USING THE ANALYTIC HIERARCHY PROCESS APPROACHFOR ASSESSMENT OF

THE STRENGTH OF UNIVERSITY-INDUSTRY-GRI COOPERATION IN VIETNAM

By

Cu Duy Tung

A research study submitted in partial fulfillment of the requirements for the degree of Master of Business Administration

Examination committee Professor Himangshu Paul (Chairman)Dr. Jung-won LeeProfessor Nazrul Islam

Nationality VietnamPrevious Degree(s) Bachelor of Chemical Engineering

HoChiMinh University of TechnologyHo Chi Minh City, Vietnam

Scholarship donor Government of Switzerland

Asian Institute Of TechnologySchool of Management

Bangkok, ThailandApril 1999

Acknowledgement

I extend my gratitude to all involved, whose contribution brought the research to this stage. Especially, my research advisor Professor Himangshu Paul, whose inspiration, guidance, valuable suggestions, constant encouragement and care not only as the research committee chairperson but also as a program Dean, deserves the author's gratefulness. I extend my esteem appreciation to the research committee member Dr. Jung-won Lee whose constructive suggestions and helpful comments enhanced the value of the work. Sincere thanks also go to the research committee member Professor Nazrul Islam for his invaluable advice and effort in guiding me at the first steps.

All the respondents and contributors for the work in data collection period in Vietnam are acknowledged for their prompt responses and interest. Many thanks gift to the friends in SIM and SAV for their help. All the friends here in AIT deserve thanks for their love and supports during the study period. The colleagues of the SOM 97 class are never to be forgotten. I express my love to all of them.

I am grateful and extend my thanks to the Government of Switzerland for its financial support during the entire study period at the Swiss-AIT-Vietnam programme in Vietnam and at School of Management of AIT.

Encouragement and support from parents and relatives are keys to the success of this work. Last but not the least, support, patience and dedication from my lover are secret of the whole success.

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Abstract

The work is a methodological framework for public involvement in the process of technological assessment. The objective of this study is to apply the Analytic Hierarchy Process (AHP) for assessing the strength of University-Industry-GRI cooperation by measuring the magnitude of different types of factor flows and the relative importance of the linkages. The model for assessment is developed on AHP taking care of major actors and factors with the linkage alternatives of University-Industry-GRI cooperation. In dealing with such problem, five steps are developed.

The first step is problem conceptualization, consisting of the identification of critical techno-economic assessment criteria, including flows of technological factors, linkage factors, and linkage types. The next step is model formulation, including factor, criterion and alternative definitions to develop a tentative AHP model. The third step mainly concerns data collection coming from various actors through structured pairwise comparison questionnaire via individual opinions and group opinions. The next step employs the geometric mean method to make a consensus from group opinions on the importance ratio of criteria and alternatives. Processing of the responses is conducted using the AHP based software called Expert Choice. The last one conducts to model validation and result interpretation.

The approach of involving public and controversy management is new in the area of assessment on technological cooperation. The results of the study show that the most preferred linkage is University-Industry cooperation. The study also indicates that government people is the most different group from others.

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Table of Contents

Chapter Title Page

Title page i

Acknowledgement ii

Abstract iii

Table of Contents iv

List of Figures vi

List of Tables vii

List of Acronyms viii

List of Appendix ix

1. Introduction and Problem Description

1.1 Introduction 1

1.2 Problem Statement 1

1.3 Objectives of the Study 2

1.4 Scope and Limitations of the Study 2

1.5 Organization of Report and Research Design 3

2. Literature Review

2.1 General 5

2.2 Linkage Types 6

2.3 Facilitators and Inhibitors to Linkages 9

2.4 The Analytic Hierarchy Process 14

3. Research Methodology and Framework

3.1 General 16

3.2 AHP Model Formulation 16

3.3 The AHP Model for Overall Linkage 17

3.4 The AHP Model for Individual Linkage 18

3.5 Model Application, Processing and Reporting 22

4. University-Industry-GRI Partnership in Vietnam

4.1 Overview 25

4.2 The Reformation of Research and Development in Vietnam 26

4.3 University-Industry-GRI Partnership Prior to 1988 27

4.4 University-Industry-GRI Partnership since 1988 29

4.5 Existing Difficulties in R&D System of Vietnam 30

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5. Data Collection and Processing

5.1 General 32

5.2 Data collection method and source 32

5.3 Data Processing 36

6. Analysis of Results

6.1 General 39

6.2 The Overall Linkage: University-Industry-GRI 39

6.3 Linkage between Food Industry and University 45

6.4 Linkage between University and GRI 50

6.5 Linkage between GRI and Industry 54

7. Conclusions and Recommendations

7.1 General 59

7.2 Conclusions 59

7.3 Recommendations 60

7.4 Further Research Direction 61

References 62

Appendix 66

v

List of Figures

Figure No. Title Page

1.1 Research design 4

2.1 The Innovation Triangle 5

3.1 Hierarchy for overall linkage 18

3.2 Flows of linkage factors in the Innovation Triangle 19

3.3 Hierarchy for individual linkage judgment 22

3.4 Procedure for Linkage Judgments 24

4.1 The organizational structure of R&D in Vietnam prior to1988 28

4.2 The organizational structure of MoSTE 29

5.1 A partial sample of questionnaire 33

5.2 Data collection and processing steps 38

6.1 Percentage of response to preference order for different linkages 40

6.2 Percent of respondents giving first priority to various factors 41

6.3 Importance to factors by actors and overall group 42

6.4 Overall group synthesis of alternatives with respect to goal and factor 43

6.5 Hierarchy for Overall Linkage 44

6.6 Magnitude flow of factors from University to Industry 46

6.7 Magnitude flow of factors from Industry to University 47

6.8 Overall judgments on University and Industry linkage 47

6.9 Hierarchy for University and Industry linkage 49

6.10 Hierarchy for GRI and University Linkage 51

6.11 Magnitude flow of factors from University to GRI 53

6.12 Magnitude flow of factors from GRI to University 53

6.13 Overall judgments for University and GRI linkage 53

6.14 Magnitude flow of factors from GRI to Industry 55

6.15 Magnitude flow of factors from Industry to GRI 56

6.16 Overall judgments for GRI and Industry linkage 56

6.17 Hierarchy for GRI and Industry Linkage 58

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List of Tables

Table No. Title Page

2.1 Orientation differences between an industrial firm and a university 11

2.2 Characteristics of GRI unit and Industry unit 12

2.3 Different Characteristics of University and GRI units 13

3.1 An example of in and out flow of factors in the innovation triangle linkage 21

3.2 Type of Linkages in the Innovation Triangle 23

4.1 Budget allocated to MoET in years 31

5.1 Distribution of questionnaire 35

6.1 Individual judgment and their priority to the linkage 40

6.2 Individual importance to factors 40

6.3 Individually preferred linkages distributed in actor group 41

6.4 Priorities of factors and alternatives from overall group and various actors 42

6.5 Summary of overall group judgments on overall linkage 43

6.6 Summary of overall group judgments on University-Industry linkage 45

6.7 Summary of overall group judgments on GRI-University linkage 50

6.8 Summary of overall group judgment on Industry-GRI linkage 54

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List of Acronyms

AHP Analytic Hierarchy Process

AIT Asian Institute of Technology

DoSTE Department of Ministry of Science, Technology and Environment

ECPro Expert Choice Professional 9.5

FAO United Nations Food and Agriculture Organization

FIRI Food Industries Research Institute (FIRI)

GRI Government-sponsored Research Institute

IMB Inter-Ministerial Board

MoARD Ministry of Agriculture and Rural Development

MoET Ministry of Education and Training

MoI Ministry of Industry

MoSTE Ministry of Science, Technology and Environment

MOT Management of Technology

MOU Memorandum of Understanding

MS Excel Microsoft Excel 7.0

PHTI Post-harvest Technology Institute (PHTI)

PORI Plant Oil Research Institute (PORI)

R&D Research and development

S&T Science and Technology

SAV Swiss-AIT-Vietnam Programme

SIM School of Industrial Management

SOM School of Management

UAF University of Agriculture and Forestry (UAF)

UNIDO United Nations Industrial Development Organization

UT University of Technology

viii

List of Appendix

Appendix Title Page

A Sample of questionnaire used 67

B Summary of judgments Individual judgment and their overall group geometric means Individual judgment in actor group and geometric mean Individual judgment and their geometric means for

University-Industry linkage Individual judgment and their geometric means for

GRI-University linkage Individual judgment and their geometric means for

Industry-GRI linkage

747576

78

79

C Matrix entry Overall linkage University-Industry linkage GRI-University linkage Industry-GRI linkage

81828384

D Details of individual judgment resultsResults of actor group judgment

8586

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Chapter 1

1Introduction and Problem Description

1.1 Introduction

A stable framework for cooperation between University-Industry-Government Research Institute (GRI) is necessary to foster progress in R&D projects. As discussed in [4], [14], [28] and [40], this objective is frequently hard to accomplish since each group has different goals. Industry focuses on the cost/profit aspects and quick application of research outcomes to recover the substantial R&D-related investments. Universities are interested in enhancing basic research and obtaining patents, funds and support. GRI is stimulated by government in order to speed up national technology capability and infrastructure. While the need for effective cooperation between industry, university and GRI in R&D has been generally reorganized, instances of successful development and implementation of such cooperative agreement are rare.

Developing countries have realized the importance of science, technology and research back up for industrial activity as a secret of prosperity and advancement in a developed country. In fact, in developing countries, very often it is observed that Industry and R&D units run on parallel tracks, without any point of convergence. There is lack of proper interface because either the technologies developed by the R&D units are not ready to be transferred to Industry or Industry is not prepared to assimilate these R&D results due to technical and economic factors.

To overcome these problems, university units, industry units and GRI units have an important role, which is directly related to scientific and technological advances. The university and GRI units supply both capable human resources and technical know how, while industry unit supplies the means and the opportunity to utilize the results of research and development for production of socially desired products at affordable prices.

1.2Problem Statement

In Vietnam, the issue of cooperation among firms, universities, GRI institutes and government administrative organizations has been a focus for policy makers as well as industrialists and academics in order for them to develop new product and technology through three provisions:

Higher growth Long-term, synchronous development and Low cost

However, this vision has just been developed in recent years and there has not been yet official assessment on the strength of the University-Industry-GRI cooperation.

Problems for Education and Research units (University)

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They often emphasize know why rather than know how. Academic programs and training has less opportunity for on-field study, because there are so many things for students to study in a short time. Curricula and research programs are either less applicable or unrealistic because they don’t focus on the markets needs or on a real case of a specific industry.

Problems for Research and Development units (GRI)Vietnam, for a long time, had had a centrally planned economy. Therefore, most of GRI units belong to the government. They passively run under central plans from the government. The concept of commercializing technology from R&D to manufacturing becomes stranger and stranger for them. Furthermore, almost all GRI units in public sectors have rigid management style and inadequate resource (capital, manpower, time) allocation and obsolete facilities that can not well serve for researches of modern technology. As a result, many projects are quitted or postponed.

Problems for Engineering and Manufacturing (Industry)Firms in the private and state-owned sectors in Vietnam are mostly medium and small. They have not enough money for possessing their own in-house R&D. Therefore, they mainly pursue short-term gain, quick return and avoid risk, whereas R&D investments require a long-term strategy and a large amount of money. For them, R&D activities are less important than high profit and cash flow.

1.3Objectives of the Study

The objective of the study is to address the measurement problem on the University-Industry-GRI cooperation in Vietnam by applying suitable multi-criteria decision making process. The primary goal of the research is to further understand importance of interrelationship among university, industry and government research institute. The specific objectives of the study include the followings: To identify various factors (criteria), sub-factors and possible types of existing linkages

among units related to the assessment of University-Industry-GRI cooperation. To explore the real situation and the perception of people toward University-Industry-GRI

cooperation in Vietnam. To establish priority basis for the assessment of relative importance among individual

linkages and the strength of the overall linkages. To identify the enhancement of the practical capability for universities and GRI institutes.

1.4Scope and Limitations of the Study

The model of technological cooperation will be applicable to developing countries, which are trying to promote research potentials of scientific and technological units and building University-Industry-GRI research relationships. The core of this study is the application of analytic hierarchy process (AHP) to measure research and development linkages in the Vietnamese Food Processing industry by selecting suitable criteria. This model is used as a framework for the assessment of strength of University-Industry-GRI cooperation.The limitations are as follows:

Though there are many factors and criteria that are interrelated in University-Industry-GRI cooperation, for purposes of simplicity and ease of analysis, and due to obvious

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constraints of time, this research study is limited to certain factors that encompass most of the crucial aspects. It can thus be labeled as a limitation that the analysis could not be carried out on a more comprehensive basis.

