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International Journal of Productivity and Performance ManagementAn application of interpretative structural modeling of the compliance to foodstandardsSilpa Sagheer and Surendra S. Yadav S.G. Deshmukh
Article information:To cite this document:Silpa Sagheer and Surendra S. Yadav S.G. Deshmukh, (2009),"An application of interpretative structuralmodeling of the compliance to food standards", International Journal of Productivity and PerformanceManagement, Vol. 58 Iss 2 pp. 136 - 159Permanent link to this document:http://dx.doi.org/10.1108/17410400910928734
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Users who downloaded this article also downloaded:Jitesh Thakkar, S.G. Deshmukh, A.D. Gupta, Ravi Shankar, (2006),"Development of a balanced scorecard:An integrated approach of Interpretive Structural Modeling (ISM) and Analytic Network Process (ANP)",International Journal of Productivity and Performance Management, Vol. 56 Iss 1 pp. 25-59 http://dx.doi.org/10.1108/17410400710717073Jitesh Thakkar, Arun Kanda, S.G. Deshmukh, (2008),"Interpretive structural modeling (ISM) of IT-enablersfor Indian manufacturing SMEs", Information Management & Computer Security, Vol. 16 Iss 2 pp.113-136 http://dx.doi.org/10.1108/09685220810879609Singh, Ravi Shankar, Rakesh Narain, Ashish Agarwal, (2003),"An interpretive structural modeling ofknowledge management in engineering industries", Journal of Advances in Management Research, Vol. 1Iss 1 pp. 28-40 http://dx.doi.org/10.1108/97279810380000356
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An application of interpretativestructural modeling of the
compliance to food standardsSilpa Sagheer and Surendra S. Yadav
Department of Management Studies, Indian Institute of Technology (IIT) Delhi, New Delhi, India, and
S.G. DeshmukhDepartment of Mechanical Engineering, Indian Institute of Technology (IIT)
Delhi, New Delhi, India
Abstract
Purpose The aim of this paper is to identify and analyze critical factors/elements influencingstandards compliance and their level of influence in a developing country food industry, with specificreference to India.
Design/methodology/approach A total of 13 critical elements were identified and structuredusing pair-wise comparisons. Structural and reachability matrices were formed and iterated to yieldlevels of hierarchical influence of each element. MICMAC analysis was also performed to determinedependency and driving power of these elements.
Findings The analysis brought out a compelling need for sensitive and responsive action bydeveloping country governments while competing globally. Food industries in developing countriestend to detour while complying with standards, owing to costs involved in setting up systems andprocedures. While a strong surveillance mechanism is the high point of a good compliant system thishas to be preceded by supporting measures such as linking of domestic and international markets,consolidation of institutional structures, strengthening of legal/regulatory systems, etc.
Practical implications Use of interpretative structural modeling (ISM) is inspired by theversatility displayed by this method, as reported by researchers, across a wide spectrum of economicand competitive complexities affecting businesses.
Originality/value The study is a hitherto unexplored attempt, using interpretative structuralmodeling, to analyze standards compliance in a developing countrys food industry.
Keywords Structural analysis, Standards, Standards organizations, Food industry,Developing countries, India
Paper type Research paper
IntroductionPerformance of a system is dependent on a set of critical factors that act as enablers orinhibitors upon it. To function successfully, enablers have to be promoted andfacilitated, while inhibitors have to be eliminated or rehabilitated. Researchers fromIndia have been widely applying interpretative structural modeling (ISM) as a tool tounderstand the relationship between these critical enablers and disablers in SupplyChain Management (Mandal and Deshmukh, 1993; Jharkaria and Shankar, 2004, 2005;Ravi and Shankar, 2004; Ravi et al., 2005; Faisal et al., 2006; Thakkar et al., 2007). Thistool offers wider application possibilities and one such area of research is safety andquality systems.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1741-0401.htm
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Received September 2007Revised December 2007April 2008Accepted May 2008
International Journal of Productivityand Performance ManagementVol. 58 No. 2, 2009pp. 136-159q Emerald Group Publishing Limited1741-0401DOI 10.1108/17410400910928734
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Quality and performance of global agrifood business today is heavily influenced bystandards and regulatory regimes. It is dependent on national policy frameworks ofgovernments, quality and safety regulatory systems, compliance to rules and standardsetc. (Sagheer et al., 2006). While a regulatory framework commands automaticcompliance, systems in developing countries have shown lapses. Although their exportchannels display certain amount of orientation towards compliance, domestic channelslag behind. The challenge to maintain safety and quality is high, as it has graveimplications for global food trade. Food standard compliance, thus has become, one ofthe most debated and indulged topics in world trade forums (Wilson and Otsuki, 2001).
This paper aims to apply Interpretative Structural Modeling (ISM) and determinethe hierarchical and contextual relationships between factors influencing foodstandards compliance in a developing country. India specific examples are drawn out,to relate to Indian scenario. Major objectives of the paper can be summed up as:
. to identify elements enabling system standards compliance in a developingcountry food industry;
. to rank the identified elements;
. to map relationship between these elements; and
. to highlight relevance of the output.
The paper is organized into five sections. First segment is an introduction withobjectives of the paper. Section two explains Interpretative Structural Modeling (ISM),its purpose and contributions to literature. Section three lists in detail, steps inapplication of ISM. Section four consists of discussions and observations and sectionfive, the last section is concluding remarks and policy implications.
Interpretative structural modeling (ISM) application and relevance to thecontextInterpretative structural modeling (ISM) is a computer assisted process, first proposedby J. Warfield in 1973. This systematic application of elementary notions of graphtheory exploits theoretical, conceptual, and computational leverage, and constructs adirected graph or network representation of complex patterns of contextualrelationship among a set of elements. The process is one-to-one correspondence,between binary matrix and graphical representations of directed network. From binarymatrix, an iterative process extracts levels of relationship of each element in hierarchy.Fundamental concepts of ISM are element set and contextual relationship (Malone,1975). It is used by individuals and groups to understand complex situations and putstogether a course of action for solving problems. This tool is chosen to model criticalelements influencing standards compliance, considering its capability to map complexrelationships between them.
ISM is used in complex situations, where the user concentrates on hisunderstanding of the elements involved, to make subjective judgments on existingor absent relationships between each pair of elements (Malone, 1975). Sage (1977)explains it as a process transforming unclear, poorly articulated mental models ofsystems into well defined models useful for many purposes.
Janes (1988) comprehending the whole process of ISM, explained the interrelationsbetween issue, group and methodology and between content, context, process andproduct. Floods (1989) investigation of future scenario systems for problem solving
Interpretativestructuralmodeling
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explored methodologies that classify the system into two-dimensional grids. Hefound ISM a befitting open system, with an affinity for consensus as individualsare involved. The method recognizes the relevance of systems age as against themachine age, where problem solving means dealing with systems filled with people,are open, have purposeful parts and requires an approach that is holistic. ISMscapability to connect with cognitive levels of those involved in complex situations ispronounced and has been recorded by Bolanos et al. (2005).
A review of literature from India since 1990 reveals wide application of ISM onproductivity enhancement issues. In most cases, it is used to determine the influence ofenablers or inhibitors on a system as well as to examine their interweaving relationships.
