaction costs such as transportation costs and spatial communication costs in particular, reinforce the relationship be-tween individual environment and the development of embedded social networks (Granovetter 1994).

Firms establish a variety of types of interactions and relationships, each of them having different impacts on the knowledge generation and diffusion process. Mariotti and Delbridge (2001) speak of the necessity for firms—in the face of knowledge ambiguity, of knowledge-related barriers, of tacit-ness and complexity of knowledge—to engage in the management of a portfolio of ties.

Organizations are therefore likely to engage in inter-organizational relations that show a variety of types of ties:

They can have quite different dimensions and can be defined according to the character of social relations between actors, the regulation of the re-lationship, frequency of use, length and duration of the relationship, and also of course in terms of the nature of the information exchange itself (Mari-otti/ Delbridge 2001, 13). It is also important to distinguish between both content (i.e. the type of relation) and the form (i.e. the social structure of relations), as has been outlined by Powell/Smith-Doerr (1994).

One additional question which needs to be ad-dressed in this context concerns the legitimacy of a pure micro-level, individual firm approach in analysing the incentives for clustering.

Individuals and firms alone are, from an eco-nomic point of view, not capable of delivering suf-ficient amounts and varieties of knowledge. We are


confronted here with one of “the most troublesome issues in the social sciences …” (Felin/Foss 2006, 1) – the question of the adequate level and unit of analysis. The question of whether the individual or social collectives (firms, networks, regions …) have explanatory primacy is of course part of an old de-bate in economics, sociology and the philosophy of science and is often now dealt with under the heading of “methodological individualism” versus “methodological collectivism” (Hayek 1945, Pop-per 1957, Coleman 1964, Douglas 1986).

Further potential for conceptual differentiation relates to the forms, channels and mechanisms of knowledge exchange. As this exchange occurs through interaction, the structure of the interac-tion influences the extent of knowledge diffusion (Gay/Dousset 2005). This coincides within the view that “spatialities and temporalities are not neutral frames, but constitutive elements of socioeconomic transformation” (Colletis-Wahl et al 2008, p.22).

The cross-sectoral dimension of knowledge spill-overs is also a source of contention in the literature. Following Marshall (1890) and Arrow (1962), knowledge is predominantly industry-specific. Knowledge spillovers may therefore arise between firms within the same industry. Jacobs (1969), on the other hand, mentioned the significant fact that knowledge may spill over between complementary rather than similar industries.

The significance of geographical agglomeration and networking is strongly determined by the par-ticular sector (industry) and the leading technol-ogy. There seems to be a clear agreement in the recent literature about cross-sectional differences in agglomeration forces: As has been emphasized by Botazzi et al (2001, 2003) and also Gordon/ McCann (2000, 2005), huge inter-sectoral differ-ences in spatial agglomeration outcomes can be identified.

Following Gordon/ McCann (2000) agglom-eration economies appear particularly relevant in “scale-intensive sectors” - hinting at the forms of hierarchical agglomeration discussed above - and in “supplier-dominated sectors”. Conversely, they appear the least relevant in “science-based” sec-tors. The importance of agglomeration depends

closely on the prevailing sectoral and technological pattern.

The following argumentation takes up two ap-proaches to differentiating typologies and focuses on the different dimensions of agglomeration and clustering viewed as helpful guidelines in the dis-cussion of the network observed in Styria and in answering the key-questions of the empirical analy-sis. An attempt is also made to combine, and dif-ferentiate, the “agglomeration” approach with the additional insights mentioned above.

Gordon and McCann (2000: 15) define and discuss three theoretical approaches for industrial clustering that reflect different (more or less ideal-ized) perspectives on agglomeration—the model of pure agglomeration, the industrial-complex model and the social-network model.n The phenomenon of economies of agglomeration as an intrinsic motive for clustering, in the sense of spatial concentration of economic activity, is attrib-uted more or less exclusively to the traditional idea of Marshallian industrial districts. Following in the footsteps of Thünen in the field of location econom-ics, and Smith’s idea of division of labor, the model of pure agglomeration, which in the tradition of Marshall is based on a local pool of specialized la-bor, on the increased local provision of non-traded input specific to an industry, and on technological spillovers may contribute to an “evolving localized environment of learning” (Gordon/McCann 2000, 517). The Marshallian approach was quickly devel-oped and extended by Hoover (1948) by distinguish-ing between localization economies and urbaniza-tion economies. Following Marshall (1890/1920), positive externalities of agglomerations are defined by regional non-traded inputs, knowledge and in-formation spillovers, and a local pool of skilled labor. From the perspective of knowledge flows and learning processes favored by agglomeration, such externalities occur more or less unheard and unseen. Knowledge exchange and learning occurs unconsciously via transfer of human or material resources. The most important point seems to be that the approach is not bound to the idea of direct supply-relationships among the bulk of actors in-volved. Following the traditional idea of Marshal-


lian industrial districts, interaction is primarily led by the needs of industrial production. n A second group of approaches pooled by Gor-don/McCann (2000: 517) under the term of in-dustrial complex models systematically tried to justify spatial concentration by the quantifica-tion and minimization of spatial transaction costs (reflecting the origins of the approach, primar-ily transportation costs). The industrial complex model is associated with cumulative learning from sources inside the industry, non-transferable experience, the role of leading firms and power asymmetries (Iammarino, McCann 2005). Al-though the implicit concealment of (unplanned) economies of agglomeration didn’t mean that they were not relevant. Attention nevertheless shifted to innovation as an interactive process involving the sharing and the exchange of different forms of knowledge between actors (Lawson and Lorenz 1999)—knowledge and competence as developed interactively and within subgroups of a regional economy (Freeman 1979, Lundvall 2002). The critique here has been concerned with the question of whether this interaction is an outcome of (neo-classical) rational behavior or the result of a more ‘associative-relational’ mode of organization, or what has been termed ‘associative governance’, leading to the creation of clubs, forums, consor-tia and other institutional schemes of partnership (Cooke 1998; Cooke and Morgan, 1998). There are elements of knowledge sharing in the sense that adopting the perspective of specific clusters represents a quasi-monopoly for the internaliza-tion of the benefits of innovation created within the (more or less) “closed club”. n The social-network model as the third type—relying on trust and social embeddedness as the dominant link between the cluster firms (and therefore not on deliberate economic decisions based on the minimization of different transaction costs)—also favors the exchange of knowledge. However, such exchange is here based on strong interpersonal relationships that transcend firm boundaries and allow for diverse forms of knowl-edge sharing. Following Iammarino and McCann (2005), traditional and recent approaches of

social networks may be differentiated. The tra-ditional approach corresponds to the ‘Marshall-stimulated’ industrial districts where knowledge is mainly codified and oriented to process in-novation transferred by personal contacts, and social and political lobbying. While in the tra-ditional approach the network seems to be based on geographical proximity rooted in historical experience, the new approach of social networks seems to be based on relational and organization-al proximity. The links between actors are then stronger the more they are based on elements of social embeddedness: norms, sets of common as-sumptions, habits formed by culture, history, and of course, but not necessarily, spatial proximity. They form social capital that favors the explicit and implicit sharing of knowledge. New physical technologies and innovations do not just happen, they need social technologies as pathways to co-ordinate human action.

As Iammarino and McCann (2005) mention, much of the discussion in the literature is based on ideal types, whereas in reality all spatial clus-ters and industrial agglomerations will contain more or fewer of the above characteristics, fur-thermore, clusters may mutate from one typol-ogy to another. From another perspective, this is also outlined by Rychen/Zimmermann (2008, p. 768): the concept of cluster “usually considered as a spatial concentration of industrial and tech-nological activities” has to be enriched and “it is more important to understand how and why firms build links and how the structure of links will give sense (or not) to the co-location of actors.” It is therefore important to incorporate the dimension of collaboration—the basic conception of firms is a “network-driven economic strategy built on col-laboration among the participants” (Reid et.al. 2008, p.2).

The following section is dedicated to interpret-ing the case network investigated in the light of the approaches discussed above. The suppositions that context, typology and significance of geographical agglomerations and embedded networks change, seems to be clearly reflected in the case of the ma-chinery sector in the region of Styria.


thE EmpiriCAl AnAlysis: A QuAlitAtivE ApproACh bAsEd on soCiAl nEtWork AnAlysisThe empirical analysis starts with an analysis of relevant regional data and expert interviews and then continues with a case study analysis of the re-lations of engineering firms in Styria.

Interaction in the observed networkNetwork analysis is a well established method in the social sciences. Recently, the method has also been applied to the analysis of production clusters (Krätke 2002), innovative activity and knowledge exchange (Giuliani 2005), and alliance or R&D networks (Gay/Dousset 2005).

Social network analysis is a helpful tool for dis-cussing the structure of networks as it allows the mapping and measuring of the relationships (com-munication and transaction) between different ac-tors, i.e., the existence, context and portfolio of re-lations between actors in a regional network. It is a method for revealing relations between different actors. Such relations are phenomena that cannot be reduced to the properties of individual actors or firms themselves and thus need to be interpreted as properties of systems than of individual actors.

The Empirical DatabaseThe present network analysis is based on an em-pirical sample of firms identified by a snowball-ing method of sampling in cluster and network investigation. This corresponds with the relational approach and is developed by means of the refer-ences to actors as revealed by previous respondents (Frank 1979, Scott 2000). 1

Our starting point was a large system supplier in the automobile sector located in the region of Styr-ia/Austria. The snowball method produced firms belonging to different sub-sectors of the manufac-turing sector and related supply-chain and innova-

tion-strategies. Starting with the initial firm, the sample was developed. Following a citation path of regional suppliers (production or commercializa-tion of goods and services) and of regional partners in the field of research and development (coopera-tive R&D and related activities and exchange, the database for the subsequent network analysis was extended to 23 firms, of which 18 are producers (with different positions in the supply-chain such as system-suppliers, component suppliers and toll-manufacturers). The remaining five are technical business services. Additionally nine R&D institu-tions (universities, co-operative R&D institutions) are included. The information and data collected are based on extensive qualitative interviews and supported by a quantitative survey concerning spe-cific data.

Indicators of Interaction Qualitative indicators revealing individual strate-gies of innovation are helpful discussing individual strategies and their aggregation at the network level. They are selectively used here to find—via network analysis—the structural features of the network of 32 actors. The selected indicators of the relations cultivated by the organizations cover three dimensions of interaction: direct delivery re-lations, R&D, and technological innovation in a competitive and a pre-competitive context.

(DELIV): The firms were questioned concern-ing direct delivery relations (goods or services) to clients, suppliers or partners (in the case of syn-ergetic product bundles).2 The direct delivery of goods and services is not reduced to the material dimension as it also covers questions of innovation in information management or capacity-extending investments.

(PRE-COMP): The dimension of interaction in the context of pre-competitive R&D was also ana-lyzed. Pre-competitive research and development aims to extend the product spectrum, as well as introduce new processes and alternative materi-

1 The assumption is that the segment of the network that forms the sample is representative of the whole network. More exact knowl-edge of present population and relevant relationships is obviously necessary. However, results from an earlier investigation support the accuracy of the present sample technique.


als. It includes fundamental research, which is an activity designed to broaden scientific and tech-nical knowledge not necessarily linked to indus-trial or commercial objectives, as well as indus-trial research, i.e. research aimed at developing or improving new or existing products, processes or services in so far as it is also not directly con-nected with a client tender, offer or an existing business relation.

(COMP): Competitive research and develop-ment and innovation processes are short- and medium-term oriented and mostly associated with direct expectations of return or with a direct tender or offer etc., which is in contrast to pre-competitive R&D that is long-term oriented.

Structure of Network and Network DensityFollowing the socio-centric approach, the density of a network is given by the ratio of relations real-ized to the total number of potentially maximum possible relations. We dichotomized the relations in that we only differentiated between existence and non-existence of a relation between two actors [0; 1], and therefore disregarded the intensity of the relations (in our case the frequency of interac-tion) surveyed. This enabled us to avoid the prob-lems typically associated with the measurement of the intensity of evaluated graphs (Scott 2000). Network density yields information on the general structure of the network as a whole.

One of the core features of an actor identified in network analysis is its centrality. Using the concept of centrality (in different forms) we gain insights into the specific features of the interaction of the actors in the network and their specific position and/or em-

beddedness in the network. While density focuses on the properties and general structure of the network as a whole, centrality tries to capture the position of individual actors or groups of actors within the net-work. This is again based on the relations revealed by the actors, where the relations are valued ordinar-ily in terms of frequency of interaction. The poten-tial centrality of an actor is determined by a broad range of industry or sector-specific factors (Cohen et al 2000), by capacity and individual motivation (Bayona et al 2001, Theter 2002). A high centrality is positively associated with multiple possibilities for receiving and generating knowledge.

Keeping in mind that interregional and interna-tional relations exist and may be of major priority, e.g. direct delivery relations, the analysis below fo-cuses on regional interaction. Table 1 presents the density measure for the three dimensions of rela-tions between the actors.

Direct delivery relations have the weakest den-sity. Although the datasets have been dichotomized and therefore relations with a very low frequency of interaction have been “up-graded”, the density of the network of direct delivery relations is lower than the density of knowledge-intensive and inno-vation-related interaction. Regional input-output relations were reduced in order to focus attention more on international markets.

While competitive R&D and innovation process-es, especially in the case of domestic system suppli-ers, are partially similar in density to direct deliv-

2 The dimension of supply-chain networks is a function of verti-cal integration and division of labor in an industry. The auto-mobile and aerospace industries are favorites in supply chain networks and relations. They are, however, special cases as middle or high volumes of products, with a relatively high number of individual parts, are produced by specified rou-tines. Regional clients in other areas of the machinery sector and their limited lot or customized orders place constraints on medium- and long-term planning, automation and growth. This approach was not used that extensively in the machinery sector. Given the importance of the systems subcontracted by assemblers, a clear strategic goal of these firms is working with a smaller number of large suppliers.

3 Even in the case of a network of 32 actors with a relatively low density the number of cross-cutting relations is relatively confusing, even more so with a network density of 0.223.

Relational Dimensions

Density

(Deliv) Direct Delivery Relations 0.068

(Pre-Comp) Interaction In The Con-text Of Pre-Competitive R&D

0.143

(Comp) Interaction In The Context Of Competitive R&D And

0.074

Table 1 Density of Observed Dimensions of Net-working


ery relations, the regional density of the network in pre-competitive R&D is much higher. While R&D institutions are of negligible significance in respect of direct delivery relations, the network is based to a considerable degree on relations with cooperative R&D institutions.

The relational data can be used to provide a graphical representation of the transaction network for the organizations observed. While network dia-grams offer a traditional and basic methodology for formalizing network analysis, and are a very helpful mean of interpretation and discussion, clarity suffers greatly as the number of actors observed increases.3

A quite useful method of graphical represen-tation, which is implemented in most software packages, follows the approach of Kamada-Kawai (1989) spring embedding algorithm. This is now employed below.

Figure 1 gives an overview of all relations re-corded, and combines the three dimensions dis-cussed above. It also takes into account the valu-ation of the relations in terms of frequency of interaction. The shape of actors (nodes) corresponds with the different types of organizations. The size of the nodes corresponds with the size of the orga-nization, and the length of lines corresponds with the distance between the actors observed.

A further interesting dimension of network analysis is ‘coreness’, which follows the idea of core and periphery. Here we use the concept of the k-core (Seidman 1983, Scott 2000). A k-core is a sub-graph in which each actor is adjacent to at least k other actors in the sub-graph. That is, for all nodes in the sub-graph minimum the number of the actors’ direct relations within the sub-graph is k (in our case eight). K-core analysis comple-ments the measurement of density, since the lat-ter is not able to reflect structural features of the network. The k-core is an area of relatively high cohesion. As can be seen at first glance, we can differentiate between those actors in the core of the network (colored black) and those actors more or less on the periphery of the network (colored white). The diagram reveals the high density of the realized relations calculated in the previous paragraphs. In the k-core of the diagram, we find a group of institutions that seem to interact mul-tilaterally. In the “core” of the network, we find R&D institutions, large system suppliers and toll manufacturers (surface-treatment, heating etc.), which maintain multiple, but weak relations, with a broad range of regional clients.

Spotting a Leading Firm in the NetworkHere we now focus on a specific firm, ss 20 in the total network. This is a highly specialized manufac-turer of measuring equipment for science and indus-try. This success is based on the direct application and transfer of scientific knowledge gained in the measurement of physical or chemical phenomena.

The firm is highly vertically integrated and is embedded in smaller networks following niche strat-egies. The partners of the firm in direct delivery (component and toll-manufacturers) and its part-

systems supplier

component supplier

toll manufacturer

technical business services

R&D- institutions

systems supplier

component supplier

toll manufacturer

technical business services

R&D- institutions

Source: Present Authors

Fig 1: Network of Firms and Knowledge Generating Institutions


ners in competitive and pre-competitive research and development (key clients, highly specialized business services, universities) are not identical.

On the delivery side, the observed firm interacts with component suppliers in the field of die cast-ing, spray casting, plastics processing, electronics, sheet metal forming, and manufacturing of high performance glasses.

Originally, the firm was a pure converter, produc-er and specialist in marketing. This division of labor has changed since the 1980s. A well-established co-operative base allows access to university partners and to an independent research laboratory that pro-vides exclusive, science-driven R&D. The firm enjoys a relatively high in-degree centrality in respect of di-rect deliveries. The out-degree centrality of the firm in the region, with respect to deliveries, is consider-ably low bowing to the high export intensity.

A high share of the turnover is reinvested in R&D activities, 10% for intramural R&D and an additional 10% of the turnover for external R&D. The degree centralities in respect of R&D (pre-competitive and competitive) are higher than for the average of the leading firms in the network. The core competences of the firm are based on combin-ing and applying findings from basic research, in precision engineering and electronics.

While radical innovations and market novelties mostly emanate from R&D or client-partners, in-cremental improvements are promoted by internal R&D. R&D and production and marketing of new products are concentrated within the region.

As the firm is not located in the core of vehicle manufacturing, but in the interface with other sectors such as manufacturing of plastic products or mea-surement techniques, it has a relatively high value for betweenness centrality. The findings for this typical firm serve to strengthen the thesis that firms acting in market niches, demanding highly specialized coop-eration, tend towards long-term cooperation.

The Historical Background and Changing Role of Geographic Agglomeration in the Medium-Technology Sector in StyriaThe majority of the observed firms have been in the region for more than ten years. The current situa-

tion and recent developments cannot therefore be adequately analyzed without considering the his-torical background and structural change of re-gional industry over the last few decades.

In the late 1960s and 1970s, the networks in the medium-technology sector were dominated by large state-owned firms that were highly vertically integrated and had lost their headquarter functions to Vienna. While supply-side linkages to the region still existed, agglomeration took a very limited tra-ditional form. In most cases, planning, R&D and marketing/distribution functions, i.e. those func-tions responsible for the monitoring of markets and technology, had been lost. Clearly, observable lock-in effects had led to agglomeration becoming a mere by-product of path-dependence with none of the advantages of agglomeration mentioned by Botazzi et al (2001).

Against the background of a history of out-ward dependence and nationalized standardized mass production, the traditional indicators used to measure the strength of social networks had become very weak. According to Iammarino and McCann (2005), social networks exhibit the fol-lowing characteristics—knowledge is largely codified and mature and mainly oriented to pro-cess innovation, transmitted essentially by way of personal contacts, and there is extensive social and political lobbying, backward and forward linkages. As far as social networks still existed (e.g. in the machinery and the automobile sector), they became a fruitful base for the restructuring of the 1990s.

During the developments of the last few de-cades, the typology of agglomeration and the role of networks have changed considerably. Many large firms were re-privatized and down-sized at the end of the 1980s. Firms, thus, needed to learn to col-laborate and develop their potential for innovation as a strategic resource. This entailed abrupt, and long overdue, change from a Fordist to a more flex-ible mode of production.

A massive structural change took place, begin-ning in the 1990s, especially in sectors related to steel production, such as mechanical and automo-tive engineering. High degrees of diversification


and broad unspecified clienteles were replaced by a focus on market niches and technological spe-cialization, while higher lot sizes enabled higher cross-functional integration and raised flexibility by leaving scope for automation. Technological up-grading (including the introduction of quality and measuring standards) also opened doors to a new clientele. This was accompanied by extending of their responsibilities for tool making and sourcing capabilities, and also by shifting the responsibility for quality and price from clients to suppliers. In-novations in these sectors were influenced by ap-plications of specialized knowledge in the field of materials, tooling and processing techniques, or by the need to solve very specific problems in the machinery sector, on the supply side, hierarchical, spatially localized relations were developed. These have been formed around the elite R&D-intensive and export-oriented large firms.

Human Resources and the Regional Labor MarketA typical characteristic of agglomerations, in the sense of the model of pure agglomeration mentioned by Gordon and McCann (2005), and also following Botazzi et al (2001)—namely, a more or less com-mon labor market pool—was not observed.

For the investigated component supplier firms (here in more-or-less rural and isolated areas) it is still the case that they operate with reference to very local labor markets, binding traditions and a low mobility of employees. Small- and medium-sized supplier firms exhibit family-based traditional struc-tures, sometimes over generations. Concerning the qualification structure, there are deep differences between original equipment manufacturers (OEMs) or system-suppliers with R&D units on the one hand, and basic technology providers, extended work-benches or third-party subcontractors on the other.

This is true for both lower- as well as high-skilled workers, where employee turnover is normally a more-or-less accepted instrument of knowledge transfer and networking among firms. Because of the immobility of the local labor force and the re-stricted capacity of the regional labor market, most of these firms were able to retain the key-personnel

and competences and the regionally integrative po-tential of their personnel. Yet, by the same token, this implies only little mobility of qualified person-nel coming from Europe (for language reasons, predominately from Germany). Also due to official restrictions, labor inflow from the new EU member countries remains limited.

Discriminative Capabilities and Heteroge-neous Strategies in the Case of R&D and In-novationAs already mentioned, leading firms do not play a dominant role on the demand side. The broad range of material input-output linkages is directed out-ward and direct material linkages on the regional level (corresponding to the industrial complex mod-el mentioned by Gordon/McCann) are considerably weak. In fact, the opposite seems to be true. In the case of large firms, agglomeration phenomena based on knowledge complementarities (Botazzi et al 2001) seem to be clearly evident.

The R&D capacities of the observed firms were highly varied. Nearly half of the investigated firms (mostly SMEs) do not employ permanent R&D staff. The leading firms have intensified R&D ac-tivities and formal co-operation with knowledge-generating institutions since the mid-1990s. Especially in the case of pre-competitive R&D, co-operative publicly-supported projects or participa-tion in cooperative R&D institutions has gained an increasing role as a policy measure during the last decade.

In respect of knowledge-driven activities, ele-ments of agglomeration phenomena based on knowl-edge complementarities were observed (following Botazzi et al 2001). These were also in line with the exclusivity characteristics suggested by the industrial complex model (Gordon and McCann 2005). The large R&D intensive firms observed here constantly seek forms of regional pre-competitive R&D coop-eration. This may result in the formation of “Clubs”

5 The Competence Centre Program was introduced in 1998. Competence centers are co-financed by the regional govern-ment, the national government and the active partners. A considerable part of co-operation involves third parties (pref-erably SMEs).


(Gordon and McCann 2005, Cooke 2000) of closer interaction especially in respect of R&D, or in some cases cooperative R&D institutions. While material input-output linkages are spreading widely, and are outward oriented, the R&D-oriented sphere is con-centrated on the local context and to a large extent supported by intensive direct and indirect social in-teraction (informal exchange, contacts in the local technical community). During the past few years, in terms of innovation, firms already active in R&D have undergone a shift from being demand-pull-driv-en (responding to market demands) to technology-push-driven (firms have become proactive in their search for new technologies and USPs). This has in-creased the motivation to be integrated in the region-al (technical) science community. The main spheres of economies of agglomeration have shifted consider-ably during the last few decades. The newly identified research ‘Clubs’ in publicly-supported R&D projects are able to utilize economies of agglomeration pri-marily concentrated in the field of R&D and science.

As long as natural spillovers are high and com-petitive conflicts are manageable (e.g. in the case of material sciences), larger firms accept weaker partners, and/or smaller firms, and are willing to integrate them into their activities. Low spillovers and a higher market orientation favor more re-strained, sometimes exclusive, behavior from the stronger side. This corresponds with the findings in the literature for partner selection in R&D coop-erations (Atallah 2005).

This form of agglomeration, partially taking place beyond formal networks, also corresponds with the idea of a new type of social network men-tioned by Iammarino and McCann (2005). Firms engaging in cooperative pre-competitive R&D and knowledge generation appeared to seek suitable equal partners.

The qualitative interviews strengthened the no-tion that firms attempt to generate a portfolio of cooperative partners, which consciously combines specialization and flexibility. In terms of knowl-edge generation and exchange, the geographic di-mension is relevant as long as the actors are able to utilize knowledge potential. While larger firms with noticeable R&D capacities are able to utilize

international contacts in research and development activities, smaller low- or medium-tech firms stick to the region and to their regional partners. Small-er firms are confronted with a self-reinforcing com-bination of low R&D capability on the one hand, and limited market demand on the other.

In agreement with the concept of absorptive ca-pacity, it was found that firms with low R&D and innovation potential (mainly component suppliers, where innovation is predominately directed by in-vestment) found it difficult to build up and retain adequate relations with knowledge-generating or-ganizations. The medium-tech component suppli-ers observed here, proved to be unable to maintain continuous relationships with knowledge-generat-ing institutions. They were not capable of defining, setting up and managing relevant projects. These low and medium-tech firms did, however, partially utilize opportunities to establish long-term contacts with individual public or semi-public R&D institu-tions (dealing with basic technologies mostly mate-rial sciences). They also tried to gain from possible spillovers from per appropriate events or informal inquiries. Here, partner behavior in direct delivery and in competitive and pre-competitive research and development, as far as existent, is not identi-cal. While cooperative R&D and knowledge gener-ation of regional SMEs are relatively seldom, and supply-chain relations are dominated by extra re-gional linkages, low- and medium-tech SMEs gain from knowledge-sharing in respect of quality man-agement, information management and promotion of the location by formal cluster organizations.

In addition, two interesting long-term partner-ships between small knowledge-intensive technical business services and large systems and component suppliers were observed, in the network analyzed here, and were based on long-term trust and infor-mal exchange.

ConClusionGeographic agglomerations, on the one hand, and networks and clusters on the other have to be in-terpreted as interdependent phenomena. The roles of clusters, networks and geographical agglomera-tion are subject to considerable co-evolution. Dif-


ferent approaches concerning forms, channels and mechanisms of knowledge exchange offer different conclusions with respect to the significance of geo-graphical agglomeration in knowledge exchange.

In the case study analysis, different dimensions of interaction can be observed. There are network-ing-dimensions of material, supply-oriented trans-actions, and networking-dimensions of knowledge sharing. The first belongs to the process of division of labor dealing with the exchange of goods and services, the second with knowledge. The main dif-ferences reside in the form of interaction and in the impact of interaction. The spheres of physical interaction (subcontracting relations) differ consid-erably from the spheres of knowledge-intensive and R&D-driven interactions. They are different in re-spect of actors involved, spatial extension, and thus significance of geographic agglomeration.