The AHP process requires experts to reweigh their judgments before a final consensus is reached. Lack of time did not allow this process to happen and hence experts' view may not be as true to life as desired.

The sample size is rather small. This is because of the limited time and resources available during the period of research as well as the high inconsistency among experts, which, due to time constraints was not possible to retake

Vietnamese is still not familiar with a quite new topic as assessment of technology. The respondents called "expert" in the study is really public persons who are able to understand the problem and have ideas on the University-Industry-GRI cooperation in the Food-Processing industry. Thus, it took much time and efforts of the researcher to guide them to fulfill the task truly and reliably.

1.5Organization of Report and Research Design

The report is organized in seven chapters and an appendix. The main text portion of the report contains the most relevant matters on the research and details input and output of analysis and supportive information are given in the appendix part.

The first chapter gives the introduction and the problem description. The next chapter deals with the literature review related to the problem and tool used in the research. In the third chapter, detail methodology of the work has been presented. Overview of University-Industry-GRI cooperation in Vietnam is given in chapter four. Chapter five contains the discussions regarding the data collection and processing work. Results and discussion have been presented in chapter six. Last but not the least, chapter seven gives the conclusion, recommendation and further research direction found from this research study.

The research has been designed in five major steps. The five steps are problem conceptualization, model formulation, model application, model processing and model validation. The detail schematic diagram of the research design is present in Figure I.1 (over page)

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Figure I.1: Research design

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2Chapter 2

3Literature Review

3.1General

When conflict and controversies are involved in any problem, especially such complicated problem as management of technology, then there is more to do with the qualitative measurement rather than quantitative measures. The qualitative aspects of the problem is to be resolved prior to the application of quantitative assessment in the conflicts and controversy free options and that would be more desirable and can result effective/efficient solution. Thus, an analytical hierarchy model is well suite for solving the problem.

In this section, the literature review with the primary goal of preserving relevant information to the study is organized on two main concerned aspects. Firstly, the work briefly explores the theory of the University-Industry-GRI linkages in the Innovation Triangle (FigureI.2) including linkage type in terms of formal as well as informal. Then, a few points toward facilitators and inhibitors to linkages are described. Secondly, a methodological consideration on the analytic hierarchy process (AHP) is introduced.

Figure I.2: The Innovation Triangle [15]

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3.2Linkage Types

Status of the linkage can be categorized according to the degree involvement of institution or individual involvement in the linkage. Linkages are also classified into Formal and Informal types.

Formal Cooperation

Formal linkage refers to institutional built linkage. Activities are carried out based on “contract or Memorandum of Understanding (MOU)". Formal collaborations are characterized by lengthy negotiations, long approval chains and extensive legal details. Adjunct professorships for industrial personnel, cooperative educational programs, direct industrial sponsorship of research, pooling of patents, sharing of intellectual properties and jointly conducted research projects are common forms with many variations. The provision of start-up or incubator facilities for new firms by a university is also a common form of collaboration. The university incubator may provide laboratories, office space, personnel or technologies, in return for fees, opportunities for faculty involvement or patent rights. Incubator programs are often partially funded by government grants or contracts, thus providing an academe-industry-government partnership [14].

Informal Cooperation

Informal linkage refers to personal or individual and collective built linkage. Activities are carried out without contract or MOU or other legal aspects with institutions. Informal linkages are mostly based on mutual trust and personal approach. The most common indication of informal linkage is that budget or funding linkage is managed only by one side.

Informal collaborations are ad hoc, discretionary arrangements involving minimal preparations and few administrative clearances. The typical academic-industry example is a student project, where the faculty member simply telephones an acquaintance in a local firm and requests an interesting term project for a student. Informal meetings of faculty and industrial representatives to exchange information, obtain mutual advice, and discuss problems of mutual interest are also typical examples. Forums for idea exchange, ad hoc interest groups formed to discuss some topical issue, and industrial advisory boards are further example [14].

Analogous relationships often form between individual employees in a government agency and a firm or a university, e.g. a task force developing a proposal for a new regulation, university-industry-government institute employees working together to collect information on a phenomenon of joint interest or so on.

The relations of the Innovation Triangle are most frequently found in the form of:

(i) Joint Research

The activity to which University unit, GRI unit and Industry unit participate or contribute manpower, funds and equipment. This varies from project to project. Joint research is sometimes also combined with contract research. It can be initiated by GRI unit, University unit or sometimes by Industry unit. Nowadays, with the creation of new institutions such as technology parks, joint research may also play an essential role.

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(ii) Sponsored Research

R&D activities that are funded by industry or other funding body such as government, AAECP, ESCAP, UNESCO, UNDP so on.

(iii) Research Contract or Research Collaboration

The GRI unit or academic unit enters a contract with industry for the performance of research or a specific project. In another alternative, a company buys some of time of the academia scientist and his/her team to help conduct the applied research in either the academia or R&D of the industrial laboratory. This is a purely temporary relation confined to a specific project. The initiative generally comes from industry, whereas the administrative side of contract research generally falls to GRI unit or University unit or other units established for this purpose.

(iv) Auxiliary Works / Provision of Services

Consultant servicesUsually faculty members or senior researchers are hired to consult during the time they are allowed to work outside. This linkage relatively inexpensive, rapid and selective means of transferring information and often serves as gatekeepers to wider scientific community.

Technical assistanceThe technical and scientific laboratory personnel with unique expertise are needed by industry in assisting their certain activity in projects or researches.

TestingIndustry asked GRI unit or academia labs to do testing a certain material or a system for them.

Staff transfers and Direct individual contactTemporary transfer of staff from GRI unit, industry to university and vice versa is aimed to solve problems or to improve the capability of its staff. This type of cooperation enables scientific staffs to work out of office without losing their rights in their previous work as an employee. Academia and industry with similar interests usually exchange scientists for a specified time (this can be a part of contractual relationship).

Sharing facilitiesThis type of linkage takes place if both units do not have complete R&D facilities and usually exist in informal form. It also happens when there is loan or grant for a certain project that involves two units.

Equipment giftIndustry as a donor gives equipment for R&D activities

(v) Training Activities

Practical training

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It is an opportunity for students to spend part of their studies in Industry, where they are exposed to the working methods and requirements of jobs at industry or other institutions while applying the knowledge they are acquiring, thus gaining experience that will be valuable in their future careers.

Further trainingTo improve capability of staff in a particular filed. The application of new technologies requires know-how which the industrial staffs who got their degrees long ago, do not generally have.

Seminar & Conference / WorkshopFrom this kind of linkage both units can discover shared interests. It can be conducted by GRI unit, University unit or Industry unit and, generally with the purpose of disseminating information on new or emerging technologies with possible applications to industry.

Scholarship/FellowshipIndustry gives fund for undergraduate and postgraduate students. For some cases, enterprises select graduates according to their needs for giving scholarship.

(vi) Information DisseminationThrough laboratory result report publications and other printed documentation.

(vii) Patent / Copyright

(viii) Science, Research Park, Techno-Park or Incubators

The Science Park is conceived as a mechanism by which academic researchers might commercialize their outputs, or where might locate in order t access academic expertise and result. The Science Park could be promoted, funded and developed in a number ways which involve the installation on a given site area, normally close to a university collaborates with a member of high-tech firms that receive official assistance in the early stages [32]. The core of the science park concept lies in the idea that scientific knowledge leads in some linear progression to technological innovation. It is often seen as one means of facilitating the transfer of academic research outputs to industry. Furthermore, science parks represent an infrastructural mechanism to bridge the gap between academy and industry.According to UK Science Park Association, “the science park is a property based initiative which:

has formal operational links with a university or other higher educational or research institutions;

is designed to encourage the formation and growth of knowledge based business and other organizations normally resident on site; and

has a management function which is actively engaged in the transfer technology and business skills to the organizations on site [32].

In many developed countries, many companies seek space near campuses for benefit of the research environment. Some are small high-tech firms that have resulted from academia “spin-off”. Academia frequently encourages such ventures in their start-up or incubating efforts by providing service, advice and often inexpensive space. Forms of the linkage here mostly contract research and technical service.

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3.3Facilitators and Inhibitors to Linkages

3.3.1 University and Industry Linkage

The motives behind the cooperation of University and Industry are many and varied. As mentioned in some articles [12,14,43], the success of the cooperation much depends on the benefits each party has and the obstacles both parties have to overcome.

Facilitator

Industry unit gains by having

A supply of better qualified graduates having more relevant training because industry’s needs have been identified.

Access to knowledge which, when applied, can enable appropriate technologies to be introduced.

Access to the academia’s physical facilities and the expertise of its staff. Access to the research, consulting and data collection of the university Access to graduate recruitment. An improved public image in the society in which it operates, which means that more

talented students will be attracted to the industrial sector.

University unit gains by having

The stimulus of relating theory to practice, important for staff development. Assistance from industry curriculum development to ensure that curricula shall be relevant

to local conditions. Strengthening staff development by giving faculty members opportunities to gain practical

experience. Access to industry for both fundamental research and applied research. Opportunities for industrial training and graduate placement. Additional income from contract research, consultant, royalties and patents. An improved image with government and society generally

Individual academics gain by having

Opportunities for consulting Means of keeping in tough with practice and thus making their teaching more effective. Opening for research Facility for personal development leading to improved promotion prospects Increased income and job satisfaction.

Society gains by having

An improved return on investment in higher education. A more effective educational contribution to economic development. Better utilization of human and physical resources Fewer of the social and political stresses that accompany unemployment of academia

graduates.

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Inhibitor

The inherent differences that exist between an industrial organization and academia are usually a barrier preventing these two parties from working together [12, 14, 43].These conflicts seem to occur along four dimensions: control, standard, authority and loyalty. A similar analogy can be drawn for the differences that exist at large between the scientific or academic world and the world of organizations and management as shown in Table 1.1. While the first world is usually occupied with accumulation of knowledge, research, the building of theory, sustaining scientific standards, and of course teaching, the second is usually more interested in short-term results like profits, sales, efficiency, satisfying the customer etc.

Academia has problems in terms of

Finance, staffing and rapidly growing number of students. The faculty has little practical experience and may hold anti-business attitude. Academic regulation and rigid convention may discourage staff from working with

industry. The difficulty of striking the right balance between teaching and research on the one hand

and consultant on the other.

Industry has problems in terms of

May be preoccupied with its own immediate problem – difficult economic conditions, currency restrictions, government regulations, which may make it neglect its long-term objectives for management development, research and training.

The attitude of businessmen, who may or may not have had an academia education, may be anti-academic. They may have a feeling that such studies are “too theoretical”.

Management, particularly in small industries, is often rudimentary.

Table 1.1: Orientation differences between an industrial firm and a university

Difference Industrial firm UniversityAttitudes and values Business attitude

Economic considerationsSatisfying the customerProduct drivenAdded Value

Scientific attitudeProfessional considerationsDo good researchKnow-how, know-whyNew knowledge

Objectives Organizational effectivenessShort-term resultsFinancial benefit

Applied research

Excellence in research Excellence in teachingLong-term resultsNew financial means for additional researchBasic research

Outputs Cost-effective products and servicesNew application

Research results, theories

New discoveriesStandard and rules Organizational rationality Professional ethics

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Organizational rulesSecrecyProtection, patentsCommercial approach

Scientific normsPublicationFree, public goodsAcademic freedom

Recognition and rewards For contribution to company goals

For scientific achievementsAcademic degree

Knowledge and learning Application of knowledgeLearning only if needed

Contribution to knowledgeContinuous learning

3.3.2 Industry unit and GRI unit Linkage

Facilitator

The motives behind the formation of Industry and GRI are many and varied through project by project. The proper linkage between GRI unit and Industry unit can give much benefit to both units [28, 29, 44, 45].

GRI unit gains by having

Reduce cost for certain research or enhance resources through cost sharing. Potentially reduce technology transfer cost Focuses on market needs leading to more transferable technologies Disseminates information quickly to industry Overcome “not invented here” syndrome.

Industry unit gains by having

Gain access to enhance resources through sharing of equipment, funds and expertise. Easy to get special R&D information through seminar, conferences, open meeting,

forums. As an economical way to acquire the necessary know-how.

Inhibitor

The difference in goals and practices between GRI unit and Industry unit caused difficulties in forming strong linkage. The differences between GRI unit and Industry unit are summarized in Table 1.2 as below:

Table 1.2: Characteristics of GRI unit and Industry unit

Characteristics GRI unit Industry unitTime horizon Long term Short term

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Financial structure Expense center Profit centerProduct Information/conceptual Goods/serviceApproach Scientific Factual/QuantitativeOrientation Novelty/Industry need Market attractiveness/Profit

potentialSources: [39]

Other weaknesses that are considered as inhibiting factors are as follows:

GRI unit point of view

Inadequate mechanisms for promotion due to lack of credibility and acceptability Demonstration and dissemination of research result Absence of resources for techno-economic and market feasibility studies to establish

commercial viability. Lack of understanding about the capabilities and potential of GRI unit to impact on the

realistic needs of the production system (e.g. non-availability of a total package of service).