Thakkar et al. (2007) used ISM along with other tools like cause-effect diagram andAnalytical Hierarchical Process (AHP) to develop a Balanced Score Card usingquantitative and qualitative approaches. Faisal et al. (2006) explored effective supplychain risk mitigation and used ISM to understand dynamics between various enablersthat mitigate risk in a supply chain. Jharkaria and Shankar (2005) used ISM toscrutinize barriers in information technology application to supply chain management.Ravi et al. (2005) found ISM practicable in determining key reverse logistic variableswhich the management should focus on to improve productivity and performance ofcomputer hardware supply chains. Ravi and Shankar (2004) merit ISMs capability toexplore mutual influences of elements and their roles in accelerating or deceleratingperformances of other elements. They applied this tool to analyze interactions amongbarriers of reverse logistics in a supply chain.
ISM has also been deployed in contexts as diverse as education program planning(Hawthorne and Sage, 1975), cross-cultural interactions (Jedlicka and Meyer, 1980),energy conservation in cement industry (Saxena et al., 1992), to information systemeffectiveness (Kanungo et al., 1999), to designs for product families based on marketrequirements (Hsiao and Liu, 2004).
Compilation of literature reviewed (Table I) brings out the versatility of ISM as atool capable of tackling myriad range of complex issues. The application bringsstructural clarity and establishes hierarchical order for prioritization and consequentaction. It is in this background that the paper attempts to analyze dynamics ofinter-relationships between critical elements enabling food standards compliance.
Applying interpretative structural modeling (ISM)Interpretative structural modeling can be applied by following certain steps. These canbe listed as:
(1) Define the background/problem.
(2) Identify elements.
(3) Pairwise comparison of elements using ISM software and generatingreachability matrix.
(4) MICMAC Analysis using dependency and driver power of elements inreachability matrix as co-ordinates.
(5) Partition reachability matrix.
(6) Form lower triangular matrix/conical matrix.
(7) Develop the digraph.
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Interpretativestructuralmodeling
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Defining the background/problemThe Oxford Dictionary defines a Standard as: a required or agreed level of quality orattainment; and something used as a measure, norm, or model in comparativeevaluations. British Standards Institution (BSI) defines a standard as a publishedspecification that establishes a common language, and contains a technicalspecification or other precise criteria and is designed to be used consistently, as arule, a guideline, or a definition. International Organization of Standards (ISO)explains that international standards provide a reference framework, or a commontechnological language, between suppliers and their customers which facilitatestrade and transfer of technology.
The Codex Alimentarius, Organization of International Epizootics (OIE) andInternational Plant Protection Committee (IPPC) are the three apex standard settingbodies in the global agrifood trade. Each one deals with food, animal health and planthealth respectively. In this paper, as discussions are on food standards compliance,references are mainly to Codex Alimentarius. This body was jointly set up by the Foodand Agriculture Organization (FAO) and the World Health Organization (WHO) in1961. Codex Standards have become de facto international standard in global foodtrade and a benchmark for national food safety legislation. From developing countriesviewpoints, compliance with Codex Standards means greater care in assuring thesafety of their food exports and improved access to export markets, especially indeveloped countries.
Despite the existence of Codex Alimentarius, many developed countries maintainstringent parameters than Codex. They have consistently upgraded their standards,particularly for imports, by installing new institutions, methods and standards toregulate food safety and hazard control. This has resulted in measures that accentuatecompliance issues. Standards are raised each time to next higher levels, in many cases,making it difficult for developing countries to cope with (Mehta, 2003; George, 2003).
Private standards. Private standards are developed by specific retailers, especiallythose with multinational nature. These standards combine food safety with certainamount of environmental health and workers safety and health requirements. Fulponi(2006) identified three major trends in emergence of private standards, these being:
(1) a shift to voluntary management systems;
(2) formation of coalitions to set-up private standards; and
(3) increased application of private standards in international businesses.
Berdegue et al. (2005) cited the near absence of public food safety and quality standardsand their ineffective implementation as reason behind emergence of these privatestandards.
Unnevehr and Jensen (1999) traced history of Hazard and Critical Control Points(HACCP) one of the earliest implemented private standards that gained acceptancein mid-nineties in Europe and North America and later in developing countries. Withthe waves of supermarket diffusions hitting developing countries of Central andLatin America, Africa and Asia, the agrifood industry has seen a spate of privatestandards (Reardon, 2006). Leading supermarket chains in Central America areimposing private standards on their suppliers to raise product quality, ensureconsistency and to differentiate their products from those of traditional retailers(Berdegue et al., 2005).
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The domestic regulatory scenario in India. The Bureau of Indian Standards (BIS) isthe main body entrusted with the framing of domestic food regulations in India. Whiletheir standards are voluntary, they play a guiding role for government agenciesformulating mandatory standards. Indian food regulations present a complex regimeand are cumbersome to manage for the enforcement authorities. Overall, sevendifferent ministries deal with food industry often causing duplicity and overlappinglegislation (Mehta and George, 2004). At the farm level, there is very little regulatorycontrol in domestic production system. The Food Safety and Standards Act FSA(2007), has proposed the establishment of a new authority called the Food Safety andStandards Authority, the reorganization of scientific support pertaining to the foodchain through the establishment of an independent risk assessment body, a new foodlaw, merging more than ten separate Acts and clarification of responsibilities of therelevant ministries.
ISM can be helpful in understanding standards compliance problem explained here.The tool can manage an in-depth scenario assessment by examining theinterrelationships between its elements.
Identification of elements enabling standards system complianceTo identify the elements, there has to be a thorough understanding of food safety andquality issues faced by developing countries.
Three tracks were followed to arrive at the critical elements. These were:
(1) Literature covering food standards compliance issues faced by developingcountries, their export challenges and cases specific to Indian scenario werereviewed. Major points emerging out of this were: increase in the number ofprivate/voluntary standards; lack of orientation of domestic laws tointernational standards and systems; absence of coordination betweenmonitoring agencies; and their subsequent impact on industry performance.
(2) Results from a survey conducted by one of the authors, as part of anindependent research earlier, to examine the impact of WTO and Codex onIndian food export industry and its responsiveness also helped to identifyelements. Out of 250 questionnaires dispatched to Indian food exportcompanies, 30 valid responses were received. Fresh and processed fruit andvegetable exporters formed a major proportion of respondents. Some of thefindings of this survey were 67 percent of respondents did not have updateson food standard developments related to their products; 77 percent were notaware of the dispute settlement mechanisms in WTO, Codex etc, 63 percentagreed that industry responsiveness to international food standards systemsand procedures were moderate. However, 70 percent of respondents felt thatgetting updated about international regulatory systems would be the bestoption to tackle trade competitiveness issues that they were facing.
(3) An expert panel consisting of five members two each from government andindustry respectively and one from research was formed. The two industryexperts were from export and domestic sectors respectively. Literature on ISMwas circulated, to familiarize experts with the tool. They were asked to list asmany ideas as possible and communicate them to authors in a specified format.
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As a result of following the three tracks, 13 elements were identified and ISM wasapplied in order to understand their relationships and impacts at compliance levels.