The observed network is, in its regional dimen-sion, dominated by knowledge-intensive relations. The qualitative evidence gathered by numerous in-depth interviews reveals that the highest number of interactions was reached in pre-competitive R&D knowledge exchange and that immaterial dimen-sions dominate the material ones. The (industrial) firms do have extensive supplier relations, but only to a very limited extent within the region and within the network. There is no automatic parallelism of interactions. This does not necessarily exclude au-tomatic spillover of knowledge connected with sup-plier relations, but it does emphasize that higher intensities of knowledge exchange, as indicated by the revealed forms of interaction are actively cho-sen and not a mere by-product. Knowledge-oriented relations within the network are regionally concen-trated to a large degree. Proximity per se is not suf-ficient to generate knowledge between firms. The diffusion of knowledge within clusters is highly se-lective and strongly depends on the position of firms within networks and their absorptive capacity. Local universities and cooperative R&D institutions have a dominating role and assume gate keeper functions, especially in pre-competitive research. Firms with a relatively high R&D capacity also take up such a role, thus indicating the necessity of a well-devel-oped internal knowledge base. The dominating role

of the newly-founded cooperative R&D institutions (competence centers) can be taken as an indication that this kind of network relation is rather new and that the pattern of interaction has a temporary char-acter, and depends on the existence of specific kinds of knowledge-generating institutions.

In the Styrian case, the main dimensions of economies of agglomeration have changed consid-erably during the last few decades. The portfolio of interactions and the meaning of agglomeration for the observed firms cannot be reduced to specific di-mensions taken as given or not. To this extent that they are determined by firm capabilities and firm behavior, not all dimensions of agglomeration, and thus economies of agglomeration, are accessible for all agents. While small- and medium-sized firms partially gain from economies of agglomeration in the field of basic technologies such as material sciences or tool making, large firms concentrated pre-competitive research in the region in order to gain from economies of agglomeration in the field of science and R&D.

These agglomeration effects still seem to be con-centrated around certain insider ‘clubs’. A consid-erable number of firms investigated are not able to participate and gain from economies of agglomera-tion. While there is a long tradition of pro-active cluster and network promotion in Styria, sectoral diversity (i.e. a low critical mass of actors) and relatively low absorption capacity serve to hamper the potential gains from economies of agglomera-tion for a considerable share of SMEs.

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WhEn poliCy GoEs ClustEr: rEflECtinG thE EuropEAn WAy(s)1

Rehfeld, Dieter2

1 In times of network and knowledge society, all research is embedded in collective structures. Thanks to Saskia Dankwart and Anita Pöltl for all support from additional research to language washing. Thanks to Judith Testriep for a lot of discussion and ideas.

2 Institute for Work and Technology/University of Applied Science, Gelsenkirchen

introduCtionIt is obvious that cluster activities are different around the world. In simple words, while Ameri-can activities are first of all business-driven, European activities are often policy-driven (Ketels 2003). In Europe, the European Union and structural funds have become few of the driving forces in early cluster-related initiatives. Cluster policy followed with best practice in cluster initia-tives could be studied. Despite success stories about cluster initia-tives, there are different ways of implementing the cluster approach in policy in Europe. Regional and national governments fol-lowed their own way de-pending on the specific cultural and political paths and the economic base. No wonder the cluster ap-proach became more and more “fuzzy” (Marcusen 1999) in the course of success.

Meanwhile, management studies as well as re-search in economics and economic geography did contribute to a deeper understanding of the struc-tures and processes of cluster development (Asheim/Cooke/Martin 2006). There is a difference, though, between how clusters develop and work in a suc-cessful way on the one hand, and how to initiate or influence an evolutionary proc-ess (Boschma/Frenken 2005) like this by political strategies and instruments on the other. The second question re-quires deeper understanding of political processes because it is well-known that policy follows rules and conventions that are different from economic ones.

In order to fill this gap, this paper is about clus-ter policy from a political science point of view. It starts with a brief outline of the context of cluster development, and then it discusses why the cluster approach became so dominant in all fields of eco-nomic policy. Going on, it attempts to work out what happens when an economic success story becomes the focus of political pro-grams. The key argument in this context is that the differences within cluster policy in Europe can be explained by the specific national or sub-national strategic traditions and cultures in eco-nomic policy. Despite those differ-ences, there are some key problems that result from different logics in policy and economy, and can be studied as dilemmas that can be rebalanced, but never solved by cluster policy. Nevertheless, cluster policies have innovative impacts on political strate-gies for two reasons. Firstly, a cluster policy takes place in the context of multi-level policy and this means that different political levels influence each other. Secondly, a cluster policy implies new modes of governance or at least a recombination of given modes of governance. In so far, cluster policy has an experimental dimension. Finally, some conclu-sions are presented about the challenges needed to improve cluster policy.

To avoid misunderstandings it is best to start with some key definitions. In this paper cluster resp. cluster development means the autonomous and evolutionary economic processes that are driven by the benefits of spatial density and re-


gional concentration. Cluster initiative refers to bottom-up, in most cases locally-driven, activities of self-organization of private (and often pub-lic) actors that aim at fostering or strengthening the local clusters. Cluster policy refers to strategic ap-proaches of central state activities that promote and support the implementation of cluster initiatives by a broad range of instruments that start with sup-porting self-organization and end with more-or-less top-down planning instruments.

thE ContEXt of ClustEr dE-vElopmEntClusters are not really new in economy. The stud-ies of Alfred Marshal in the late 19th century are a point of reference in most cluster studies, but spatial inequalities and regional concentration had been broadly discussed in economic studies in this century (Scheuplin 2006). This is not the place to tell the story of cluster studies in the last decades. There are good reasons to assume that clus-ters have been an important aspect in the spatial divi-sion of labor in the course of the 20th cen-tury, too. For instance, the automotive industry has been clustered at a very early stage of the development of this value chain. In Germany, the clusters that can be studied today had been established in the 1930s (Rehfeld 1999). Nevertheless, we can as-sume that in the course of mass production, stan-dardization of the value chain, internationalization and global diffusion of pro-duction technology, the local environment lost strategic importance in busi-ness strategies and in academic studies as well.

When the end of standardized mass production became inevitable, the spatially differentiated pat-terns of spatial division of labor came back on the global maps. Piore/Sabel (1984) worked out the importance of regional networking for the rise of more flexible production systems and in regional studies (cf. the retrospective view in Cooke 2009) successful regional innovation sys-tems (the “holy trinity” of regional studies refers to Third Italy, Silicon Valley and Baden-Württemberg). In the end, it was Porter’s research on the competitive advantage of nations (1990) that gave the decisive

impulse to pay more attention to cluster develop-ment in policy as well.

In brief, there are four trends that are important in order to understand the new interest in clus-ters. These trends are societal, but they all have in com-mon a specific focus on the regional level, they are overlapping, and are strongly related to the cluster approach (see figure 1).

Firstly, in the course of the last two or three decades, there was a fundamental change in com-pany culture (Boltanski/Chiapello 2003, Castells 1996) driven by different factors:

n Companies became more embedded in value chains than years before (this means, there is a new balance between market relations and network re-lations).n They faced rising insecurity caused by changes in innovation speed and complexity (net-works are helpful in reducing several of these insecurities).n Rising integration of technology, production and service function requires more internal and exter-nal cooperation, and a related absorption capacity of companies’ organization.n Globalization requires a deep understanding of the specific impacts of different markets and the interaction of different cultures.

This change went from a more-or-less lonesome rider culture to a network culture that influ-enced and partially changed the whole companies’ cul-ture, and did not start in clusters. In com-parison to former decades, this change raised companies’

Fig 1: The Context of the Rise of the Cluster Ap-proach

Search of new policy strategies

DecentralizationRegionalization

Global shifts: New role of regions in a global spatial division

of labor

Rise of the network economy "Entgrenzung"

Cluster Approach


awareness of the region and encouraged compa-nies’ embeddedness in clusters.

Secondly, hand-in-hand with the rise of the network economy, the spatial division of labor is changing. The balance between national, state and local or regional areas is rebalancing (Sas-sen 2008, Rehfeld 2009). From a business point of view, regions became more important than the na-tional environment. Even if this is studied by differ-ent concepts (agglomeration, cluster, met-ropolitan areas, or world cities), there is a strong focus on the reasons and impacts of spatial con-centration on business activities.

Thirdly, in Europe the last decades became the high-time of regionalization and decentralization (Hooghe/Marks/Schakel 2010). Nearly all Eu-ropean countries started a reorganization of the political institutions that was driven by the idea of decentralization—more than a new division of responsibilities between the different political and administrative levels. It refers to the search of new modes of governance, especially to public-private-partnerships, to activating instruments and to learning processes (Benz et al 2010).

Summing up, the new spatial division of labor and the rise of the network economy go hand in hand and related decentralization and regionalization in the political-administrative system gave space for new activities that corresponded with this econom-ic change. Clusters are of importance in all three aspects. We can suggest that fourthly they work as the missing link that gives policy the chance to re-organize institutional and strategic terms, and face the economic change in a more successful way. The next section will discuss why the cluster approach not only became an economic success story, but a self-enforcing process in policy as well.

thE risE of ClustEr poliCy Cluster policy is a late comer on the cluster agenda, though there are differences. Austria and Finland are pioneers, France and the German federal state Baden-Württemberg hesitated for a long time, the Middle and Eastern European countries are somewhere in-between, and Turkey is just start-ing. Lower Austria, Grenoble resp. Rhone-Alpes in

France and Tampere in Finland functioned as early birds. West-Midlands in the UK, Wolfsburg and Dortmund in Germany and Catalonia in Spain were some of the most prominent followers.

Today, nobody really knows how many cluster initiatives are active in Europe. The European Cluster Organization Directory (2010) lists 1205 cluster organizations in 216 regions, but there are lots of initiatives—like the privately-funded initia-tives not listed in public documents—that are miss-ing in this list.

The key impulse for cluster policy came from two sides. On one hand, successful cluster initia-tives had been established bottom-up. On the other, international activities contributed to the dissemi-nation of the cluster approach. The World Bank conference in Mexico in 1997, the insti-tutional-ization of The Competitiveness Institute (TCI), the Cluster White Book (2003) and the Cluster Green Book (2004) are some of the milestones in interna-tional cluster discussion.

In the European Union, cluster policy became a strategic key issue in the context of the Lisbon Strategy. Program lines like PAXIS, ProInno, In-nova or KIS aimed at organizing and disseminat-ing: good praxis, supporting networks between Eu-ropean clusters in order to organize shared learning and to improve capacity building in emerging clus-ters and EC-policy moves towards strengthening world-class clusters (EC 2008).

Broadly speaking, national states and federal states have been the last actors in the field of clus-ter activities. The dynamics of former activities were such that the central or federal state became involved in the process. There are four reasons why the cluster approach became so prominent in policy.

In strategic terms, the cluster approach filled a gap in economic policy. The idea of a support driv-en macro-economic policy that became the leading idea in the 1980s and 1990s, in combina-tion with the hope of rising service industries that compen-sate the rising weakness in productive industries, became outdated with the crisis of the new econo-my around the turn of the century. The cluster ap-proach gave the ideas to fill both gaps: to reinvent


meso-economic policy combin-ing regional and sec-tor issues, and to renew the interest in productive industries in a future-oriented way.

In institutional terms, cluster policy is a chal-lenge for the traditional institutional setting in Europe. Departments of different ministries had been complementary with industrial associations that often represented a sector and not a value chain. Regional activities had been focused on a small local level with strong administrative bor-ders. Bottom-up cluster initiatives showed that it is possible to overcome those institutional limits and cluster policy hopes to renew the institutional setting for economic policy.

In instrumental terms, the fuzzy character of the cluster approach makes this approach fit in different philosophies in economic policy. You find versions of cluster policy that are based on hard incentive and planning on one end and ver-sions that try to activate private actors on the other, an aspect that will be discussed in more detail in the following section.

The embedding in national philosophies on how to drive economic policy especially explains the variations of cluster policy in Europe. Nev-ertheless, there are three basic assumptions in all vari-ations of cluster policy (see fig. 2). This is not the place to discuss the reliability of those assump-tions because they are handled as quasi-

Fig 2: Key Ideas of the Intervention Model of Cluster Policy

© 2007 IAT – own illustration

Cluster-management

FP1 FP2 FP3

Cluster-politik

externe Rahmenbedingungen

Cluster

ClustereffekteKoordination

Innovation t0

Innovation t 1

Spill-over-Effekte

Cluster-management

FP1 FP2 FP3FP1 FP2 FP3FP1 FP2 FP3

Cluster-politik

externe Rahmenbedingungen

Cluster

externe Rahmenbedingungenexterne Rahmenbedingungen

ClusterCluster

ClustereffekteClustereffekteKoordination

Innovation t0

Innovation t 1

Spill-over-Effekte

realities in cluster policy and in so far they are a social fact (Durkheim 1961):n Clusters are more the innovative spatial and functional core in a knowledge-based global econ-omy.n The potential of clusters is high and can be mobilized. The expected synergetic effects espe-cially promise a new dynamic in competence and innovation.n Policy has the knowledge and the strategic ca-pacity to make the potentials work in a dynamic and self-enforcing way.

Following these key ideas the basic model of intervention entails the following aspects (fig. 2):n There is a need for deciding what clusters (where and who) promise good results when they get political support.n The different fields of economic policy (labor market policy, technology and innovation policy, regional policy, infrastructure policy) have to be coordinated. n The implementation needs strong cluster ini-tiatives that are based on a commitment from the companies. n If this process works, it helps to improve the development of the cluster in a synergetic way that brings out spill-over effects that work as in-novative drivers in the national econ-omy.

From a political point of view, this approach is near to the task to square the circle and can be studied by the dilemma approach (Prud’homme/Dankbaar 2007):n Policy, especially in European welfare states has strong legitimating from equality and co-her-ence. Cluster policy needs to select and focus on the strong actors (“strength-en the strength”).n The different fields of economic policy are em-


bedded in very specific institutional con-texts and networks, and there is a lot of doubt about the chances of coordination.n Implementation needs bottom-up activities, but there is no guarantee that the interest of those activities matches the top-down interest of cluster policy. n Cluster initiatives, even well-running ones, are only one aspect in a broad range of factors that influence cluster development. So far, evaluation failed when they tried to isolate the impact of economic policy and evaluation has always been based on plausibility and indi-rect indicators.

The consequence is not that cluster policy has no chance, but that we have to be careful when we discuss the expected results.

Map 1: Biotech Regions in Germany

BMBF 2005

hAndlinG dilEmmAs in ClustEr poliCy: tAsks And illustrAtionsThis chapter aims to discuss the way policy handles the dilemmas that have been discussed in chapter three. The first dilemma is to select promising clus-ters, which means the question of who and what. Discussing this aspect we have to keep in mind that clusters are selective by definition in at least two ways.

First, in regional terms, clusters base on con-centration. The higher the concentration of related variety (Boschma/Frenken 2005) of economic ac-tivities (including research, education, qualifica-tion and so on), the more dense the interaction (in-ternal as well as external) and higher the chance of dynamic cluster effects. Therefore, cluster policy

in ideal terms has to focus on a small group of promising clusters. To illus-trate this dilemma, the case of the Ger-man biotechnology cluster is of inter-est. The idea was great. Germany was a late-comer in biotechnology. It was lag-ging behind in the 1970s and 1980s, but in the late 1990ies the situation got better. There are different reasons for the rising dynamic. It had to do with the rising presence of international ven-ture capital companies in Germany, and with innovation in measurement and analytic meth-ods and equipment. Fur-ther, all activities of sector formation speed up: professions in education by new curricula, different fairs, building of an business association (biotechnol-ogy had been em-bedded in the chemi-cal companies association before) and so on.

The most cited reason for take-off is the success of the bio-regio-competitive call that was initi-ated and organized by the German Ministry of Research and Technology in the second half of the 1990s. This competitive call is of special interest in our context because it aimed


Brandenburg North-Rhine-Westphalia Bavaria

Biotechnology Biotechnology Biotechnology

Aerospace Aerospace

Media/IT ITC ITC

Media

Creative industries

Automotive Automotive Automotive

Energy economy Energy economy

Oil/Bio energy Energy research

Geo Science

Wood industry

Plastics Plastics

Logistics Logistics Logistics

Optic Nano-Micro Nano

Paper industry

Railway Railway

Food industries Food Industries Food Industries

Tourism

Environmental Technologies



Health Care Medical Technologies

Medical Research

Mechanical engineering

Mechatronic/Robotic/Production Systems

Chemistry Chemistry

Financial services

at strength-ening the most innovative and best or-ganized biotech-regions. Regions had been asked to work out cooperative development strategies includ-ing crucial issues like venture capital, public ap-provals, university-company ties or specialized in-frastructure. Due to the aims of the competitive call, the three leading bio-technology regions (Rhineland, Mittlerer Neckar, and Munich) were pointed out as winners and one East-German Region (Jena) was put in as a support region be-cause of its special competence in biotech equipment.

Thus far, the story looked good if we think about cluster building. Unfortunately, soon it became ob-

vious that the losers did not accept the result. Up to twenty regions were involved in the com-petitive call and most of them had the feeling that they did a good job, has high potential, and they build up a shared vision. They tried to find new ways to get funded, and because Germany is a strong federal political system, most of them applied for fund-ing by their federal state govern-ment. The federal states programs, additional programs by the Ger-man Ministry of Research and Technology and sev-eral ways of European funding were available and helped nearly all regions to stay in the game.

At the end of the day, there are around 30 biore-gions in Germany that claim to be or to become biotech clusters (see map 1).

Germany has nearly 600 biotech companies and each biotech region counts for 20 companies on an average. A lot of these regions are missing local venture capital funds and some of them have no laboratory infrastructure. The dilemma is that the process was highly successful in activating lo-cal actors, but the local actors became so strong in lobbying for public funding that at the end, public resources became more disperse and were not con-centrated on the most promising re-gions.

Secondly, in functional or sector terms, one key result of Porter’s (1990) study is that no country has the resources to establish globally successful clusters in a broad range of sectors. Concentra-tion or focusing is needed. The problem is that there is high insecurity about industrial sectors that will be the driving forces in the future. In this case again, the German example illustrates that the practice is more driven by the fear to miss an interesting chance than by selective deci-sion. Figure 3 summarizes the cluster activities of three German federal states—Bavaria, North-Rhine-Westphalia and Brandenburg. We can see that despite some differences in wording and lo-cal spe-cializations, the fields of cluster policy are very similar.

Maybe the approach in Brandenburg is more oriented towards productive industries, the North-Rhine-Westphalian and the Bavarian one have a stronger focus on new technologies, but the dif-fer-ences are not really strong. Policy makers in charge

Fig 3: Fields of Cluster Policy in Three German Federal States


of cluster policy are aware of this problem without any doubt. In all three countries, there is a broad consensus that 15 or 18 clusters are too much, but because it is difficult to select without knowing the future the key strategy is to wait for evaluation. It is too early to discuss the results because the evalu-ations are in a very emerging state, but whatever the result is the dilemma remains—in all sectors cluster policy intends to acti-vate self organization and when you have done this it is very hard for poli-

ticians to stop the fund-ing even when the results are not the expected ones.

As pointed out, there is need of coordination of different fields of policy (this part bases on (cf. for this chapter Muth/Rehfeld 2007, Rehfeld/Terstiep 2007, Terstriep (2006)). There is a long hope that regionalization will bring out more solutions and coordinated processes. The problem is that clus-ter policy on a central level is often embedded in traditional philosophies and contexts. In most Ger-man federal states, the roots of cluster policy are in the field of regional policy. The consequence was that clusters got funding in regions that were lag-ging behind in average eco-nomic performance or

Fig 4: Cluster Policy and Cluster Initiatives Compared

Brandenburg

NRW

Czech Rep.

Austria

BavariaFinland

France

Switzerland

FundingBottom-up dezentral

Bottom-up

Top-down zentral

Stra

tegy

Top-down

in regions that faced heavy sector restructuring. This means that those regions had weak potentials in clustering. At the same time, and without any coordination, the central state focused strongly on technology-driven clusters. With the shift in Eu-ropean structural policy towards Lisbon strategy, the framework changed and today cluster policy becomes linked with technology policy.

In contrast, in Finland, cluster policy had a strong start in the context of Finnish technology

and innovation policy. Today, there is a shift to strategy centers that are driven by the most im-portant Finnish industrial value chains. In France, we find a combination of traditional planning ap-proaches rooted in the 1950s, in ongoing decen-tralization strategies and in a strong technology driven focus. In Switzerland, cluster initiatives are bottom-up driven in most cases and central policy is in its emerging phase. In the German fed-eral state Brandenburg, cluster policy was part of the regional policy but the instruments (incentives on the one hand, network projects on the other) started in different contexts and now they have the problem of coordination. In the Czech Republic,


you find the combination of central- and state-driven planning strategies and market-driven in-struments.

These are only few examples. They illustrate that cluster policy is often embedded in national traditions and the related fields of economic policy. It shows that it is far from coordinating dif-ferent fields of economic policy, and labor market policy has very few links with cluster policy (maybe Swe-den is a case where this coordination with labor market policy works).

Third, and this has links with the arguments above, there is a dilemma between bottom-up and top-down approaches, in other words, between cluster policy and cluster initiatives. Figure 4 shows the position of cluster policy in selected countries resp. federal states along the top-down bottom-up axis “funding” and “strategy”. More cluster funding and strategy are bottom-up driven and cluster policy is only supporting, but most strategies in cluster policy have a strong top-down impact and they aim at activating self-organiza-tion. The problem comes to life when new activi-ties in cluster policy meets long-standing bottom-up initiatives. This is the case in most German federal states, in certain French regions and in some parts of the Czech Republic. The dilemma is that if policy wants to initiate self-organization, it has to risk that the priorities of the societal actors are different from the central state priorities.

ClustEr poliCy As multi-lEvEl poliCy: fiElds for EXpErimEnts And lEArninGCluster policy is a multilevel policy. Such a multi-level policy is characterized by the following fea-tures (cf. contributions in Tömmel (ed.) 2007, Benz et al. (ed.) 2007):n Complex institutional and actor patternsn Boarders between the levels and the actors are not clearly defined, so responsibilities are not al-ways clearly attributedn No actor is able to achieve the desired goal on his own, actors are interdependentn Aim and implementation are acted out in an in-

terplay between public and private actors, and are mainly about self-regulation and not about classi-cal state interventionn Which is why steering techniques that do (and can) not fall back on authoritative instruments can be found.

If we follow the political science discussion about new patterns of governance, especially in the Europe-an Union, there seems to be reasons for doubt about the success of cluster policy, since it is assumed that multilevel policy only works if the “shadow of hier-archy” is given in the back-ground, i.e., if the state has the possibility to fall back to other authoritative instruments if self-organization does not work.

However, this is precisely what is not possible with cluster policy, as without the active (and in-creasingly also financial) participation of the ad-dressees, such a policy is not realistic. In order to become aware of the demands made on cluster policy, it is useful to keep in mind the key task.

Cluster policy wants to encourage self-organi-zation, usually through an initial funding with di-gressive public participation. At the same time, cluster policy aims towards the provision of col-lec-tive goods that have not been provided by private actors so far (if this was not the case, cluster policy would not be necessary). Consequently, it is not solely about the activation of potentials that have been latent so far, but also about a change in cor-porate behavior. It is no longer the lonesome rider company that is requested but the socially respon-sible and economically net-worked entrepreneur. It should be noted that this is a development within a specific policy field, but that such a collective ad-justment of corporate action opposes diametrically competition law, which acts on the assumption of isolated actors only mediated through the market and puts di-rect communication under the suspi-cion of not permissible agreements.

The dilemmas cluster policy has to balance are diverse. Therefore, cluster policy can only be suc-cessful, if it proves to be adaptive with regard to its strategies and instruments. Elements of such an adaptive process can in fact be seen. There seems to be a division of labor within the Euro-pean mul-tilevel system.


On the European level, the field for experiments can be found. In the mentioned program areas (PAXIS, INNOVA and PRO INNO, KIS), experi-ences from established cluster management activi-ties are concentrated, new tools and instruments

are tested, standards for the professionali-zation of cluster management are elaborated and, last but not least, the information basis for a comparability and evaluation of cluster development is built.

The multiplicators are consultancies integrated into the activities, networks of cluster managers, institutions of advanced training and big interna-tional conferences. Even if the landscape of clus-ter management in Europe is still very heterogeneous, certain standards with regard to profes-sionalism have been accepted that cannot be ignored in the long run.

Cluster policy of central states, respectively of federal states in federalist states, still has to find its own place. If we take key categories of the gov-ernance discussion (steering through market, hier-archy and networks) as a point of reference, almost all possible fields are covered in this triangle (fig. 5). The proceedings of states (respectively federal states) with extreme restructuring prob-lems (e.g. in Eastern and Central European states or Bran-denburg) or of states with a strong planning tradi-tion like France are influenced the most by classical steering. Here, the challenge is to line the central

Fig 5: Modes of Governance in Cluster Policy

© 2007 IAT – own illustration

Network

Hierarchy

centralplanningl

award activation

self-organization

bundling

formation

corporatism

Market

implementation

„venture capital“„

state impulses with the initiation of societal self-organization.

At the other end, and this is often disregarded, there are activities of regional self-organization of companies that do not depend on public funding, of-ten don’t even want to because they want to achieve their goals independent from political requirements and public attention.

In between, there are all sorts of hybrid forms—initial financing aimed at a societal self-organization that later will be self-supporting or the promotion of extraordinary cluster proj-ects won through promotional competition—still closely linked to markets and networks. The bun-dling or formation of national resources through an intensive technological co-operation or a co-operation comparable to classical corporatism between state, unions and companies are linked closer to public interests. It is precisely these ac-tivities that stand to face the challenge, not to interconnect too closely but to stay open to the outside and therefore to new impulses.

In a certain way, such different models will al-ways be found, depending on the economic starting position, the readiness of social actors to partici-pate in the provision of collective goods or na-tional political-administrative steering philosophies and regulation systems. However, all these different ap-proaches have in something in common—starting from a certain point in time they all rely on the active participation of those addressees. This is es-pecially true for the participation of companies.

Regardless of the starting point, cluster policy will have to solve the distribution problems men-tioned before in a different way because clear forecasts of future economic developments are not possible. The most promising way at the moment seems to be to form cluster policy in accor-dance with the promotion of venture capital.n At first, it is reasonable to promote broadly, also keeping in mind that not all promoted pro-jects will be successful.n Next, it is important to connect the promotion to clearly defined (financial as well as material) goals and to organize a form of support in order to achieve those goals.


n Finally, at a certain point in time it is to be de-cided where projects can now run by themselves and have the desired societal use, where further support is needed because the achievement of the desired goals take longer than foreseen and where public activities have to be termi-nated.