Industry unit point of view

Lack confidence in the ability of GRI unit to provide meaningful solutions to its problems in a reasonable time and at a realistic cost.

Lack confidence in the knowledge and experience of GRI unit in solving industrial problems, their competence in specialized industrial technology, and appreciation of cost/benefit industrial motivation.

Industry believes that it should not pay for the services provided by GRI unit, which is largely subsidized by government funds derived from industrial taxes.

Industry is usually wary of the GRI unit and government relationship which could result in disclosure of potential patent possibilities, technical secrets, or management information to government agencies or competitors.

Industry does not often evidence a genuine interest in the research results of an institute until these has been carried through a pilot or demonstration plant phase, and productions, economic and marketing feasibility have been resolved.

3.3.3 GRI unit and University unit Linkage

Facilitator

Both of them are benefited from proper linkage, for example: To maintain a balance between attention to research and development and to build the

capable human resources. To bridge communication gap and assist the growth and development of research having

direct relevance to the academic program.

Inhibitor

Over the past decade, the interaction between industry and universities or independent research centers has become of increasing importance. Based on an iterative process of technology-driven and market-pull oriented approaches. An independent research

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institute has a set of goals, which are quite different from those of university [39] as shown in Table 1.3. Furthermore, such objectives can only be reached successfully through delicately balanced compromises between apparently conflicting forces with respect to:

Table 1.3: Different Characteristics of University and GRI units

Characteristics University unit GRI unitGoal Scientific-oriented Delivering

research results of high quality within selected technological fields (excellence in research),Actively assisting in postgraduate education (excellence in education)

Economic-oriented Industry-oriented research and development (R&D),Know-how transfer to industry,Creating a favorable climate for new industrial initiatives.

Time horizon Longer-term research programs

Shorter-term research programs

Funding Fundamental-oriented research

Industry-oriented research

Scientific infrastructure Minimal need Optimal useRick assessment Scientific research centre Independent research centreConfidentiality Publication needs Property rightsMotivational climate Academic rewards Research rewardsInteraction & feedback needs

Fundamental research Applied research.

In many developing countries, GRI unit really depends on the government, because the biggest funding research also comes from government. Thus, research activity is limited to the existing budget. This also applies to the university. The difficulties include not only in terms of funding research, but also in terms of out-dated physical facilities, and rigid management styles in both units.

3.4The Analytic Hierarchy Process

The Analytic Hierarchy Process is a general theory of measurement to solve a specific problem in consistency planning, developed by Thomas L. Saaty in 1971-1975 while at the Wharton School (University of Pennsylvania, Philadelphia, Pa) [49]. It is used to derive ratio scales from both discrete and continuous paired comparisons. These comparisons may be taken from actual measurements or from a fundamental scale which reflects the relative strength of preferences and feelings. When applied in decision making it assists one to describe the general decision operation by decomposing a complex problem into a multi-level hierarchic structure of objectives, criteria, sub-criteria and alternatives. People then express their preferences by making judgments on a variety of paired comparisons of both the criteria and the alternatives.

People make two kinds of decision: those in which they definitely know the criteria they intend to apply and the importance of these criteria apart from any alternatives they may be considering. Related to this are situations where they have ranked their alternatives by assuming that the ones they are aware of all are there.

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Another type of decision is one in which people are unsure of the importance of their criteria. In this case to sharpen their knowledge of the criteria a wide selection of alternatives must be examined. In the second situation, when looking at alternatives to decide the criteria in the first pace is more difficult and more common in the face of complexity where new criteria and re-arrangement of old criteria occur constantly [48].

Three principles guide one in problem solving the AHP [49,50]: decomposition, comparative judgments and synthesis of priorities.

The decomposition principle is applied by structuring a simple problem with the elements in a level being independent from those in succeeding levels, working downward from the focus in the top level, to criteria bearing on the focus in the second level, followed by sub-criteria in third level, and so on, from the more general (and sometimes uncertain) to the more particular and concrete. Saaty [50] makes a distinction between two types of dependence that he calls functional and structural. The former is the familiar contextual dependence of elements on other elements in performing their function, whereas the later is the dependence of the priority of elements on the priority and number of other elements.

The principle of comparative judgments is applied to construct pair-wise comparisons of the relative importance of elements in some given level with respect to a shared criterion or property in the level above, giving rise to the kind of matrix encountered above and its corresponding principal eigen-vector.

The third principle is that of synthesizing the priorities. In the AHP priorities are synthesized from the second level down by multiplying local priority of their corresponding criterion in the level above and adding, for each element in a level according to the criteria it affects.

An important aspect of the AHP is the idea of consistency [49]. If one has a scale for a property possessed by some objects and measures that property in them, and then their relative weights with respect to that property are fixed. In this case, there is no judgment inconsistency. Although if one has a physical scale and applies it to objects in pairs and then derives the relative standing of the objects on the scale from the pair-wise comparison matrix, it is likely that inaccuracies will have occurred in the act of applying the physical scale and again there would be inconsistency. When comparing with respect to a property for which there is no established scale or measure, we are trying to derive a scale through comparing the objects' two at a time. Since the objects may be involved in more than one comparison and we have no standard scale, but are assigning relative values as a matter of judgment, inconsistencies may well occur. The calculation procedures for weights and for the inconsistency index leads to an eigen-value formulation [50].

However, the AHP has proven to be a very effective decision aid. The two advantages, which the AHP has over the other multi-criteria methods, are the ease of use and the ability to handle inconsistencies in judgments. The AHP does not force an individual or group to be consistent when making pair-wise comparisons. This ability to handle inconsistency is a major contributor to the second advantage – the ease of use [52].

This methodology has been applied to problems as diverse as decision analyst, strategy formulation, forecasting, finance and marketing [28, 50, 51]. And over the year, there

14

are many scientists, researchers, decision analysts and managers pay much attention to this methodology and it is also introduced in many countries.

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Chapter 4

4Research Methodology and Framework

4.1General

The work on the study may be broadly classified into two parts namely the AHP model formulation and model application on overall linkage as well as individual linkage. The first part of the work involves fixation of objective, actors, factors, and the linkage alternatives and then structuring of hierarchy to represent the judgment process. In the second part, model application includes the preparation of questionnaire, pre-testing of questionnaire for the confirmation and interpretation of the factors and then processing of the completed questionnaire and reporting. The second part of the work also includes the validation and discussion on the results obtained. Scheme of the research methodology is represented in Figure I.6.

4.2AHP Model Formulation

Formulation of hierarchy model to address any decision or measuring problems is more to do with art than science. It is important to grasp the problem to address first, then to start drawing the hierarchy model. Guidelines for formulation of a hierarchy are available in the literature and numerous proven ready-made hierarchies are also available. Saaty and Forman [55] have published a book called The Hierarchon: A Dictionary of Hierarchies, which contains four hundred models covering areas ranging from business, government planning, policy and strategy, military applications and sport speculations. But the so far know hierarchies relating to the assessment in management, especially in management of technology are limited, there are few hierarchies in technological assessment on firm level, national level and cooperation between university, industry, and GRIs. As each model is specific to the problem to be addressed, its nature and environment of use makes each model unique to some extent. Fortunately, existing few hierarchies and value trees addressing the problem related to assessment of the University-Industry-GRI already appeared on the literature [15], [56], [58] and Saaty's guidelines will certainly help to formulate a new model to address the problem perceived.

As per Saaty "A hierarchy is a linear structure in which influence is distributed from top to bottom". The relative position of elements in a hierarchy depends upon three factors namely correctness, controllability and certainty. Normally narrower and more concrete properties are at lower level, less concrete and more general, less controllable, more certain and risky elements are at higher level in a hierarchy. Influence is distributed downwards from the top with the goal having the greatest influence of importance. The AHP model formulation process starts both from bottom (the alternatives) and from the top (the objective, goal) or the hierarchy construction process in more specification is top down plus bottom up [57].

In assessing the strength of University-Industry-GRI cooperation, two judgments should be considered. The first is the judgment of the individual linkage. The purpose for

16

assessing the individual linkage is to determine the rank of linkage types between the two units. It can be applied for particular product as well as for the whole unit activity. The rank of linkage types enables both units to evaluate the lowest rank and to maintain or increase the highest rank. The second is the overall linkage judgment of University-Industry-GRI cooperation. One of the results of the overall linkage evaluation would be very useful for policy makers in allocating resources, such as money or manpower in the linkage activity.

4.3The AHP Model for Overall Linkage

4.3.1 The Goal

The primary purpose of the overall problem is to determine the relative importance of different linkages. The goal of the problem for overall linkage judgment is at the top of the model.

4.3.2 The Actors

The second level in the hierarchical model is constituted with the various actors having direct or indirect influence in the judgments and having conflicted interests in the cooperation among units. The five actors considered in the model are: Business people Government officers Political people Freelance Consultants Scientists

4.3.3 Main Factors

The procedure of getting the relative importance is starting with the pairwise comparison of existing linkage types. Therefore, the factors considered for overall linkage judgment are linkage type namely joint research, research contract, training activity, provision of services or so on, which are on the third level.

4.3.4 Alternatives

Finally, the last level of the hierarchy for overall linkage judgment is the alternative of linkages known as University - Industry, Industry - GRI; GRI - University. The Figure I.3 shows the hierarchical model for determining relative important of different linkages.

Assumption All actor group play equal role in giving judgment The relative importance among actor groups does not depend on the number of

respondents each group has.

Based on these assumptions, the hierarchy applied for group decision making would be seen as the one for personal decision making after using geometric mean to make consensus [66]. Thus, to simplify the work, the second level would be omitted in computing process without any change in alternative priorities.

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Figure I.3: Hierarchy for overall linkageNote: University: education & research unit

GRI: research & development unit (Government research institute)Industry: engineering & manufacturing unit (Specific industry)

4.4The AHP Model for Individual Linkage

4.4.1 The Goal

The goal of the single problem is primarily considered to identify the strength of the individual linkage by determining the relative importance of the linkage types. The goal is at the top of the model.

4.4.2 The Actors

Like the AHP model formulated for overall linkage judgment, the second level in the hierarchy model for individual linkage judgment is involved with various actors. These also come from different sectors (Industry, business, university, government, institute, or so on).

4.4.3 Main Factor and Sub-factors

The relative importance of the individual linkage is determined by magnitude of flows from each unit to the others. For example, the flow from University to Industry and vice versa. Therefore, these flows become the main factor in the individual model and are considered as the third level. The next level (e.g. sub-factor) of the hierarchy is the linkage factors namely Magnitude of money (M), Human interactions (H), Organizational interactions (O), Facility

18

utilization (F), and Information interactions (I). The Table 1.4 provides example of how these sub-factors flow from certain type of linkage in certain units to another. The Figure I.4 shows flows of linkage factors in the Innovation Triangle.

Figure I.4: Flows of linkage factors in the Innovation Triangle

Briefly explanation on sub-factors are presented as below:

Magnitude of Money (capital investment, revenue)Flow of money in the linkage may happen in two ways. First, one way flow. An industry pays for GRI unit or University unit in a certain type of linkage (e.g. contract research), which is usually in their interest. In this case money refers to input for GRI unit or University unit, and money also as an output for Industry unit. Second, two ways flow. Both units are responsible for funds allocated in the linkage, e.g. joint research. From GRI unit and University unit point of view, the trend of money as input in the linkage may considered as one of indicator strength of linkage.

Facilities Utilization (tools, equipment, machinery, vehicles, structures..)Facilities Refers to the flow of object-embodied form of technology or the physical facilities required for the transformation operation, such as instrument, equipment, devices, pilot plant and prototypes [15].

Human Interactions (skill, craftsmanship, expertise, creativity..)

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Refers to the flow of human-embodied form (brainpower) of technology or all the acquired abilities necessary for the transformation operation, such as expertise, proficiencies [15]. To a great extend the relationship among these units rely on a relationship of trust, induced by the potential of the partner's unit and its track record in helping to produce commercially successful products [31]. Furthermore, the successful cooperation between Industry unit and GRI unit or University unit is most determined by the capability of people in doing that research cooperation. For assessing the linkage between two units, number of people involved for certain type of linkage at a certain period, can be classified in terms of skill and time consumed in the linkage. Output in terms of people mostly come from educational relationship such as training, seminar, staff transfer etc.