The 13 elements are:
(1) Develop a strong legal/regulatory system. Athukorala and Jayasuriya (2003)underlined the need for strong legal or regulatory mechanisms capable ofenforcing standards compliance. In most developing countries, while aregulatory framework exists, standard setting lacks a scientific rationale.Industry responsiveness to standards is dependent on the degree ofgovernments manageability of regulatory mechanisms in each country.
(2) Link domestic regulatory framework and performance in international markets.Competitive results in global trade demand extensive negotiating power, builtupon a strong domestic regulatory framework. Contrary to Porters (1990)theory of a highly demanding domestic market that can trigger betterinternational performance, there is dichotomy seen in compliance systems ofmost developing countries. The export channels are better compliant ascompared to domestic channels in countries such as China, India, Brazil, Kenya,Chile, etc. (Donovan et al., 2001; Athukorala and Jayasuriya, 2003; Sawhney,2005; Honma, 2006; Okello and Swinton, 2007).
(3) Lower certification costs. The highly prohibitive certification costs are adeterrent for developing country firms to adopt certification processes.EurepGAP (European Retailer Parties Good Agricultural Practices) nowre-christened GLOBALGAP the most commonly implemented certificationsystem at farm level has proved to be expensive for average farmer producers.To counter this practice, developing countries are preparing their own domesticstandards of Good Agricultural Practices (GAP) and benchmarking it withEurepGAP and similar standards. This reduces costs and establishes acustomized certification system for domestic sector. Except India (where thedraft IndiaGAP document is awaiting clearance from Ministry of Agriculture),Kenya, Uganda, Tanzania, Chile, Thailand, Indonesia, Philippines etc. are in theprocess of completing this exercise (UNCTAD, 2005, 2007).
(4) Increase control over primary production processes. Exercising control overprimary production systems means a methodical keeping of culture calendarsspray schedules, etc. at farm level. Tracking food from the field can reducecontaminants like microbiological, chemical and pesticide residues.Implementation of GAP standards is a strategic intervention to gain controlover primary production processes. GAP is currently restricted in mostdeveloping countries to only farms producing for exports. In India, thoughEurepGAP has been introduced in several farms producing for exports, firmsare concerned that the system exercises extreme controls over pesticide usage,cropping patterns, harvest mechanisms, post harvest handling etc.
(5) Consolidate and strengthen institutional structure. Duplication of regulationsand its administration are constantly highlighted issues in developingcountries, India being an apt example of this situation. Objective of the newfood law Food Safety and Standards Act, 2006 is to unify the system andconsolidate fragmented institutional structures. Good Agricultural Practices(GAP) at farm level, Good Manufacturing Practices (GMP), Good Handling
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Practices (GHP) and Hazard Analysis and Critical Control Points (HACCP) andsimilar manufacturing certifications require coordinated controls anddetermination of all institutional partners in government.
(6) Profile industry structure. The success of developed countries in ensuringregulatory compliance has a basis in the organized structure of their agrifoodindustries. Memberships of industry bodies or associations can be helpful, asplayers are structured to fit into various tiers of the industry. Law in mostdeveloped countries mandate entrepreneur registration with their respectivenational chambers of commerce. This helps in building a structured profile ofthe industry facilitating faster system implementations. The unorganizednature of Indian food industry is a major hindrance in tackling compliance.Producers and processors with small land holdings and medium and smallprocessing businesses are not well organized or are not registered members ofindustry associations and hence do not find proper representation in policymaking. The majority do not even have an understanding of the benefits ofjoining an industry association.
(7) Invest in physical infrastructure. Quarantine facilities, diagnostic laboratoriesand research centres equipped with sophisticated instruments and similar otherphysical infrastructure are decisive factors for food safety at operations level. InIndia, there are specialized government research centers for agrifood sector.While there are well equipped testing facilities operated in the private andgovernment sectors, there is need for more of these facilities to be establishedand existing ones to be upgraded. State-of-the-art food systems have emerged indeveloped countries, as a result of consumer interest and attention in the subject(Beulens et al., 2005). This has helped exporters of developing countries testresidue levels up to parts per trillion (ppt) as opposed to parts per million (ppm).Testing equipment and software capable of integrating the analytical,procedural and systemic functions that ensure a seamless flow of supplychain and traceability is a requisite to ensure competitiveness (Veen, 2005).Although this is an expensive exercise, developing countries in Asia such asChina, Thailand etc. and those in Africa that have extended their horticulturechains to developed markets, have their respective governments eithersupporting or driving installation of such testing infrastructure. In India, exporttesting facilities for some products and produce of spices and fruits have seenmuch investment and improvement.
(8) Track international food standards systems. A major role is accorded to Codexin international food regulatory systems, this being the basic and generalframework affecting almost any form of food traded in global markets. CodexCommission presents an opportunity for all countries to join the internationalcommunity in formulating and harmonizing food standards and ensuring theirglobal implementation. Hence, it is crucial for food companies to trackstandards setting at various stages in Codex. It can also be the referraldocument for food policy formulation by national governments. Stakeholders(represented by the farmer-producers, processors, exporters, government etc)participation is necessary in representing, debating and finalizing standardsand ensuring compliance at every level. National government representatives
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attending Codex sessions should be well prepared to defend their countrysstance. This can be realized only through consistent and co-ordinatedinteractions between relevant government departments and other stakeholders.
(9) Develop and maintain resource pool of human capital. The role of human capitalin agrifood industry operations and the regulatory framework is spread overstages of standard setting, its implementation and compliance. These processesprimarily involve scientists and other technical experts who provide inputs andalso government officials who represent the regulators. The scientificcommunity has specialized research centres in the country and specialistsfrom agriculture, horticulture, food technology, microbiology and such otherfields. Antle (1996) and Martin et al. (1999) have made notable contributions todeveloping the strength of agrifood industry in developed countries. Butdeveloping countries either exhibit dearth of scientific personnel or are laggardsin technology progress through research and developments in areas related tofood science and technology. Agrifood educational programs at universities indeveloping countries often do not attract best talents and this has a bearing onavailability of well trained personnel in the industry. Majority of the small andmedium farmers and food processors in developing countries including India,lack focus and understanding of regulatory requirements they need to fulfill.
(10) Sensitive and responsive government intervention and support. The significanceof interrelationship between regulatory activities of government and behaviorof firms has been researched by Caswell and Johnson, 1991; Henson andHeasman, 1998 etc. But there is a dearth of similar research in food industry(Henson and Hooker, 2001). As standard making and implementation aredemanding procedures, only governments exhibiting sensitiveness andresponsiveness to domestic and international regulatory scenarios canbecome competitive. This is further reinforced by the stringent regulationsimposed by developed countries. Weak institutional and physical infrastructureand disjointed administrative controls and multiplicity of laws can cripplegovernment action and encourage non-compliance. These have to be addressedto allow reaction and response from the government in the form of gradedpenalties on an offence committed.