If this reference to self-organization is miss-ing, the bottom-up developed cluster management activities and central state activities will conflict. In the worst case, not only public resources are wasted because of a lack of effectiveness, but the autonomous processes of cluster development are also thwarted, if public resources are distributed widely as the above discussed example of German biotechnology shows.

strEnGths And WEAknEss-Es of ClustEr poliCy in Eu-ropEThe European Union bases on the idea to combine regional diversity and coherence in a fruitful and dynamic way. The cluster approach offers a strong strategic frame to bring this idea to life. Due to regional diversity, in structural as well as cultural terms, clusters and cluster initiatives are very dis-tinct from region to region, from value chain to value chain. Facing this situation, cluster policy can be studied regarding the way it balances dilemmas. First of all, on one hand, the di-lemma allows re-gional distinctive ways of cluster development and cluster initiatives; and on the other, the dilemma makes it possible to work out general quality stan-dards and success criteria. Without this balance, the cluster approach becomes more fuzzy and runs the risk of losing the potential of cluster development.

The problem is that cluster policy needs new concepts and strategies and that there is a high inse-curity about the results that can be expected in a realistic way. So far, cluster policy is highly ex-perimental and needs strong learning process-es. This is, by no means, self-evident because, as pointed out, cluster policy always runs the risk of becoming embedded in traditional paths of single fields of economic policy. Nevertheless, there is a good chance of policy innovation for three reasons:

n Cluster policy needs to combine different modes of governance and in the course of im-plementa-tion; there is the chance to reflect promising ways and to adapt policy.n Cluster policy is a multi level policy, and in best case the level work in complementary way.n Cluster policy is very different on the local or regional level and cluster managers need to act on an international level (otherwise they risk to cause lock-in effects), as this offers the opportunity to share experiences and to learn from each other.

This cannot solve all the dilemmas mentioned in the chapters above. Is it realistic to expect that cluster policy in strong regions is so successful that all regions benefit by spill-over effects in the long run? Do weak regions have a realistic chance to strengthen their economic performance when they focus on cluster, especially in those value chains with a long standing spatial division of labor? Is there a realistic chance to overcome the traditional boundaries of administrative insti-tutions? What is needed to avoid a destructive clash between bot-tom-up and top-down activities?

The key idea behind this paper is that the clus-ter approach has a high potential to strengthen economic performance in regions as well as in Europe. The danger is that the cluster approach becomes diffused and that cluster policy becomes more vague and, in consequence, the potential of the cluster approach becomes wasted.

Focusing on cluster policy, it is urgent to discuss four challenges.

First, if it is true that clusters are selective and that it makes no sense to try to develop clusters in each region, we need further strategic concepts for those regions that have no promising starting points to develop clusters. A cluster is one way to strengthen the innovative performance of re-gions, but we need different ways to work out “innovative spaces” (Rehfeld 2006). This includes the question in which way these regions can make good use of key ideas of the cluster approach, like networking, linking local-global chains, improving competence, organizing collective learn process and so on.

Second, we need a deeper understanding of how cluster policy is positioned in the trends of global


change. A lot of future trends are highly decentral-ized. Sustainable strategies or new health concepts are basic challenges to improve quality of life in all regions and it is not helpful to dis-cuss these chal-lenges from a cluster point of view. No region is autonomous in a global world and access to global knowledge, and the competence to make good use of it, is crucial for the future of all regions again. Global migration brings out more geographical fluid or borderless spaces and innovative, as well as, fi-nancial flows transfer geographically-fixed regions. Clusters are nods in all trends or they have the po-tential to work as nods like this and cluster policy has to avoid to fix on a given geographical level.

Third, we need evaluation concepts that are aware of the complex aspects of cluster policy. In certain terms it will be very successful when cluster policy contributes to reorganize the institu-tional setting of economic policy, when it succeeds in combing private activities and public re-sources or when it helps to make institutions more flexible. So far, evaluation concepts are focus-ing on indicators, hard ones as well as weak ones (see the examples on the homepage of Scottish Enterprise), but, in order to evaluate cluster policy, we need an under-standing of the underlying intervention concept and the related strategy.

Fourth, doing this we cannot expect perfect so-lutions, but different ways to balance dilemmas. Good practice always is good practice in a specific context of space and time. Clusters develop in an evolutionary way and cluster policy has to do the same thing. Cluster policy in this way, has to keep in mind that it is public policy and therefore, it has to stand for more than the economic evolutionary way. It has to focus on public goods and benefits, and when it does so successfully, there is a chance for a fruitful co-evaluation between public and pri-vate interests.

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from industriAl ClustErs to GlobAl knoWlEdGE hubs

Reve, Torger1

Knowledge-intensive industries are increasingly lo-cated in global knowledge hubs, which are charac-terized by a high density of interrelated knowledge firms operating globally. Examples include Boston in life sciences, Silicon Valley in information and communication technology, and Houston in oil and gas. Typically, such global knowledge hubs emerge from well-reputed universities and private research labs, but they also include a wide array of com-mercial actors and a competent venture capital market. Successful global knowledge hubs are able to attract knowledge functions from major multi-nationals in the industry. Together with universi-ties and their related research labs this creates an advanced, specialized job market attracting talent and knowledge workers on a global scale.

Global knowledge hubs emerge from industrial clusters or geographical agglomerations of related firms, thus such knowledge hubs are highly path dependent, not easily lending themselves to indus-trial development policies. While industrial clus-ters typically center around large manufacturing or service firms and their network of suppliers, knowledge hubs are more diverse in their compo-sition, placing universities and R&D institutions at the center. As the density and interactions of

1 BI Norwegian School of Management, Norway

ABSTRACT

knowledge organizations increase, the result is vi-brant innovation competition and high commercial-ization of innovation, given the active presence of competent venture capitalists and investors.

Some of these knowledge hubs take global lead-ership positions, such as Boston in life sciences and Silicon Valley in information technology, but they are constantly challenged by other knowledge hubs such as San Francisco and San Diego in biotech, and Bangalore and Hyderabad in software and IT services. Despite the prevalence of modern commu-nication technology, geographical proximity mat-ters even in high-tech industries.

In the current paper, the global knowledge hub concept is extended to the global maritime indus-try, as illustrated by the Norwegian and Singapor-ean maritime clusters, and policy measures are proposed to transform these maritime clusters to global maritime knowledge hubs or super clusters.

The global knowledge hub concept is presented as a new industrial paradigm with important im-plications for knowledge-based industrial develop-ment and industrial policy making.

Keywords: Knowledge hub, Maritime clusters, Nor-way, Singapore, Knowledge-based industries


introduCtionIn classical writings of microeconomics and orga-nization theory, the firm is viewed as an autono-mous unit facing factor and product markets. Ba-sically, the firm is conceptualized as a production function or an input-output system transforming raw materials and other input factors into finished products and services to be sold to customers in a competitive market. The firm is basically seen as a manufacturing unit, represented by a typical value chain—from inbound logistics through operations, outbound logistics, marketing and sales and after-sales service (Porter 1985).

In the writings on industrial marketing, dis-tribution and logistics, the firm is seen to be part of an industrial network, focusing on supplier and distributor relationships, and the field of inter-or-ganizational research came to power (Stern & Reve 1980, Håkansson & Snehota 1995). The same holds true in strategy where research on strategic alliances has been strong for many years (Lunnan & Haugland 2008).

Rather than studying inter-organizational rela-tions in terms of buyer-seller dyads (Stern & Reve 1980) or simple industrial networks (Håkansson & Snehota 1995), many researchers in the fields of economic geography (Asheim 2000) and indus-trial development, most notably Professor Michael Porter (1990) at Harvard Business School, have studied industrial agglomerations at given loca-tions. The main terms used are industrial districts or industrial clusters, which have been defined as “a geographically proximate group of intercon-nected companies, suppliers, service providers and associated institutions in a particular field, linked by externalities of various kinds,” (Porter 2003).

Let us take the auto industry as an example and see how it can be studied using various industrial lenses.

In the first paradigm, business as manufacturing, the auto industry is studied by analyzing major in-dustrial actors such as GM, VW or Toyota as facto-ries. The roots go back to scientific management and Fordism. The analytical model applied is typically a value chain (Stabell & Fjeldstad 1998), and the goal is to optimize productivity and value creation.

In the second paradigm, business as industrial clusters, the auto industry is studied as a network of car manufacturers, auto part suppliers, service providers and car dealers, particularly as the in-dustry centers from various key locations such as Detroit, Stuttgart or Osaka. The major manufac-turing firms are placed at the core of the indus-trial cluster, while the other industrial actors are referred to as related and supporting firms. This also included universities and other knowledge pro-viders. The model has been made world famous by Michael Porter (1990), and empirical studies are prevalent.

Industrial clusters represent superior locations due to lower transaction costs of operations, and the existence of knowledge externalities and network effects. Knowledge externalities arise from sharing of knowledge and from utilization of a common, specialized infrastructure. Thus, industrial clusters not only require a critical mass of firms at all levels of the value chain, but there also have to be close interactions between the industrial actors within the cluster. The result is accelerated learning and higher rates of innovation and commercialization, and there seems to be clear scale effects (Krugman 1991). Thus, major industrial clusters tend to be growing, while minor industrial clusters tend to be reduced as firms consolidate and co-locate.

On a global scale, a hierarchy of industrial clusters in any particular industry can typically be observed. The first tier consists of a few key indus-trial locations, like what we observe in the auto-mobile industry; with Japan, Germany and United States being the three major auto industry loca-tions. These are often referred to as global clusters. Global clusters have the highest concentration of firms and control the full range of industrial knowl-edge required within the given industry. This is also where major R&D and new product development takes place.

The second tier clusters can be found in runner-up auto manufacturing countries like Korea, China and India. These are new industrial clusters or re-gional clusters challenging the existing global clus-ters. Many previously strong regional actors in the auto industry (e.g., Skoda, Saab and Volvo) were


first taken over by the major global players (e.g., VW, GM and Ford). Recently, new auto actors from emerging economies are taking over old car manu-facturers, e.g., Tata taking over Jaguar and Volvo getting new Chinese owners.

The third tier of automobile clusters has a con-centration of more specialized suppliers and ser-vice providers to the auto industry, such as the auto parts manufacturers of many European and Asian countries. These specialized clusters are built around more specialized industrial knowledge, and the supplier clusters are highly dependent on their global customers. The vertical inter-organizational relations are governed by strong contractual ar-rangements tying these clusters to the main actors in the global clusters.

The fourth tier of automobile clusters simply consists of standalone auto assembly or auto parts plants located in countries with favorable factor conditions, such as Brazil, Mexico, Poland and Thailand. We may refer to these clusters as trans-plant clusters. In transplant clusters, industrial knowledge generation is limited, and transplant clusters tend to be local in nature. Most of the for-eign direct investments in emerging economies are of this kind.

Finally, there are raw material producers that could be anywhere where factor conditions are fa-vorable. Sometimes, these producers form com-modity clusters, as we see in many countries that are strong in natural resource industries.

In this paper, I will study the industrial cluster structure in knowledge-intensive industries. Exam-ples of such industries are life sciences, biotech, in-formation and communication technology, although most industries today are highly knowledge-inten-sive in some sense or another. Thus, the argument in this paper is that studies of knowledge-intensive industries are transferable to many other indus-tries, such as the maritime industry, which is my empirical focus in the second part of the article.

Finally, in applying these concepts to the mari-time industry, I will introduce the concept of global knowledge hubs. Thus, the third industrial para-digm discussed is industries as global knowledge hubs. This concept has substantial implications for

industrial development and suggests more radical knowledge-based industrial policies.

thE EmErGEnCE of knoWl-EdGE hubsSome of the most famous industrial clusters can be found in knowledge-intensive industries. If we study the development of Silicon Valley (Saxenian 1994), it started with the development of the semi-conduc-tor industry and computer manufacturing. Key actors at this stage were companies like Fairchild and Intel in semi-conductors, and Hewlett Packard and Apple in computers. Over time, the dynamics changed into communication technology, producing such key players as Cisco in network technology, and Yahoo and Google in internet search technol-ogy. Behind the rapid development of the IT indus-try in Silicon Valley was leading edge research and development, most notable at Stanford University and related R&D facilities.

What characterized the Silicon Valley IT clus-ter was the high amount of entrepreneurship re-sulting in thousands of startup firms within any possible knowledge niche of the industry. The transition of startups into commercial successful firms was fueled by a dynamic venture capital in-dustry, providing competent capital to new entre-preneurs. Venture capitalists speeded up the selec-tion processes, both in terms of killing ventures with low commercial potential and by providing ample funding to ventures with high growth com-mercial potential. Entrepreneurs, who were often young university graduates or former employees of some of the major IT firms in the Valley, had the opportunities to transform their knowledge in-vestments into stocks or cash, and many became serial entrepreneurs, setting up new IT, software or service companies in many locations around the world. The Bangalore IT cluster in India is a well known example, and a company such as Infosys has its roots in Silicon Valley.

Empirical studies of knowledge-intensive clus-ters like Silicon Valley reveal dense networks of knowledge linkages and rapid transfer of knowl-edge workers among the key actors in the cluster


(Saxenian 1994, Stuart 2000). The major uni-versities (Stanford, Berkeley and San Jose) and their associated research labs became major link-ing pins in the knowledge network. The important role of public research organizations should be noted (Whittington et al., 2008). New technology and new commercial concepts came out of close cooperation between universities, labs and major IT companies that were all located close to each other. The waterholes in the Silicon Valley became famous for rapid exchange of new ideas. The driv-ing force was innovation competition, and the re-wards for commercial success were substantial. It all peaked during the dot.com era, but the Silicon Valley still kept up its reputation as one of the global new venture hubs, not only in information and communication technology, but in many new knowledge industries, including life sciences and biotech that we now turn to.

An even more amazing story of the rapid growth of a new knowledge-intensive industry is the emer-gence of the Boston life science industry. The pat-tern of development in Boston is even clearer than in the Silicon Valley case, and recently, excellent research data has been presented for the develop-ment of the Boston and San Francisco life science industries (Whittington et al. 2008).

The new life science industry developed from scientific advances in biotechnology, and the de-velopment took place at the three major research universities in Boston: MIT, Harvard and Boston University with their associated university hospi-tals. As these universities were international lead-ers in life sciences, educating the most capable, new knowledge workers, doctors and scientists, major commercial actors in life science, including major biotech and pharmaceutical companies from around the world, set up their labs and test facili-ties in the Boston area. The idea was to be close to the rapid scientific development and to be among the early adaptors of new technologies into com-mercial products and services. At the same time, many entrepreneurs trained in life sciences saw opportunities for themselves, and a large wave of biotech startups emerged. Again, the driver was the venture capital industry. This industry does not

have its main hub in New York like the rest of the US financial industry, and is more concentrated in cities like San Francisco, Boston and San Diego.

These cities also happen to have the highest con-centration of firms in the new knowledge-intensive industries, such as life sciences. Recently, Genome Technology (2008) placed Boston/Cambridge, MA way ahead of all other biotech locations in the world, followed by the San Francisco Bay area and San Di-ego.

The recent empirical study of the development of the Boston and San Francisco life science in-dustries, 1988-1999 referred to above, not only demonstrates the importance of critical mass of co-located knowledge companies, but it shows the importance of close linkages between the same knowledge actors (Whittington et al 2008). At the early stage of development of the life science clus-ter in Boston, 1988, 114 organizations had 201 observed formal ties, while in the more mature stage of cluster development, 1999, 740 organi-zations had 1559 observed formal ties. Formal ties include research partnerships, licensing agree-ments, financial investments and manufacturing and marketing contracts. Of the 740 organizations, 212 were dedicated biotechnology firms, 96 were public research organizations (which also include universities, university research hospitals and in-dependent research institutes), and 240 were capi-tal venture firms. Public R&D institutions play a pivotal role in knowledge generation, while venture capital firms play a similar pivotal role in venture commercialization. In sum, these actors not only form a strong industrial cluster, they form a global knowledge hub.

What characterizes a global knowledge hub is a strong core of public research organizations (PROs), mainly universities and independent re-search institutes, interacting closely with the R&D units of major commercial actors in the industry. In the biotech industry, this means the labs and de-velopment units of dedicated biotechnology firms (DBFs) and the many pharmaceutical, chemical and healthcare companies. When a knowledge hub reaches a certain critical mass, we see that most of the global actors in the industry establish


centers of excellence in the same geographical lo-cation. This is done to be an integral part of the advanced learning and innovation milieu, taking advantage of learning by interaction and diffusion of knowledge (Sorensen & Fleming 2004), and of learning by hiring (Song, Almeida & Wu 2003). As the knowledge hub also contains major world-class universities offering specialized graduate programs and high quality doctoral programs, young talents from around the world seek the same knowledge hubs. This again creates a dynamic, high-talent la-bor market that gives rise to network externalities that benefit all the actors in the hub.

The second layer of firms in a global knowledge hub consists of a competent venture capital indus-try that increases commercialization opportunities by funding ideas that come out of the universities and labs at the same location. The venture capital industry covers all stages of the innovation and en-trepreneurship process—from early stage business angles and seed capital firms, to hard core venture capital firms going in at various stages of develop-ment before the most successful ventures reach the IPO stage and are quoted on the stock exchange. There is, of course, extensive takeover activity tak-ing place during the venturing process, where large companies take over promising startups or spinoffs. In both cases, new ideas are turned into commer-cial success, giving entrepreneurs strong economic incentives to continue to innovate. The heroes are topnotch scientists and serial entrepreneurs that become rich in the process.

The third layer in global knowledge hubs con-sists of the large array of technological and com-mercial actors that turn science and technology into products and services. This is where large numbers of small and medium-sized firms in the knowledge industry grow up, and this is where large multinationals, like Genentech and Novartis, try to play dominating roles. Mergers and acquisi-tions are frequent and sometimes major in nature, e.g., Japanese Takeda Pharmaceuticals taking over Cambridge-based Millennium Pharmaceuticals in 2007 for $8.8 billion.

As in regular industrial clusters, there are numer-ous suppliers, intermediaries and service providers

that have an active supporting role in the knowledge hub. Actually, such firms, in particular, brokers and consultants, are very important in knowledge diffu-sion. This is the same network mechanism that is vi-tal in open innovation (Chesbrough 2003)—creating social capital that facilitates innovation and com-mercialization. Global knowledge hubs are different from research hubs where universities and R&D labs exist in splendid isolation from business and venture capital demands. In knowledge hubs, investors con-stantly chase ideas and vice versa.

Within global knowledge hubs, there is a small world of scientists and commercial actors (Fleming et al 2007) that are world experts within their ar-eas of specialization. Small worlds are character-ized by intensive information exchange and shared values, reducing communication barriers to almost zero, although the membership of small worlds is often culturally diverse. The two overriding values are the drive to succeed scientifically and the drive to succeed commercially.

Another important feature of global knowledge hubs is that they typically consist of several small worlds that are in intense internal rivalry. The scien-tific rivalry between Harvard and MIT is well known, and in the biotech case, key biotech firms tend to be-long to either one of the two spheres. Under such competitive circumstances, there is no time to rest on your laurels, and innovation competition is fierce.

What we find in studying knowledge hubs, is that governmental agencies may also play an im-portant role, partly in terms of funding various R&D initiatives and also by setting industry stan-dards and new regulatory regimes. In the Boston biotech hub, 24 different governmental agencies had located there in 1999, and they were all ac-tive members of the knowledge hub. Thus, the role of private-public partnerships in innovation milieus seems to be a major driver, although the roles may differ across nations.

The global knowledge hub of the biotech indus-try in Boston is beautifully illustrated by cluster map in colors developed by Whittington (2007) in her doctoral research. Here, the distribution of the main components in Boston biotech inven-tions, 1976–2002, is illustrated by mapping the


formal inter-organizational ties between universi-ties (21%), biotech firms (38%), public research organizations (26%) and cross-sector (16%). The number of actors and their formal ties is incredibly high. In addition, there are many informal linkages and networks that are hard to capture in this type of quantitative network research.

In order to capture the structure of a global knowledge hub like the Boston life science clus-ter, I would place the universities and the public research institutions at the core of the hub. In the Boston biotech case, you may well put the four “Research One” universities in Boston in the mid-dle (Harvard, MIT , Boston and Tufts), along with research hospitals like Massachusetts General and research institutes like Dana Farber Cancer Center and Whitehead Institute of Biomedical Research. Its geographical center is at Kendall Square, Cam-bridge, Mass which is also the home of MIT. Re-cently, major international pharmaceutical firms like Pfizer and Novartis have located their R&D facilities at Kendall Square.

The knowledge plus orientation of American re-search universities (Mowery et al. 2004) include early movement of university graduates into com-

mercial firms, consulting relationships between faculty and companies, licensing of university tech-nologies, industry gifts supporting university re-search and student training, faculty entrepreneur-ship founding new companies, faculty involvement on scientific advisory boards, and formal contrac-tual partnerships to pursue joint R&D, product or prototype development and clinical tests.

If we look at the innovation output in terms of patents in the biotech cluster in Boston, two-thirds of the 900 biotech patents registered in Boston between 1976 and 1998 came from a university, while one-thirds came form biotech companies. It is fair to say that there are seamless relationships between universities and private business. The re-sult is that much of published academic research now comes out of the R&D units of corporations, while many new commercial ventures come out of universities. This forms the core of the global knowledge hubs.

What makes the core of R&D and innovation so successful, in global knowledge hubs like Boston, is the network of venture capital firms and investors surrounding the universities and public research institutions. This is a substantial economic force

Distribution of Scientific ClustersMain Component, Boston Inventors 1976-2002

Color Legend

Reds: University (21%)All othercolors: Biotech (38%)Light Grey: PRO (26%)Black: Cross-sector (16%)

Fig 1: Boston Biotech Knowledge Hub Linkages


funding the majority of the commercialization ac-tivity in the knowledge hub, and offering powerful incentives to those who succeed by taking an in-vention or innovation into the commercial stages. Venture capital markets discount future earnings into the present, thus offering venture capital to startup firms whose earnings are uncertain future prospects. Only major corporations are able to do the same, e.g., by corporate funding of internal ventures. The role of government money is limited, except in the funding of basic research and in large defense contracts.

The next layer of actors in global knowledge hubs is the whole array of commercial firms, covering the various stages of development, test-ing, manufacturing, marketing and services that constitute the majority of value creation in most industries. In knowledge-intensive industries, the role of manufacturing is much more limited than in more traditional industries, while product develop-ment, marketing and service represent the substan-

tial part of value creation. The focus is on R&D, commercialization and marketing. The analytical model is one of value shops or value networks (Sta-bell & Fjeldstad 1998). Finally, there are numerous suppliers and service providers serving the knowl-edge firms.

The structure of the global knowledge hub in the biotech industry in Boston can be illustrated as in Figure 2.

At the core of the global knowledge hub are the PROs such as universities and private R&D institu-tions. These interact closely with venture capital and other competent investors that know the indus-try well.

The knowledge-capital core is surrounded by a number of DBFs that breed on the ideas developed at the universities, working closely not only with PROs, but also with large multinationals from the pharmaceutical and chemical industries (PHAR).

The development of an efficient biotech knowl-edge hub also requires well functioning healthcare organizations (HCO), which in this sector repre-sents both a resource and an important market. The role of university research hospitals is critical. Finally, there is a large fabric of specialized and supporting knowledge services (SSS) serving and developing the knowledge hub. This is the layer typically creating most jobs.

Network externalities can also be better real-ized if effective institutions for collaboration (IFCs) exist. These organizations also have a branding role for the global knowledge hub. Finally, the role of new standards and effective government regula-tions (REG) is critical in turning emerging indus-tries into growth industries.

If we compare the knowledge hub concept with traditional industrial cluster maps, we can note the inversion from having the major manufactur-ing companies at the core, to having the research and innovation at the core. The basic premise is that new business emerges from knowledge and market needs. This also changes the role of capital and investors whose role is to match the two. The knowledge dynamics primarily come from R&D and small knowledge based firms rather than from manufacturing and large multinationals. Universi-

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LegendPRO Public Research OrganizationsVC Venture CapitalDBF Dedicated Biotech FirmsPHAR Pharmaceutical IndustryHCO Health Care OrganizationsSSS Specialized Supporting

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Fig 2: Boston Biotech Global Knowledge Hub Structure


ties and R&D institutes become industrial actors that are sometimes even more important than ma-jor business corporations. Thus, close knowledge interactions between academia and private busi-ness are vital in any knowledge hub.

GlobAl mAritimE knoWl-EdGE hubsThe maritime industry has been extensively studied in industrial cluster terms (Reve et al. 1992, 2001, Jakobsen 2003, 2004). On the one hand, the mari-time industry, such as ship building and shipping, represents relative traditional industries, not typi-cally thought of as knowledge-intensive industries. On the other hand, a large part of the maritime in-dustry runs purely on the knowledge-serving global transportation markets. Shipping has no other re-source base than the people owning and operating the ships. Ship building in high-cost countries can only survive if it is able to innovate technologically. The remaining parts of the maritime cluster are technical and commercial services, from the most advanced knowledge services to simple operational support.

The most complete maritime clusters can be found in Norway, Japan and China, but Greece (shipping), Korea (ship building) and Singapore (port) are also strong maritime clusters, along with several other EU countries.

The Norwegian maritime cluster can be illus-trated by Figure 3 (cf., Reve et al. 2001:196).

The core of the Norwegian maritime cluster is the shipping companies providing seaborne trans-portation services worldwide. The Norwegian mar-itime cluster can be traced back to about a 1000 years back when the Vikings ruled the Northern shores. The Norwegian maritime cluster has been highly innovative, particularly when it comes to new ship designs, advanced ship equipment, mari-time IT and new commercial concepts. Interest-ingly enough, ship owners from a country with less than 1/1000 of the world population control about 1/10 of world shipping. Norway is also home to some of the largest global actors in shipping fi-nance, ship brokers, marine insurance, ship classi-

fication services and maritime law. The North Sea offshore oil industry has developed from much of the same maritime knowledge base, making Nor-wegian companies world leading in new advanced sectors such as offshore oil drilling, floating oil and gas production and subsea technology. Thus, the Norwegian maritime cluster is becoming a knowl-edge-intensive industry, thriving on innovation and with the ability to commercialize maritime activi-ties on a global basis.

Given the large concentration of maritime ac-tors in Norway, its knowledge intensity and the

dense network of interactions within the industry, the Norwegian maritime cluster (cf. Figure 3) can be re-conceptualized as a global knowledge hub. The maritime knowledge hub model, as it applies to the Norwegian maritime cluster, is presented in Figure 4.

At the core of the knowledge hub is research and innovation. This not only includes universities and public research organizations, but also to a large extent what takes place of R&D among the com-mercial actors in the industry. Much of this R&D activity takes place outside the labs, in interactions among the various maritime actors, customers, suppliers and consultants.

Unlike the Boston and Silicon Valley cases, the next circle in the knowledge hub model does not mainly consist of venture capital, but includes a host of private capital and investors, ranging from risk capitalists, private equity and large commer-cial investors with a long history of investments

UPGRADING INTERNATIONALIZATION

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Fig 3: The Norwegian Maritime Cluster


in the shipping industry. The ability to fund large maritime projects, e.g., in the global oil and gas rig industry, is astounding.