Information Interactions (know-how & know-why, facts & formula, design parameters, specifications, manuals, theories, etc.)Refers to document-embodied form of technology or all the accumulated facts and figures required for the transformation operation, such as design, specifications, observations, charts, theories or so on [15].

Organization Interactions (methods, techniques, organizational networks, and management practices)Refers to institution-embodied form of technology or all necessary arrangements required for transformation operation such as practices, groupings, networks, systematization etc [15].

4.4.4 Alternatives

At the bottom of the model, the alternatives of individual linkage hierarchy are the existing linkage types. This level will determine the rank of linkage type. The hierarchy developed for individual linkage is illustrated in the Figure I.5. Brief description of linkage types playing as alternatives in the individual linkage hierarchy is illustrated in the Table 1.5

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Table 1.4: An example of in and out flow of factors in the innovation triangle linkage

Item flow Type of linkage LinkageGRI-Ind Ind-Uni Uni-GRI

Magnitude of Joint research with or without sponsor I I I I I IMoney Industry sponsored research I O O I I I

Contract research I O O ITraining I O O I I,O I,ODegree granting scholarship O I I OConsultant service I O O I O,I O,ITechnical assistance I O O I O,I O,ITesting I O O IStaff transfer I,O O O I O,I O,IPatent, copyright I O O I O O,I

Facilities Joint research / Sponsor research O O O O O OUtilization Contract research O I I O

TrainingDegree granting scholarshipConsultant serviceTechnical assistanceStaff transfer

Human Joint research / Sponsor researchInteractions Contract research

Patent, copyrightTraining I,O I O,I O,I O,I O,ISeminar / workshop I,O I,O O,I O,I O,I O,IDegree granting scholarship I O I O O IConsultant service I O I O I,O I,OTechnical assistance I O I O O,I I,OStaff transfer I O I O O,I I,O

Information Joint research with or without sponsor O O O O O OInteractions Industry sponsored research O I I O O,I O,I

Contract research O I I OTraining I,O I,O I,O I,O O,I O,IDegree granting scholarship I O O IConsultant service O I I O O,I O,ITechnical assistance O I I O O,I O,ITesting O I I O O,I O,IStaff transfer I,O I,O O,I O,I O,I O,IPatent, copyright I O I O O, O,I

Organization Joint research / Sponsor researchInteractions Contract research O O O O O O

Training O I I O O,I O,IDegree granting scholarshipConsultant serviceTechnical assistanceStaff transfer

Note: I: Inflow; O: Outflow; Blank: not applicable; Ind: Industry; Uni: University

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Figure I.5: Hierarchy for individual linkage judgment

Note:Linkage factors: Magnitude of money, human interactions, organization interactions, facility utilization, and information interactions.Linkage types: joint research, research contract, sponsored research, training activities, provision of services, etc.

4.5Model Application, Processing and Reporting

The factors, sub-factors classification of actors and alternatives for model development are finalized by the first round talk with the key-informants who are competent in the technological assessment. Based on the model, sets of pairwise comparison questionnaires are prepared. Before, presenting the questionnaire to the concerned personnel, it was pre-tested (pilot interview), because in the AHP application clarity on the problem and clarity in the pairwise comparison is very important to get the correct result and judgments. The decision makers have to do the value judgments. As the study is based on the subjective judgment, no numerical values are directly used.

22

The processing of the completed questionnaire is carried out by using the AHP based lasted software called the Expert Choice (Professional version 9.5 for Windows). The software is versatile specially conducting the sensitivity analysis. Expert Choice is considered as well regarded software package for the AHP [59].

Finally in depth analysis report is prepared and the sets of recommendations and conclusion are drawn to address the prevailing viewpoints regarding the relative importance of different linkages and the strength of each linkage in Vietnam. The experience and learned from the research and recommendation for further study research is also included in the following chapters of the report.

Table 1.5: Type of Linkages in the Innovation Triangle

LINKAGESIndustry and GRI University and Industry University and GRI

Formal Formal Formal1. Contract research2. Industry sponsored

research / project3. Patent, Copyrights

1. Contract research2. Industry sponsored

research / project3. Patent, Copyrights4. Further training

1. Joint research (with or without sponsor)

2. Patent, Copyrights3. Staff transfer

Informal Informal Informal4. Auxiliary works / Provision

of services Consultant service Technical assist /

Maintenance Testing Sharing facilities Equipment gifts5. Training activities Special training Seminar / Workshop

5. Auxiliary works / Provision of services

Consultant service Technical assist Testing Staff transfer Sharing facilities Equipment gifts6. Training activities Practical training Further training Seminar / Workshop Granting scholarship

4. Auxiliary works / Provision of services

Consultant service Technical assist /

Maintenance Sharing facilities Equipment gifts5. Training activities Practical training Further training Seminar / Workshop

Missing Link Missing Link Missing Link

23

Figure I.6: Procedure for Linkage Judgments

24

Chapter 5

5University-Industry-GRI Partnership in Vietnam

5.1Overview

The framework for University-Industry-GRI cooperation in research and development (R&D) in Vietnam has undergone significant changes in recent years as a result of political and economic reformation. The role of large government-controlled enterprises and government agencies in supporting R&D has diminishing. The dynamically growing small business sector has not been able to fill the vacuum left by these entities in sponsoring R&D. The unstable business environment and prevailing traditional management practices make difficult the creation of effective agreements with foreign partners in the field of technology management. Thus, the issue of technology cooperation among University-Industry-GRI becomes an essential need for the economic development of Vietnam.

The rapid economic, political reformation and social changes occurring in Vietnam 's infrastructure combined with the slow rate of change in the attitudes of people involved in R&D make the creation of an efficient market-based R&D system difficult. The budget requirements for these changes are enormous and the change of attitudes takes time. Consequently, R&D programs find it increasingly difficult to compete for funds from the central budget. The system of government subsidies and preferences used to support government-controlled enterprises has been eliminated. The products from Vietnam's government-controlled sector are often no longer competitive in terms of price, quality, delivery or payment terms. The privatization programs and business infrastructure development including the relaxation of tariffs, duties and other free-trade restrictions were initiated by the Open Door policy formed in 1986, when the Communist Party of Vietnam decided to introduce economic renovation line to the 6th congress held in December 1986. These measure have exposed Vietnam's economy to fiercer competition, if Vietnam wants to integrated into the global market.

Since the joint R&D projects, particularly those with foreign partners, are inherently long term, instability in the business environment restricts such opportunities in terms of numbers and magnitude. As a result, the government enterprises frequently adopt a short-term approach based on a struggle for survival. Reduction and elimination of domestic R&D programs and purchasing technology from abroad is frequently part of such a strategy. A more appropriate approach would be based on long term view calling for effective management of domestic R&D projects.

Emerging small business in Vietnam are mainly low-tech and are often directed at generating quick short term profits in the field of service and distribution. For these reasons, many of them are neither interested in nor capable of supporting significant R&D projects. The need to ensure the long-term growth of Vietnam's economy necessitates the development of new ways of supporting R&D and managing technology. Furthermore, a new framework for University-Industry-GRI cooperation needs to be developed.

5.2The Reformation of Research and Development in Vietnam

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WHILE attention to reform in Vietnam often focuses on economic and social reform, there have also been reforms in scientific and technological policy (S&T), bringing it from the realm of research into the realm of business. Scientific institutes have awakened from being a tool monopolized by State agenda to playing an active role in the business of research, development, production, and sales. S&T reforms have been introduced in three stages.

Stage one, coming in the mid-70s within the framework of the monopoly of S&T activities by the State, endeavored to create conditions for the State to pool all its resources into what were then considered key tasks, at central and local levels.

Stage Two decentralized State S&T activities. The corresponding economic decentralization of the late 80s led industrial producers to seek out cooperation with engineering research organizations, and with institutes studying management, marketing, and economics. The cooperation wedded production and science, including social science and engineering research. S&T researchers began, in effect, to help shape economic policy, and to make clear the need for the State to continue on its path of decentralization.

The turning point in this stage of reform was a 1991 decision (No. 49-HDBT) permitting S&T agencies to sign direct contracts with production enterprises. With the decision, R&D institutes involved in engineering received contracts from enterprises not only to do research and conduct technology transfer, but also to create products to supply scientific and technical services.

New contracts with various interests meant new funding. Money came in from a variety of sources, not only directly from the State but also from Vietnamese cooperatives and from foreign countries. With the new cash, S&T researchers were able to delve into areas previously beyond their means.

Gradually, S&T institutes became financially autonomous, no longer relying on State funding (and State direction) to proceed. Institutes became able to set up their own scientific and technical development funds, welfare funds and prize funds. They are entitled to open bank accounts and borrow for their technological renovation activities.

The diversification of activities of institutes has led to important changes in their organizational structure. They are allowed to organize experimental workshops, small size production establishments, bureaus to sell the institutes' products, and to establish joint ventures with economic organizations.

In stage three of the reform, taking place over the past eight years, the State recognizes the private sector's role in S&T activities; government decisions recognize the rights of private businessmen in technology transfer from foreign countries, and the protection of industrial property rights. S&T activities are effectively no longer a State monopoly.

5.3University-Industry-GRI Partnership Prior to 1988

The framework for cooperation between industry, university and the government in R&D prior to 1988 lacked the flexibility needed to manage technology efficiently. The role of the central government was primarily to provide direction, areas of research and necessary resources. The research priorities were established by the central plan and were based upon the Communist Party doctrine. The industry and university establishments did not have much

26

choice in pursuing R&D independently. They were, in essence, order taker in stead of being equal partners.

The organizational structure of the R&D support system in Vietnam prior to 1988 is presented in Figure I.7 (over page). The Council of Ministers categorized research as either basic or applied. Basic R&D projects in Vietnam prior to 1988 were mostly conducted under the management of the Ministry of Education and Training (MoET). Applied research was normally controlled by the Ministries of Industry (MoI) and other Industries (Medical, Culture etc).

Basic research projects were conducted by several departments (Social Sciences, Biological Science, etc.) under MoET. On the other hand, basic research was also carried out by R&D Institutes and Central Laboratories under control of MoI. The industry and universities representatives participated in governmental basic projects through R&D committees. The applied research projects were conducted under the administration of the Inter-Ministerial Board (IMB). IMB consisted of representatives from every ministry and MoET. IMB coordinated applied research projects sponsored by branch ministries (Ministry of Energy, Ministry of Machine Engineering, etc) other ministries (Ministry of Health, Ministry of Culture, etc) and projects conducted by the university R&D institutes. These projects were funded from the central budget either directly by government or indirectly through other branch ministries, industrial associations or large state-owned companies.

The R&D entities reporting to the branch ministries, including institutes, central laboratories, independent centres and factory centres, focus their efforts on applied research and implementation. The institute conducted projects of interest to the entire industrial branch. Central laboratories provided support to the specific industry. Independent centres focused their attention on a narrow scope of applied problems within a branch. Finally, factory centres conducted work of interest restricted to individual factory.R&D projects were classified as to their relative importance as: governmental R&D projects crucial R&D projects branch projects individual R&D projects

Governmental and crucial projects were the most important in terms of their roles in the national economic development. They were part of the five-year plans and were funded directly from the central budget. Branch projects were of moderate importance and were sponsored by and controlled at the ministry or industrial association level. The scope of branch projects was limited to a narrow group of industrial enterprises. These projects were mostly directed toward developing technologies based on licensing agreements with foreign companies. Individual projects were considered of little significance and were sponsored by and controlled at the branch level. Projects given the highest ranking in the long-term development plan (i.e. 5-25 years) were also given priority in budget allocation.

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Figure I.7: The organizational structure of R&D in Vietnam prior to 1988

The highly bureaucratized organizational structure shown in Figure I.7 nurtured conservative management practices based on reporting and control. R&D programs frequently suffered from under-funding, low worker morale and slow implementation due to inefficient operation of the system. On the positive side, a lack of competition between entities sponsoring R&D projects made possible the acquisition and sharing of expensive-specialized equipment and trained staff.

In the late 1988, the government attempted to foster the development of cooperation among industry, university and GRI in R&D and the transfer of technology. New legislation was introduced facilitating the purchasing of new technology. One of the objectives of these efforts was to accelerate collaborative R&D projects between research establishments and industry.

5.4University-Industry-GRI Partnership since 1988

In order to stimulate economic activity, fundamental changes were initiated in Vietnam by the government in 1988. In the economic area these changes were aimed at reducing the central government role and creation of a free market. This involved further reduction of the central bureaucracy, privatization of state-owned enterprises, introduction of currency convertibility, facilitation of trade, etc. The system of technology management is severely affected by these changes.