(11) Bridge industry and research academia gaps. Agrifood business being a sciencebased industry demand technical knowledge, transfer of technology and accessto well trained personnel and infrastructure. These services when provided byconsulting companies in research can be costly for the small and mediumfarmer-producer or processor in developing countries. Research academiarepresents an alternative and cost efficient, but vast repository of scientificknowledge in the industry. One way of capitalizing on this knowledge forbusiness is to bridge the industry-academia gap (Etzkowitz and Stevens, 1998).Developed country experiences with academia interaction have led to theincorporation of successful business models (Defazio and Garcia-Quevedo,2006). An understanding of the industry at operational level by academia cangenerate creative and strategically efficient economic solutions.
(12) Strengthen surveillance systems. Surveillance implies watchful approach with acontinuous feed of measured performance on defined parameters of food safety
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by personnel with scientific knowledge. Standards compliance, especially indeveloping countries can be implemented only with the aid of strongsurveillance systems (Wilson, 2001; Aloui and Kenny, 2005). This has to besupported by an appropriately structured feedback mechanism, strategicallymanaged information system, coordinated interaction between relevantagencies, technically sound infrastructure, financially empowered resourcesand well trained manpower. As an integral part of the food safety framework,surveillance systems in developed countries conduct surveys on areas likechemical contaminants in food, chemical contaminants from food contactmaterials, food additives, food authenticity, microbiological contamination offood, etc. (Lang, 1999). In the UK, a consumer is allowed access to details ofanalysis and brand names disclosed as a result of open policy followed by thegovernment (FSA, 2007). As a result of mandatory export norms brought out byIndias national food export development authority Agricultural andProcessed Food Export Development Authority (APEDA) the first successfulcase of complete compliance to domestic traceability standards, right from thefarmer to the importer, has been implemented in grape exports to EuropeanUnion.
(13) Respond to customer/market requirement. Producer/processors compliance ofstandards is influenced heavily by market and customer requirementsparticularly in export channel. On the contrary, domestic scenario in developingcountries depicts consumer awareness and sensitiveness only at a basic level.This dichotomy is well documented in an empirical research conducted onBrazilian agrifood industry (Donovan et al., 2001). The study shows higherimplementation rates of HACCP systems in meat export firms, as compared tothe domestic firms dealing in fisheries. This pattern is however changing asretail chains now emerging as major players in the domestic market arebeginning to enforce compliance requirements (Reardon et al., 1999; Punjabi andSardana, 2007).
The identified elements along with their labels used for ISM are given in Table II.
Element No. Element detail
1 Strong legal/regulatory system2 Linking domestic regulatory framework and performance in international
markets3 Lowering certification costs4 Increase in control over primary production processes5 Consolidation and strengthening of institutional structure6 Industry structure7 Investing in physical infrastructure8 Tracking international food standards system9 Resourceful pool of human capital
10 Sensitive and responsive government intervention and support11 Bridging industry and research academia gaps12 Strengthening surveillance systems13 Market/customer requirement
Table II.Identified elementsenabling food standardscompliance in developingcountry
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Pairwise comparison of identified elements that enable standards complianceA contextual relationship leads to was chosen to identify the interacting position ofeach element. This means that one element leads to the other. An initial 13 13 matrixwas developed for identified elements. Paired comparison between each pair wasconducted and their relationship was indicated using Y for Yes and N for No ina matrix and was sent to experts for their opinion. This, instead of the Structural SelfInteraction Matrix (SSIM) method, was adopted as two experts were not very familiarwith SSIM matrix formation. Based on expert opinion, some relationships presentedwere modified. To generate the Reachability Matrix, ISM software was used. Thesoftware utilizes mathematical algorithms that minimize number of queries necessaryto explore relationships among a set of ideas (Warfield, 1976). The final pairedcomparison result was used as input. In earlier studies conducted using ISM, thisexercise was manually performed by Mandal and Deshmukh (1993), Ravi et al. (2005),etc. A sample window depicting structural analysis comparison between each pair towhich answer is Yes or No, is shown in Figure 1.
The Reachability Matrix, indicating the relationship between elements in binaryform was thus formed (Table III). Yes was encoded as 1 and No was encoded as0.
The horizontal summation of entries (i.e. 1) indicates driver power and verticalsummation of the same indicate dependence power. For example, driver power anddependence power of element 4 are 6 and 8 respectively.
MICMAC analysisDeveloped between 1972 and 1974 by J.C. Duperrin and M. Godet, MICMAC Analysis,stands for: matrice dimpacts croises multiplication applique a un classement(cross impact matrix-multiplication applied to classification). It complements andextends impressions experienced users draw from visual analysis of influencestructures. Specifically, MICMAC explores influence and dependence between issuesand classifies them into dominant, relay, dominated and autonomous (Godet et al.,2003) clusters. From Reachability Matrix, driver power of each element is obtained bythe summation of 1s in corresponding row. Similarly, dependence power of each
Figure 1.Sample window of ISM
software depictingstructural analysis
comparison
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element is obtained by the summation of 1s in the corresponding column. Afterobtaining driver power (influencer) and dependence of each variable, they arepresented as driver power-dependence matrix. Elements are plotted as points usingconventional x-y co-ordinate system.
A movement to the right of the scale indicates an increase in dependence while thatfrom bottom to top shows a rise in driver power. South-West quadrant the area nearorigin with lowest points on both scales indicate an autonomous cluster I. TheSouth-East quadrant with highest point on dependence and lowest point on driverpower is the dominated/dependent cluster II. North-East quadrant with its highdependence and high driver power is the relay/linkage cluster IV. This quadrantindicates high driver power and low dependence and is therefore calleddominant/independent cluster III.
The MIC-MAC Analysis Matrix (of elements enabling food standards compliance) isshown in Figure 2. It can be seen that both Cluster I and III representing autonomousand relay/linkage elements have no constituents. Elements have gathered in clusters IIand IV respectively and provide clear hierarchical indication on the nature of theirdependencies. In the order of most dependent with least driving power, elements stackup from 12 (strengthen surveillance systems), 11 (bridge industry and researchacademia gaps) and 9 (develop and maintain resource pool of human capital), 8 (trackinternational food standards system), 7 (invest in physical infrastructure) leading up to4 (increase control over primary production processes) in cluster II representingdominated/depending element.
In cluster IV, indicating dominance or independence, elements stack down from 10(sensitive and responsive government intervention and support), to 5 (consolidate andstrengthen of institutional structure), 1 (develop strong legal/regulatory system), 2 (linkdomestic regulatory framework and performance in international markets), 3 (lowercertification costs) and 13 (respond to market/customer requirement). They plot adiagonal pattern starting from most driving and least dependent to least driving andmost dependent element in this cluster. Element 6 (profile industry structure) plotted in
Elements (i/j) 1 2 3 4 5 6 7 8 9 10 11 12 13 Driver power Ranks
1 1 1 1 1 0 0 1 1 1 0 1 1 1 10 III2 0 1 1 1 0 0 1 1 1 0 1 1 1 9 IV3 0 0 1 1 0 0 1 1 1 0 1 1 1 7 V4 0 0 0 1 0 0 1 1 1 0 1 1 0 6 VI5 1 1 1 1 1 0 1 1 1 0 1 1 1 11 II6 0 0 0 1 0 1 1 1 1 0 1 1 0 7 V7 0 0 0 0 0 0 1 1 1 0 1 1 0 5 VII8 0 0 0 0 0 0 0 1 1 0 1 1 0 4 VIII9 0 0 0 0 0 0 0 0 1 0 1 1 0 3 IX
10 1 1 1 1 1 1 1 1 1 1 1 1 1 13 I11 0 0 0 0 0 0 0 0 0 0 1 1 0 2 X12 0 0 0 0 0 0 0 0 0 0 0 1 0 1 XI13 0 0 0 1 0 0 1 1 1 0 1 1 1 7 VDependence 3 4 5 8 2 2 9 10 11 1 12 13 5Ranks IX VIII VII VI X X V IV III XI II I VII
Table III.Reachability Matrix
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this cluster is, but seen, breaking away from the diagonal pattern followed otherwiseby all elements. At driving power 7 and dependence 2, this element indicates itscapability to exert considerable influence on standards compliance, but requires to besupported by driving power of other independent elements as well.