In the third circle of the knowledge hub model we find the critical mass of maritime actors that make up the majority of the maritime industry, such as shipping, ship industry, offshore industry and maritime services. These four sectors have been described in detail in the maritime cluster studies, and the main challenge is to find out whether they interact closely enough to create network exter-nalities that are so important to dynamic industrial clusters (Orvedal 2002).

Finally, I have added four external forces that will shape the maritime industry in the years to come. These include the global battle for talent and technology (Florida 2005), and the overall forces of economics and environment. The econom-ics have to do with world trade and global trans-portation markets, which in turn closely depend on upturns and downturns in the world economy. The recent global financial crisis illustrates the point. Oil prices play a particularly strong role, especially for a country like Norway. which is also a major oil and gas producer. Environment has more and more to do with climate, primarily the emission of CO2, which of course, is also produced by carbon energy usage in the maritime industry.

The knowledge hub model applied to the Nor-wegian maritime industry, has two main purposes.

First, it can serve as a de-scriptive model to guide empirical research of the maritime industry, e.g., how strong is the research and in-novation core, and how close do the various maritime ac-tors interact. In particular, it is important to find out how closely the maritime indus-try interacts with PROs, and how well academia meets the future knowledge needs of the maritime industry.

Second, the maritime knowledge hub model is a

normative model that can guide industrial action and industrial policy toward the maritime cluster. Thus, in order for Norway to succeed as a lead-ing maritime nation when facing keen competition from aggressive maritime nations in Asia, Norway needs to strengthen its strategic core of maritime knowledge generation and dissemination. This means strengthening maritime R&D, maritime ed-ucation, and maritime innovation milieus, includ-ing investing in leading edge maritime knowledge at universities. It also includes plans for creating the largest and most advanced research and testing facilities for ocean technology, referred to as the Ocean Space Center.

In fact, the concept of Norway as a global maritime knowledge hub was pioneered by Oslo Maritime Network in an effort to strengthen the attractiveness of Oslo as a location for global shipping operations. In May 2008, the Global Maritime Knowledge Hub Initiative was launched in order to make Norway a global knowledge hub for maritime research, innovation and education at all levels.

Initially, the Norwegian maritime industry fund-ed 10 new maritime professorships (or research chairs) at Norwegian University of Science and Technology (NTNU) in Trondheim and BI Norwe-gian School of Management in Oslo. NTNU already had a Center of Excellence in maritime research—Centre for Ships and Ocean Structures (CESCO),

Shipping

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Fig 4: The Norwegian Maritime Knowledge Hub


while BI had developed a Global Executive MBA program for shipping, offshore and finance, in co-operation with Nanyang Technological University (NTU) in Singapore.

Two years later (in April 2010), there are close to 20 new privately-funded maritime professorships in place at four different universities and maritime colleges in Norway, and a similar number of profes-sorships and maritime research centers are under negotiations. Proposals for a large national research program, called Maritime 21, have been put for-ward by the Norwegian maritime industry, focusing on demanding maritime operations, ocean technolo-gy, environmental technology and arctic technology, as well as on new business models for the maritime industry. Plans and designs for the Ocean Space Center in Trondheim have materialized.

sinGAporE And norWAy CompArEdSingapore has much of the same role in the mari-time industry in Asia that Norway has in Europe, although its strategic base is different. Singapore derives much of its maritime power from its port, strategically located on the major sea route between East Asia, Middle East and Europe. In addition, Singapore has become a major location for ship-ping and maritime service compa-nies, including many Norwegian companies. Singapore also has a competitive offshore industry, with leading shipbuilding compa-nies specializing in drilling rigs and floating production vessels. What characterizes Singapore is its aggressive industrial policy toward attracting international knowledge-based companies, par-ticularly in the maritime industry. Singapore has concentrated its maritime policies, including own-ership and operations of its ports, into one single government agency, Maritime & Port Authority (MPA) of Singapore.

Although Singapore wants to become one of the high-tech players of Asia, focusing on such knowl-edge-based industries as IT and biotech, Minister Mentor Lee Kuan Yew recently put things more in perspective, “Biotechnology and pharmaceuticals are ‘sexy and glamorous’ industries, but the mari-time sector is basic to Singapore’s development. Thus, Singapore wants to move from being a major hub port to becoming an international maritime center with a full suite of services.” (The Straits Times, Sep. 26, 2007).

The international maritime center idea cor-responds closely to a global maritime cluster, but it has relatively little emphasis on the knowledge content required in order to succeed. Thus, it is also possible to re-conceptualize the international maritime center of Singapore to a global maritime knowledge hub, cf., Figure 5. The figure comes out of the work of the 3rd Maritime R&D Advi-sory Panel of Maritime & Port Authority (MPA) of Singapore, where the author was one of the inter-national members.

Research, innovation and education have been placed at the core of the global maritime knowl-edge hub of Singapore, surrounded by a network of venture capital and competent investors. Again, there are four major industrial sectors constituting the majority of the corporate content of the mari-

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A Global Maritime Knowledge Hub shall propel theSingapore Maritime Cluster

Fig 5: The Singaporean Maritime Knowledge Hub


time knowledge hub. In Singapore these sectors are port, shipping, offshore & marine engineering and maritime services. It all started with the stra-tegic location at the Malacca Strait, and it is fair to say that the port is still the major driver of the Singapore maritime industry. More and more ship-ping companies are placing their global or Asian headquarters in Singapore due to favorable tax rates and a good infrastructure. This in turn has lead to an influx of many maritime service com-panies. Offshore and marine engineering consists of two major ship builders focusing on offshore structures, expanding into global offshore markets. Singapore is also a major port for bunkering and repairs, and there are also major oil terminals and a petrochemical industry that are important for the maritime industry.

Singapore lags behind Norway, Japan, Korea and China when it comes to maritime R&D, but the two major universities, Nanyang Technological University (NTU) and National University of Sin-gapore (NUS) have started activities in maritime research and development, as well as launching several maritime educational programs, initiated by MPA. Both in maritime research and maritime education, MPA has been instrumental in setting up strategic alliances with Norway. MPA has es-tablished a Maritime R&D Fund of S$ 400 million, and A*Star (Singapore’s Research Foundation) has initiated R&D programs, building international R&D bridges, e.g. with Norway.

knoWlEdGE-bAsEd indus-triAl dEvElopmEnt poli-CiEsGlobal knowledge hubs are rare, and even the more knowledge-intensive industries have room for more than two or three global knowledge hubs. Boston and San Francisco Bay are examples in the bio-tech industry. Thus, becoming a global knowledge hub for a specific industry is more a long term goal than a reality for most regions.

What is common is to find more specialized global knowledge hubs. In the maritime industry, Norway, Singapore, Japan and China are candi-

dates to become global maritime knowledge hubs. Greece already has such a position when it comes to shipping, while Korea has a strong position in ship building. London has a global knowledge hub position when it comes to the financial aspects of shipping, while Rotterdam and Hamburg have strong maritime hub positions as ports and mari-time services.

The same type of specialization can be observed within countries. In Norway, shipping is concentrat-ed in Oslo and Bergen, while the ship industry (ship design, shipbuilding and ship equipment) is mainly located on the northwestern coastline of Norway. What distinguished industrial clusters from global knowledge hubs is the reliance on research and development, its emphasis on innovation and com-mercialization, and its global reach.

Most ship yards around the world do little or no research and development. They simply build ac-cording to spec, and the competitive edge is to be the cheapest. The more advanced end of the ship-building industry invest in long term technologi-cal innovation, working closely with major clients, suppliers and public research organizations. The knowledge intensity can be measured by the knowl-edge composition of the workforce (percent of workforce with PhD and MSc), the relative amount spent for R&D (as percent of sales), the number of knowledge alliances, the number of patents ob-tained, etc. These measures can be calculated for individual companies, but more importantly such measures apply to the industrial cluster in a given region.

The underlying rationale is that industries in regions compete not only in terms of productiv-ity and low cost, but also in terms of innovation and knowledge content. For high cost locations like Norway and Singapore in the maritime in-dustry, competing on innovation is simply a must. This can be done by attracting a critical mass of maritime actors that spend substantial amounts of resources on R&D and who interact closely to create knowledge externalities that benefit all the actors in the knowledge hub. The battle is often times over the location of centers of excellence that the multinationals set up in several countries.


Such global knowledge hubs also attract the best talents, both in the educational phase and in the industrial practice phase, creating a highly at-tractive labor market and large opportunities for entrepreneurship. This gives a special role for the research universities, but also for more vocational and technical colleges, educating the specialized workforce needed in a particular industry. More and more such knowledge hubs are able to attract talent and companies from many countries, some-times even globally. A key requirement again is the availability of competent risk capital.

The implications of the knowledge hub model for industrial policies have not been fully spelt out yet. What we see is that common tax subsidies are re-placed by more focused knowledge-based policies. Examples include developing world class universi-ties, specialized research institutes, labs and test facilities, along with the hard and soft infrastruc-ture required to attract knowledge-based compa-nies and highly educated staff on a global scale. What governments need to consider, are stronger incentives for R&D and innovation, better knowl-edge infrastructure, easier immigration rules, and improved venture capital markets. Often it is a matter of making it simpler to locate companies and easier to do business. This is not simply a ques-tion of policies and regulations, but it also has a strong cultural component. Florida (2005) refers to this as tolerance and acceptance for diversity and a multi-cultural population. Many totalitar-ian countries, e.g., in the Middle East, have seri-ous problems in meeting the cultural dimensions of knowledge development. Stability, security, a clean environment and good quality of life can also give a region a competitive edge.

It is not new to reframe industrial policy into innovation policy (e.g., OECD 2008). The knowl-edge hub model, however, puts the main emphasis on knowledge policies, putting schools, universities, R&D, innovation and entrepreneurship at the cen-ter stage, rather than considering these knowledge functions as support services to corporations. This is very clear when you study new and emerging knowledge industries, such as biotech and nano-tech industries. These industries were created in

research labs, and new commercial actors emerged from the new knowledge base. On the other hand, this was also how most other industries were origi-nally created. Take a traditional and mature indus-try like the fertilizer industry and the establish-ment of Norsk Hydro, now Yara. Norsk Hydro was established based on a new technology invented by a research scientist, William Birkeland, who convinced a venture capitalist, Sam Eyde, to put money behind the idea of taking nitrogen out of the air by using electricity generated by a water fall at Rjukan, Norway. Today, Yara is the world’s largest fertilizer producer, manufacturing and operating globally.

One of the main theses in this paper is that in-dustrial development mainly comes from innovative industrial environments, here called global knowl-edge hubs, where specialized and basic knowledge meets demanding markets with a drive to commer-cialize. Universities, public research organizations, venture capital and competent investors have par-ticularly critical roles in such knowledge hubs.

Global knowledge hubs are path dependent and culturally bound, but there are also examples of how new knowledge hubs have been created by cluster-based policies focusing knowledge and network de-velopment. The catalogue of cluster-based policies needed to stimulate the growth of global knowledge hubs is still not complete, and more work needs to be done to understand all the mechanisms inherent in knowledge-based industrial development.

Another thesis in this paper is that the develop-ment of knowledge-intensive industries is basical-ly similar to the development of other industries. Such a thesis asks for new comparative research. Based on the premise that knowledge forces are similar across industries, the maritime industry has been analyzed in largely the same terms as the biotech industry. In both industries, we find glob-al knowledge hubs that take lead roles in shaping these industries. Boston and San Francisco Bay have such roles in the biotech industry, while Nor-way and Singapore may well take similar global knowledge hub roles in the maritime industry. The major common competitor in the maritime indus-try is China, as in so many other industries. Used


normatively, the global knowledge hub model points to knowledge-based industrial policies that are different from what is typically implemented in industrial development.

ConClusionThis paper argues for a new knowledge-based para-digm for understanding industrial development. Rather than understanding the firm as manufactur-ing or seeing firms as part of industrial clusters, in-dustries can be analyzed as knowledge hubs. Global knowledge hubs have world class universities and public research organizations at their core, and are in close interaction with venture capitalists and competent investors. From this knowledge core, ex-tensive industrial development can take place, as il-lustrated by the development of the Boston biotech industry.

Based on the premise that most industries are becoming knowledge-based, and that knowledge dynamics are basically the same across industries, the global knowledge hub model was applied to the Norwegian and Singaporean maritime industry. Both countries are in a strategic position to shape the future development of the maritime industry, but this requires substantial knowledge invest-ments and closer interactions between the actors in the industry and between private industry and academia.

The global knowledge hub model can be applied both as a descriptive model of industrial develop-ment or as a normative model for industrial de-velopment policies. Both approaches ask for new comparative empirical research.

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from thE indiA City CompEtitivEnEss

rEport 2010


CitiEs, CompEtitivEnEss, And EConomiC dEvElopmEnt: untAnGlinG thE linkAGEs

Dr. Christian Ketels, member of the Harvard Business School faculty at Professor Michael E. Por-ter’s Institute for Strategy and Competitiveness and Member of the Advisory Board, Institute for Competitiveness emphasizes the need for Indian cities to have a clear competitive agenda in order for the nation to achieve higher competitiveness.

More advanced economies are more urbanized economies. As the interest in economic geography has increased, this empirical fact has been more widely acknowledged. The 2010 World De-velopment Report provided significant evidence on how cities and different levels of economic

activity across space therefore have to become a more important aspect of the policy dialogue on develop-ment.

In less-developed economies, the growth of cities and the increasing level of urbanization are largely a reflection of the widespread weaknesses that exist in economic conditions. With infrastructure, education, and many other aspects of competitiveness weakly developed in rural regions, cities tend to be the only places where companies and individuals find opportunities for successful economic activity. The growth of cities is thus more a reflection of the development challenges that exist elsewhere in these economies, not so much a sign of true improvements. In fact, the rise of mega-cities in many developing economies cre-ates many problems of their own, as these huge agglomerations struggle to provide public services to an exploding number of citizens. This is why in developing economies the rise of cities is seen as an inevitable part of development, but also as a policy challenge—it creates the need for policies that enable cities to cope with the massive demands that are placed on them. It also creates the need for policies that enable citizens in rural regions to develop their own economic opportunities. The challenge is to avoid a political schism between metropolitan and rural regions that would threaten to halt urbanization and thus hurt development.

In advanced economies, cities are able to play a radically different role. With both rural and metro-politan regions providing at least the basic level of competitiveness, the choice of where to locate specific economic activities becomes an issue of relative productivity and cost levels. This allows cities to attract activities that are usually more skill-intensive and where there are strong local knowledge spill-overs while rural regions attract more capital-intensive or labor-cost sensitive activities in standardized production processes. Cities turn out to be the places where different types of proximity benefits can reinforce each other—specialization in specific clusters can occur as well as cross-cluster agglomeration of general types of activities. This mixture is especially important for innovation. High-skilled people are attracted to places that provide variety and interesting contrasts. Ideas are born where different intellectual tradi-tions and approaches meet. But to evaluate whether these ideas have any market potential, and to then translate them into profitable products and services, a specialized cluster of related and supporting activi-ties is needed.

From the competitiveness perspective, the policy imperative for cities as well as for rural regions is essentially the same, independent of the stage of economic development—develop the competitiveness of the local economy in order to achieve higher levels of company productivity and thus support higher levels of prosperity. The specifics steps that are needed, however, differ significantly based on the type of locality and the level of economic sophistication it has reached. What is true in both more- and less-developed economies is the need to focus on the specific role that an individual region can play. This requires for


cities and for the rural regions around them to cooperate closely. It is crucial to enable less-advanced manufacturing activities to be placed in rural regions in the vicinity of the cities, especially in developing economies. The city can provide the advanced services and management functions, the rural regions the land and lower cost labor. This division of labor can relief pressure on the city’s infrastructure and create economic opportunities outside of the large agglomerations.

In the past, cities—also in India—have tried to manage their growth by creating artificial limits. In many cases, this approach has failed and made living conditions worse. Mumbai, for example, limits the height of buildings, which has reduced space use and forced people to live farther and farther away from the city center. This has created increasing pressure on an already struggling transportation system. Rent control has further reduced the incentives for land owners to re-invest in housing stock. Mumbai has continued to grow nevertheless, but the city is less efficient in providing even basic services in terms of housing and infrastructure than it could be. What is needed is a different policy approach that focuses on better public services and land use inside the city, while creating real economic opportunities outside of the city as well. There are no magic solutions. But there is a need to move away from the failed approach of dealing only with the consequences of increasing urbanization. Instead, there needs to be a competitive-ness-oriented policy approach that changes the economic fundamentals of where people live and work.

Many of the policy choices that have to be made in order to enable a balanced development of cities and rural regions require the action of all levels of government—national, state and local. But there is an increasing realization that cities are not helpless, and in fact control many policy tools in land planning, infrastructure investments, and the implementation of general policies set at higher levels of geography. Cities need to have a clear competitiveness agenda. Without cities that push for competi-tiveness, it is hard to see how a nation like India can make any sustained progress in its overall quest for higher competitiveness.


GroWinG With ClustErs

Dr. Amit Kapoor, Professor of Strategy and Industrial Economics, Management Development Insti-tute (MDI) and Honorary Chairman, Institute for Competitiveness explains how clusters can trans-form and add value to the competitive landscape of a city.

Cities and townships are the vantage point for the growth and development of states. The World Bank has released a status report “Reshaping Economic Geography” on the world economic re-gions and emphasized on urbanization, territorial development and international integration for a

country to grow economically. Thus far, India has focused on creating industrialization, but its accidental confluence with urbanization and clusters has provided the governance with a tool for enabling industrial-ization in lieu of creating it. Close to 36% of the population in Maharashtra and 45% in Goa live in urban areas and their annual growth rates are 9 and 10%, respectively. Urban centers allow for concentrated economic activity and specialization and hence, cluster formation comes more naturally. The focus of this article is to highlight the importance of clusters and drive location advantages to convert to economic benefits.

Sriperumbudur, a lackluster village near Chennai with no history of industrialization is the largest electronic hub in India. The Alappuzha coir cluster, the leather cluster in Chennai, the diamond industry in Surat, the petroleum cluster in Bombay, the cotton yarn industry in Ahmedabad and numerous other examples indicate the prerequisite presence of a cluster for the industry and the region to prosper. The diamond cluster contributes 17.22% of the world export of non-industrial diamonds and iron ore and con-centrates contribute 14.20%. Close to 65% of India’s exports stem from clusters. Industrialization could never reach pinnacles of international integration without cluster formation and industry specialization.

Clusters perform a function as basic as bringing the worker and the machinery together to manufac-ture. Downstream and backstream industries, educational support, financial institutions and other service providers prop up together linked by complementarities and commonalities. Clusters create the impetus for innovations and competitiveness and facilitate commercialization. Easy access to raw material and labor, rapid diffusion of technological innovations and incentives against rivals enable newer lines of products and opportunities to get readily developed and absorbed in the market stream. Thus, the first challenge that the governance faces for industrialization is the formation of clusters.

Urban agglomerates possess the factors required for a cluster to develop. With Nashik, Mumbai, Pune, Nagpur and other centers of economic activity within the state, Maharashtra contributes approximately 15% of the national GDP. Another striking example of the effect of urbanization is Delhi; despite a small size and population, this city-state contributes about 3% of the GDP. Sriperumbudur could develop into an electronic hub due to its proximity to Chennai (Bombay High and Alappuzha near Mumbai and Cochin, respectively). These regions had the resources but the means to process them came from their neighbors. Infrastructure and human expertise available due to their proximity to relatively developed cities enabled the regions to specialize and their industry to grow.

Location development cannot, however, be carried out oblivious of the inherent advantages of the loca-tion. Chandigarh as a tech hub failed as they could neither cater to the demand of engineers and the like for the industry nor support the inflow of migrants who filled the job vacancies. The misconception was that only a high-tech industry would lead to growth, but there is no such thing as a high-tech industry. Companies in the same domain can be seen operating with different quotients of technological prowess. Agriculture can be done with sophisticated machinery and give high returns. Location development must


be in consideration with the local resources. Another major barrier in cluster formations and urbanization is the creation of unsustainable urban

agglomerates. Bengaluru and Gurgaon emerged with great promises parallel to that of the Silicon Valley and Singapore, but the decrepit state of their infrastructure tells a different tale. Economic policy should reinforce the established and the emerging clusters; however, regulations need to be carefully laid out.

The Indian economic geography is waiting to be mapped. However, urbanization remains a challenge for India with more than 70% of its population falling under the rural category. India reels under the burden of income disparities and economic backwardness and urbanization would encourage industrial clusters to create the much-needed income and employment opportunities. A cluster-based regime would open the doors for competitive advantage to lead the entourage towards growth and progress and unlock umpteen avenues for states and regions to create an agglomeration of prosperity.


Good urbAn GovErnAnCE:An impErAtivE for EQuitAblE GroWth

Gordon Feller, CEO of Urban Age Institute, succinctly describes how improving governance—at the central, regional and local levels—is now a critical part of the agenda for urban economic growth and social development worldwide.

Good urban governance means inclusion and representation of all groups in the urban society, as well as accountability, integrity and transparency of government actions. Capable urban manage-ment means the capacity to fulfill public responsibilities with knowledge, skills, resources and

transparent procedures. There isn’t a single model that could fit the complex process of local capacity building in all countries across the region; the ultimate success is determined by national policies and local leaders’ willingness and ability to carry out their mandates. The World Bank provides technical as-sistance and advisory services to assist in public administration reforms and capacity building at the level of local governments.

Firstly, we need a good definition to guide our thinking: governance is the science of decision-making. The concept of governance refers to the complex set of values, norms, processes and institutions by which society manages its development and resolves conflict, formally and informally. It involves the state, but also the civil society at the local, national, regional and global levels.

Good governance implies effective political institutions and the responsible use of political power and management of public resources by the state. Essentially, it is about the interaction between democracy, social welfare and the rule of law. Good governance, thus, extends beyond the public sector to include all other actors from the private sector and society. Good governance is guided by human rights and by the principles of the rule of law and democracy, such as equal political participation for all. Particular atten-tion is devoted to the needs of the weaker members of society.

In the United Nations’ Millennium Declaration, the international community reached a consensus that good governance is not only an aim in itself, but also a key factor in attaining human development and in successful poverty reduction and peace-building.

Some of the most important work now underway on good urban governance covers the promotion of democracy and rule of law. Human rights play a particular role in this context, especially women’s rights. Effective works in the field of law and justice means fighting corruption and promoting the responsible use of public finances. It means supporting smart and effective government and adminis-trative reforms, the decentralization and regionalization of state power, and the development of local and municipal government. In doing so, it implies the promotion of locally appropriate approaches; it not only cooperates with government institutions, but it must also promote and strengthen civil-society actors.

Decentralization is crucial to the whole process of creating better, smarter and cleaner urban gov-ernance. Citizens, companies and associations approach the state requesting an enormous diversity of services; the law must regulate which of these the state is required to perform. It is also necessary to define the tasks to be undertaken at each government level—central government, regional authorities or local administrative units. Decentralized governmental structures work closer to the grassroots and are more cost-efficient and flexible. However, local authorities and regions are not able to solve all of soci-ety’s problems. An important criterion for dealing with the question of governmental organization is the


‘subsidiarity’ principle. This says that tasks should be performed wherever possible at the closest level of competence appropriate to the given situation.

Many countries want to exploit the advantages offered by an expedient allocation of tasks within the government administration. This requires regulating decision-making responsibilities and earmarking suf-ficient resources for implementation.

Many governments and parliaments are in the process of defining these tasks. For which services and corresponding infrastructure measures is the state itself responsible? Which tasks can it entrust to oth-ers? How does it plan and finance these? Which government levels should perform which tasks? Should responsibility lie with the central government, or a regional or local authority? Who decides on the quality of services, and how? And who monitors the actors?

In order to find technically and needs-appropriate solutions, a growing number of government actors are focusing on performing the tasks allocated to them—what competencies do the local authorities need in order to promote local development? How can the support measures be organized so as to produce sustainable results? This also means involving representatives from the regions and municipalities, civil society and the private sector in these decisions on reform.

Cities with good governance have a greater potential to create and support good living conditions. These cities have a better chance to offer their inhabitants a more equitable share in economic growth, access to infrastructure and services, and participation in political decision-making. Accompanying these opportunities, however, are growing demands on the capacities of municipal institutions. As national-level public funding dwindles for cities, public resources must be stretched to meet the needs of the growing numbers of urban dwellers. This is one of the central challenges of our time.


smArtEr indiA

Transportation bottlenecks increase business costs considerably in Indian cities. Dr. Amit Kapoor, Professor of Strategy and Industrial Economics, Management Development Institute (MDI) and Honorary Chairman, Institute for Competitiveness and Susan Zielinski, Managing Director of SMART (Sustainable Mobility & Accessibility Research & Transformation, a project of UMTRI, the University of Michigan Transportation Research Institute and TCAUP, the Taubman College of Architecture and Urban Planning, in Ann Arbor) tell us how innovations in information technology can pose some solutions.

India reels under the burden of congestion and traffic. While urbanization traces a new path for the Indian populace to race and prosper, the pace of the Indian economy is slowed down due to its grossly inadequate infrastructure. The implications of the rise in urban population on urban transportation

and subsequently on business require urgent attention. The current state of transportation leaves vast gaps between demand and supply, and future projections indicate we are nowhere near closing those gaps.

Precious time is wasted waiting in traffic jams and at signals. The woefully inadequate public transport system, and the insufficient routes and roads available are the prime reasons for the hours-long traffic congestion that most people in metropolitans have learnt to live with. The number of cars and private transport are on the rise as towns and urban areas expand, and the provision of infrastructure to support the influx is insufficient to create conditions for the smooth flow of all forms of traffic.

The problem is not small, and the subsequent consequences cannot be ignored. The cost of doing business rises as employers need to get their employees to work. Hours are wasted managing the traffic situation in place of working productively. What’s more, the health and welfare of all urban dwellers are compromised with the rise in pollution, not to mention the longer-term threat of climate change. The dual economy means different modes of transportation are suited to needs differentiated by variance in income, in turn creating a bigger mess on the roads if the system is not properly integrated and optimized (which is usually the case).

In a nutshell, there is no space left and the urban areas are only attracting more people. As such the need-of-the-hour is not just a more fuel-efficient technology (that will actually continue eating up that space), but rather a more multi-faceted, human-oriented, integrated system that connects and optimizes all modes and services in an innovative and cost-effective way. The transportation problem has too far-reaching an impact on land use, urban sprawl, pollution and climate change, infrastructure, and safety to be ignored or reasoned only in the wake of congestion on the roads.