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In 1988, the central government responsibility for sponsoring, coordinating and monitoring R&D was taken over by the Ministry of Science, Technology and Environment (MoSTE). In order to provide continuity, other government agencies such as MoET and the branch ministries continued to sponsor industry and university R&D projects with the approval of MoSTE. In fact, most of research budget plans are currently derived from MoSTE. For example, in 1993 MoSTE received forty-two grant applications including six state-level and thirty-six ministry-level projects from universities, of which MoSTE budgeted VND 13,400 millions in grants for basic and applied R&D. The Ministry of Science, Technology and Environment has plans to spend VND200 billion (US$18.2 million) on research and upgrading of national laboratories in 1995. Nearly 75 per cent is earmarked for capital investment. The organizational structure of MoSTE is presented in Figure I.8.

Figure I.8: The organizational structure of MoSTE

As shown in the figure, planning and managing R&D has become the responsibility of one government agency. MoSTE includes R&D committees which closely work with universities and branch ministries. Such a system enables efficient communication and speeds up the decision-making process on issue related to technology management. The decision-making process is improved because all parties involving R&D projects have equal standing. Therefore, the decisions with regard to R&D are based more on consensus rather than a political directive. Furthermore, providing all entities conducting R&D work with access to MoSTE' s infrastructure (computer networks, libraries, administrative support, etc) improves resource utilization.

5.5Existing Difficulties in R&D System of Vietnam

According to the latest statistics [64], Vietnam has more than 800,000 university graduates, 8,775 Ph.D. (in scientific fields) and candidates, 3,000 professors and professor candidates, 45,000 scientists and 20,000 university lecturers. Vietnam has 300 research

29

institutes, 105 universities and colleges and 86 institutes which specialize in training post-graduate students. However, the distribution is unbalanced from region to region. Around 80 per cent of research institutes are concentrated in Hanoi and another 12 per cent in Ho Chi Minh City. Statistics calculate 59 per cent of universities and colleges are also in Hanoi, 25 per cent in the south and the remaining 26 per cent in the Central Provinces. More than 63 per cent of Ph.D. holders in Vietnam in scientific fields are over the age of 50, revealing an urgent shortage of a strong skilled base for scientific and technological research for the future.

According to the Ministry of Education and Training, just 2 per cent of the State Budget are allocated to scientific and technological development. To further complicate matters, only 1 per cent of these funds, or 0.2 per cent of GDP, has been disbursed annually. The estimated expenditure for a scientific researcher averages $1,000 a year, compared to an international average of around $55,324. At the same time, policies for scientific researchers do not include adequate incentives to production and research. A severe shortage of funds has resulted in under-qualified training of science researchers, while experts claim the resources in almost all the universities are too backward for advanced scientific research projects. Others blame obsolete technologies applied to domestic industries for wasting production materials and impeding productivity and competitiveness.

In Vietnam, scientific equipment in research centres is, by and large, obsolete in comparison with other countries in the world. Among the main reasons suggested by experts working in this field, capital shortage is considered the principle cause for this lag. Firstly, although the regulation establishes a science and technology fund, commercial banks around the country have been slow to provide the required capital. Secondly, it is often difficult for businesses and organizations to secure mortgages and loans as regulated, as science and technology development is based primarily on credibility. Finally, the lending criteria for science and technology projects are considered too rigid by banking experts around the country.

Though the Resolution on Science and Technology specifies that "universities should be both training and research centres," they have so far failed to become hothouses of new ideas and discoveries.

With the Open Door Policy, Vietnamese leaders had hoped to hand over the tasks of scientific research and technological applications to academics. Universities are also good hunting grounds for governments staffing advisory bodies. But poor investment and lack of adequate incentives have undermined these aims. University professors remain mainly teachers, and their students continue to cram knowledge that their masters learned years ago.

Equipment in university laboratories is in general antiquated, while some expensive new equipment sits idle or is used inappropriately. Most university libraries lack adequate reference materials and magazines. And scientific seminars, symposia and conferences are scarce, being conducted occasionally for the sake of university tradition only.

The budget allotted to scientific research in universities is generally around three to five per cent of the entire budget dedicated for science and technology. With an average of VND4-5 million (about US$400-500) available for ministry-level projects, scientists - and government - can hardly expect great achievements. The Table 1.6 shows that while the

30

amount of scientific research has been increasing over the past few years, it is too small for the number of universities and professors in the country.

Table 1.6: Budget allocated to MoET in years

Programs \ Years 1988-1990 1991 1992 1993

State-level 100 - 120 (*) 120 (*)Ministry-level 200 450 438 640State-level projects/Fund (Million VND)

15/1890 12/2000 10/1850 6/1600

Ministry-level projects/ Fund (Million VND)

27/615 16/395 23/630 36/1525

Budget allotted to MoET (Million VND)

- 3,168 5,910 13,400

(*) including state-level programs on basic sciences and independent projectSource: Department of Science & Technology, Ministry of Education and Training

So far universities have received financial support from neither production units nor major development projects. Aid from international programs assists in conducting research on specific, short-term programs.

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Chapter 6

6Data Collection and Processing

6.1General

In the chapter, as indicated in the title discussed on three aspects. Firstly, discussed on the data collection method, source, relevant work undergoing, field experience on questionnaire and interview, response from respondents and data statistics. Secondly, discussed on the matrix entry and consistency checking. Finally, the processing steps on the work have been described.

6.2Data collection method and source

Due to the specific characteristic of the research study, data was collected from different sources: interview, survey, observations, reports, newspapers.

Firstly, secondary data was obtained by interviewing researchers, lecturers, and engineers in order to have a general view about linkages among units. Moreover, interview also help to gather data, which is not available in reports. Missing data in important reports is also a weak point of Vietnamese management systems as well as participants themselves in R&D cooperation. Secondly, data is also collected from observations and records of existing cooperation or missing links among units. Another type of data is background and annual reports of organizations studied. Lastly, the primary data would be obtained through questionnaire survey.

The primary data collection using structured pairwise comparison questionnaire is conducted in a highly planned fashion within the period of two weeks. During the same period, relevant information on University-Industry-GRI cooperation in Vietnam was also collected as second data. This kind of data was useful in determining existing linkages among units, which would be used for building the hierarchy model. The data is mostly collected at the biggest city of Vietnam, HoChiMinh City, Where all the necessary respondents were seated.

The respondents on the survey were the individuals (experts, actors, scientists or food processing concern people) from government, political parties, freelance consultant, scientists, and business people. The respondents considered have been taken those who have idea and experience on the issue of University-Industry-GRI cooperation and could understand the factors and linkage alternatives considered.

The organizations covered during the data collection, primary as well as secondary were as follows, in addition to these organizations some individuals who are working as freelance consultant were also covered.

University of Technology and (UT)University of Agriculture and Forestry (UAF)Food Industries Research Institute (FIRI)Post-harvest Technology Institute (PHTI)

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Plant Oil Research Institute (PORI)Ministry of Science, Technology and Environment (MoSTE)Department of Science, Technology and Environment (DoSTE)United Nations Industrial Development Organization (UNIDO) in VietnamUnited Nations Food and Agriculture Organization (FAO) in VietnamCau Tre Enterprise (CTE)New Technology CorporationVissan Import Export CorporationSong Hau Farm (SHF)Ministry of Agriculture and Rural Development (MoARD)Ministry of Industry (MoI)

6.2.1 Questionnaire and Interview

In the first meeting, the respondents were told that the researcher was developing a model for the assessment on University-Industry-GRI cooperation in Vietnam and wanted to identify factors, sub-factors and technological interactions among units that people thought were most important.

Following this introductory discussion, a pre-formulated questionnaire was administered to the people who were then asked to rate relative importance of factors and alternatives. The questionnaire used was patterned after Grizzle [60] and a partial is represented in Figure I.9. Detailed of questionnaire is attached in the Appendix A. As the quality of the questionnaire depends on the reliability of data, a detailed, concise and clear one was emphasized. Furthermore, most of questions are designed in a manner of tabulated expression which look easier for the respondent to fill in. The respondent is requested to compare the relative importance or attractiveness of two alternatives or factors at a time considering the given factor for the achievement of the goal. Because the study is based on the subjective judgment, no numerical values are directly used. The relative importance or attractiveness is measured in scale values ranging from one extreme "Absolutely important / Preferred" down towards "Equally important / Preferred". Finally, column I and column II represent factors and alternatives dimension under pairwise comparison.

Relative importance of linkage alternatives with respect to Sponsored ResearchColumn

Iextreme

very stron

g

strong

weak

equal

weak

strong

very stron

g

extreme

ColumnII

Industry-GRI University-Industry

Industry-GRI GRI-UniversityUniversity-

IndustryGRI-University

Figure I.9: A partial sample of questionnaire

6.2.2 Matrix Entry

The respondents were given a week before they attempted to provide data for the hierarchical model. Preliminary discussion with the researcher about analytic hierarchy

33

process concepts and the contents of the questionnaire was conducted at the first meeting itself. After a week, the forms were collected from them. If they had additional question or the questionnaire were not filled in, direct or telephone discussion took place again and they provided a relative re-weighing on the spot. However, a "repeat of process" after sometime as discussed by Saaty [61], where the experts returned after their relative weighing of the factor for a second comparison after detailed discussions, could not be done due to time constraints and the 146 different alternatives to choose from.

In the case where relative importance of the factors by individual respondents might be dissimilar, many researchers have used the geometric mean matrix eigenvector (GM) and mean of eigenvector of individual expert's response (ME). In the GM method, the geometric means for all respondents were tabulated and rounded to the nearest integer due to the fact that the AHP model requires only a discrete scale from 1 to 9 [62].

It has been mathematically proved that the way to accumulate each pairwise comparison from a group of participants is to take the geometric mean of the various judgments after sufficient debate. This approach can save both time and money for researcher [57].

ME method is the ease with which consensus preference ranking can be derived as means of expert eigenvector. These means are the ME solutions. Geometric means can also be derived from the initial paired comparison responses of experts. For example, let aij = (a1

ij.a2ij…am

ij)1/m depict the geometric mean for the responses of m experts. Unlike the arithmetic mean of expert responses, the geometric mean has reciprocal priorities (i.e., aij=1/aij).

A serious drawback of the second (ME) method when compared to the first (GM) one is that when we are dealing with a large number of respondents (say 1000) the requisite computation of eigenvalues and eigenvector for every expert becomes impractical. With the "GM method", however, only one eigenvector needs to be computed for the consensus matrix as compared to the "mean of eigenvalues" (ME) approach, where the mean of all the individual eigenvalues corresponding to each respondents is calculated, to arrive at the consensus. The "GM method", nevertheless, may require exponential arithmetic on computers or sophisticated calculators to deal with very large or very small numbers [63].

On the time being, a personal computer with Pentium chip inside is powerful enough to support the calculation on geometric mean of a large number of individual judgments. Furthermore, the latest software called Expert Choice pro 9.5 is considerably sensitive and comfortable in dealing with the AHP problem. Another software also employed during the data processing is Microsoft Excel 7.0. In this study, therefore, the geometric mean method is used.

6.2.3 Responds from Respondents

Response on the research work from various organizations and individuals were encouraging. Almost all the respondents have responded with high interest. The pairwise comparison fashion of questionnaire was new to most of the respondents. Clarification on the format and factors are made to all the respondents. Additional clarification and explanation were made to the respondent, if they are not clear or confused with the initial briefing. Respondents were happy to see the evaluation process which considers the importance or preference to various factors of their concern. The process was found easy to understand to

34

the priority of respondents. However, some interviewees asked did not respond or were not interested in the problem.

The research work involving the value judgment on various factors needs clear interpretation and definition on the factors used. For this purpose, a written explanation was included with each questionnaire, a briefing on fashion of questionnaire and definition and idea on factors were explained to each respondent before their judgment. The respondents were requested to make further clarification, if they had any confusion during the judgment, accordingly some respondents marked the confusing factors to them and make their judgment discussing with the researcher, in this case they got clarification instantly on each factors.

6.2.4 Response Statistics

Response statistics is basically the figures on the total number of questionnaire distributed, responded questionnaire, acceptability of responded judgment on the questionnaire and the distribution among various actors. The number of judgment collected from three actor groups is around five. However, the number of responses from either government or political group is only two. The total questionnaire distributed is thirty. The number of responded questionnaire is about twenty-five. However, six of that were rejected after checking consistency. Therefore, the total accepted judgments is finally nineteen. The numerical values of the distribution of questionnaire are presented in Table 1.7.

Table 1.7: Distribution of questionnaire

Distribution and Response Number Total questionnaire distributed 30 Responded questionnaire 25 Invalid questionnaire 6 Total accepted judgment 19Distribution among actor group Business people 4 Government officers 2 Political people 2 Freelance consultants 6 Scientists 5

6.2.5 Check for Consistency

Expert judgment is a necessary component in applying AHP to measure the relative importance of technological linkages. The frequent lack of object, the highly interdependent nature of system variables, and the uncertainty of future events make it necessary to rely upon expert prediction of social effects of alternative technologies or actions. Practically, in all case, experts must go beyond the boundaries of their substantive disciplines. Thus, the drawback of AHP is the possibility of inconsistent response in pairwise comparisons.