Partitioning the reachability matrixTo obtain ISM hierarchy, the reachability matrix was partitioned, by derivingreachability and antecedent sets. The element itself and other elements, to which it mayreach to, generate reachability set whereas the element itself and other elements whichmay reach to it generate antecedent set.
For example, in the case of element 4 (in Table IV), reachability set consists ofelements with entry 1 in horizontal row corresponding to element 4. These are 4, 7,8,9,11 and 12. Similarly, for element 4, antecedent set consists of those elements withentry 1 in vertical column corresponding to element 4. These are 1,2,3,4,5,6,10 and 13.
Intersections of these two sets were iterated and levels derived for each element.Result of the first iteration is shown as level I. No other element can be reached abovethis top-most level (Mandal and Deshmukh, 1993). With identification of each level,corresponding element(s) were separated from other elements and further iterationsperformed until levels of all elements were identified. Result of this exercise showingthe first level of iteration is shown in Tables IV.
Figure 2.MICMAC Analysis Matrix
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For any element, if reachability set is a complete subset of antecedent set, that elementwas taken out and iteration process continued. Thus, after iteration1 (Table IV), forelement 12 alone, the reachability set {12} is a complete subset of its antecedent set{1,2,3,4,5,6,7,8,9,10,11,12,13}. Hence, element 12 was taken out of the process and keptat Level I. Thereafter, the iteration process was continued to determine the elements atlevels II, III, IV, etc. Results of iterations at level II and XII (final level) are shown inTables V and VI respectively.
Forming lower triangular matrix or conical form of matrixLevels of enabling elements for standards compliance brought out by the intersectionsof reachability and antecedent sets can be converted into a lower triangular matrix orconical matrix. It provides a clear indication of each elements hierarchy of influence.Beginning with the element at level I and its corresponding elements that reach to it, abinary matrix is formed. In this case, presented in Table VII, at the top level is element
Elements Reachability set Antecedent set Intersection(Pi) R(Pi) A (Pi) R(Pi) > A(Pi) Level
1 1,2,3,4,7,8,9,11,13 1,5,10 12 2,3,4,7,8,9,11,13 1,2,5,10 23 3,4,7,8,9,11,13 1,2,3,5,10 34 4,7,8,9,11, 1,2,3,4,5,6,10,13 45 1,2,3,4,5,7,8,9,11,13 5,10 56 4,6,7,8,9,11 6,10 67 7,8,9,11 1,2,3,4,5,6,7,10,13 78 8,9,11 1,2,3,4,5,6,7,8,10,13 89 9,11 1,2,3,4,5,6,7,8,9,10,13 9
10 1,2,3,4,5,6,7,8,9,10,11,13 10 1011 11 1,2,3,4,5,6,7,8,9,10,11,13 11 II13 4,7,8,9,11,13 1,2,3,5,10,13 13
Table V.Partitioned ReachabilityMatrix at level II
Elements Reachability set Antecedent set Intersection(Pi) R(Pi) A (Pi) R(Pi) > A(Pi) Level
1 1,2,3,4,7,8,9,11,12,13 1,5,10 12 2,3,4,7,8,9,11,12,13 1, 2,5,10 23 3,4,7,8,9,11,12,13 1,2,3,5,10 34 4,7,8,9,11,12 1,2,3,4,5,6,10,13 45 1,2,3,4,5,7,8,9,11,12,13 5,10 56 4,6,7,8,9,11,12 6,10 67 7,8,9,11,12 1,2,3,4,5,6,7,10,13 78 8,9,11,12 1,2,3,4,5,6,7,8,10,13 89 9,11,12 1,2,3,4,5,6,7,8,9,10,13 9
10 1,2,3,4,5,6,7,8,9,10,11,12,13 10 1011 11,12 1,2,3,4,5,6,7,8,9,10,11,13 1112 12 1,2,3,4,5,6,7,8,9,10,11,12,13 12 I13 4,7,8,9,11,12,13 1,2,3,5,10,13 13
Table IV.Partitioning ReachabilityMatrix Iteration I
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12 (strengthening surveillance systems). This was placed as the first element followedby elements 11 (bridging industry and research academia gaps), 9 (resource pool ofhuman capital), 8 (tracking international food standards system), 7 (investing inphysical infrastructure) etc.
Development of digraphISM application in agrifood industry can be successful only if it is rightly interpretedby relevant stakeholders. While lower triangular or conical matrix is a familiar form ofpresentation in discipline of mathematics, it is not so for food industry practitioners orpolicy makers. Hence, a structural model was generated by means of vertices or nodesto present the results graphically. The relationships between elements are shown withthe help of arrows. Presentation of this nature is called a directed graph or digraph. Adigraph pictorially interprets contextual relationships between each of these elementsand their hierarchies, as derived by modeling.
Elements 12 11 9 8 7 4 6 13 3 2 1 5 10
12 1 0 0 0 0 0 0 0 0 0 0 0 011 1 1 0 0 0 0 0 0 0 0 0 0 0
9 1 1 1 0 0 0 0 0 0 0 0 0 08 1 1 1 1 0 0 0 0 0 0 0 0 07 1 1 1 1 1 0 0 0 0 0 0 0 04 1 1 1 1 1 1 0 0 0 0 0 0 06 1 1 1 1 1 1 1 0 0 0 0 0 0
13 1 1 1 1 1 1 0 1 0 0 0 0 03 1 1 1 1 1 1 0 0 1 0 0 0 02 1 1 1 1 1 1 0 1 1 1 0 0 01 1 1 1 1 1 1 0 1 1 1 1 0 05 1 1 1 1 1 1 0 1 1 1 1 1 0
10 1 1 1 1 1 1 1 1 1 1 1 1 1
Table VII.Lower triangular/conical
matrix
Elements Reachability set Antecedent set Intersection(Pi) R(Pi) A (Pi) R(Pi) > A(Pi) Level
1 1,2,3,4,7,8,9,11,12,13 1,5,10 1 X2 2,3,4,7,8,9,11,12,13 1, 2,5,10 2 IX3 3,4,7,8,9,11,12,13 1,2,3,5,10 3 VIII4 4,7,8,9,11,12 1,2,3,4,5,6,10,13 4 VI5 1,2,3,4,5,7,8,9,11,12,13 5,10 5 XI6 4,6,7,8,9,11,12 6,10 6 VII7 7,8,9,11,12 1,2,3,4,5,6,7,10,13 7 V8 8,9,11,12 1,2,3,4,5,6,7,8,10,13 8 IV9 9,11,12 1,2,3,4,5,6,7,8,9,10,13 9 III
10 1,2,3,4,5,6,7,8,9,10,11,12,13 10 10 XII11 11,12 1,2,3,4,5,6,7,8,9,10,11,13 11 II12 12 1,2,3,4,5,6,7,8,9,10,11,12,13 12 I13 4,7,8,9,11,12,13 1,2,3,5,10,13 13 VII
Table VI.Partitioned ReachabilityMatrix at final level XII
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Observations and discussionStandards compliance is a key area affecting competitive performance of food industryand has implications for both global and domestic markets. Interpretative StructuralModeling (ISM) of critical enabling elements for food standards compliance in adeveloping countrys food industry is shown in Figure 3. Specific cases from Indianconditions have been used throughout the study. Depending on their levels ofhierarchy of influence, elements are presented in the form of a digraph.