Fortunately, some exciting options are emerging, that may just meet urgent transportation needs and result in business opportunity and urban competitiveness at the same time. Much as our present telecom-munication network has evolved to include and connect iPods, PDAs, laptops, desktops and cell phones, SMART’s innovative approach integrates the various IT technologies with a wide range of transportation modes, services, designs and infrastructure to create an urban portfolio that permits an easy, convenient, door-to-door trip. Only a step outside the house would link the traveler to ‘New Mobility Hubs’ or places that connect a whole range of transport modes and amenities, day-care centers, satellite offices, cafes, shops and entertainment, all linked for information and fare payment through a cell phone, PDA or in-formation kiosk (for those who cannot afford a cell phone). The information is relayed in real time on the arrival, departure or availability of transport modes and services including information on restaurants, shops and services, maps, etc. The system works to offer smooth transition between various modes of


transport and to use the information on scheduling and options to plan the most appropriate path or jour-ney. It also works to offer new “last mile” services that provide on-demand transfer from the hub to the front door. A person needs to just pick a waiting car or train or hop on to the next bus cutting delays to the minimum. Imagine getting information about the waiting carpool to reach the nearest metro station just in time to leave in the ongoing train, only to be dropped to the office or may be the airport, all within a single, effortless and non-stop journey. All the modes of transport are streamlined to form a single net-work to transport people with smoothness, efficiency and speed.

SMART (Sustainable Mobility and Accessibility Research and Transformation) is an initiative of the University of Michigan that began in collaboration with Ford Motor Company around 2005 to address the transportation challenge in global cities as the world rapidly urbanizes. (In 2007, 50% of the world lived in city regions. In the next 20 years that figure will climb to 2/3 of the planet). The exciting co-benefit of addressing the urban transport challenge is that companies and entrepreneurs that work together to respond to the need for sustainable, integrated, multi-modal urban transportation stand to tap rapidly emerging (and sizable) ‘New Mobility’ markets.

In this spirit, SMART and Ford have engaged a myriad of industry partners related to the future of transportation (New Mobility) to support a comprehensive entrepreneurial and business base. The initia-tive promises to change the way cities comprehend urban transport. Public-private partnerships can make room for public-private innovation where business is involved from the outset in understanding and co-defining the problem, and then offering solutions that support the public good and stimulate new business opportunities at the same time.

Apart from addressing urban congestion, this approach has the potential to provide an ideal opportu-nity for businesses and entrepreneurs to develop integrated New Mobility systems building on the Ford-SMART collaboration. The question remains however, on how companies will envision the India-specific needs and opportunities and uses of New Mobility Hub Networks and how they might create an intricate web of technology and transport to simplify the current complications of the urban agglomeration and offer an almost perfect (and cost-effective, business-positive) solution.


hAbitAts At risk: ChAllEnGEs of urbAn GovErnAnCE in indiA

Raj Liberhan, Director India Habitat Centre, warns of impending disaster unless a realistic needs assessment of the infrastructure needs of Indian cities is made. Ultimately, pressure from the citi-zens, who seek a better quality of life, will be the ultimate motivation and test for city governments and managers.

Humans have used nature’s assets since time immemorial in the belief that these resources had always been around and would be so forever. The implicit view was ‘use what you need and do not worry about regeneration or replacement’. The finiteness, however, of nature’s life-sustaining

treasures like water, energy, fossil fuels and forests has come home in a pointed manner to policymakers and consumers alike, and is pushing us to rapidly find substitutes, supplements and replacements.

The stark reality facing us and demanding answers is that nature’s assets need to be secured and only then can human security be ensured. The two are closely interlinked, though our perspective solely from the prism of human security distorts the solutions we seek. This anthropogenic focus leads to a lopsided investment of time and money and consequential unsatisfactory outcomes.

Urban habitats in South Asia (a region that gave us the immaculately planned towns of the Indus val-ley Civilization thousands of years ago), and indeed in much of the developing world, are fast becoming vulnerable to multiple hazards. Mega cities, in particular, are crucibles of hazards. Smaller cities too are deteriorating at an alarming rate and there is not even a modicum of concern in evidence, much less an effort to ameliorate the situation. Water availability is an issue and its quality an even greater issue. Energy concerns, both of availability and access, plague every city, big or small. Sanitation and waste management strategies are beginning to be talked of only for mega cities. In the rest, disposal of waste generally implies throw-what-you-do-not-need-in-any-vacant-site. Similarly, sanitation in small and me-dium towns is virtually non-existent. The cumulative impact of the needs of burgeoning urban populations is depleting physical resources, and given the absence of a perspective plan for managing our cities, there is no regeneration of sources of supply.

The big question is—will our cities survive? Or is there certain inevitability about the degradation of city infrastructure and civic amenities that no organization or planning process can address as the vol-umes to be serviced are huge? In this context, questions about the sustainability and survival of the city and its population acquire great urgency. If we couple this with the inadequacy of the solution providers one could argue not much time is left before the inadequacies swamp any chance of a solution.

There is no doubt that the state is making efforts to provide for capital investments in infrastructure and services at the city level as well as undertaking urban reforms (the Jawaharlal Nehru National Urban Renewal Mission is an important example). However, the current state of civic infrastructure is a sorry tale and the challenges are enormous.

For the capital city of Delhi alone, as per Prof. Kumon, with the number of agencies in charge of the capital’s water supply, sanitation, health services and pollution control, it could be reasonably assumed that the city enjoys an enviable standard of cleanliness and health. Nothing could be further from the truth. Let us look at a few telling statistics for solid waste, water and energy as illustrative examples.

About 6000 tons of solid waste was generated daily in Delhi during 2004, up from 1960 tons in 1981. According to the 1997 White Paper on Pollution in Delhi, this figure is expected to increase to about 12,750 tons per day by 2015 (http://www.envfor.nic.in/divisions/cpoll/delpolln.html). Per capita waste


generated ranges from 150-600 grams daily, depending on economic status. This includes waste from households, industries and medical establishments. In addition, the two thermal power plants burning coal produce 6500 tons of flyash daily. Out of this, only 65% gets collected per day by the Municipal Corporation of Delhi and another 10-12% by other agencies (http://www.teri.res.in/teriin/camps/delhi.htm#waste). What happens to the rest? Where does it go?

For the country as a whole, solid waste generated daily per person has increased from about 295 grams in 1947 to 490 grams in 1997 and is expected to further increase to 945 grams by 2047 (http://www.devalt.org/newsletter/feb04/of_1.htm). The estimated land required for disposing such huge amounts would be humongous.

With respect to water pollution even though Delhi constitutes only 2% of the catchment of the Ya-muna basin, yet the area contributes about 80% of the pollution load (White Paper, op. cit.). There are 16 drains that discharge treated and untreated waste water/sewage of Delhi into the Yamuna river. The municipal sector is the main source of water pollution in terms of volume. In 1997, about 1900 mld of wastewater was discharged from the municipal sector (up from 960 mld in 1977) and 320 mld from the industrial sector. Though the installed capacity for treatment was 1,270 mld, the treatment quality was/is not up to the desired level of secondary treatment. Thus, a substantial quantity of untreated sewage and partially-treated sewage is discharged into the Yamuna every day. The Najafgarh drain contributes 60% of total wastewater, and 45% of the total BOD load being discharged from Delhi into the Yamuna.

With respect to groundwater as well, 75% of the samples taken from hand pumps were found unfit for human consumption. Delhi does not have enough clean water: as against the present demand of 800 MGD only 650 MGD potable water is available (http://www.delhijalboard.nic.in/djbdocs/r_w_harvesting/harvesting1.htm).

The gap between demand and supply is partly being met by extraction of groundwater through wells, tube wells and deep-bore hand pumps. It is estimated that water quality and availability problems will become acute in the near future because fresh water sources will decrease, and the city will be forced to use brackish and saline water.

Finally, we take a brief look at the energy scenario. The power situation is grave. At a general level it can be said that India’s economic growth will continue to be hampered because of power supply con-straints. What does this bode for India’s cities? The stories and statistics of shortages can be repeated across the length and breadth of the country.

Yet our urban centers are growing by the day. What we need is an analysis of our cities’ strength and deficits on five fundamental parameters that will determine their survival and growth or extinction. These are water, energy, transport, sanitation and waste management. In our view, these are absolutely critical and unless development in these areas keeps pace with demographic trends, the resultant disaster is going to happen sooner than later.

We need realistic surveys and needs assessment of our cities on a given set of indicators, make an as-sessment of current pace of investments and the levels needed, technology supplements and strategies to keep ahead of the volumes that will impact our cities. In the process, we also need to take a hard look at structures of governance and their capacity to address the challenges of the five fundamental factors for city survival and growth.

It is clear that placing the management of cities on the roadmap to sustainable development will re-quire interventions on many fronts. Innovations are required to reduce inputs per unit of output (resource management efficiency), restrict consumption of services (efficiency in service delivery), and augmenta-tion of input flows (resource mobilization). Further, to assess the visible risks, alternative scenarios need to be worked out, for example:nBusiness-as-usual, if no changes take place on demographic and related fronts


nFeasible interventions that control demographic and related parametersnInnovative approaches with respect to city management processes

Some questions/issuesFor initiating this process, several critical issues have to be addressed and a demand-driven strategy designed to be implemented over a give time frame. Some illustrative issues or challenges that need im-mediate attention are:nWhat have been the deficiencies in managing the growth of cities?nWhat local innovations and policies are required to manage the rate of slum formation?nWhat are the most effective interventions to assist the urban poor—slum upgrading, slum relocation

or other types of interventions?nWhat are the three most critical tasks to bring back a safe and hygienic city environment—waste

management, water management, slum management, traffic management, energy management?nWhy has the present set of interventions not worked—bad planning and policies, inefficient manage-

ment, weak information base on the problems and on people’s aspirations?nIs there a hope for our choking cities and what should be the roadmap for them to reemerge not only

as centers of sustainable growth, but as attractive destinations for healthy living?Documentation can be the starting point of a dialogue for the citizens to demand provisioning of al-

locations in a given time frame and to create benchmarks for every city so that the citizen can demand performance of their city managers and representatives. The ultimate equation of environmental security creating the ambience of individual security will get created as a benchmark and the initiative can be ex-tended to other cities. This will serve as a citizen’s mandate for civic governance that in turn can impact the attitude and agenda of the political executive, irrespective of party affiliation.


WAlkAbility: thE CritiCAl urbAn pArAdiGm

Sanjeev Sanyal, Founder & President of the Sustainable Planet Institute advocates urban planners to include walkability into the DNA of Indian cities as a simple, yet radical step, towards increased sustainability and social inclusion.

When China began to reform its economy in 1978, it had an urbanization rate of barely 18% (roughly equivalent to India in 1950). Thirty years later, the proportion is estimated at around 55%! We have every reason to believe that India will experience something similar in the next

three decades. Within fifteen years, states like Tamil Nadu, Maharashtra and possibly Gujarat and Punjab will have an urban majority. By 2040-45, we can expect the country to have an overall urban majority. This raises the problem of accommodating another 350-400 million people in our cities. Indian cities already struggle to serve the existing urban population, how will they deal with this deluge? In particu-lar, how do we ensure that these cities are environmentally sustainable at a time when climate change is becoming a major global issue.

Of course, environmental sustainability is not the only factor to consider. Cities have to be economi-cally- and socially-sustainable as well. This is true for existing cities as well as the many new cities that India will build in the next half century. So we need to think of an urban paradigm that combines eco-logical concern with inclusive growth. Furthermore, it must be a paradigm that applies equally to small mofussil towns like Purulia and Jorhat as well as mega-cities like Mumbai and Delhi. Finally, it must be simple to understand, easy to apply on a mass scale and flexible enough to adapt to local conditions. Is there a way to combine all this?

Need to think systemicallyGrowing awareness about climate change has recently focused a great deal of attention on “green build-ings” as the future of urbanism. A plethora of “green codes” have been initiated including LEED, GRIHA and so on. My discussions with leading architects suggest that these codes typically give us energy savings of around 15% (higher savings are possible but they involve sharply higher costs). This is a useful saving, but it is hardly a major strategic intervention.

The problem with so-called green codes is that they exclusively focus on maximizing an individual building whereas the real gains come from overall urban form. Is the city dense or sprawled? Do people live in apartments or free-standing houses? Is the city designed for public transport? For instance, energy use drops by over 30% just by moving people from houses to apartments even if we ignored the green codes. In other words, India needs to think more about the overall scheme. Given the scale of the impend-ing shift in population, we urgently need to think of simple and universal paradigms that can be replicated on a mass scale across the country.

Walking: The ultimate form of public transportThe history of every city is ultimately defined by the nature of its transportation network. London is defined by its underground rail network, Manhattan by its street-grid (and its underground rail), Los An-geles by the highway network, Paris by its avenues and wide side-walks, and so on. This is critical to both their evolution as well as their urban experience. This is also true of Indian cities. Mumbai developed two railway corridors built in the nineteen-century while Delhi is the result of a car-based design (cars had just appeared when Lutyens was designing New Delhi). Once the transportation network has been fixed, the DNA of the city is very difficult to change. This means that our quest for environmentally and socio-


economically sustainable urban form must start with the transportation network. Given our concern with environmental impact and social inclusion, it must be some form of public transport—but what?

Any discussion of public transport ends up being a debate about buses and trains. Oddly, the simplest and most widely used form of public transport is walking (and its sister mode, cycling). A 2008 study of 30 Indian cities showed that almost 40% of all trips in urban India involved no motorized vehicles at all—28% walked and 11% cycled. The proportion was sharply higher in smaller towns as distances were usually small and the roads less congested. However, in bigger cities, the proportion of people using conventional public transport was high, and consequently commuters walked the last mile. For instance, in cities with more than 8 million population: 22% walked all the way, 8% used cycles and 44% used public transport. This adds up to 74% of people who rely on non-motorized transport for at least part of the commute.

Not only is walking a democratic form of transportation, it is clearly ecologically-friendly, healthy, en-hances social interaction and gives the city a personality. Moreover, social interaction and street life have enormous economic value as this is what makes cities dynamic and creative. This is why the core of all the world’s great cities is consciously walkable—central London, Paris, Manhattan, Singapore and so on.

Note that walkability and public transport must be embedded in the urban DNA as soon as possible because it is very difficult to retrospectively change urban form. Take for instance, Atlanta and Barcelona. Atlanta has a metro network of 74km while Barcelona has one of 99km. These may seem comparable but per capita CO2 emissions for Atlanta are ten times that of Barcelona. The difference is mostly explained by Barcelona being compact while its American rival is spread out. As a result, less than 4% of Atlanta’s population lives within a reasonable walking distance of a metro station compared to 60% for Barcelona. If Atlanta now tried to give its citizens the same accessibility, it would have to build 2800 new metro sta-tions and 3400km of new tracks!

Despite this overwhelming evidence, very little thought is given to pedestrians in Indian urban plan-ning. A brand new city like Gurgaon does not have any network of sidewalks at all! Note that it is not just a matter of building sidewalks. Walkability is about making it possible for the average citizen to be able to lead his/her life by relying largely on walking for day-to-day activities. This requires a whole gamut of urban design requirements like density, mix-use, street life, pedestrian crossings, tree-shade, public-spaces and so on. All these parameters are important in their own right, but walkability is a simple way to encapsulate this philosophy of urban planning. This is why I strongly feel that walkability is the single most important urban design paradigm that must be adopted while thinking of India’s urban future.

“Traffic and Transportation Policies and Strategies in Urban areas in India”, Wilbur Smith Associ-ates (sponsored by Ministry of Urban Development), 2008.

World Development Report 2009, The World Bank.


brAndinG A City from Within

Madhav Raman, Partner at Anagram Architects and Anupam Yog, Director with Mirabilis Advisory take a look Delhi’s inherent urbanism, its urban identity and experience and at the interstitial ele-ments within Delhi that could be used to build a brand for the city, from within.

Urban experience“A single exhaustive definition eludes a city’s “urban experience”—which can also be interpreted as a city’s brand. Nevertheless, it could perhaps be described as a woven composite, mainly defined by its built character, its urban identity and the behavior of its residents.”

Built character: The evolution, conservation and renewal of the built character of a city is governed by planning norms, building controls and urban policy, which are the traditional instruments of urban plan-ning and urban design. The built character makes the most immediate spatial and visual impact of the city’s “hardware” on the psyche of its residents. Through its deliberate control and careful manipulation, a physical sense of “place” may be created within different precincts of the city. It is even possible to cre-ate “urban icons”, spaces that induce a sense of belonging through their distinct and unique singularity.

Urban identity: However, “place-making” is truly the work of the citizens of a city. Certain urban contexts of the city strike a deep chord with its residents. Even though they may be unremarkable archi-tecturally, the chord resonates with the citizenry so strongly that a collective identity gets invested in these “places”. The “places” then move beyond the realm of physical symbolism and become iconic within the minds of the residents, contributing immeasurably to their urban identity. Quite often, this is less through physical engineering, but due more to the nurturing of numerous inherent characteristics such as historic-ity, accessibility, multi-vocal qualities and inclusive nature.

Urban behavior: Multi-vocal urban contexts carry unique meaning to each individual; their simultane-ous inclusiveness allows people to openly engage with them both individually and collectively. Such spaces and contexts within a city have a deeply reciprocal relationship with the urban behavior of the residents, the manner in which they view and engage with their city, and with each other. The urban behavior of a city replicates itself in recognizable patterns at multiple scales.

Interstitial urbanism“As emerging cities hurtle along the path of rapid urbanization, many issues that pertain to urban experi-ence fall outside the purview of formal tracks of urban planning and policy.”

Urban experience evolves over many years of habitation in a settlement and has deep cultural and socio-economic roots. Its very nature makes it impossible to describe, and therefore analyze, in purely statistical terms. Yet, it adds immeasurable value to the city. It enhances the livability of the city and increases its ability to attract and absorb human capital. In short, it vitalizes a city, encouraging a sense of belonging amongst residents and widening their engagement with the city and with each other. This helps empower segments of urban society whose means are limited and who seem to have a reduced stake in the city. It increases the adoption and utilization of the city’s infrastructure and spaces through cultur-ally congruent means. Other aspects of healthy urban behavior such as syncretism, tolerance, a social conscience and a liberal outlook are intrinsically linked to a vibrant urban experience.

The urgency for development in emerging cities puts a strong emphasis on global models of infrastruc-ture development and technological advancement. Yet, this often results in eroding the intangible quality of urban experience. Moreover, the pace of development frequently allows inadequate time and space for


the city to adopt new physical infrastructure and spaces, and infuse them with its inherent urban charac-ter. Crucially, the rapid introduction of new physical assets to the city renders older, often more vibrant assets, redundant, defunct or underutilized. Their reinterpretation and regeneration may help in creating timeless, relevant socio-cultural anchors that are vital for cities experiencing vast change over a relatively short period of time.

What are these core assets that hold the key to revealing a city’s identity or character? What is the nature of their potential to add value to the urban living condition? In what manner could these be tapped or reinvented to create more inclusiveness? How can these assets empower residents, and result in socio-ecologically aware lifestyles?

Branding DelhiLet us evaluate the possibilities of building Brand Delhi by looking within.

Redundancies enroute: Within Delhi’s grade separators, interchanges and rotaries, pockets of redun-dant spaces and surfaces such as flyover soffits, traffic islands, medians and roundabouts exist. Such features are permanent components to our cityscape. While they are constantly on view (to commuters for example), there is scant engagement with the city. Can these spaces do more than merely channelize traffic?

Defunct urban hardware: As Delhi acquires new infrastructure and buildings, old structures, “hard-ware” and edifices are abandoned, get under-utilized, or become superfluous. Many of these have signifi-cant urban value due to their age, iconic status or location. Could they be innovatively leveraged?

Water conduits: From the natural drainage systems (nullahs) to sewers, water supply pipelines to water tankers, various conduits and channels of water scour Delhi. How can their value as existing networks be better used by the city?

Green reserves: Delhi’s Ridge Forests were a contiguous belt that ensconced the formal city just a few decades ago. Rapid agglomeration has reduced these to green enclaves of various sizes. While it is impera-tive that these are protected and allowed to thrive, it is equally important for them to be part of Delhi life. What form of engagement should this be?

Urban villages & historic settlements: Delhi’s many “original” settlements and rural enclaves give a unique flavor to the city, but seem to be at odds with development policies. Being outside the ambit of ur-ban controls, they remain excluded from the fabric of the city. Could these settlements potentially enhance the inclusiveness of the city and become vibrant contributors to Delhi’s urban experience?

Wholesale markets and street commerce: Delhi’s urban culture, like that of most other old cities across India, is very deeply linked to the commerce of the street. This is the essence of Indian city life and Delhi has its own special relationship with what is now termed as the “informal tertiary sector”. Similarly its wholesale markets, some of which have existed for many centuries, are significant cultural anchors. Can these seedbeds of interstitial urbanism be revived?

This is a radically different way of looking at building a contemporary city brand. Eventually, however, in the context of India, and perhaps elsewhere too, it is important to look within to build a city brand that finds resonance and has the ability to endure.


An ElEvEnth intErmission

Sam Miller, journalist and author of ‘Delhi: Adventures in a Megacity’, recounts his experience of crafting and then running his beloved Delhi on SimCity from the year 1900 till the present day. His frustrations as Mayor of Delhi in the game mirror the tremendous complexities of real-life urban planning and management, both disciplines increasingly critical to the growth trajectories of cities across the world and areas where Indian cities like Delhi urgently need expertise and intervention today.

The year 1999 was one of the worst in Delhi’s history. Air pollution reached record levels, there were daily power cuts and water shortages, rioters took to the streets, a tornado struck the south of the city, there were huge fires in the largest industrial area; a plague of locusts descended on Delhi’s

suburbs, space junk landed in the city center and the Yamuna turned into a raging whirlpool. The popula-tion halved in the course of the year, with people fleeing to the neighboring countryside, and the city went bankrupt. Delhi’s long-standing mayor, Shyam Mitra, leaned back, stared at his computer screen, and felt he had no option but to resign. Or he could go back to his previous saved version of SimCity, when Delhi was still a flourishing metropolis.

Until my son introduced me to SimCity, I thought all computer games were about killing or winning, or both. In SimCity you can’t win, and no one ever dies (even during an earthquake). Instead, you build your own ‘simulated’ city, call it what you want, become its mayor and see how successful you are at run-ning it. As the clock of history ticks by, at your chosen speed, on the toolbar at the bottom of the screen, your city grows and shrinks. People (‘Sims’) migrate to your city when it’s an attractive place to live and work in. And they leave if they don’t like it, perhaps because you haven’t built enough schools or there are too many power cuts, or because it’s too boring. I became a secret addict. It’s unexpectedly realistic, and because there is a serious side to it—like a beginners’ course in urban planning—I felt able to pretend that I was hard at work.

SimCity has a number of pre-installed cities—real and invented—including London, Los Angeles and an all too plausible Dullsville. But there’s not a single city from the developing world. So, no Delhi. I felt it was time for me to have a shot at running this city that had become my home. First, I had to recreate the terrain of Delhi on an empty greenfield site, carefully sculpting, with mouse-and-toolbar, the contours of my virtual city. Delhi would not be Delhi without the Ridge and the Yamuna, and I was able, god-like, to raise and sink the land to create the ancient topography of Delhi on my computer screen. I then had to skip the next few millions of years of Delhi history, since the game automatically gave me a formal start-date of Jan 1, 1900.

I hurriedly created Old Delhi first, with a central street, just like Chandni Chowk, as its main east-west axis. I carefully placed homes, factories and shops around Old Delhi in a way that mimicked the real city at the start of the twentieth century. I could lay out the streets as I wished, and had a choice between residential, commercial and industrial buildings of low, medium or high density. The population began to grow. I laid railway lines, created landfill sites, built hospitals and schools. The architecture of the build-ing was very Western, so compromises were necessary. For the Red Fort I had to make do with a Disney-style Cinderella’s castle; a lighthouse became the Qutub Minar, surrounded (this was the early 1900s) by a small village. The only nod to India in the entire pre-packaged SimCity game is the Taj Mahal, which, quite appropriately, I was able to place on the site of its precursor and inspiration, Humayun’s Tomb.

In 1920, I began building British New Delhi. The avenues of India’s new capital were laid out accord-


ing to the plans of Lutyens and Baker, with the Arc de Triomphe and the White House proving suitable substitutes for India Gate and the Viceregal (now Presidential) Palace. I moved on quickly to the concen-tric circles of Connaught Place. The city’s population continued to grow slowly. The new parts of the city were too low-density, I was told by Constance Lee, one of a series of virtual advisers.

I soon came upon the ‘disaster’ menu, a drop-down list that allowed me to summon up a wide range of catastrophes. And so, at the click of a mouse, I was able to replicate the great North Delhi tornado of 1978. Similarly, the Partition riots of 1947, the anti-Sikh riots of 1984, the anti-Muslim riots of 1992 all took place (this time without serious casualties) on the streets of SimDelhi.

However, the SimCity computer model was not working like the real Delhi in a number of telling ways. Sims are a lot more fussy, or spoilt, than the people of Delhi. By the late 1990s my city only had a popula-tion of just over half a million, a twentieth of the size of the real Delhi. If the roads aren’t kept in perfect condition, or there are a few power-cuts, Sims leave the city in droves. They began demanding a Metro as early as the 1920s, and would not put up with what were, by Delhi standards, rather low levels of pollu-tion. Sims won’t move into homes without an underground 24-hour water supply.

As mayor of Delhi, I became more and more frustrated, and began to run out of money. Most of the city’s income came from taxes, and its residents kept moving out if I raised tax rates. In early 1999, an old electricity generating station became overloaded, and blew up. I didn’t have enough money to buy a new one, and all the other electricity plants tripped. Suddenly Delhi had no power, not even enough to work the water pumping stations—and my lovingly created city had no water either. In the real Delhi, poor people would have used handpumps and wells, the rich would have used water tankers and generators. But Delhi just collapsed. A self-destructive anger, born of impotence, overtook me. I pressed every disaster button, and went to get a beer from the fridge. My city was black with the carcasses of deserted buildings by the time I returned a few minutes later. In two SimCity years, the population had dropped to almost nothing. I realized that I hadn’t destroyed the city quite as quickly as the British had following the 1857 uprising, or as Mohammad Tughlaq had in 1327; but I had come pretty close. Delhi was dead.

I searched out my son, and told him my tale of woe. And he told me a secret. He taught me about cheat codes. Most computer games have them, he told me with a slightly patronizing air, as if I were the child. ‘With SimCity, you just need to type in the special code, and everything is free.’ He reverted to my older stored version of SimDelhi from 1993, held down four keys at once, (Ctrl-Alt-Shift-C) and up jumped a little dialogue box. He typed ‘I am weak” and suddenly I had unlimited credit. Everything was free. Another cheat code “nerdz rool’ converted all my old industrial buildings into hi-tech ICT businesses. I began to create the perfect Delhi, my version of Amir Khusro’s heaven on earth.

Like Delhi’s city planners of the nineteen-sixties and seventies, I was able to ignore reality. They just pretended it was a middle-sized city without major infrastructure problems. I could just print money, and buy any solution I wanted. I did still try to keep the city authentic. So the Metro appeared in 2002, and an earthquake shook the city in 2005. Lots of sporting facilities sprang up across the city in time for the Commonwealth Games of 2010, by which time the Metro had spread across all of Delhi; there were still more sports stadia for the 2020 Olympics, and I was delighted when my city became an international hub for space travel in 2045.