Saaty suggested a decision rule for accepting decision makers' judgments based on a consistency measure from the decision maker's importance index. Saaty recommended that inconsistency should be less than ten percent of the mean for matrices of that size [57].

35

The pairwise comparisons and consistency index were then performed on the matrices. Interviewees had few problems in answering the questions: 83.3% responded to interview (25 out of 30 interviewees) and of these, 76 % had acceptable consistency index (19 out of 25 interviewees).

In the case of the expert importance index – if they are too inconsistent, according to Saaty, the analyst should reconfirm with the respondent. As time was extremely limited in the case of Vietnam and the fact that inconsistency amongst the respondents was rather high, some of data was rejected, as reconfirming was not possible. So, in this study, it follows that if the Inconsistency Index was more than 0.3, the respondent's opinions were discarded. Thus, in the primary data collected, 6 out of 25 interviewees were not considered. An acceptable inconsistency index can be derived if it is between 0.1 and 0.3. If the inconsistency index were less than 0.1, the respondent's opinions would completely be accepted without any re-examination.

In each questionnaire, consistency of overall as well as individual comparison matrices has been checked. About seventy five percent of the responses have been checked for overall consistency in the filed. The consistency on each matrix has been checked at the time of detail processing of the data. The highly inconsistent judgments with bleak chance to improve the consistency have been rejected. When the inconsistency is within the re-examination limit, consistency improvement has been carried out without effecting the priority of the judgment. Expert Choice version 8.0 has been used in quickly checking consistency. However, for the detail processing is conducted in a high-speed desktop computer using the latest version of Expert Choice Professional (ECPro) for Windows.

6.3Data Processing

The completed pairwise comparison questionnaire is the main data to be processed. As mentioned in the matrix entry section, Expert Choice Professional (ECPro, version 9.5, for Windows) and Microsoft Excel, version 7.0, have been used for the processing work. FigureI.10 shows data collection and processing steps.

The data processing steps has been set as follows:

6.3.1 Individual Judgment Calculation

The second step in the processing work is the calculation of synthesis of individual judgment, priorities to factors, sub-factors as well as the alternatives. The individual judgment is analyzed in the overall group as well as in the actor group.

6.3.2 Overall Group Judgment

Priority on the alternatives from the group is arrived from this synthesis of the group judgment. The overall group judgment has been calculated and presented in chapter six. The group judgment is processed with the geometric mean of all the judgment from each respondent. Geometric mean calculation is performed with the ECPro and cross-checked from Microsoft Excel 7.0. Detailed data source of overall group judgment is attached in the appendix B.

36

6.3.3 Actors Group Judgment

Group judgment from the various five actors is computed in the same manner as in the case of overall group. In this case the geometric mean is calculated only among the respondents of the actor group. Because the research has a limited time and the result of actor group judgment is most useful for the overall linkage analysis, this step is not applied for the individual linkage analysis. Detailed data source of actor group judgment is attached in the appendix B.

Figure I.10: Data collection and processing steps

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Chapter 7

7Analysis of Results

7.1General

The chapter has been divided into two parts. The first part of this section discusses on the result obtained from the overall linkage in the study. The second part presents results and discussions on each of individual linkage.

7.2The Overall Linkage: University-Industry-GRI

7.2.1 Model Application

According to data collected, three main players involving in the Innovation Triangle are academic universities, R&D organizations, and industrial productive enterprises. These players interact with each other through three kind of two-way linkages: University-Industry, Industry-GRI, and GRI-University, which would be three alternatives for overall assessment. Besides, each player involves in two-way linkages mainly through such linkage types as research contract, sponsored research, provision of services and training activity which would be criteria for linkage judgments. Therefore, the hierarchy model established for overall assessment of the University-Industry-GRI cooperation is represented in the Figure I.15.

7.2.2 Results

Individual Judgment on Overall GroupIndividual judgment gives the result of individual preference on the alternatives and importance of various factors to them. The results could be analyzed in overall group as well as in actor group. Details of individual judgment results are attached in the appendix D. Result of individual judgment is presented in three headings. Preference to the alternatives, factors and the sub-factors respectively.

Individual Preference to alternativesAlmost fifty eight percent of respondents gave first preference to the University-Industry linkage. Around thirty seven percent gave first preference to the Industry-GRI linkage and only five percent preferred GRI-University linkage. Graphically the result of individual judgment is presented in Figure I.11 and numbers are shown in Table 1.8.

Table 1.8: Individual judgment and their priority to the linkagePriority / Linkages Industry-GRI University-Industry GRI-UniversityFirst Priority 7 (36.8) 11 (57.9) 1 (5.3)Second Priority 11 (57.9) 7 (36.8) 1 (5.3)Third Priority 1 (5.3) 1 (5.3) 17 (89.5)Note: The number outside the parenthesis is number of respondent and percentage is indicated inside the parenthesis

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Figure I.11: Percentage of response to preference order for different linkages

Individual Importance to FactorsResearch contract is considered the most important factor by fifty eight percent of respondents. Training activities is assigned as first important factor by around thirty two percent of respondents. And only ten percent of respondents gave first priority to sponsored research factor. No one consider provision of services as the first priority. Detailed individual importance to factor is indicated in Table 1.9 and percent of respondents giving first priority to various factors is shown in Figure I.12.

Table 1.9: Individual importance to factors

Priority / Factors Research Contract Sponsored Research

Provision of Services

Training Activities

First Priority 11 (57.9) 2 (10.5) - 6 (31.6)Second Priority 6 (31.6) 6 (31.6) - 7 (36.8)Third Priority 2 (10.5) 5 (26.3) 9 (47.4) 3 (15.8)Last Priority - 6 (31.6) 10 (52.6) 3 (15.8)Note: The number outside the parenthesis is number of respondent and percentage is indicated inside the parenthesis

39

Figure I.12: Percent of respondents giving first priority to various factors

Individual Judgment in Actor GroupIf the result of the individual judgment is seen from the actor group as shown in Table 1.10, all people (except one) in the Business, Government, Political, Consultant and Scientist groups preferred either Industry-GRI or University-Industry linkages. Almost individuals of group gave the stronger priority to University-Industry cooperation. The government group has the most different idea from others.

Table 1.10: Individually preferred linkages distributed in actor group

Actor groupLinkages

Business People

Government Officers

Political People

Freelance Consultant

Scientists

Industry-GRI 1 1 1 2 2University-Industry 3 - 1 4 3GRI-University - 1 - - -

Actor Group JudgmentActor group judgment has been analyzed for the five different actor groups proposed in the AHP model. Summary of results of the actor group judgment is presented in Table 1.11 and Figure I.13. The result is discussed on the following:

All actors gave first priority to University-Industry linkage. All actors preferred secondly to promote the cooperation between GRI and Industry. GRI-University linkage was considered as the least importance according to actor group judgments. Most of actor groups gave the most important factor to Research Contract and Training Activities was considered as the secondly preferred factor with regards of all actor group judgments except Freelance Consultant group. Lastly, provision of services was assigned as the least important factor referring to the ideas of the five actor groups.

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Table 1.11: Priorities of factors and alternatives from overall group and various actors

Actor Group Factors

Business People

Government Officers

Political People

Freelance Consultant

Scientists

Research Contract 35.4 45.1 39.5 39.5 48.9Sponsored Research 23.8 7.8 27.2 27.3 14.2Provision of Services 7.8 9.1 6.1 10.9 8.6Training Activities 33.0 38.0 27.1 22.3 28.3LinkagesIndustry-GRI 42.8 34.4 42.3 42.5 43.5University-Industry 44.2 42.4 46.5 44.6 43.7GRI-University 12.9 23.2 11.1 12.9 12.8

Figure I.13: Importance to factors by actors and overall group

Overall Group JudgmentSynthesis of overall group judgments is important result of AHP model application. The result takes care of individual preference or importance of each factor, sub-factor and alternatives with respect to the overall objective of the problem. So the result is the consensus of the decision makers for the alternatives taking care of multiple conflicting preference to various factors and alternatives for the achievement of the objective of the problem.

The result of synthesized group judgment shows that Research Contract factor has drawn highest importance, forty three percent, then Training Activities got the second priority by twenty seven percent. Twenty percent is gained by the Sponsored Research factor and the least importance of nine percent is to the Provision of Service factor. According to respondents, University-Industry linkage is the most important with forty eight percent. Industry-GRI is the next one and GRI-University is the lowest preference. The data and figure are illustrated in Table 1.12 and Figure I.14. More results are presented in the appendix D.

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Table 1.12: Summary of overall group judgments on overall linkage

FactorsLinkages

Research Contract

Sponsored Research

Provision of Services

Training Activities

Overall results

Industry-GRI 21.6 7.8 4.6 5.5 39.5 University-Industry 17.7 9.4 3.6 16.9 47.6 GRI-University 3.8 3.2 1.1 4.7 12.9 Synthesis 43.1 20.4 9.3 27.1 100.0 Inconsistency 0.010

7.2.3 Implications of the result

Assessment of the overall linkages in the University-Industry-GRI cooperation is to determine which linkage is relative more important among the three links, namely University-Industry, Industry-GRI, and GRI-University. The final result for the judgments of the linkage alternatives shows that University and Food Industry have the strongest interaction as shown in Figure I.14. Therefore, it is necessary for policy maker to pay more attention on the linkage between University and Food Industry. However, the linkage between GRI and Food Industry also plays an important role and nearly has the same weight with the Industry-University linkage (39 % versus 47 %). The linkage between University and GRI is assigned the lowest rank that urges policy maker to revise the current structure of innovation.

Figure I.14: Overall group synthesis of linkage alternatives with respect to goal and factor

7.2.4 Discussion

Closely coupled innovation triangle is absolutely essential. Academia, research units and production units – when inter-linked with minimum critical mass – together form the innovation triangle producing: product/process; knowledge/skill; and methods/packages type of innovations. As discussed above, the strong degree of linkages – University-Industry, Industry-GRI, GRI-University – is not equal. The severe weakness of the linkage GRI-University makes the effectiveness of the whole triangle considerably reduce. Thus, in order to improve the current situation, all players should closely get together and actively speed up

42

Synthesis of Leaf Nodes with respect to GOALDistributive Mode

OVERALL INCONSISTENCY INDEX = 0.0

U_I .476

I_R .395

R_U .129

Abbreviation DefinitionU_I Linkage between UNIVERSITY and INDUSTRY

I_R Linkage between INDUSTRY and GRI

R_U Linkage between GRI and UNIVERSITY

OVERALL LINKAGES: INDUSTRY - UNIVERSITY - GRI

0.01

their cooperation. However, it is not enough to do so. They need a positive support from the government through encouraging mentor institutions to further strengthen the University-Industry-GRI cooperation. These mentors – financial institutions (investment promotion corporations and venture capital banks); and technical institutions (certification, testing, quality assurance and standardization organizations) – play catalytic roles to promote the commercialization of indigenous technologies. Absence or sub-critical strength of any necessary agents involved in the innovation chains will reduce drastically the effectiveness of technology infrastructure.

Figure I.15: Hierarchy for Overall Linkage

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7.3Linkage between Food Industry and University

7.3.1 Model Application

According to data collected, existing linkages between Food Industry and Academic University studied in Vietnam were generally limited in research contract, sponsored research, provision of service and training activities. The missing link in formal type is joint research and other missing links in informal type are staff transfer and practical training in some cases. From that argument, there are four alternatives as regards of existing links. Factors and sub-factors for judgments of these alternatives are referred to section 3.4. Therefore, the hierarchy model established for the linkage between Food Industry and Academic University is illustrated in Figure I.19.

7.3.2 Results

The result of synthesized group judgment shows that Training Activities cooperation has drawn a prominent importance, thirty percent, then Research Contract got the second priority by twenty six percent. Twenty two percent is gained by the Provision of Service and the least importance of twenty one percent is to the Sponsored Research cooperation. The numerical data is illustrated in Table 1.13. More results are presented in the appendix C.