On top level of the hierarchy lay dependent factors. These can be achieved with thesupport of drivers or independent elements, as found out from MICMAC analysis.Element 10 (sensitiveness and responsiveness of government) showed maximumdriver power while element 12 (strengthening surveillance systems) showed maximumdependence, and this was further brought out in the digraph. Thus, element 10(sensitive and responsive intervention of government) was identified as the key enablerinfluencing compliance of standards. This element needs continuous monitoring, asgovernment sensitiveness and responsiveness has an overarching effect on allother elements. Element 5 (consolidate and strengthen institutional structures), next inthe hierarchy, is decisive in translating governments sensitiveness and responsivenessto compliance.
Element 3 (develop strong legal/regulatory system) is third in hierarchy. It imbibesstrength from the two earlier explained elements 10 and 5 respectively. Entrepreneursin developing countries are faced with business and economic inefficiencies, due towhich a majority take detour to compliance. This, they believe will help reduceoperating costs and increase profits.
Element 2 (link domestic and international markets) is instrumental in realizingelement 3 (lower certification costs) as certification (private standards a sine-qua-nonfor the export industry) is becoming a necessity in global competitive trade.
Element 8 (track international food standard systems) can give major impetus tostandards compliance. Agrifood companies engaged in this exercise are very limited.Element 10 (sensitive and responsive government intervention and support) is theenabler for other elements 5 (consolidate and strengthen institutional structures), 1(develop strong legal/regulatory framework), 2 (link domestic and international marketperformance requirements), 3 (lower certification costs), 13 (respond to market orcustomer requirements), 4 (increase control over primary production processes) and 7(invest in physical infrastructure) respectively. They play a major role in successfullytracking the progress in food standard setting at international levels.
Element 6 (profile industry structure) falls in the independent/ dominating clusterIV of MICMAC analysis, but is not very strong an element as depicted. However, itimpacts other elements. Entrepreneurs and their farming/processing units, whenlawfully registered become part of an organized group. This can structure the industryand provide it greater visibility, making this an enabling factor for standardsenforcements and subsequent compliance. Standards enforcement is an acceptablechallenge when industry is organized. The food sector in developing countries has verylittle organized component. Membership of organized professional groups will enhanceopportunities and exposure of farmer-producers or entrepreneurs. It will also helpunderstand competitors processes and standards compliance measures. The practicalapplication of element 12 (strengthen surveillance system) is recognized. It is alsorealized that industry structure further influences elements 4 (increase control over
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Figure 3.Interpretative structural
modeling (ISM) forelements enabling
standards compliance indeveloping country food
industry
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primary production, 7 (investment in physical infrastructure) and 9 (develop andmaintain resource pool of human capital) etc.
Element 11 (bridge industry and research academia gap) is critical in standardsenforcement and indicates high dependency. This can tap potential of scientificcommunities and research facilities available in developing countries such as India.Competitive strengths in knowledge domain possessed by research academia canenhance understanding of standards and their relevance/implications for a produce orproduct. The element however is dependent on elements 1 (develop stronglegal/regulatory system), 10 (sensitive and responsive intervention of government) etc.
Concluding remarks and policy implicationsAs digraph in Figure 3 indicates, the most critical element capable of firing up enablersfor standards compliance is element 10 (sensitive and responsive governmentintervention and support). Role of government in a developing country scenario can becrucial, as shown by the output of ISM process. This element can initiate, revive andgenerate responsive action from all stakeholders, provided commitments are assuredin its own ranks. Each element identified has a policy implication and these are listed,keeping Indian context in focus:
(1) Element 5 (consolidate and strengthen institutional infrastructure) can be thefirst measure of action towards compliance. Fixing accountability in managerial(officer) cadres will enable responsive and timely action leading to realisticmonitoring of institutional set ups, preparation and ground work for policymaking involving stakeholders at all levels, expeditious but prudent andrationalistic decision making on policy programs and their successfulimplementation.
(2) Government initiative towards element 1 (develop strong legal/regulatorysystems) has to move on fast track. Taking other developing countries cases asexample, Indian government should implement IndiaGAP at the earliest tostrengthen domestic producers at the farm level and equip them to handleglobal private standard systems.
(3) The government should do away with dichotomy in production channels forexports and domestic markets. This can be done in phases and domesticstandards can progressively move towards global production standards, thuselement 2 (link domestic regulatory framework and performance).
(4) Element 3 (lower certification costs) can be realised with the implementation ofIndiaGAP. Lower costs thus can not only help government make IndiaGAPmandatory but can also motivate farmer producers to implement it. While in theshort run, this exercise could bring a certain amount of hardship to theproducers in terms of compliance, in the long-run, this will benefit domesticproducers and give them impetus to produce better quality products and realizehigher incomes::. The government should update and annually publish the registered list of
food processing companies in agrifood sector. This should be consolidated ata central location rather than with different government divisions handlingfruit and vegetables, meat and meat products, marine products etc.
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. A single national chamber of commerce or industry association should berecognized by government as apex body for agrifod processing sector. Itshould be made mandatory for all producers and processors to be registeredwith this association. It should be capable of readily providing a groupstructure to the sector. Membership of association should entitle members toinformation feeds on regulatory requirements pertaining to investment,production, processing, global practices etc. through a single window. Thisassociation can also act as a major link between industry and government inpolicy making and other activities.
The two action points will help element 6 (profile industry structure) and thushelp in systems monitoring, tracking compliance practices etc.
(5) Campaigns have to be initiated to sensitize and develop, especially in producerprocessor communities, an appreciation for standards compliance and itsimplications for them in global context. Using visual media aids anddocumented publications, these campaigns should be actively initiated andimplemented. Responsibilities for running these campaigns can be entrustedwith village level extension officers at grass roots, a cadre whose performancehas been a cause of concern for producer and hence require urgentaccountability and action. This, along with other recommendations would becrucial for element 4 (increase control over primary production processes).
(6) The government should encourage element 7 (invest in physical infrastructure)such as testing facilities, research centres etc. through Public-Private-Participation (PPP) mode. Community infrastructure is costly to build andgovernments have meager resources which tend to be thinly spread over differentprojects. A collaborative effort, involving industry stakeholders will helpgovernment leverage private sector capital, project management expertise etc.