As the population continued to grow, I felt pleased with myself, despite the double artificiality of a city that exists only on a computer hard drive and in which construction costs are zero. But it did raise the same issues, which remain at the heart of Delhi’s modern dilemma. I had chosen population growth as my indicator of success; recognizing that improved services mean more migrants, which puts greater pressure on services. If these services can be improved, the city’s population would, well, spiral.

SimCity has a limited number of pixels, or land squares, on which I can ‘grow’ my city. And in the end I ran out of space, with a population of just over two million. There are no geographical limits—no


mountains and no coastline—to the expansion of the real Delhi; it could, for better or worse, continue to grow in every direction, and it may once again become the most populous city in the world.

Outside the ConsoleAgreed, this is just a video game. But this “game” puts forth some serious considerations for all of us.

While we are busy ranking our mega cities, SimCity, by not having any Indian cities as an option, lands a blow to our ego. One might contend that it is a western game and hence it might have been created to cater to a similar audience. That is very sound logic, especially since it had no cities from the developing world. Well, to the competitive Indian that is still an insult: it is okay to ignore the rest of the developing world, but they must have chosen some Indian cities to represent the emerging world!

The policymakers do not have it easy. Even inside the console, creating and maintaining a city turned out to be a tough task. As the author discovers, coping with the population growth alongside the growth in the diverse demands of the people is overwhelming even in a virtual world. By how much this difficulty compounds in the real world is a matter of debate, what is a certainty is that the difficulty does com-pound.

Unlike Miller, our mayors do not have ‘special codes’; hence everything is not free! That’s the real world for you. Hence, it is not possible to create everything perfectly like in SimCity. However, unlike Sims, real Delhi-ites do not think luxurious amenities as being mandatory before choosing a city to live. So we don’t really need to build Delhi to perfection, and can still be rest assured that it will continue to grow. The end result, just as in the video game, we have ourselves a situation where the population spirals and Delhi continues to grow until it reaches its boundary, like in the game, or a point of self-destruction.

In a strange way, the simulation augurs the need of careful planning for Delhi—and any big city in India for that matter—as we concentrate on making our cities productive, competitive and livable. It calls for detailed vision and implementation of decisive regulations pertaining to advancement of infra-structure, population control, environmental sustainability, etc., from the policy makers. Thus, while our mayors fence away to make their respective cities as competitive as possible as business destinations, they may fare better if they heed this SimCity fable!


fdi, CitiEs And CompEtitivEnEss

Sandeep Mann, COO, Remorphing writes about how cities can leverage their competitive position to attract investment and what a long path Indian cities need to tread to really interest investors.

Anand Mahindra once stated that any region aspiring for a healthy incremental capital output ratio (ICOR) of 4, with the usual growth rate of 8%, needed reinvestments to the tune of 32%. Unfor-tunately, no region has savings matching this figure, usually capping savings at 5-20%. Naturally,

this deficit has to be plugged with foreign investment. All regions have to chase higher and more sus-tainable planes of prosperity; falling in line with a Nietzsche kind of directive to emerge as ‘exceptional regions’ with ‘exceptional inhabitants’. Though the competitiveness of any region can be measured in dif-ferent ways, the enhancement of all such levels would always be fuelled by further investments.

The Gandhian thought that work remains so long as there is a tear in any eye is contemporarily matched by initiatives that seek to provide a decent life for workers and citizens be they from Brasilia, Vladivostok or Hyderabad. Levels of affluence have been correlated with quanta of foreign direct invest-ments (FDI) received, whether the trigger was selfless service or ‘sacrificing one’s own selfishness via making all prosperous’.

Indeed, like any vanilla investment, FDI too is an investment by an investor in a specific industrial sec-tor, which is highly linked to geographical moorings, as in a parallel sense observed about international trade by Ghemawat’s CAGE model. FDI would find its appearance in industrial activity over a large tract of land, or setting up marketing channels or placement of offerings on buying shelves for consumers or industrial buyers; but it essentially resides in a city. The administrative function of any commercial enterprise, willy-nilly, is based in a city, maybe with production facilities situated in the near or distant precincts. Consequently, although FDI influences the economy of a vast region per se, it emphatically in-fluences cities therein. So any city wishing to shoot up its competitiveness has to go gunning for FDI—for regions around it and for its own direct upliftment. The same goes for quasi-cities that spring up in and around SEZs.

Data over the past years would indicate that a ranking can be developed for FDI attracted by various cities, apportioned pro rata over their GDP onto the state’s FDI. This shows that the top winners are Delhi, Mumbai, Bengaluru and Hyderabad. However, as FDI winnings is a global canvas battle, Indian cities are far from entering such face-offs with other cities in the world. For Indian cities, competitiveness via FDI still carries a surrealist feel. Tangible realism needs to be brought forth.

It needs no vociferous proclaiming that there is a compelling urgency for all cities to project them-selves as branded destinations for FDI. Intense soul-searching and mapping of competitive positioning alone shall enable every city to carve out its unique appeal as an investment destination, rather than a faceless, generic, monolithic we-are-open-to-all-kind of investments pitch. Aping the leading cities by the laggards shall be surely a futile and counter-productive exercise.

As Professor Porter illuminates, factor advantages are to be created not inherited. On the value chain, the regions that are factor-led scores lower than the ones that are efficiency-led, which again score lower than the innovation-led regions. Indian cities have to discover where it is they have and can pitch for competitive advantages and advantages that can be sustainable. An integrated analytic look at the four pillars of Porter’s Diamond Model, done carefully, sifting realistic assessments from biases and political-ly-motivated slanting of facts, shall duly brighten the path ahead. For instance, why should Ahmedabad


ask for FDI in voice-based outsourcings, when it does not have suitable labor pool (as large as Bengaluru, Pune or Delhi). Instead, it should walk into showing itself as the best destination for concept arbitrage, a knowledge kind of outsourcing, drawing on entrepreneurial and managerial traditions its people are very strong on. Bengaluru can’t beat Hyderabad on cost of living index; why doesn’t it move its IT sector onto high-end priced services. Why can’t Jaipur be an all-season tourist hub, conceiving adventure sports for its harsh summers? After all, cities in Arizona are as hot as Jaipur and still enjoy significant tourism.

Again, we have seen that attracting FDI is shadily managed by Indian cities and governments. In this world of online connectivity, no city has a decent tell-all website. Ironically, Holland maintains a better FDI India site than does the Indian Union Government! There is no serious activity to associate an FDI investor with a local alliance partner; and how can that be done, there is no detailed profiling of local entrepreneurs who can thus be brought together! Which city has a dedicated think tank tracking what cycle industries are undergoing in various parts of the world? The investor is nothing other than an orga-nized or loosely-formed think tank, acting for a large organization, seeking optimal or maximal returns on investment (RoI).

Is this FDI investor being reached? Some itsy-bitsy foreign tours with ministers and their entourage meeting small pools of the Indian community abroad never do the trick. Is adequate faith being won over by showing accountability and objectivity in governance, inspiring confidence that investments wouldn’t run into hot weather down the line? If these questions make policy-makers squirm, the first tentative seedlings towards shaping competitiveness have been sowed.


pApErs And idEAs prEsEntEd At thE 13th tCi GlobAl

CompEtitivEnEss ConfErEnCE 2010, indiA


Examining Open Innovation Practices Among International Networks Of ClustersAndersen, Lise, University of Southern DenmarkSmith, Madeline, EKOS LtdWise, Emily, Lund University, Sweden

Those who work with clusters spend time trying to encourage collaborative behaviors between com-panies through trust-building, knowledge-sharing and learning. The social capital generated can make the difference between being just a group of compa-nies in the same sector, and being a truly innovative, growing and successful cluster.

The importance of social capital wasn’t always at the heart of cluster approaches. Initial studies focused on agglomeration, benefiting the companies through economies of scale, pools of specialized skills and shared infrastructure. However, this spatial anal-ysis failed to adequately explain the success of some industrial groupings and the failure of others.

It is therefore with interest that cluster practi-tioners and policymakers have viewed the rise of open innovation, which acknowledges the require-ment for companies to collaborate beyond their or-ganizational boundaries. Open innovation builds on the assumption that valuable ideas and knowledge can emerge from internal as well as external sourc-es and can enter the market from inside or out-side the company. Therefore, companies that look outside their in-house resources have better access to ideas, expertise and technology than those that rely solely on in-house sources. In a global econ-omy, global links and connections are essential. Such connections help in the dissemination of new techniques, facilitate the adoption of new practices and the development of new products and customer value. This fundamental shift in behavior from a previously internally-controlled innovation process and mindset to a more open innovation process has led a recent paper from the Economist Intelligence Unit to claim “the future belongs to those who col-laborate...with many players, from customers and partners, to competitors, distributors and univer-sity researchers.”

Clusters play a key role in helping to build those networks and connections. Clusters can be a valu-able means to bring the different knowledge triangle actors in an innovation system together, connecting companies to universities and research institutions. Research-driven clusters build on the knowledge strength of a region and through establishing link-ages, joint strategies and collaborations across the Triple Helix, help produce a route to exploitation from those ideas. For policymakers, clusters are a great opportunity to support this type of collabora-tive behavior, to help companies explore open in-novation, and help overcome barriers that prevent companies engaging in this type of innovation.

Social capital plays an essential role in the pur-suit of open innovation collaborations, and many companies are already stressing the importance of clusters when engaging in open innovations activi-ties with external actors.

It’s not surprising, then, that policymakers are beginning to ask “What does social capital within and between clusters have to do with open innova-tion practices? What role, if any, can policy play?”

The presentation introduces action research on a network of ICT clusters in the Baltic Sea Region that is scheduled commenced in early October. The research will explore the role that cluster organiza-tions and other actors have in facilitating open inno-vation activities between companies in a cluster. The research will also examine whether open innovation activities within and between clusters support greater collaboration within and among clusters thereby fos-tering a stronger international innovation dynamic.

The action research will lever the cluster dynam-ics survey (introduced and discussed at previous TCI conferences) to examine social capital between clus-ters in an international context, as well as a newly developed interview questionnaire to gain insights on open and user-driven innovation tools used by companies working in international contexts.

The aim of the presentation is to discuss and gain peer perspectives on the research approach planned for exploration of the following research questions:a) Is it important to have strong internal cluster dy-

namics (i.e. social capital) before pursuing open innovation activities internationally?


b) Do open innovation activities between clusters create a stronger international innovation dy-namic?

c) Do existing policies support open innovation ac-tivities within a cluster and between clusters in-ternationally?

n What activities are undertaken by regional au-thorities in this regard? n What role is played by cluster organizations/in-termediaries?n What are companies’ perspectives on these poli-cies?

A further challenge to be explored is whether encouraging open innovation between clusters at an international scale threatens to undermine the internal dynamics and growth of social capital with-in a regional cluster. How can the best balance be achieved between building social capital and strong dynamics on a local level with sourcing knowledge and working with open innovation practices inter-nationally?

The aim of the research is to gain a better un-derstanding of the interdependence between social capital, open innovation, cluster building and inter-nationalization. The role of social capital in open in-novation activities and cluster building will be looked at, and social capital and open innovation processes function in an international context will be explored to gain a better understanding of how open innova-tion activities between clusters can contribute to a stronger international innovation dynamic. Finally, how policies can support open innovation activities within and between clusters in an international con-text will be explored.

Comparative Analysis of Marketing Externalities and Process Knowledge Spillovers Among Various Industrial ClustersArbi, Khalil A. University of Management and Technology, Lahore

Fast-paced globalization has put corporate and SME firms under great pressure to maintain their comparative advantage. Prevailing literature on

cluster development suggests that small and me-dium firms consider location as key point for their sustainable comparative advantage. From various studies across the globe, businessmen take location of their business as a fundamental source of suc-cess. It is claimed that networking and co-location are big sources of business knowledge that are nec-essary to compete in the international market.

The studies done by Brown, P. et al (2010) and Felzensztein et al (2008) cover analysis of market-ing externalities across various geographical loca-tions. Studies done by Brown, P. cover electronic clusters of New Zealand in which the authors have given analysis of active and passive marketing externalities. On the other hand, research from Felzensztein et al covers a comparative study of salmon-farming industry cluster across two differ-ent geographic locations i.e. Scotland and Chile. Both studies have given a detailed analysis of mar-keting externalities, but the difference among them is that one is confined to only a single geographic location, while the other takes into account one cluster in two different geographic locations. The results of both studies are somehow same with lit-tle differences due to different nature of industrial clusters.

This research has been executed to make a com-parison of marketing externalities and production process knowledge spillover across various indus-trial clusters of Pakistan. It is different from the above mentioned studies in many aspects. Here we have taken four different industrial clusters in the Punjab province of Pakistan. Two of these clusters, surgical instrument and sports goods are found in the same geographical location of Sialkot, whereas the other two cutlery and textile clusters are found in Wazirabad and Faisalabad, respectively. The re-sults from these clusters will be multidimensional and provide more in-depth knowledge about the behavior of various firms working at the same as well as in different locations. Interesting findings will come from two different clusters working in the same location.

The objective of the research is to provide an analysis about how various firms working in the same cluster differ with firms working in other


industrial clusters. Obviously there are differenc-es and similarities of their behaviors. We want to catch the nature of benefits from marketing and production process externalities that these firms currently enjoy. The results of this research will ex-pose the underlying characteristics of various clus-ters situated at the same and at different locations. The research results will show the extent of benefits gained by firms across various locations and vari-ous disciplines of business. It has been statistically seen that the selected four industrial clusters have varied performance in the international market. Some of them are highly export-oriented whereas some are performing fairly in the international arena. The results of this research can also be used to evaluate cluster performance at an international level. Along with export performance, we have also tried to catch innovation in the clusters as well. An increased networking and knowledge spillover has a logical consequence of increased innovation. In this research, our intention is also to gauge the level of innovation in each sector as well.

Clusters as Incubators for InnovationBode, AlexanderHessenmetall Cluster-Initiative, Germany

During recent years clusters have gained much attention from both practitioners as well as re-searchers. The organization of clusters is regard-ed as one vital instrument for increasing competi-tiveness of member companies or even of a whole region. The underlying assumption is that col-laboration of companies that compete in different fields, the so-called “competition”, stimulates in-novation. Knowledge spillover among companies from a region shall result in a unique combination of resources and a pool of knowledge. As a result of this process, specific cluster companies achieve a competitive advantage. However, one problem many clusters face is that they have trouble in acquiring money for the work they are providing. Many clusters are founded by public funding e.g. in Europe by funds for regional development from the European Union. This sponsorship ensures a sufficient cash flow for a certain period, mostly

three to five years. However, after the funding pe-riod most clusters got into trouble for they could not implement a sustainable business model. The member companies are not willing to pay the total cost of the cluster-coordination because the ben-efits of the cooperation for the members are not transparent or maybe too low to justify the costs. Most clusters in the EU will disappear after the funding period, if to they cannot deliver measur-able results for their members.

It is this paper’s aim to introduce a sustainable cluster model that delivers measurable and valu-able benefits to its members. Hence, we like to in-troduce a model of a cluster with network charac-teristics that is used as a platform for collaborative innovation activities.

The central constituent element of clusters, which is agreed upon, is the geographical concen-tration of its players. As is evident in literature, the (competition) relations between the players are subject of ongoing discussions. Therefore, the re-lationship between the individual players of clus-ters can be anything from competitive (respectively non-competitive) to cooperative.

Networks are characterized by the relations be-tween the parties, which are mainly of a coopera-tive nature. The geographical expansion, however, is not a constitutive characteristic of networks. Production networks for example can span globally while innovation networks between suppliers and customers cover a smaller region. Networks may prove to be an essential element of clusters. The presence of a cluster does not necessarily lead to the establishment of a network.

These observations lead to two possible param-eters for classifying both clusters and networks: (1) geographical expansion—a network can be at any point on the continuum between global and re-gional, while a cluster is concentrated in a region, and (2) intercompany relations—while a network is initiated for close cooperation, companies within a cluster can cover the total bandwidth between co-operation and competition.

The “cluster with network characteristics” is an approach that uses the most promising aspects of both concepts. As a prerequisite for generating


competitive advantage the cluster with network characteristics is established among companies from one industry that have overlapping but com-plementary assets. The regional component facili-tates the control, as people from one region see each other again, and they may easily lose their reputation they will not so easily be attracted by “free-riding”.

The collaboration in a cluster with network characteristics is based upon mutual trust. Estab-lishing trust is a work-intensive process that re-quires commitment from all members. The level of value-generating activities within a cluster is close-ly linked to an increasing level of trust. As high value generation requires collaboration in fields with core competencies, companies only open up the heart of their company if they have confidence in the other cluster members. Cluster activities in the start-up phase are comprised of activities not crucial to competition in order to slowly establish some level of trust. Starting from exchange of ex-periences on the market in general or the collabo-ration for sourcing of indirect materials lasting to sharing knowledge on general topics, for example the effect of the economic crisis.

Once a sufficient level of trust is established, the members can tackle more core activities leading to the enlargement of the common knowledge base. This is also the starting point for joint technology and R&D projects together with research institu-tions. As clusters are a pool of relevant players from one industry with complement resources and competences, this is the ideal pool for starting up intercompany innovation projects.

A certain level of trust is mandatory for col-laborative innovation projects. In order to establish trust some prerequisites are necessary:n Participating companies need a phase for learn-ing and getting to know potential co-innovation partners n The number of cluster members should not be too high so that it is possible to get to know every-body within a reasonable time frame n Open mindset of participating persons n Continuity in participating employees from one company

n Eternal cluster-management, as an uncommit-ted coordinator

These prerequisites show that huge regional clusters with 50 or more companies, organizing just “get-togethers” are not the ideal platform to establish sufficient trust. Therefore, such kind of clusters can’t be used to initiate intercompany in-novation projects. For establishing a platform for technology-driven collaborative R&D projects, companies need a cluster with network charac-teristics that provides a smooth initiation phase for trust building among a manageable number of companies. The companies can see and mea-sure the benefits of such an approach and are more willing to pay for the beneficial activities of the cluster. All in all one can state that the cluster with network characteristics is a sustain-able business model for an innovative cluster that creates benefits for the member companies and for the region.

Analytical Framework towards Competitive Clusters Local Economic Development [CCLED]: Application to DelhiChoe, KyeongAe, Asian Development BankRoberts, Brian, SPMS Australia

Cities play a significant role in the economic development of Asian countries. The urban GDP per capita in most developing countries in Asia is two-times greater than that in rural areas on an average. Within a decade, more than 50% of the population of Asia will live in cities. By 2030, al-most all new jobs and wealth in Asian countries will be created in cities. This means that most of the secondary and tertiary industry sectors are ag-glomerated in cities and city-regions, as the key forces of the engine of economic growth.

In tandem, economic challenges in developing Asian countries have become more complex—urban populations are growing at great cost to the environment; income gaps between countries and urban and rural areas widening; and climate change has increased risks of natural disasters.


These trends affect the sustainable industry growth and reduce the effectiveness of the local economic development.

Industries tend to locate where businesses can have a competitive advantage, relying on cities’ competitiveness too. Cities offer shared access to common infrastructure linking supply chains and networks, and to required human resources and skills, which help to reduce production and transaction costs. Yet, government resources are limited to provide supporting infrastructure for rapidly growing urban areas and pose enormous challenges. Governments and entrepreneurs in Asian cities need to find ways to improve their competitiveness, if they are to maintain sustain-able development in a world where cities compete for global trade and investment.

Despite these backdrops, structured system-atic information is hardly available to assist surging industries and micro, small and medium enterprises to achieve competitive clusters in and around city-regions in Asia. How can Asian cit-ies and industries become more sustainable and more competitive? What are the attributes that make their urban industries competitive? How can governments or development agencies iden-tify and strategically invest, to boost competi-tiveness and sustainability? If so, which industry clusters in which locality should get support un-der limited resources available? Most of these issues have not been well assessed systematical-ly—until now.

An innovative new analytical framework ex-amining clusters and competitiveness of cities has been initiated and formulated by the Asian Devel-opment Bank (ADB). The Competitive Cluster Lo-cal Economic Development (CCLED) approaches to assess not only the strengths but also the defi-ciency gaps in facilitating competitive industrial clusters, in a selected city-region. At the end, ac-tion plans are prepared for enhancing competi-tiveness of industry clusters and the cities.

This presentation will demonstrate the inno-vative analytical process of CCLED, applying the 6-step method in the Delhi National Capital Terri-tory in India as a case study.

Step one: Ranking competitivenessMajor competitiveness factors with relevant attri-butes are prepared. In this case, five key factors are used (Ernst and Young, 2007)—city prosper-ity, urban governance, infrastructure, business environment and quality of life. Using weighted and aggregated scores from the five key competi-tiveness factors, a group of cities can be ranked for their competitiveness, and national average is calculated as the benchmarking score.

Step two: Evaluating the key drivers of cit-ies’ competitivenessFrom the result of step one, a city (or a city-region) could be selected for its local economic development. The technique in step one details out strengths and deficiency gaps toward enhanc-ing competitiveness of the selected city within a country. This result will be matched with the in-frastructure needs of the industry clusters, which will be identified at step five.

Step three: Assessing structures and chang-ing patterns of multisector industry in a se-lected city-regionUsing the government’s standard industry classi-fication, this step explores the profile of the in-dustry; how the percentage distribution of local industrial sectors in the city-region have changed (using location-quotient and shift-share tech-niques), by comparing census data of at least five years interval. It demonstrates which industry sector is the largest contributor to the local econ-omy, and how industry sectors have been grow-ing or declining over time in the city-region. The top three employment-generating industries in the Delhi-region in 2005 were manufacturing (31% of total employment), retail trade (25%) and ser-vices (16%).

Step four: Mapping the selected industry clusters using GISOnce key stakeholders determine which industry is to be invested in to increase competitiveness, those firms and enterprises in the selected indus-try-sector are geographically mapped out. This result is useful for geographically locating clus-


ters in a city-region and for further infrastructure supports by the government. In the Delhi-region, automobile component manufacturing, general machinery/equipment manufacturing and textiles industry-clusters were identified under the manu-facturing industry.

Step five: Analyzing competitiveness of se-lected industry clusters using Porter’s Dia-mond ModelEach selected industry cluster is analyzed for its competitiveness using 39 attributes under the five factors of Porter’s Diamond Model. For example, in case of the textile industry-cluster in the Delhi-region, out of the 39 competitive-ness attributes, 72% have an average score of less than 2.5 out of the maximum score at 5. To compete at the international textile market, all five competitiveness factors in the textile indus-try cluster in Delhi need to be improved above the score of 3.66.

Step six: Preparing business and action plans for the selected industry cluster The results from step two and five provide use-ful information in what the deficiencies are to strengthen the competitiveness of industry clus-ters as well as supporting infrastructure in the city-region. Key stakeholders pursuing further interventions, based on the analysis results from the previous steps, prepare a business plan. Action plans are also prepared laying out priorities and urgencies to foster the competitiveness of industry clusters, as well as infrastructure needed for the selected industry cluster area. Pre-feasibility in-vestment proposals can also be included for seek-ing investments by PPP, government or interna-tional development agencies.

The CCLED analysis framework provides a strategic foundation that is useful to enhance competitiveness of the selected industry clusters, as well as helpful for informed decision-making by the government to decide where and what in-frastructure to provide first, for fostering local economic development, important for Asian cit-ies in the context of a rapidly-changing global economy.

Stimulating Transsectoral Innovation in ‘Mature’ ClustersEetgerink, Frank East Netherlands Development Agency (Oost NV)

The region East Netherlands (two provinces) accommodates three universities, acting as crys-tallization points of knowledge-intensive entre-preneurial activities and clusters. The clusters are well established with cluster organizations supported by the triple helix partners. Food Val-ley is built on knowledge from Wageningen Uni-versity and Research (WUR). Health Valley is located at the campus of the Radboud University (RU) Nijmegen, close to the academic hospital UMC St. Radboud. Innovation Platform Twente is based close to the Technical University Twente (TU). The three main cluster organizations are connected through an innovation policy program Triangle of the provinces Gelderland and Overijs-sel. Triangle aims at stimulating the synergy be-tween the clusters through the funding of innova-tion projects.

Connecting the clusters there are three themes: bio-based economy (combining agrofood and tech-nology), food and health, and RedMedTech High-way (medical technology, imaging, biomedical). These themes recently emerged out of the cluster activities.

The regional innovation policy was quite suc-cessful in the last few years. The cluster organiza-tions are in place and enjoy support and legitimacy with the regional partners. At the national level, the food cluster is best recognized. The flipside of the coin is a tendency of clusters to institutional-ize into ‘sectors’, which is in a way counterproduc-tive to open innovation and ‘neue Combinationen’. Clusters could develop into a state of lock-in, where transactions become suboptimal.

The region needs sectoral and economic diver-sity to balance too much dependency on spearhead sectors or big dominant companies. Transsectoral innovations stimulate economic diversity, which is by definition related to variety.

A question to answer could be: how can a region stimulate related variety through transsectoral in-


novations, how to keep networks and clusters open enough to prevent stagnation or lock-in?

A part of the answer can be found in analyses of dynamics in alliances and the groups/teams involved in open innovation projects. All sorts of multi-party collaborations, combinations of partners, exist in the triple helix. If we understand the dynamics in such groups, the agenda building, leadership, pat-terns of processes better, we could intervene and stimulate better.

The Triangle innovation policy grew out of ‘Knowledge Mapping NEW Triangle’ (NEW = Nijmegen, Enschede, Wageningen). The starting point was the assumption that if you can identify ‘hot’ spots of cutting-edge knowledge or technolo-gies and the persons who are the leading and ac-knowledged experts in these fields, and, if they do not know each other, you can connect and facili-tate them in research programs. This will with high probability lead to new combinations of knowledge and can eventually lead to innovations through con-nected businesses.

This approach could be combined with the po-tential market drive of societal challenges relevant for the main clusters, like ‘Feed the World’, ‘Re-newable energy and sustainable production’, ‘Af-fordable health care in an ageing society’ etc. Or a starting point can be a by definition be a trans-sectoral integrating theme, like Smart Living (ICT, domotica, smart energy, care, building, technical installation, etc.).

Another challenge would be the international-ization of clusters trough international cross sector combinations of clusters. We are currently devel-oping a European project under the Interreg 4B scheme addressing this subject.

Clusters 2.0: How to Think Positive and Think Big in a Crisis Period?Estévez, Joan Martí ACC1Ó, Catalonia Government

In Catalonia, cluster policy was started around 1993 with a focus on promoting strategic change in the 23 micro-clusters (narrow approach in small geographical areas) identified at that time. Since

then, there has been an interesting evolution in inter-cluster reinforcement—an open-cross innova-tion approach.

One of the most remarkable experiences we are involved in is a corporate entrepreneurship project with 20 cluster leaders of the clusters we are devel-oping at the moment. Through this process we are generating a new community of inter-cluster lead-ers (fashion, ICT, motorcycles, pharmaceutical, food, etc.) working together, sharing interests in new projects, which become new companies, having these leaders as investors. The result is, basically, the generation of new companies with an expected high growth and a global reach, because they have the powerful management skills and finance capac-ity of these leaders. These cluster leaders share the view of thinking positive and big to get out of the crisis through transformational projects.