Table 1.13: Summary of overall group judgments on University-Industry linkage

AlternativesFactors and Sub-factors

Research Contract

Sponsored Research

Provision of Services

Training Activities

Synthesis

FLOW from UNIVERSITY to INDUSTRY 71.4 Magnitude of Money 4.0 0.7 1.9 2.3 8.9 Human Interactions 5.1 4.0 2.5 10.1 21.7 Organization Interactions 3.8 5.7 1.2 2.3 12.9 Facility Utilization 3.2 2.5 4.9 1.2 11.7 Information Interaction 1.8 2.1 5.6 6.6 16.1

FLOW from INDUSTRY to UNIVERSITY 28.6 Magnitude of Money 3.9 0.7 1.8 2.3 8.7 Human Interactions 1.1 0.8 0.5 2.1 4.5 Organization Interactions 2.0 3.0 0.6 1.2 6.8 Facility Utilization 1.3 1.0 2.0 0.5 4.7 Information Interaction 0.4 0.5 1.3 1.6 3.8

RESULTS 26.4 21.0 22.4 30.2 100.0 INCONSISTENCY 0.01

7.3.3 Implications of the Result

According to the result of judgments, the model gave emphasis more on the magnitude flow of factors from University to Food Industry than that from Food Industry to University. In addition, the difference between the two flows is considerably high (71.4 against

44

28.6). So it can be said that the initiative to build the linkage would come from University – the first player stimulates the connection. The strength of the linkage would be maintained when the Food Industry believes in the trust and research capability of the University – the second player responds to the cooperation.

Priorities of brainpower and information are the most important (30.4 and 22.6) with respect to other factors in the flow of factors from University to Food Industry as presented in Figure I.16. People in industry look university as the source of information which is highly reliable and cheap. In fact, information Food Industry needs from University is often embodied in human power of the university. So it is obvious that information and brainpower always go together in the flow from University to Food Industry. In addition, the flows of brainpower and information from University to Food Industry are mostly through training activities and provision of service such as consultant and staff transfer. Organization and facility factors play less important role. And money is the least important (12.4) as resulted in the model. The reason is simple. At present, almost academic universities in Vietnam are operating under funds subsidized from the government.

Figure I.16: Magnitude flow of factors from University to Industry

Money has the highest priority (30.5) in the flow of factors from Food Industry to University as shown in Figure I.17. People in university look industry as a source of capital to fund their research activities. The second priority is organization interaction (23.8). Faculties and graduate students often consider working on field as the best way for them to practice their management capability and to apply their know-how and know-why. Brainpower and facility play less important role. And the lowest priority is assigned for information factor. University for a long time had run as a training center, so it did not well understand about industry. As a result, many research projects were not commercialized due to lack of information about R&D market.

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Synthesis of Level 2 Nodes with respect to FLOW U-IDistributive Mode

BRAINPOW .304

INFORMAT .226

ORGANIZA .181

FACILITY .164

MONEY .124

Abbreviation DefinitionBRAINPOW Human Interactions

INFORMAT Inf ormation Interactions

ORGANIZA Organization Interactions

FACILITY Facility Utilization

MONEY Magnitude of Money

LINKAGE BETWEEN INDUSTRY AND UNIVERSITY

Figure I.17: Magnitude flow of factors from Industry to University

The overall result for the judgments on the alternative types of linkage between University and Food Industry shows that Training Activity is the most important one (30.2) as shown in Figure I.18. Although there are many efforts from university to improve its image of research capability, it is still considered as educator and provider of talent. The least important linkage type is sponsored research. Although the biggest budget for university's research activities still comes from government, another source of money University need is now more and more from research contract and collaboration research with Industry.

Figure I.18: Overall judgments on University and Industry linkage7.3.4 Discussion

On the industrial side, most production design and manufacturing organizations accomplished their applied research work using three primary resource: in-house R&D operation, supplier R&D activities and university research capabilities. In the current situation, most of food enterprises in Vietnam are small and medium. Therefore, they can not have enough money to develop their in-house R&D operations. University would be the cheapest R&D source for them to achieve their technological capabilities. Moreover, food enterprises

46

Synthesis of Level 2 Nodes with respect to FLOW I-UDistributive Mode

MONEY .305

ORGANIZA .238

FACILITY .165

BRAINPOW .158

INFORMAT .134

Abbreviation DefinitionMONEY Magnitude of Money

ORGANIZA Organization Interactions

FACILITY Facility Utilization

BRAINPOW Human Interactions

INFORMAT Inf ormation Interactions

LINKAGE BETWEEN INDUSTRY AND UNIVERSITY

Synthesis of Leaf Nodes with respect to GOALDistributive Mode

OVERALL INCONSISTENCY INDEX = 0.01

T A .302

R C .264

P OF S .224

S R .210

Abbreviation DefinitionT A Training Activ ities

R C Research Contract

P OF S Prov ision of Serv ices

S R Sponsored Research

LINKAGE BETWEEN INDUSTRY AND UNIVERSITY

as regards of respondents' idea pay much attention on brainpower factor which is mostly known as university faculties with unique expertise and good graduate students, and information factor like intellectual property and latest knowledge derived from lecturer’s consultant, training activities, and conference/seminar. Industry needs new knowledge and in-dept understanding for scientifically and technologically new or emerging ideas from University in order to build new technologies and to improve upon old ones. Industry essentially needs brainpower from University because the latest knowledge of technology is mostly embodied in human resource of the university. In a case, industry interviewees stated that they find the most fruitful form of collaboration to be a bottom-up approach based on one-to one relationship between Food Industry and university scientists. Arrangements with consultant and informal interactions also are strongly supported.

Therefore, in order to attract more food enterprises, strengthen existing linkages and revive missing links, University should concentrate more attention on developing its faculty staff and providing reliable information and good quality of services as well as more relevant preparation for graduates about to enter industry. University should shift their emphasis away from traditional basic research to applied research directed toward more immediate practical implementation in order to suit more relevant R&D results for industry.

On the university side, the primary role for University in innovation is as a basic research center. In Vietnam, during the time of subsidy mechanism the main financial source for supporting University’s research activities had come from the government. However, in the current situation this role of the central government to sponsor R&D activities more and more decreases. Consequently, the declining central budget allocation has forced University actively to seek R&D partnerships with domestic and international organizations. Therefore, from University’s viewpoint, industrial partnership is one of the most important sources to satisfy their need of money for basic and applied researches. On the other hand, as one university (faculty) interviewee stated that the initiative of commercializing R&D results is mostly from university side. When the university were successful in certain research contracts with some industrial partners, the others would believe in university’s R&D capabilities and then they would automatically come to university and ask to solve their technological problems.

Therefore, in order to strengthen the University – Industry linkage, industrial partner should be more active in funding R&D activities in University. On the other hand, research activities in University had frozen for a long time due to the rigid management of central mechanism. Most of R&D projects were commercialized into Food Industry through organic relationships such as university alumni, old friend, old colleague and relatives.Industry should view University as a training center for their future human resource. They should not only recruit university students with out any reimbursement for training expenditure, but also has to long term invest in training activities by sending their engineers and workers and by giving fellowships and sponsorships to University.

These findings suggest that to strengthen the linkage, Industry should be the first one in actively taking initiative for building the linkage and, secondly, University should improve their image of R&D capabilities toward Industry.

Industry-University collaborative programs should be established with a clear understanding by both parties in which the mutual trust and appreciation are of the utmost importance for developing the linkage between these two units.

47

Figure I.19: Hierarchy for University and Industry linkage

SR: Sponsored researchRC: Research ContractPS: Provision of ServicesTA: Training activities

48

7.4Linkage between University and GRI

7.4.1 Model Application

Regarding to data collected, existing links between University and GRI studied in Vietnam were mostly limited in provision of services and training activities. There are many missing links between the two units. Most of formal types such as joint research, research contract and collaboration are absent. Other missing links in informal type are staff transfer and consultant. From these points, only two alternatives are established as regards of existing links. Factors for judgments of these alternatives are referred to section 3.4. Therefore, the hierarchy model established for the linkage between University and GRI in Vietnam is presented in Figure I.20.

7.4.2 Results

The result of synthesized group judgment shows that Training Activities cooperation has drawn higher importance, fifty six percent. The rest of forty four percent is gained by the Provision of Service. The numerical data is illustrated in Table 1.14. More results are presented in the appendix C.

Table 1.14: Summary of overall group judgments on GRI-University linkage

AlternativesFactors and Sub-factors

Provision of Services

Training Activities

Synthesis

FLOW from UNIVERSITY to GRI 50.0 Magnitude of Money 2.9 2.9 5.8 Human Interactions 2.8 13.0 15.8 Organization Interactions 2.9 7.3 10.2 Facility Utilization 4.8 1.5 6.2 Information Interactions 6.5 5.4 11.9

FLOW from GRI to UNIVERSITY 50.0 Magnitude of Money 3.1 3.1 6.2 Human Interactions 1.6 7.4 9.0 Organization Interactions 2.5 6.4 8.9 Facility Utilization 11.6 3.6 15.2 Information Interactions 5.8 4.8 10.6

RESULTS 44.5 55.5 100.0 INCONSISTENCY 0.01

49

Figure I.20: Hierarchy for GRI and University Linkage

PS: Provision of Services

TA: Training activity

50

7.4.3 Implications of the Result

Firstly, the model result shows that both of actors (GRI and University) play equal role in determining the strength of the linkage between University and GRI. The magnitude flow of factors from GRI to University is almost as same as the magnitude flow of factors from University to GRI. The reason is that both of parties are government-funded organizations and they also have some similar R&D activities such as basic and applied research, technology transfer etc. However, both have different objectives and roles. GRI’ objective is to commercialize R&D results to make profit whereas University’s know-how is freely published. University pays much attention on academic result rather than profit. Thus, each party has different strong points the other can tap on.

Secondly, in the flow from University to GRI, brainpower (31.6) is still the most dominant factors as shown in Figure I.21. University known as an educator and provider of talent has a strong point in providing pool of competent faculties and graduate students. On the other side, in the flow from GRI to University, facility (30.4) is the most important aspect as shown in Figure I.22. GRI with advancements of professional and efficient laboratories can satisfy university’s needs of improving technique and methods. Moreover, in both flows, information plays the second highest preference. Thus, most of cooperative activities the two parties involve are mainly to exchange technological information.

Finally, the overall result of the judgments for the alternative types of linkage between University and GRI is illustrated in Figure I.23. It shows that Training Activity (55.5) took over half of interactions between the two units. The implication of this result means that the communication between University and GRI is really limited in such activities as student practicing in GRI’ laboratory, university faculty as R&D collaborator in Institute, and researchers as visiting faculty in University.

7.4.4 Discussion

Like many developing countries, R&D units in Vietnam really depend on the government because the biggest funding research also comes from the government. Thus, research activity is limited to existing budget. Unfortunately, academic university also suffers the same fate. Money is the most important resource both of parties need to nurture their R&D activities, but no one can afford. Therefore, it is easy to understand that cooperation between University and GRI is only training activity and provision of services.

The missing of almost research cooperation suggests that the linkage between the two units is so weak that they should not depend on the sponsor from government and should positively speed up the cooperative linkage in terms of joint R&D project to tap technological advantage of each other.

51

Synthesis of Level 2 Nodes with respect to FLOW U-RDistributive Mode

BRAINPOW .316

INFORMAT .239

ORGANIZA .204

FACILITY .125

MONEY .116

Abbreviation DefinitionBRAINPOW Human Interactions

INFORMAT Inf ormation Interactions

ORGANIZA Organization Interactions

FACILITY Facility Utilization

MONEY Magnitude of Money

LINKAGE BETWEEN GOVERNMENT R&D INSTITUTE AND UNIVERSITY

Synthesis of Level 2 Nodes with respect to FLOW R-UDistributive Mode

FACILITY .304

INFORMAT .212

BRAINPOW .181

ORGANIZA .178

MONEY .125

Abbreviation DefinitionFACILITY Facility Utilization

INFORMAT Inf ormation Interactions

BRAINPOW Human Interactions

ORGANIZA Organization Interactions

MONEY Magnitude of Money

LINKAGE BETWEEN GOVERNMENT R&D INSTITUTE AND UNIVERSITY

Synthesis of Leaf Nodes with respect to GOALDistributive Mode

OVERALL INCONSISTENCY INDEX = 0.01

T A .555

P OF S .445

Abbreviation DefinitionT A Training Activ ities

P OF S Prov ision of Serv ices

LINKAGE BETWEEN GOVERNMENT R&D INSTITUTE AND UNIVERSITY

Figure I.21: Magnitude flow of factors from University to GRI

Figure I.22: Magnitude flow of factors from GRI to University

Figure I.23: Overall judgments for University and GRI linkage

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7.5Linkage between GRI and Industry

7.5.1 Model Application

From data collected, existing links between GRI and Food Industry studied in Vietnam were mainly limited in provision of service, training activities, research contract and sponsored research. The missing link in formal type is joint research and other missing links in informal are staff transfer and sharing facilities. From that point, there are four alternatives as regards of existing links. Factors for judgments of these alternatives are referred to section 3.4. Therefore, the hierarchy model established for the linkage between GRI and Food Industry in Vietnam is illustrated in Figure I.27.