It should be mandatory to initiate preparatory processes in sufficient advance ofCodex and such other international negotiation meetings, Government shouldalso make it mandatory to include a designated technical-cum-legal expert(entrusted with tracking of Codex meetings and preparatory processes) whoseminimum serving period should be five years. This will ensure continuity andregularity to the team preparing for such missions. Industry also should besensitized through campaigns on significance of element 8 (track internationalfood standards systems) at their ends.
(7) Under the main authority on food standards, government should set up a teamof exclusive and well trained scientific and legal professionals (element 9 develop and maintain resource pool of human capital) qualified to deal withtechnical and regulatory issues in agrifood sector. They should be trained underexpert guidance to follow Codex and allied or related global regulatory systemsand procedures and be capable of developing trade documents if necessary orprovide advisory services to the government as well as industry.
(8) Projects ensuring collaborative working by academia and industry can beinitiated under government schemes for program implementation and growth.Incentives to firms implementing academia researched projects in theirbusinesses and similar incentives for team based academia initiatives, whereresearch is transformed and utilized in actual businesses can provide impetus toelement 11 (bridge industry academia gaps).
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Standards compliance in developing countries can be realized only throughcoordinated efforts led by government which is well participated and collaboratedby industry stakeholders and sustained by element 12 (strengthen surveillancesystems).
This paper has attempted to model, using Interpretative Structural Modeling (ISM),elements that influence the standards compliance in a developing country with specificexamples from India Standards compliance issues are major limiting factors in globaltrade for developing economies. While ISM has been widely used in supply chainresearch to examine performance of operations related activities, this is a hithertounexplored use of the tool to examine food standards compliance and its dimensions.The paper spells out the need for the government in a developing country, to take thelead by becoming more sensitive and responsive to its regulatory framework. Thiswould have a cascading effect on the working of other elements and thus lead to higherstandards compliance results and consequent positive business performances. Theexercise has highlighted the hidden relationships between various elements andprovides clear directions to areas where actions need to be taken.
References
Aloui, O. and Kenny, L. (2005), The costs of compliance with SPS standards for Moroccanexports: a case study, World Bank Agriculture and Rural Development Discussion Paper,The World Bank, Washington, DC.
Antle, J.M. (1996), Efficient food safety regulation in the food manufacturing sector, AmericanJournal of Agricultural Economics, Vol. 78 No. 5, pp. 1242-7.
Athukorala, P. and Jayasuriya, S. (2003), Food safety issues, trade and WTO rules: a developingcountry perspective, The World Economy, Vol. 26 No. 9, pp. 1395-416.
Berdegue, J.A., Balsevich, F., Flores, L. and Reardon, T. (2005), Central American supermarketsprivate standards of quality and safety in procurement of fresh fruits and vegetables,Food Policy, Vol. 30 No. 3, pp. 254-69.
Beulens, A.J.M., Broens, D., Folstar, P. and Hofstede, G. (2005), Food safety and transparency infood chains and networks relationships and challenges, Food Control, Vol. 16, pp. 481-6.
Bolanos, R., Fontela, E., Nenclares, A. and Pastor, P. (2005), Using interpretative structuralmodeling in strategic decision-making groups, Management Decision, Vol. 43 No. 6,pp. 877-95.
Caswell, J.A. and Johnson, G.V. (1991), Firm strategic response to food safety and nutritionregulation, in Caswell, J.A. (Ed.), Economics on Food Safety, Elsevier, New York, NY,pp. 273-97.
Defazio, D. and Garcia-Quevedo, J. (2006), The government-academia-industry relationship inCatalonia, International Journal of Foresight and Innovation Policy, Vol. 2 Nos 3/4,pp. 327-44.
Donovan, J.A., Caswell, J. and Salay, E. (2001), The effect of stricter foreign regulations on foodsafety levels in developing countries: a study of Brazil, Review of Agricultural Economics,Vol. 23 No. 1, pp. 163-75.
Etzkowitz, H. and Stevens, A.J. (1998), Inching toward industrial policy: the universitys role ingovernment initiatives to assist small innovative companies in United States,in Etzkowitz, H., Webster, A. and Healey, P. (Eds), Capitalizing Knowledge: NewIntersections of Industry and Academia, SUNY Press, New York, NY, pp. 215-39.
IJPPM58,2
156
Dow
nloa
ded
by U
nive
rsita
s Gad
jah M
ada A
t 00:2
3 03 M
ay 20
15 (P
T)
-
Faisal, M.N., Banwet, D.K. and Shankar, R. (2006), Supply chain risk mitigation: modeling theenablers, Business Process Management Journal, Vol. 12 No. 4, pp. 535-52.
Flood, R.L. (1989), Six scenarios for the future of systems problem solving, Systems Practice,Vol. 2 No. 1, pp. 75-99.
FSA (2007), Food surveys information page, Food Standards Agency, UK, available at: www.food.gov.uk/science/surveillance/ (accessed September 14, 2007).
Fulponi, L. (2006), Private voluntary standards in the food system: the perspective of major foodretailers in OECD countries, Food Policy, Vol. 31 No. 1, pp. 1-13.
George, J. (2003), Food standards and market access time for a new engagement?, BusinessLine, September 11.
Godet, A.J., Meunier, M.F. and Roubelat, F. (2003), Structural analysis with the MICMACmethod & actors strategy with MACTOR method, in Glenn, J.C. and Gordon, T.J. (Eds),AC/UNU Millennium Project: Futures Research Methodology-V2.0, AC/UNU, Washington,DC.
Hawthorne, R.W. and Sage, A.P. (1975), On applications of interpretive structural modeling tohigher education program planning, Socio-Economic Planning Sciences, Vol. 9 No. 1,pp. 31-43.
Henson, S. and Heasman, M. (1998), Food safety regulation and the firm: understanding thecompliance process, Food Policy, Vol. 23, pp. 19-23.
Henson, S. and Hooker, N.H. (2001), Private sector management of food safety: public regulationand role of private controls, The International Food and Agribusiness ManagementReview, Vol. 4 No. 1, pp. 7-11.
Honma, M. (2006), WTO negotiations and other agricultural trade issues in Japan, The WorldEconomy, Vol. 29 No. 6, pp. 697-714.
Hsiao, S. and Liu, E. (2004), A structural component-based approach for designing productfamily, Computers in Industry, Vol. 56, pp. 13-28.
Janes, F.R. (1988), Interpretative structural modeling: a methodology for structuring issues,Transactions Institute of Measurement and Control, Vol. 10 No. 3, pp. 145-54.
Jedlicka, A. and Mayer, R. (1980), Interpretive structural modeling cross-cultural uses,Transactions on Systems, Man, and Cybernetics, Vol. 10 No. 1, pp. 49-51.
Jharkaria, S. and Shankar, R. (2004), IT enablement of supply chains: modeling the enablers,International Journal of Productivity and Performance Management, Vol. 53 No. 8,pp. 700-12.
Jharkaria, S. and Shankar, R. (2005), IT-enablement of supply chains: understanding thebarriers, Journal of Enterprise Information Management, Vol. 18 No. 1, pp. 11-27.