Learning Clusters in Creative Environ-mentsHaasis, Klaus MFG Baden-Württemberg mbh

In our days the business environment that we work in changes nearly every day. Globalization causes developments that are hard to understand and even harder to foresee, the financial crisis af-fects sectors you wouldn’t expect and two years later business again develops faster than ever. To cope and keep track with such developments doing business as usual isn’t enough—not for companies and at least not for cluster initiatives.

The classic cluster management approach needs to be thought through and adapted. The Manifesto of the European Year of Creativity and Innova-tion 2009 states that workplaces need to be trans-formed into learning sites. More than ever, this ap-plies to cluster organizations. They have to support their members in difficult times and open their eyes for strategic future developments. New cluster ap-proaches shouldn’t only be business-oriented, but also need an empathic component focusing on in-dividual persons. The presentation addresses these challenges and will demonstrate how learning and change processes can be organized.


We will look at two components that are essen-tial for learning organizations, knowledge manage-ment and relationship management—knowledge management to learn from and with each other, and relationship management meaning to trust each other.

Knowledge managementPeter Senge explains in “The Fifth Discipline: The Art and Practice of the Learning Organization” that a learning organization has to be skilled in specific fundamental disciplines. He describes five components a “learning organization” requires:1. Personal mastery of one’s capacities 2. Team learning through group discussion of indi-

vidual objectives and problems 3. Employees and managers are also encouraged

to examine together their often negative per-ceptions or “mental models” of company people and procedures

4. Shared vision5. Systems thinking

These principles support the “learning from and with each other” in organizations. This concept not only applies to organizations, but also to regions and clusters. The presentation gives an overview on how to adapt this very appealing concept to a cluster environment and why cluster managers and regional representatives will be well advised to im-plement it in their future strategies.

Relationship managementOne aspect that remains a key element of all suc-cessful clustering approaches is relationship man-agement and along with it the aspect of trust. Clus-ter actors need trust to learn from each other and to benefit from collaboration and exchange.

Currently we find people cautious about shar-ing their knowledge and information with each other—a development also mirrored in Europe in public discussions on privacy issues of services like “Google Street View” or Facebook. Boundaries between open and closed, real and virtual become more blurred. How do we deal with that challenge? Creating a trustful environment for cluster organi-zations is a crucial first step that can be supported by different approaches:

n Appreciative inquiry, a concept brought to life by David Cooperrider, serves to analyze the strengths of an organization and how to foster them. This method promotes positive relationships and builds on the basic goodness in persons, situations or or-ganizations. That way it enhances a system’s ca-pacity for collaboration and change. n The person-centered approach from Carl Rog-ers, who was an influential American psychologist, can contribute to create, ensure and increase trust between the different actors. Carl Rogers has devel-oped his own approach to understand personality and human relationships, the so-called person-cen-tered approach. This approach found wide appli-cation in various domains such as psychotherapy and counseling, education, organizations and other group settings. It can be used as an effective tool for cluster management. n Positive psychology by Martin Seligman and Mihaly Csikszentmihalyi is a branch of psychology that seeks “to find and nurture genius and talent”, and “to make normal life more fulfilling” not sim-ply to treat mental illness.

Using the example of MFG as a well-experienced cluster organization (recognized as “Excellent Knowledge Organization” by the Federal Ministry of Economics and Technology) and the Creative Industries in Baden-Württemberg, the presenta-tion will demonstrate different practical examples on how to make use of the concepts introduced in terms of regional and cluster management.

Internationalization of regional innova-tion networksHyder, Akmal , University of Gävle, SwedenRoxenhall, Tommy, Mid Sweden University

It is becoming increasingly common for net-works of actors (universities, research institutes, enterprises and government organizations, etc.) to be formed in order to jointly develop innovations. Such networks are often encouraged and financed by regional and national authorities. However, more and more innovations are created between actors in the international arena. The regional in-novation networks must therefore be able to at-


tract international operators and investors, and to recruit individuals with key skills that are active in the international market.

Studies show that regional innovation network has established relationships with international ac-tors, but few have knowledge of how to interna-tionalize it (Vinnova 2008). Furthermore, ongoing globalization creates new challenges for process in-novation networks. Research institutions and com-panies are woven together in very complex networks that cut across national boundaries. An increased number of companies that are continuously look-ing for research expertise around the world create considerable pressure on regional innovation net-works to enable them to compete with the leading innovation networks in the world. Paradoxically, the regional innovation networks in their specific areas of expertise collaborate with world-leading innovation networks so that competitive knowledge and skills are guaranteed.

In many cases, regional innovation networks are working with many small businesses and they need to attract more foreign companies as partners. This is to help smaller companies to come out on foreign markets with technology solutions and products that smaller companies have developed in the re-gional innovation system. This is of course not an easy task for regional innovation networks as there are many competitive players active in the global market seeking international outlets. This com-plexity also explains why many regional companies with high technological potential fail to grasp a satisfactory position in the international market. It is our conviction that mere contact or certain access to other foreign networks is not adequate, regional networks need to establish some vital ties with foreign partners for long-term collaboration and development.

In general, there is a lack of knowledge about how regional innovation networks are internation-alized through collaboration with innovation net-works in other countries. The purpose of this project is therefore to study such processes. The hub of a regional innovation network contacts their foreign colleagues in order to create a partnership between them by forming a strategic alliance. Once such a

vital alliance is established, it becomes easier for member companies to identify relevant partners to establish different kind of contacts for getting a foothold in the foreign market. By exploring the knowledge on internationalization of regional in-novation networks, this work can make a practical contribution in organizing innovative companies around hub of their local networks and get ben-efit of internationalization through long-term ties (strategic alliances) established with vital foreign partners.

Arizona Nanotechnology: Our Cluster StrategyKim, MattQuantTera, Arizona

In general terms, nanotechnology, the science of the small, involves research and development of extremely small components and structures, and transcends many disciplines. Semiconductor firms, for example, have process geometries approaching 65 nanometers and require intense research and development to produce high quality integrated circuits at those extremely small dimensions. In more specific terms, nanotechnology involves using quantum properties that occur at very small sizes, and by utilizing these effects that arise from small dimensions it is possible to create structures that have unique properties that are normally unrealiz-able in nature.

The presentation describes how the two main categories of nanotechnology—nano-engineering of the solid state and molecular nano-engineer-ing—allow the formation of new types of manmade structures and how it is possible to nano-engineer the materials to enhance certain physical proper-ties, with applications of these materials to energy, biology and the environment.

With nanotechnology allowing for control and tailor making of materials properties, its impor-tance in Arizona, nationally and internationally will be discussed. The Arizona Nanotechnology Cluster promotes technology statewide for Arizo-na. How linkages to the general public, government and other organizations make for an important and


necessary base for economic technology develop-ment will be described.

New Approaches towards Cluster Man-agement ExcellenceKöcker, Gerd Meier zu Agency Competence Networks, Germany

Clusters provide fertile ecosystems for compa-nies to thrive, which drives innovation, regional de-velopment and competitiveness. After many years of efforts to develop clusters, the challenge today is not to create more clusters, but rather to enhance the competitiveness and sustainability of existing and new clusters, and to create more dynamic clus-ters with global reach.

One of the key questions today is how to better pro-mote clusters and how to make better use of excellent clusters in response to societal challenges. This would require shifting focus from supporting clusters to us-ing them more effectively. Clusters are said to pro-vide a more productive and innovative environment for enterprises, and this could also be used to achieve a higher impact of research and innovation support. The issue is not to consider clusters as privileged or even exclusive partners for finding better solutions, but to build upon and exploit the cluster concept, which is based on collaboration between companies and research institutes and other institutions offering knowledge to businesses. Thus, clusters and cluster organizations must seek excellence in order to bet-ter serve the needs of enterprises and support their competitiveness; this should be the baseline objective of all cluster initiatives worldwide.

However, today enterprises and clusters face new ways of dealing with innovation and management of knowledge in order to be efficient and success-ful in a more open‐knowledge environment. Cluster organizations play an important role in catalyzing and facilitating action in cluster initiatives.

Promoting cluster excellence is of high rel-evance, especially for cluster managers. So far, there are three approaches prevailing how to pro-mote cluster management excellence.n Benchmarking of cluster managements2 n European Cluster Excellence Initiative3

n Quality Frame4 Benchmarking organizational cluster manage-

ment performance and the quality of cluster orga-nizations is already an accepted approach within Europe. There is clear evidence that benchmarking can lead to much better results than conventional evaluation approaches. As benchmarking has to be understood as a voluntary comparison among clus-ter in order to stimulate mutual learning among the involved cluster management, it is not a new type of ranking or rating. Furthermore, it is not policy-or scientific-driven.

The most common cluster management bench-marking approach was designed in 2007 by the Agency of Competence Networks Germany, in or-der to enable measurement, assessment and com-parison between clusters’ performance. Dedicated focus is given to cluster organizations, but other aspects related to the cluster framework conditions and cluster actors are also regarded.

The benchmarking approach is based on seven dimensions and 60 specific indicators:

n Cluster structuren Financing of cluster organization n Typology and governance n Diversity of services offered by the cluster or-ganization n Output of services n International orientation and visibility n Achievements and reputation

Besides the practical approach, the quality and completeness of the comparative portfolio, against the individual cluster managements are compared, is the key success factor for benchmarking. So far, the comparative portfolio contains 85 clusters benchmarked so far. All of them fulfill high quality in order to be listed in this portfolio. Clusters from various European countries are listed, like from

2 Meier zu Köcker, Rosted (eds.), Promoting Cluster Excellence-Measuring and Benchmarking the Quality of Cluster Organiza-tions and Performance of Clusters, Conference Proceeding of EC-Expert Workshop, 2010, http://www.clusterobservatory.eu/index.php?id=102&nid=

3 http://www.cluster-excellence.eu 4 http://www.iit-berlin.de/veroeffentlichungen/quality-frame.pdf


Austria, Denmark, Germany, Hungary, Norway and Switzerland.

An additional key success factor for the recogni-tion of the benchmarking approach is the following aspects that are regarded in the current approachn Cluster managements can be benchmarked against pre-selected groups with specific charac-teristics (technological domain-wise, size-wise, age-wise)n A flexible approach allows to encompass the broad variety of clusters and cluster initiatives n A simple procedure consisting of a face-to-face dialogue (max. half-day) between the cluster man-agement and the Benchmarking Team n The benchmarking is mainly addressed to the cluster management. It doesn’t provide informa-tion whether a publicly-funded cluster initiative has met the political objectives nor can substitute an impact assessment

The main objective of the European Cluster Ex-cellence Initiative (ECEI) is to gather key Euro-pean organizations in order to identify and set up quality indicators and peer-assessments of cluster management. The ECEI aims at developing train-ing materials and setting up a relevant approach to label the quality of cluster organizations. Such labeling is intended to support cluster managers in achieving high levels of excellence and succeeding in their peer-assessments. Besides, the ECEI will

then create and act as a club of professionals and institutions promoting cluster management excel-lence. Figure 1 reveals the four key areas.

Quality frame stands as quite a new approach, which is based on a peer-assessment according to

the internationally recognized EFQM-Model (Eu-ropean Foundation for Quality Management). The presentation reveals the specific approach, how to set up the peer review groups and results

European Clusters Go International: Current Status and Key Success Fac-torsKöcker, Gerd Meier zu, Agency Competence Networks, Ger-manyMüller, Lysann, Agency Competence Networks, GermanyZombori, Zita, POLUS Programme, Hungary

Creating stronger linkages between clusters in different locations that offer complementary strengths is one of the most promising ways to get access to the most advanced technologies, best know-how or relevant markets. Changes in the global economic environment are also making cluster linkages on the international level more im-portant. As firms within clusters internationalize their activities in creative ways, it is important that cluster initiatives and organizations (which support them) internationalize too. Policy makers on all levels as well as cluster organizations give a lot of attention and make considerable efforts in order to better internationalize clusters and their firms. Al-though, as evidence shows, most actors involved in clusters are interested in learning from and devel-oping concrete activities with partners in other geo-graphical locations internationally, there is still a lack of knowledge about main barriers and drivers as well as about the progress made so far. Future policy supporting measures can only be effective if the real demand of the cluster organizations and cluster firms are known.

The findings presented here are the outcomes of the second European cluster poll in which more than 100 clusters from 11 countries participated. Dedicated attention was given to involve mainly matured and internationally-competitive clusters. As the first poll was made in 2007 and the Euro-pean cluster landscape and framework conditions have changed dramatically, the current findings show what has been gained within the last three years and how the current challenges looks like.

Figure 1: The key areas of the European Cluster Excellence Initiative


The main findings can be summarized like fol-lowing:n Cluster organizations in Europe are taking over more and more responsibility to actively support their cluster firms in internationalization matters.n The barriers and enablers for internationaliza-tion did not change much over the last few years. Financial and personnel shortages are still the main huddles, but quality of products and technologies is still an important aspect. n Whereas the existence of an internationalization strategy was still an exception in 2007 (only 10% of the participating clusters had have such strategy set into force), nowadays more clusters have an ap-propriate strategy in force.n Most European clusters made considerable prog-ress in going international with often positive impact on the business development of the cluster firms.n There is clear evidence that cluster organizations being in charge with internationalization matters on behalf of the cluster firms perform much better in this respect than clusters where the cluster firms feel responsible to internationalize.n Whereas good progress in initiating international co-operations has been gained, little progress is re-ported of increasing international visibility and rep-utation. This is considered a considerable challenge.n EC-funded projects with focus on internation-alization matters have been very successful, if the benefiting cluster organizations really have a man-date to support cluster firms to go international. If not, those projects mostly fail and do not reveal any positive impact on the cluster organizations or respective firms.Based on the statistical evaluation and deepening expert interviews, there is clear evidence that clus-ter firms and cluster organizations tend to be more successful in going international than others, if the following key success factors are fulfilled:n High competitiveness of the products and ser-vices provided by the cluster firms n The cluster organization is officially in charge and has a mandate to support cluster firms going international n The cluster (organization) has developed and implemented an internationalization strategy,

which is implemented and accepted by the cluster firms

The presentation will discuss the findings men-tioned and also reveal that there are considerable country specific differences although mainly the most competitive clusters have been invited to the cluster poll. The findings are expected to contribute to better understand how clusters and cluster or-ganizations should internationalize, what the main key success factors are and how policy makers can better support clusters and cluster organizations going international.

The authors are convinced that the main findings are of relevance not only for the current situation in Europe rather than for all clusters world wide interested in internationalizing their business.

The Road to Prosperity is Paved with Innovation: Embracing the Prosperity “Value Chain”McCord, Mark T.Deloitte Consulting, LLPUSAID Jordan Economic Development Program

The presentation discusses the effects of innova-tion on the creation of prosperity, as well as a five-pronged methodology for promoting innovation. This methodology focuses on business development, research and development, access to financing, de-velopment of a world-class workforce, and creation of an enabling environment that promotes innova-tion. This methodology is the common thread that innovation-oriented countries have used to build a culture of prosperity. The methodology is outlined in order to promulgate the development of a pros-perity “value chain”, the premise of which is that innovation drives productivity, thereby building competitiveness, which creates prosperity.

The major themes of the presentation are: n Linking innovation and prosperityA. If it isn’t broken, fix it anyway: The practical

definition of innovation Innovation is the prac-tice of turning ideas into reality, thereby improv-ing process, outputs and ultimately prosperity.

B. Begin with the end in mind: The groundwork for


innovation is laid through the development of a cohesive strategy that includes the involvement of the public and private sectors as well as aca-demia, and the implementation of the strategy in an organized manner to promote prosperity.

C. Acceleration is the Key: Innovation accelerates a country’s ability to achieve impact targets by creating a culture of prosperity.

D. Innovation’s Dirty Little Secret: Countries that are known for innovation must continue to in-novate or they will not sustain the prosperity de-veloped through implementation of their initial strategies.

n The prosperity value chainA. Innovation drives productivityB. Productivity builds competitivenessC. Competitiveness creates prosperityD. Prosperity is sustained through innovation

The premise of the prosperity value chain is that prosperity supports economic, social, and political stability, countries must continue to innovate to sustain prosperity, and that innovation must per-meate society, which comes through a change in the way citizens think about their quality of life, their government, their economy, and ultimately their value system.n The innovation methodologyA. Develop a strategy: The development of an in-

novation strategy must include influential mem-bers of the public, private, and academic sectors, as well as civil society. Until a cohesive strategy is developed, other elements of the methodol-ogy cannot be implemented. The strategy should include a focus on target sectors where innova-tion can make the country competitive and ulti-mately prosperous.

B. Develop a world-class workforce: Countries must focus on core sectors and develop a workforce within these sectors that will promote competi-tiveness. Development of the workforce has to come before other elements of the methodology in order to lay the foundation for success.

C. Develop a supportive enabling environment: The catalyst for innovation can come either from the private sector (as in the case of Nokia in Finland) or the public sector (as in the cases of

Ireland and New Zealand). However, a public sector must collaborate with the private sector to develop an enabling environment that sup-ports innovation and ultimately the creation of prosperity.

D. Business development: Innovation begins at “home”, meaning that if local companies begin to innovate, thereby moving up the prosperity value chain, significant impact will be created in the areas of job creation, revenue enhancements and public support. This will create a “mass” of innovative and competitive companies that will in turn create opportunities for foreign direct investment.

E. Support for research and development: For in-novation to take root, a country must develop significant support for research and development by building alliances between the academic com-munity, the private sector and the government.

F. Access to financing: Access to capital is cru-cial if companies and ultimately countries are to move up the prosperity value chain. This in-cludes, but is not limited to, start up capital, an-gel networks, research and development funding and other mechanisms designed to promote in-novation.

n Conclusions:A. Prosperity trickles down not up: Countries

must focus on high value jobs that are creat-ed through innovative approaches in targeted sectors. High value jobs will create economic opportunities throughout the strata of society, thereby increasing prosperity. The premise is that poverty alleviation programs, which have long been a staple of development in emerging markets, will not build prosperity because they do not promote innovation and/or productivity. They do not build competitiveness, but simply make countries “less poor”.

B. Innovation is like cellular division: Innovation has to continue in order for countries to main-tain prosperity, which means that mental models have to be changed and that there must be broad-based support for innovation throughout society.

C. Every day without innovation is another day of falling behind: The gap between countries around


the world is widening. Therefore, it is time to stop thinking about the development of an innovative culture and move on with making it happen.

Cluster Research in Norwegian Regions: The Case of the Norwegian Water ClusterNormann, Anne Katrine Research Council of Norway

The presentation has two interlinked parts; one is on the Program for Regional R&D and Innovation (Norwegian acronym: VRI), which is the Research Council of Norway’s main support mechanism for research and innovation in Norway’s regions; the other part is a presentation of a case study—the creation of a water cluster, which has been funded by this program. Here the method for developing learning networks is central.

VRI is one of the main programs funding inno-vation and organization research. VRI encourages innovation, knowledge development, and added value through regional cooperation and a strength-ened research and development effort within and for the regions. The program’s time-frame is ten years (2007-2017), and it offers professional and financial support to long-term, research-based de-velopment processes in the regions. It is designed to promote greater regional collaboration between trade and industry, R&D institutions and the gov-ernment authorities, and to establish close ties to other national and international network and inno-vation measures. Fundamental components of the VRI program include research activity, exchange of experience, learning, and cooperation across scientific, professional and administrative bound-aries. Results of the funded research projects are an indicator of the success of this kind of research program and funding mechanisms.

Innovative networks and clusters have been the subject of extensive research, while there is less re-search on how they develop. It is debatable to what extent it is possible to impact on and manage the development process of clusters. The assumption here is that while it is not possible to manage, it is possible to spark mechanisms that support and

stimulate the cluster development process. This must be done according to the participants’ needs, and building legitimacy is a vital part of the pro-cess. Legitimacy and trust are intertwined. An as-sumption is that development of trust is essential for the establishment of regional networks. Net-work IGP (individual, in group and in plenary) and network reflections are methods that can develop trust through organizing persons from different enterprises to partake in individual and collective reflection processes. These methods have proven to have a positive effect on the development of inno-vative networks. IGP function as meeting places, and implies that the participants are from different enterprises; group work with persons from different enterprises; people rotate for each group work so that people that are new to each other have to col-laborate. Optimal organizational learning process-es are assumed to be achieved through a combina-tion of individual and collective processes, which is conducive to high levels of innovation.

The case is the water cluster in the VRI region of Vestfold in Southern Norway, where 20 core firms form the cluster. The research poses the question whether social researchers can contribute directly to the development of inter-firm networks, condu-cive to an industrial cluster. Furthermore, which methods are adequate for facilitating networks among knowledge-intensive small and medium-sized enterprises? The method chosen is decisive for the process of developing networks. The method needs to center on ways to impact on and develop interpersonal relations. The nature of interpersonal relations has an impact on innovation. It is not suf-ficient to be innovative in terms of products. The production of services is rapidly expanding and it is necessary to work smarter, and hence, process innovation becomes increasingly more important. Process innovation depends on abstract, tacit and contextual knowledge. Such knowledge can only be shared through interaction, and hence, the devel-opment of personal relations and social networks can be an efficient innovation strategy. The nature of interaction depends on, among other factors, geographical distance. Geographical proximity between enterprises makes interaction easier than


long distances, but the innovative power of geo-graphical proximity is under debate. For proximity to stimulate innovation, the regional networks must be knowledge-intensive, open to global knowledge and global capital. Regional networks are essen-tial to innovation, but they must be part of global cooperation.

The water cluster as a project works towards creating arenas and establishing networks in order to increase the activity and strengthen the value creation and innovation in water treatment enter-prises. Social researchers have used network IGP in an early phase of the development of the water cluster. The water cluster has developed from being a losely organized network with an interim board without commitment for the enterprises, to be es-tablished as a project with an elected board. While there initially was skepticism towards group work, reflection processes are now in demand at the clus-ter’s meetings.

Balancing Bottom-up and Top-down Cluster Activities: The Case of North Rhine-WestphaliaRehfeld, DieterUniversity of Applied Science, Gelsenkirchen

In 2007, the federal state of North Rhine-Westphalia launched its new and in our view very ambitious cluster strategy focusing on 16 sectoral clusters and related professional cluster management infrastructures. While some of the clusters where upgraded from successful regional to federal state clusters, others are based on sec-tor initiatives or focus completely new thematic areas.

In doing so the North Rhine-Westphalia ap-proach combines top-down and bottom-up activi-ties. It tries to balance key performance indicators on the one hand and to base on a strong commit-ment by the companies and their self organisation on the other hand. Doing this, different institution-al settings have been established, each with specific strengths and weaknesses.

The presentation will begin with an introduction of the North-Rhine Westphalia cluster approach,

its institutional and strategic settings. This intro-duction will be followed by a discussion of key chal-lenges and questions that arose in the course of the first three years namely:n How to balance regional and federal state inter-ests and activities?n What set of functions is needed and who pays for it?n How to balance the need of strategic orientation and the requirement of openness facing short-term new challenges?n How to evaluate young cluster initiatives that aim at long standing impacts?n How to organise cross-cluster management with clusters based on very specific sector and cultural backgrounds?

Summing up, the strengths and weaknesses of the North Rhine-Westphalia approach will be dis-cussed.

Development Challenges in Network-ing/Partnering/Clustering ManagementRezec, IrenaWotra Ltd

The networking/partnering/clustering approach is of extreme importance for competitiveness, how-ever only with a duly selected form or type of net-working/partnering/clustering in relation to a spe-cific problem or vision of a company. At the same time, with the right management that considers both the different aspects of networking/partnering/clus-tering as well as the trends in the environment and together with this also introduces suitable methods and tools used among individuals in a selected con-nection. In practice, numerous combinations are of course established, and the influence alone of these combinations on management or even development of suitable tools has not yet been systematically re-searched. Different combinations of the elements ev-ident in the following graph substantially affect the selection of suitable management, and all together affect the final success of any networking/partner-ing/clustering forms.

Companies face the issue or search for suitable ways to reach their goals, strategies and visions on


a daily basis. Networking/partnering/clustering is without a doubt one of the strategies that can be used in various cases for various purposes. However, a company usually does not possess such knowledge on the appropriate networking/partnering/cluster-ing form or later the implementation. Governmental support usually refers either to clusters or techno-logical platforms, while the other forms are prac-tically not promoted. This is appropriate in certain cases, but from the viewpoint of consultants and companies, this is at the same time also a “trap”, as especially small and medium-sized companies do not decide at the same time or only also for other types of networking/partnering/clustering, which might be even more appropriate for their own cases. The ap-propriate form or perhaps more forms of network-ing/partnering/clustering at the same time, as well as management adapted to this has a important in-fluence on the development or even competitiveness of an individual company or a group of connected companies.

The next question that arises in the process of networking/partnering/clustering is connected to various aspects of networking/partnering/clustering, which can be classified under general managerial aspects (e.g. legal-formal, financial, HR, etc.), and numerous other aspects, among which are regional, sector-based aspects and the aspects connected with the basic purpose of networking/partnering/cluster-ing, i.e. the interest or economic aspect, innovation aspect, knowledge-sharing aspect, perhaps the as-pect of internationalization, etc. This is actually the central element of connecting that originates from the purpose of networking/partnering/clustering, and also substantially affects the selected network-ing/partnering/clustering form, networking/partner-ing/clustering management, the selection of methods and tools, and others.

If we analyze the needs for the appropriate management style or the necessary methods and tools with regard to the current phase of the life-cycle of networking/partnering/clustering devel-opment, or if we analyze the trends in the envi-ronment for all previous elements of the model or trends in relation to the selected combination, we perhaps get the recommended business, orga-

nizational and managerial model and the recom-mended methods and tools.

Researching combinations that originate from the research model bring numerous new questions to light, as well as new development challenges of the networking/partnering/clustering management, for example:n Can we similarly to technology transfers, where we can successfully transfer technology even from one sector into a completely new, seemingly non-complementary sector, develop also a business, or-ganizational or managerial model of networking/partnering/clustering and related methods and tools, which is transferred from one networking/partner-ing/clustering form into a completely different net-working/partnering/clustering form even for a dif-ferent purpose? Can we learn something from good or bad practices, good or bad training programs, or applied methods and tools introduced in strategic al-liances, and transfer part or all of these experiences, good practices, methods and tools to clusters or per-haps technology platforms, cooperatives, etc. If yes, in which cases and in what way? n In what way and which trends should be moni-tored, or which are the trends that most affect the management and methods and tools in a network? n Which methods and tools will be necessary for successful networking/partnering/clustering of com-panies or networking/partnering/clustering manage-ment in the future, and do potential governmental initiatives for the development of these methods and tools meet the trends? n In what way should companies, consultants and also those offering governmental or other support to companies be taught that the issue of network-ing/partnering/clustering is complex, and that it therefore should also be treated this way, and that professional management correspondingly qualified for networking/partnering/clustering management is necessary especially for some individual networking/partnering/clustering forms or perhaps according to an individual combination of elements evident in the graph?

There are many other questions and development challenges arising, yet all probably demand more managerial dynamics than what we are used to.