Kanungo, S., Duda, S. and Srinivas, Y.A. (1999), A structured model for evaluating informationsystems effectiveness, Systems Research and Behavioral Science, Vol. 16, pp. 495-518.
Lang, T. (1999), Efficient food: the complexities of globalization: the UK as a case study oftensions within the food system and the challenge to food policy, Agriculture and HumanValues, Vol. 16 No. 2, pp. 169-85.
Malone, D.W. (1975), An introduction to the application of interpretative structural modeling,Proceedings of the IEEE, Vol. 62 No. 3, pp. 397-404.
Mandal, A. and Deshmukh, S.G. (1993), Vendor selection using interpretative structuralmodeling, International Journal of Operations & Productions Management, Vol. 14 No. 6,pp. 52-9.
Interpretativestructuralmodeling
157
Dow
nloa
ded
by U
nive
rsita
s Gad
jah M
ada A
t 00:2
3 03 M
ay 20
15 (P
T)
-
Martin, E.E., Knabel, S. and Mendenhall, V. (1999), A model train-the-trainer program forHACCP based food safety training in retail/food service industry: an evaluation, Journalof Extension, Vol. 37 No. 3.
Mehta, R. (2003), Food safety: distorting standards that impede exports, Business Line, June 30.
Mehta, R. and George, J. (2004), Food Safety Regulations Concerns and Trade, Macmillan India,Delhi.
Okello, J.J. and Swinton, S.M. (2007), Compliance with international food safety standards inKenyas green bean industry: comparison of a small- and a large-scale farm producing forexport, Review of Agricultural Economics, Vol. 29 No. 2, pp. 269-85.
Porter, M.E. (1990), New global strategies for competitive advantage, Planning Review, Vol. 18No. 3, pp. 4-14.
Punjabi, M. and Sardana, V. (2007), Initiatives and issues in fresh fruit and vegetable supplychains in India, paper presented at 3rd International Conference on Linking Markets andFarmers: Exploring Leading Practices to Foster Economic Growth in Rural India, NewDelhi, India, March 11-15.
Ravi, V. and Shankar, R. (2004), Analysis of interactions among the barriers of reverselogistics, Technological Forecasting and Social Change, Vol. 72 No. 8, pp. 1011-29.
Ravi, V., Shankar, R. and Tiwari, M.K. (2005), Productivity improvement of a computerhardware supply chain, International Journal of Productivity and PerformanceManagement, Vol. 54 No. 4, pp. 239-55.
Reardon, T. (2006), The rapid rise of supermarkets and the use of private standards in theirfood procurement systems in developing countries, in Ruben, R., Slingerland, M. andNijhoff, H. (Eds), Agrofoodchain and Networks for Development, Vol. 14, Springer,Dordrecht.
Reardon, T., Codron, J., Busch, L., Bingen, J. and Harris, C. (1999), Global change in agrifoodgrades and standards: agribusiness strategic responses in developing countries,International Food and Agribusiness Management Review, Vol. 2 Nos 3/4, pp. 421-35.
Sage, A.P. (1977), Interpretive Structural Modeling: Methodology for Large-Scale Systems,McGraw-Hill, New York, NY, pp. 91-164.
Sagheer, S., Yadav, S.S. and Deshmukh, S.G. (2006), Assessing international success andnational competitive environment of shrimp industries of India and Thailand with PortersDiamond Model, Proceedings of 6th Global Conference on Flexible Systems Management(GLOGIFT 2006) Bangkok, Thailand, November, pp. 20-2.
Sawhney, A. (2005), Quality measures in food trade: the Indian experience, The WorldEconomy, Vol. 28 No. 3, pp. 329-48.
Saxena, J.P., Sushil, J. and Vrat, P. (1992), Hierarchy and classification of program plan elementsusing interpretive structural modeling: a case study of energy conservation in the Indiancement industry, Systems Practice, Vol. 5 No. 6, pp. 651-70.
Thakkar, J., Deshmukh, S.G., Gupta, A.D. and Shankar, R. (2007), Development of a BalancedScorecard: an integrated approach of interpretive structural modeling (ISM) and analyticnetwork process (ANP), International Journal of Productivity and PerformanceManagement, Vol. 56 No. 1, pp. 25-69.
UNCTAD (2005), EurepGap Asia 05: potential and challenges of EurepGap in Asia, paperpresented at the United Nations Conference on Trade and Development, Manila,Philippines, 29-30 November 2005, available at: www.unctad.org/trade_env/meeting.asp?MeetingID 166 (accessed September 8, 2007).
IJPPM58,2
158
Dow
nloa
ded
by U
nive
rsita
s Gad
jah M
ada A
t 00:2
3 03 M
ay 20
15 (P
T)
-
UNCTAD (2007), Good agricultural practices in Eastern and Southern Africa: practices andpolicies, paper presented at the United Nations Conference on Trade and Development,Nairobi, Kenya, 6-9 March 2007, available at: www.unctad.org/trade_env/meeting.asp?MeetingID 217 (accessed September 8, 2007).
Unnevehr, L.J. and Jensen, H.H. (1999), The economic implications of using HACCP as a foodsafety regulatory standard, Food Policy, Vol. 24 No. 6, pp. 625-35.
Veen, T.W.S. (2005), International trade and food safety in developing countries, Food Control,Vol. 16, pp. 491-6.
Warfield, J. (1976), Implication structures for system interconnection matrices, Transactions onSystems, Man, and Cybernetics, Vol. 6 No. 1, pp. 18-24.
Wilson, J. and Otsuki, T. (2007), Global trade and food safety: winners and losers in afragmented system, Research Paper, World Bank, available at: www.sice.oas.org/geograph/standards/otsukiw.pdf (accessed September 6, 2007).
Further reading
Wilson, J.S. (2001), Bridging the standards divide: recommendations for reform from adevelopment perspective, background paper, World Development Report 2001/2002,The World Bank, Washington, DC.
About the authorsSilpa Sagheer is PhD candidate, Department of Management Studies (DMS), Indian Institute ofTechnology (IIT), Delhi. Currently on sabbatical, she is Senior Assistant Director in the foodprocessing division (Confederation of Indian Food Trade and Industry CIFTI) of Indias apexindustry body Federation of Indian Chambers of Commerce and Industry (FICCI), New Delhi.Silpa Sagheer is the corresponding author and can be contacted at: [email protected]
Surendra S. Yadav is Professor and Head, Department of Management Studies (DMS), IndianInstitute of Technology (IIT), Delhi. His interest areas are, International Business and Trade,Corporate Finance, International Finance and Security analysis & Portfolio Management. He isvisiting faculty at University of Paris, INSEEC Paris and Paris School of Management.
S.G. Deshmukh is Professor, Department of Mechanical Engineering, Indian Institute ofTechnology (IIT), Delhi. He has more than 18 years of teaching and research experience. Hisresearch interest includes Operations Management including modeling and analysis of SupplyChain and Quality issues and Small Enterprise Management. He has been coordinator of AppliedSystems and Research Programme, and Quality Improvement Programme at IIT Delhi and isalso associated with renowned societies like IIIE, ISME, POMS, NCQM etc.
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