Links between Business Competence and Learning Networks: Theoretical ModelRissanen, Riitta Savonia University of Applied Sciences, Finland

Business competence and capability to use and create knowledge in learning networks are in a key role among business leadership skills. Especially, past research in management (Nonaka, von Krogh & Voelpel, 2006; Doz & Kosonen, 2007, Prahalad & Krishanan, 2008) emphasizes the meaning of strategic competences, learning, networking and innovation as a success factor in various business contexts. Earlier studies have found the connection between dynamic capabilities and organizational learning as a source of innovation-based strategy, where management can effectively coordinate in-ternal and external competences and create new competences (Teece, Pisano, Suen, 1997; Zollo & Winter, 2002). Furthermore, empirical research results show (Ritter, 1999), that such factors as availability of internal resources, network orienta-tion of human resources management, integration of communication culture and openness of corpo-rate culture, influence a company’s network com-petence.

Learning organizations (Senge, 1990) and net-works (Tidd, Bessant, Pavitt, 2005) have a key role in sharing knowledge and learning to design alli-ances. In successful alliances, the people-related factors or competences, for example creation of trust and informal networking, are significant.

The theoretical orientation of this paper encour-ages diverse approaches of business competences, learning networks and innovation performance, into to the same field of discussion, in order to lay the foundation for later empirical testing. This pa-per aims at giving a conceptual basis of “business competence” and “learning network” for future empirical research, as well as attempts to identify the components of a theoretical model.

This study attempts to answer the following questions—how the concept of business competence and the concept of learning network is defined and verified empirically in previous research, and what

are the links and interaction between these two concepts.

Funding Innovation in Atacama, Chile: Where the Money Comes FromSalvador, Marynella Atacama Regional Development Agency, Chile

Implementing competitiveness programs and innovative initiatives with a regional and local perspective, sometimes represent problems that go far beyond putting in place perfect methodolo-gies and to have in place social capital, because what it is needed in practice is funding in order to put in place actions and projects that would be able to keep the energy of the process and the con-fidence of both the private and the public sector.

Atacama Regional Government, under the Inno-vation Fund for Competitiveness (FIC), released the first public competition to fund innovative projects to promote and develop economic and institutional environments that encourage innovation in the re-gion.

In a process never held before, the Atacama Re-gional Council, through its Commission of Science and Technology, the Regional Government and the Regional Development Agency (ARDP) developed the basis of a contest that responds to a vision of the requirements of the territory and innovation needs of the region.

In this contest may participate universities (state or recognized by the state), or institutes, technology centers, public or private, having suit-able human and material resources as well as ex-perience in research, technological development, transfer and technology diffusion, and whose main activity is research, technological development and transfer and technology diffusion.

The projects should be framed in the axes de-fined as strategic by the Regional Government, which are contained in the Regional Innovation Agenda 2010, prepared by the ARDP, after exami-nation and evaluation of regional experts. The ini-tiatives presented in this contest, shall be designed to promote science, applied research, innovative entrepreneurship, development, dissemination and


technology transfer, including for the strengthen-ing of regional innovation networks, training and attracting skilled human resources, infrastructure and equipment support and promotion of culture towards innovation and entrepreneurship.

In the case of the Atacama region, the overall amount available for this item is $ 671,633,100, approx. 1.4 million dollars.

The FIC is a financing tool for the implementa-tion of national and regional innovation, aimed at strengthening the national innovation system and in regions, providing transparency, flexibility and strategic direction for public action by the State. Thus, this fund is the main instrument to provide new and additional resources to the various efforts that the State is doing around innovation.

With this orientation, the instrument is joining the regional institutions in the process of strategic decision on the issue of innovation and resource al-location, under the leadership of the Regional Gov-ernments (Gores), from the provisions of the Bud-get Law Public Sector, which states that they define the destination of the resources available, taking into account the National Innovation Strategy for Competitiveness, the respective Regional Develop-ment Strategy (ERD), the Strategic Innovation and Improvement Plans Competitiveness (PMC).

From the point of view of local innovation and competitiveness, this case marks a milestone for decentralization in the management of public funds with resources from the FIC. On the one hand, accredited institutions can submit projects that strengthen regional capacities and networks for in-novation, training and attracting skilled human re-sources, infrastructure and equipment support and promotion of culture towards innovation and entre-preneurship. On the other hand, is in innovation, where indicators of competitiveness place Atacama in eighth place (2008 SUBDERE Competitiveness Indicator), the percentage of public funding allo-cated to I+D+ is relatively low, of the 15 regions occupied last, there are 21 doctors, which places it at number 13; not file patents which places it in last place, along with three other regions.

Therefore, we are working of the quartile model: government, private sector, technological institution

and financial issues, in a technical model that ac-knowledges the gaps and constraints that currently exist in the region to innovate the requirements for a qualitative leap and streamline—a model that recognizes the particular character of innovation according to a regional but global vision, and has also been built on the basis of an agenda that was elaborated with a bottom up technique.

Thus, through this competition, the innovative culture will be strengthened, implementing and transferring methods to activate the regional sys-tem, generating elements to balance economic de-velopment depending on the conditions of the terri-tory in respect of water, energy and environment.

It is being considered that people are important for innovation and competitiveness so it is impor-tant to attract, develop, strengthen and maintain skills, promoting, inter alia, training initiatives and advanced technical work for innovation through programs—construction and updating maps of ap-plied skills in the regional productive sector, set of researchers in industry, specialized internships and technological development, dissemination and transfer of best business practices in innovation.

These are some of the lines to which institu-tions can access a proposal that is expected to be welcomed and represents a clear effort to shift to-wards decentralization of productive innovation, towards increasing business initiatives to improve productivity and boost the regional economy on a sustained basis as a contribution from Atacama to a more developed Chile in 2020.

Emerging Business Clusters in Russian Toys and Baby-Goods IndustrySheresheva, Marina, State University - Higher School of Economics, RussiaGorokhov, Dmitry, State University - Higher School of Eco-nomics, Russia

The purpose of the paper is to analyze the case of building relationships within the Russian toys and baby-goods industry. After all the macroeconomic and political changes of the past decades in Russia, the industry was heavily damaged. At the beginning


of the decade Russian toys and baby-goods produc-ers seemed to have no competitive advantages at all. Their market share has fallen to less than 10% of the fast growing Russian toys and baby-goods market (14 to 20% per year).

The situation in the market began to change re-cently. The most active firms of the industry start-ed to build intensive relationships aiming to raise competitiveness in Russia and abroad. Russian toys and baby-goods producers and retailers started to create win-win situations considering each other as collaborators, not as adversaries. There are some obvious results of such activity. Relational assets built by actors that now appraise the role of inten-sive relationships helped them to strengthen their consolidated position and to gain governmental support of their initiatives as well as to create new value by combining complementary assets and key competencies.

The paper presents the results of preliminary research carried out by means of in-depth inter-views conducted with top managers, as well as interviews with industry experts. The study is based on the IMP network approach that offers a solid ground to observe network relationships in which economic actors are involved. Looking at the changes in the industry and analyzing the recent evolution of inter-firm networking, we aim to find out which forms of long-term relationships are the most promising for the industry in modern conditions. What forms of inter-organizational cooperation can better help Russian toys and ba-by-goods enterprises to gain sustainable competi-tive advantage and to fight the problems brought by the world economic crisis?

The paper is organized around the following topics. Firstly, it focuses on the literature on the subject, followed by a brief overview of the de-velopments in the Russian toys and baby-goods industry pointing out some industry-specific and country-specific features and showing the trend to reappraisal of long-term inter-organizational rela-tionships, regarded now as one of the main factors of success. It also aims to discuss some results of the research paying main attention to recent initia-tives in clustering and their possible effects on the

competitiveness and profit-generating capacity of cooperating actors.

What is the Role of Government in Cre-ating Prosperity in the New Economy?Singh, IndiraOntario Mineral Industry Cluster Council

Governments around the world aspire to create prosperity for their citizens but, over time, very few have been successful in achieving and sustaining this goal. The presentation will focus on what con-stitutes prosperity, what are its key components, and how governments can activate and harness them. In this context, a number of government pol-icies, programs and interventions will be explored and presented to illuminate the pivotal role of gov-ernments at the federal, provincial, and regional/municipal levels as they participate in the creation of enduring prosperity.

Internationalization Initiatives within Clusters: Both the Means and the EndSolé, AlbertCluster Development, Barcelona

Boosting exports is usually seen as one of the top goals within a cluster. Not surprisingly, a group of local companies within a region and a value chain is better equipped to compete in the glob-al arena when cluster dynamics are in place and SMEs tackle strategic common needs collabora-tively. Nevertheless, internationalization is more than that. Field experience increasingly tells us how clusters turn to internationalization in order to strengthen cluster strategies that will improve and sustain overall competitiveness. Just like the ‘cluster’ concept, internationalization therefore be-comes the ‘means’ to an end (competitiveness), not an end in itself.

The focus of the presentation is to demonstrate the above by means of cases and examples that al-low the audience to familiarize them with cluster practice cases, and get inspired by the ongoing ap-plications of cluster initiatives worldwide.


Two key concepts discussed are international-ization as the ‘means’ to strengthen cluster strate-gies, and internationalization and access to global markets as the natural goal of any cluster. Inter-nationalization sustains and enriches the execution of the strategies for the future by improving the value chain of its member companies with interna-tional initiatives and alliances. On the other hand, in an increasingly globalized economy, the interna-tional component must be inherent to any cluster’s strategic plan. In a cluster development project, companies are more confident and committed to collaborate in non-local markets. Both these things are done with the ultimate goal of increasing com-petitiveness in a global context.

The presentation introduces examples in the fol-lowing two areas, classic export-oriented set and more strategy support ones.

Initiatives to increase sales by expanding into in-ternational marketsn International public procurement n institutional support to foster Cluster initiatives in strategic countries n Inter-cluster collaboration in third markets n Representation in strategic markets

Initiatives to reinforce strategyn By strengthening competitiveness along the val-ue chain

-Delocalization of phases of the value chain -Joint productive internationalization

n By innovating in product design and manufac-turing

-Penetration of markets with sophisticated de-mand (test your product or service)

-Partnerships, alliances and consortiums with companies of superior know-how or technology on international projects / programs

-Gain access to the consumption habits of the end consumer in order to innovate in product/ser-vice n By excelling at the raw materials sourcing

-Grant access to key raw materialsSpecial attention is given to cross-national, in-

ter-cluster collaboration, a field where cluster de-

velopment is increasingly getting involved through-out Europe. The case of solar power clusters in Spain and France that collaborate to penetrate third countries around the Mediterranean basin, taking advantage of geographical and cultural links, with complementary specializations along the value chain, and the establishment of European decision-making institutions being headquartered in both Barcelona and Marseille.

In addition, a third section explores how region-al development agencies can support the interna-tionalization process of companies and how clus-ters facilitate this public-private effort. Based on four years of experience being in charge of sectoral policies at the Catalan Competitiveness Agency, examples of how a cluster approach had helped the agency to tackle initiatives that were in fact in position to better assist the real strategic needs of the companies, and optimized public resources to support the companies’ long-term strategies are introduced.

Long-term Sustainability of Cluster ini-tiatives: The Cluster Innovation SystemSolé, AlbertCluster Development, Barcelona

Cluster Development’s high degree of special-ization and the fact that, throughout its history, the firm sustained long-term relationships with a wide array of public-sector clients has gradually trig-gered the materialization of cluster development projects that, because of its approach and nature, are at the front line of the cluster arena at present times. That is to say, experienced clients with clus-ter experts on their teams (from regional govern-ments to local development agencies) increasingly require to take the cluster concept one step for-ward, defining solutions to guarantee the cluster’s ability to collaboratively identify and implement those initiatives that better serve winning competi-tive strategies.

Generally speaking, clusters are developed fol-lowing this basic methodological process:0. Strategy development: Shared vision and discus-

sion on the strategic focus of the cluster


1. Cluster activation: Formalization and articula-tion of the cluster, with transfer of leadership from the sponsor of the initiative to cluster com-panies and institutions

2. Cluster innovation system: Systematization of promotion and management of projects within the cluster and consolidation of the visibility and international positioning of the clusterStep number 2 will be the goal of the presenta-

tion. Those cases in which the cluster manages and participating companies and institutions manage to sustain the innovation-driven collaborative dynam-ics, to later draw the theoretical conclusions based on field experience (not the other way around) will be outlined. Often times we see how a cluster initia-tive successfully manages to kick-start the process and captures the ‘momentum’ to deliver short-term action initiatives. The real challenge, though, is how to bring into the formula the proper struc-tures, leadership and support to do that on a regu-lar basis, and without missing the strategic focus the cluster needs.

Given that Cluster Development SL works with both emerging and mature clusters, it is with this second group particularly that we have learn the dos and don’ts of long-term cluster dynamization, and the purpose of this presentation is to convey our learning experience in this field.

How to establish a cluster innovation systemThe training of the cluster manager is not enough to guarantee that the cluster faithfully follows a road-map towards the shared vision and, more so, that it is able to reinvent itself and refine the strategy as inescapable changes take place in global business. It is not a matter of the cluster manager’s ability alone, as that ‘roadmap’ is seldom a detailed plan that goes beyond the first year of implementation. Rather, the enduring cluster operations and process-es require that a specific set of ingredients are in place in order to foster the continuous mushroom-ing and implementation of strategic projects within the cluster. Therefore, it is imperative to establish a working methodology that goes beyond the mere facilitation of group discussions. This methodology will have to encompass three basic areas and three

different phases towards the generation of strategic projects:

Area 1: Strategic contentThe strategic content deals with the ongoing abil-ity to continuously identify, structure and develop those key areas of special interest for cluster com-panies that better support the strategic framework agreed upon during the activation of the cluster. Unlike other tools used to identify the current stra-tegic position of a cluster (often criticized for being too ‘static’), the proposed working scheme has to do with building on successes and failures of pre-vious years. The strategic content must noticeably influence the annual calendar of cluster activities and projects.

Area 2: ProcessThe process development has a dual objective—among cluster companies, first, and internation-ally speaking as well. Often times the local value chain is not comprehensive enough, forcing us to look overseas and to establish strategic alliances among clusters in order to develop state-of-the-art or excellent projects.

Area 3: CommunicationThe communication process is key to the cluster’s national and international visibility and to facili-tate the integration of new members and to estab-lish linkages with other clusters and international networks of experts.

The methodology is divided into three phases, each one consisting of different tools to generate content, to establish a cluster’s network of innova-tion (process), and for the visibility and positioning of the cluster (communication). The phases are the following:n To establish a technology monitoring and com-petitive intelligence system

It has to do with the definition and updating of strategies for the future of the cluster. It is nurtured by the continuous exposure to business trends and international best practices that may influence the key success factors within a business segment. This activity does not need to be done constantly, but the


platform for debate and discussion must be taken into account.n To reach consensus on and definition of the dif-ferent areas to developn To identify and select those projects that must be pursued immediately because either they represent short-term opportunities or because of strategic relevancen To establish a process for the execution of proj-ects

The project management process of those proj-ects identified in the previous phase has to be spe-cific, measurable and duly timed. It has to allow for a diversity of company typologies (with different capacities and resources) to participate according to the initiative, main objective and included tasks.

Improving Competitiveness and Innova-tion Through Better Cluster Manage-mentStürzebecher, Daniel Project Manager, Cluster Excellence, MFG Baden-Württem-berg mbH

How can cluster initiatives be managed profes-sionally? And what skills do cluster managers need when striving for cluster excellence? These ques-tions are being explored by the consortium around Cluster-Excellence.eu—the European Cluster Ex-cellence Initiative, a PRO INNO Europe Project lead by IESE Business School, University of Na-varra. Thirteen project partners from nine coun-tries—all well experienced in the field of cluster management and support—create a uniform set of cluster quality indicators and develop a label for promoting excellence in cluster management. The European Cluster Managers’ Club and the Cluster-Collaboration Platform set up within the frame-work of Cluster-Excellence.eu are modules to fos-ter excellence in cluster management.

Today, everybody can claim him or herself to be a cluster manager. While management at the compa-ny level has been developed as a science by business schools across the world, the skills needed for cluster management are still in a nascent stage. They are

only transmitted from master to apprentice based on experience on good judgement in codified knowl-edge. Cluster excellence means a more efficient cluster management that follows a methodological approach. Needless to say that better cluster man-agement not only serves the companies involved but results in a more efficient use of public funds pro-vided through cluster organizations. All modules of Cluster-Excellence.eu, therefore, target those clus-ter organizations who want to become excellent.

In order to make clusters competitive, the excel-lence of cluster management organizations has to be improved based on the given framework conditions. The promotion of high quality standards of cluster-related activities and services could be one of the main approaches to make cluster management more efficient. But to translate this overall goal into real-ity, a precondition is to make excellent cluster man-agement measureable before it can be improved.

Cluster-Excellence.eu thus is structured around a set of indicators that will define “quality cluster management”. The cluster quality label developed within the project will be based on these indicators. The overall approach is to create an independent, voluntary proof of cluster management excellence that is accepted and recognised all over Europe. The quality label will motivate cluster managers to com-pare with each other and to learn from the best. It is applicable for all different types of clusters exist-ing all over Europe and will enable cluster managers to demonstrate their excellence towards interested third parties like members, stakeholders and policy makers. The following aspects are important to point out, in order to clarify the intention of the label:n The quality Label focuses on cluster manage-ment, not on the framework conditions or a cluster as such.n It is based on a modular set of quality indicators and a transparent process of how to benchmark them.n The quality label is voluntary and enables cluster managers to receive proof of their cluster manage-ment excellence by an independent third body ac-cording to clear indicators.

The European Cluster Managers’ Club and the European Cluster Collaboration Platform, both


modules in the framework of Cluster-Excellence.eu, will support and promote the adoption of the label.

The Club will be the first professional associa-tion for cluster managers striving for excellence. It will provide different services to improve cluster managers’ skills. These range from the promotion of the label and the training materials to tailored activities like workshops and case studies on issues of special concern for cluster managers.

Clustering in the Republic of MacedoniaTrajanoska, NikolinaMinistry of Economy, Republic of Macedonia

Clustering represents a new, fairly unknown method for economic development and busi-ness partnership in the Republic of Macedonia. According to the research, three factors can be identified that are critical for the development of successful clusters in the region: 1. The presence of functioning networks and

partnerships2. A strong innovation base, with supporting

R&D activities where appropriate3. The existence of a strong skills base

Assessment of current situationThe process of clustering in the Republic of Mace-donia started in 2002 with the support of USAID project Macedonia Competitiveness Activities (2002-2006).

2002: Mapping, identification of potential clustersConclusion from the mapping exercise: Culture of cooperation is low but there are groups with potential for cluster development

Strategic decision: “Bottom-up approach”, learning by doing

2004: Pilot projectsStart with the pilot projects, invitation for the in-terested groups to become pilots

Selection of five projects with the highest in-terest and potential2007/2009: Cluster policy design (Ministry of Economy)

Cluster development programDirect measures: n Incentives for networking: Specialization in valued/production chains, development of tech-nology networks n Promotion of networking: Network of experts, management support in development of “local clusters”, experiences exchange n Incentives for cluster development: Support for initial phase (one year), support in develop-ment (two years)

Indirect measures: n Incentives for investment in R&D: Industrial research, technology investment for groups of companies and R&D institutions n Incentives for productivity increase measures: Introduction of new management tools, quality standards and continuous improvement systems in value/production chain

Several cluster initiatives are already oper-ating in Macedonia—textiles, information tech-nology, wine, tourism, lamb meat, sheep cheese, agricultural mechanization, automotive compo-nents, wood processing, food-processing, fashion design, etc. These clusters are at various stages of development and as such need specific support to further accelerate their development.

The key weakness that all existing Macedo-nian clusters share is a lack of potential for inno-vation, development of new products and services to compete better in the global markets. Existing clusters have mainly been created with the pur-pose of “grouping of small enterprises” to better sell on the markets and have done much less in the area of sharing and creating economies of scale in purchasing, applicable research and develop-ment and innovation. Big companies are gener-ally not active members of Macedonian clusters. Analysis of successful clusters around the world shows that successful clusters gather, apply and expand knowledge and create innovative solutions to business challenges. These qualities of cluster-ing still need to evolve in Macedonia.

According to the survey, Macedonian firms would highly appreciate policy measures oriented


in the enhancement of collaboration in networks and clusters regionally and internationally (5.26 on the scale between 1 and 6).

According to the interviewees, the most promising areas for networks/clusters in Mace-donia are the food industry (35.3%), agriculture (39.4%), tourism (23.5%), winery (20.6%), tex-tiles (18.6%), IT (18.6%), etc.

Macedonian companies exhibit the highest intensity of cooperation (networking) with their suppliers (score of 3.71 on the scale between 1 = weak and 6 = strong). The intensity of coopera-tion with the customers is not far behind (3.67). As expected the intensity of cooperation with competitors is much lower (2.23). In all three kinds of cooperation the exchange of information is the expertise, training and joint development of products/services. In the case of cooperation with competitors, there are possibilities of joint purchasing and joint marketing, but this proved to be less customers is stronger in the case of majority foreign-owned than majority domestic-owned firms, and in the case of export-oriented than in domestic-market-oriented firms. Thus, it seems that export market orientation stimulates cooperation/networking with other firms and that foreign-owned firms are more aware of the ben-efits of networking.

MeasuresThe following measures for collaboration in clus-ters and networks are introduced by the govern-ment:1. Further awareness raising and training for

clustering/networking: Awareness raising activities will be implemented by seminars, regional and international conferences and match-making events. Knowledge about clustering and cluster management will be strengthened by training sessions and interna-tional knowledge and experience exchanges.

2. Support cluster analysis and strategy develop-ment accompanied with action plan and spe-cific projects: Cluster analysis and strategy development will be supported by the govern-

ment together with action-oriented initiatives mobilizing a set of strong leaders from busi-ness, government and universities in a process that will enable competitiveness of Macedo-nian clusters. Specific development and inter-national cooperation projects of clusters would be co-financed by the government.

3. Supply chain partnerships acceleration: To im-prove the competitive position of the Macedo-nian industry, stronger supply chain partnership led by key exporters needs to be created. Groups of companies that co-operate as buyers and sup-pliers will be invited to apply for co-financing of analysis of existing supply chain and joint projects. Such projects can deal with variety of their business challenges, for example “on time delivery” implementation, better positioning on the wholesale or retail markets, implementation of common information system to track orders, inventory, etc.

4. Stimulation of, technological centers and parks on the regional level, support of networks of R&D institutions to provide a variety of ap-plicable technological services and integrated and efficient innovations: Members of such a network are to become a complete network of highly-qualified individuals and advanced tech-nological infrastructures driven towards pro-moting a solid and competitive industrial web.

Expected resultsImplementation of policy measures in clustering and networking will lead to the improvement of understanding of the positive effects of clustering and networking for the Macedonian industry.

Governmental support to clustering and net-working will emerge throughout the public-pri-vate dialogue, which will be beneficial for both, the public and private sector, to better overcome challenges of collaboration.

Implementation of policy measures (supported by the government as well as other donors, EU programs and funds) will contribute to the cre-ation of demonstration clusters as best practices for future innovation-based clustering.


The Role of International Cluster Coop-eration in Increasing the Prosperity of RegionsTõnnisson, Rene Baltic Innovation Agency, Estonia

When in 1776 Adam Smith published his seminal work Wealth of Nations, his intention was to exam-ine what makes nations prosper, but incidentally he also laid down the foundations of classical economic theory.

Based on some empirical experiences the presenta-tion examines what role clusters play in making their regions prosper and more specifically what is the role of international cluster cooperation in this respect, defined in the current presentation as intentional and structured attempt for internationalization.

The presentation focuses on the ways how clus-ters and cluster initiatives that are strongly engaged in international cooperation can contribute to the increase of prosperity in their own and other coop-eration regions. It particularly focuses on innovative cluster-based international cooperation approaches as new ways to stimulate prosperity.

The presentation includes the firsthand experi-ences gained from such innovative cooperation proj-ects like European Business and Technology Cen-ter (EBTC) in India, iRegions (Internet-based and mobile technologies for regions in the net economy), CLOE (Cluster Linked over Europe) and also reflects on the policy discussions and recommendations by the European Cluster Policy Group in this area.

Special mentionsAl-Zo’ubi, Kawthar A., Ministry of Planning and International Cooperation, Jordan; Asra, Sunil,

MDI, India; Ba, Ibrahima, PCE-USAID; Breault, Bob, Breault Research Organization, USA; Ca-vanagh, Stephen, Auckland Tourism, Events, Eco-nomic Development Ltd, New Zealand; Chaplin, Gareth, New Zealand Trade and Enterprise; Chap-lin, Gareth, New Zealand Trade and Enterprise; Eklund, Lars, The Scandinavian Competitiveness Group, Sweden; Enright, Michael, Enright Scott and Associates, HK; Ffowcs-Williams, Ifor, Clus-ter Navigators Ltd, New Zealand; Frater, Paul, Green Chip Ltd; Fuller, Cliff, New Zealand Trade and Enterprise; Gulati, Mukesh, Foundation for MSME Clusters, India; Gupta, V. K., MDI, India; Hagenauer, Simone, EcoPlus, Austria; Johansson, Cecilia, Vinnova, Sweden; Korpi, Anna, EduClus-ter Finland; Koziarski, Alan, New Zealand Trade and Enterprise; Kunt, Vedat, Vego Consulting, Turkey; Lalis, Georgette, European Commission, DG Enterprise and industry; Lehmacher, Wolf-gang, GeoPost Intercontinental; Maini, N.K., SIDBI, India; Markkanen, Mikko, Business Arena, Finland; Marsé, Marta, Government of Catalonia, Spain; Mittal, Manoj, SIDBI, India; Montoya, Manuel, CLAUT Automotive Cluster of Nuevo Leon, Mexico; Nawangwe, Barnabas, Makerere University, Uganda; Pamminger, Wer-ner, European Cluster Collaboration Platform and Clusterland Upper Austria; Ribas, Eduard, Cluster Development, Spain; Sarkar, Tamal, Foundation for MSME Clusters, India; Shah, Jagat, Cluster Pulse, India; Sorvari, Rauli, Regional Council of Central Finland; Subirà, Antoni, IESE Busi-ness School, Spain; Taylor, Joy, Desert Knowledge Australia; Wade, Ibrahima, SCA, Senegal; Wael-broeck-Rocha, Elisabeth, BIPE, France; Walker, Richard, Economic Development Australia

Institute for Competitiveness, IndiaAn international think tank dedicated to conducting meaningful research in the core fields of strategy, economic development, productivity and prosper-ity, the Institute for Competitiveness (IFC) works to put together a body of knowledge that encompasses economic distribution, business environments, distribution of wealth and enhancing productivity.

IFC is affiliated with the Institute for Strategy and Competitiveness at the Har-vard Business School and is dedicated to enlarging and disseminating the body of research and knowledge on competition and strategy as pioneered over the last 25 years by Professor Michael Porter.

PublicationsCity Competitiveness ReportDistrict Competitiveness ReportJournal of CompetitivenessLivability Index: The Best Cities in IndiaState Competitiveness Report

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