7.5.2 Results

The result of synthesized group judgment shows that Sponsored Research cooperation has drawn a highest importance, twenty eight percent, then Research Contract got the second priority by twenty six percent. Twenty four percent is gained by Provision of Service and the least importance of twenty one percent is to the Training Activities cooperation. The numerical data is illustrated in Table 1.15. More results are presented in the appendix C.

Table 1.15: Summary of overall group judgment on Industry-GRI linkage

AlternativesFactors and Sub-factors

Research Contract

Sponsored Research

Provision of Services

Training Activities

Synthesis

FLOW from GRI to INDUSTRY 68.75 Magnitude of Money 2.0 3.9 1.6 1.0 8.5 Human Interactions 1.7 2.0 5.4 6.4 15.5 Organization Interactions 5.1 0.9 2.4 3.0 11.3 Facility Utilization 3.4 2.6 5.2 1.3 12.4 Information Interactions 6.2 9.2 2.0 3.7 21.1

FLOW from INDUSTRY to GRI 31.3 Magnitude of Money 2.3 4.6 1.8 1.1 9.8 Human Interactions 0.6 0.6 1.7 2.0 4.9 Organization Interactions 1.9 0.3 0.9 1.1 4.3 Facility Utilization 1.4 1.1 2.1 0.5 5.1 Information Interactions 2.1 3.1 0.7 1.3 7.2

RESULTS 26.5 28.4 23.7 21.4 100.0 INCONSISTENCY 0.01

7.5.3 Implications of the Result

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Firstly, the model result shows that the strength of the linkage between GRI and Food Industry is much more determined by the magnitude of flow (68.8) from GRI to Food Industry in comparison with that (31.3) from Food Industry to GRI. It is said that the first factor to build a strong linkage between the two units would come from GRI. However, the survival of the linkage depends on not only GRI’ R&D capability, but also Food Industry’s interest. That is why Food Industry somewhat has responded to GRI's stimulation. In the beginning, almost initiatives of establishing the cooperation come from GRI, and then the cooperation interest gradually becomes necessary need of Food Industry, because they realize that cost of R&D in GRI is sometimes much cheaper than that of international supplier.

Secondly, it is likely that the model result shows information (30.6) as the most important criterion for maintaining the linkage between GRI and Food Industry with respect to the magnitude of flow from GRI to Food Industry. People in industry consider GRI as the source of know-how for them to acquire. The second priority is brainpower (22.5) factor. In the linkage, GRI mostly just provide technological resources. It is reckon that human resource is the most valuable asset for GRI to build relationship with industry. The next is facility utilization and organization interaction factors. The least important factor is money as presented in Figure I.24.

Figure I.24: Magnitude flow of factors from GRI to Industry

Thirdly, in the magnitude of flow from Food Industry to GRI, people gave more emphasis on money factor (31.4) as the most important one. Researchers in GRI always expect that industry would be the first source of funding their R&D project. The second priority is assigned for information factor (23.0) as shown in Figure I.25. Well understanding Industry behaviors such as R&D needs, technological capability or so on is much helpful for GRI to commercialize and transfer its technologies. The importance of brainpower (16.2) and facility (15.8) factors is almost equal and they are given in the third rank. The weakest one in the flow from Food Industry to GRI is organization interactions. This factor much concerns to the top management’s vision toward technological cooperation. When the industry involves in technological linkage, the top or high level of management is usually the decision-maker. However, many managers are neither aware of nor believable in R&D capability of GRI.

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Synthesis of Level 2 Nodes with respect to FLOW R-IDistributive Mode

INFORMAT .306

BRAINPOW .225

FACILITY .181

ORGANIZA .164

MONEY .123

Abbreviation DefinitionINFORMAT Inf ormation Interactions

BRAINPOW Human Interactions

FACILITY Facility Utilization

ORGANIZA Organization Interactions

MONEY Magnitude of Money

LINKAGE BETWEEN INDUSTRY AND GOVERNMENT R&D INSTITUTE

Figure I.25: Magnitude flow of factors from Industry to GRI

In the final result of judgments for the alternative type of linkages between GRI and Food Industry, the collaboration in research project is considered as the highest rank in priority. The implication of this result means that in order to maintain the strength of the linkage, GRI and its industrial partner need capital not only from industry itself but also from outside sponsors such as government and international organizations to support their R&D activities. As presented in Figure I.26, sponsored research and research contract took more than half of linkage activities and followed by training activities and provision of services in terms of informal linkage such as consultant, technical assistance and sharing facility

Figure I.26: Overall judgments for GRI and Industry linkage

7.5.4 Discussion

On the industry side, as discussed in the previous part, most production design and manufacturing organizations have three primary resources to draw upon in order to accomplish required applied research: in-house projects, supplier efforts and university capabilities. However, most of small and medium food enterprises in Vietnam do not have enough technological resource to be self-reliance on in-house projects. Thus, they have to

55

Synthesis of Level 2 Nodes with respect to FLOW I-RDistributive Mode

MONEY .314

INFORMAT .230

FACILITY .162

BRAINPOW .158

ORGANIZA .136

Abbreviation DefinitionMONEY Magnitude of Money

INFORMAT Inf ormation Interactions

FACILITY Facility Utilization

BRAINPOW Human Interactions

ORGANIZA Organization Interactions

LINKAGE BETWEEN INDUSTRY AND GOVERNMENT R&D INSTITUTE

Synthesis of Leaf Nodes with respect to GOALDistributive Mode

OVERALL INCONSISTENCY INDEX = 0.01

S R .284

R C .265

P OF S .237

T A .214

Abbreviation DefinitionS R Sponsored Research

R C Research Contract

P OF S Prov ision of Serv ices

T A Training Activ ities

LINKAGE BETWEEN INDUSTRY AND GOVERNMENT R&D INSTITUTE

rely on the two remain sources. In addition, cost of R&D of domestic supplier is likely cheaper than that from outside. Therefore, more and more food enterprises look for R&D source from local GRI. For food enterprises, brainpower such as researchers and engineers with unique expertise is highly preferable. Officially, this force is employed as researchers by government. Sometimes they may become part-time employees in food enterprises or serve as R&D collaborators. The technological information such as know-how and know-why, which are always embodied in institute researchers, is the most preferable factor for industry to develop their own technology. The flow of information from GRI to Food Industry presents through almost linkage types. For example, research contract, training activities through on-filed training, practical training, and provision of service like consultant.

From that viewpoint, in order to maintain and strengthen the linkage, GRI should pay more attention on disseminating information and developing a competent staff including researchers and engineers. GRI should play an essential role in providing reliable and valuable information for Food Industry. On the other hand, GRI should keep in mind that its R&D cost should be cheap and quality of R&D result should be high.

On the GRI side, as government funded institute, the primary role of GRI is to develop needed technology and then transferring the results of such research over to industrial sector [18]. However, the current fund for R&D budget from the government is not enough, that forces GRI actively seek other financial sources to fund their R&D projects and to survive. Therefore, GRI looks industrial sector as the substitute player. Inherently, almost Vietnamese GRI’ efforts to commercialize R&D results into industry derive from organic relationships such as friend, alumni, relatives, old colleague or so on. Therefore, in many cases the level of organization involving in on the GRI side is only individual or group, whereas that on the Food Industry side is usually top or high level of management. From these arguments, in order to strengthen the linkage, industrial partner should be more tolerant in financing R&D projects in GRI and top management should more appreciate the technological linkage as an important engine for their development.

In general, most of linkage activities are dominated by research contract and sponsored research. The sponsored research type plays the most important role. This implicates that the third party should present such as government to facilitate the linkage. Besides, both parties should concentrate more on provision of services and training activities that are cheapest ways in disseminating technology.

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Figure I.27: Hierarchy for GRI and Industry Linkage

SR: Sponsored research

RC: Research Contract

PS: Provision of Services

TA: Training activity

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Chapter 88

9Conclusions and Recommendations

9.1General

The final and concluding section of the research report is further divided into three sections namely, conclusion, recommendations and further research direction. The conclusion portion gives the findings of the study to justify the fulfillment of the objective of the research study. The second section focuses on recommendations on the basis of experience gained from the study. Guidance for the further research direction has been highlighted on the last part of the chapter.

9.2Conclusions

Hierarchy Analysis can be applied at many levels of policy making – global, national, industrial and specific technology levels. The AHP approach is used in developing a model for assessment of University-Industry-GRI cooperation as a means for structuring and analyzing the complex, multifaceted problem of technological assessment. The adaptability of the method used is highly dependent on people judgment. Thus, data collected from 19 respondents through a structures questionnaire, maintaining an inconsistency index of less than 0.1 for each respondent further supplemented by individual interviews, whenever possible.

The AHP has produced a viable model to ease strategic measurement during the process of technological assessment at industrial level. One benefit from the analysis by considering different linkages, their respective weighted criteria, namely linkage factors and linkage types is in the applying them to the technological alternatives. Furthermore, the hierarchy models as illustrated in previous sections, show how Expert Choice Software can be effectively used to analyze different multicriteria decisions involving subjective judgment.

The factors, sub-factors and criteria considered in the study models deserves its full value in the judgment process with public involvement for assessing the strength of University-Industry-GRI cooperation. Hence all the factors, criteria and sub-factors identified in the model are relevant to the measurement process of the problem.

The results of the AHP models developed for overall and individual linkages show that all inconsistency indices are under 0.1. Thus, the validation of the work is satisfied. Moreover, as per Aczel and Saaty [66], when applying the AHP on group judgment, the geometric mean is the uniquely appropriate rule for combining individual judgments because it preserves the reciprocal property in the combined pairwise comparison matrix. For the individual to be compatible with the group the inconsistency index should not exceed 0.1. Therefore, the inconsistency index of group judgment would be satisfied when that of individual is acceptable. The group inconsistency index comes to 0.0 limitation when all individuals are consensus and consistent.

In accordance to the result of assessment of the overall linkage, the first priority is gained by the University-Industry linkage, second by Industry-GRI and the last one by GRI-

58

University linkage. In the types of linkages, Research Contract is the most prominent, followed by Training Activities, Sponsored Research and Provision of Services.

In the result of assessment of individual University-Industry linkage, the strength of the cooperation is mainly determined by magnitude of flow from University to Industry. Human resource is the most important "product" Industry demands from University. On the other side, money is the essential need for University to satisfy its R&D activities. Training Activities is the most preferred alternative both parties want to cooperate.

The result of assessment of Industry-GRI linkage shows that the strength of the cooperation is mostly determined by magnitude of flow from GRI to Industry. From the viewpoint of Industry, information is the most valuable benefit GRI can provide for Industry. On the GRI side, it found that Industry would be the substitute player of government in supporting financial source for R&D activities. Thus, Sponsored Research and Research Contract is the highest priority both side consider in technological cooperation.

In the linkage between GRI and University, the result indicates that almost cooperative programs between these two units are in terms of education-oriented activities. The common linkage activities are staff transfer and training. The result of experts' choice shows that the strength of the linkage is determined by equal magnitude of flow in this linkage and the most dominant factor is Human Interactions and Facility Utilization.

9.3Recommendations

9.3.1 Overall University-Industry-GRI Cooperation

Assessment of the strength the overall linkages in the Innovation Triangle is to determine which linkage is relative more important among the three links, namely University-Industry, Industry-GRI, and GRI-University. The final result for the judgments of the linkage alternatives shows that University and Food Industry have the strongest interaction as shown in Figure I.14. Therefore, it is necessary for policy maker to pay more attention on the linkage between University and Food Industry. The linkage between University and GRI is assigned the lowest rank that urges policy maker to revise the current structure of innovation. In both linkages with University and GRI, Industry always has less enthusiasm in initially building cooperation. These findings suggest that to strengthen the linkages, Industry should be the first one in actively taking initiative for establishing the linkage.

9.3.2 University-Industry Linkage

University should concentrate more attention on developing its faculty staff and providing reliable information and good quality of services as well as more relevant preparation for graduates about to enter industry. University should shift their emphasis away from traditional basic research to applied research directed toward more immediate practical implementation in order to suit more relevant R&D results for industry. On the Industry side, it should view University as a training center for their future human resource. They should not only recruit university students with out any reimbursement for training expenditure, but also has to long term invest in training activities by sending their engineers and workers and by giving fellowships and sponsorships to the university. Industry-University collaborative programs should be established with a clear understanding by both parties in which the mutual trust and appreciation are of the utmost importance for developing the linkage between these two units.

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9.3.3 GRI-University Linkage

The missing of almost research cooperation suggests that the linkage between the two units is so weak that they should not depend on the sponsor from government and should positively speed up the cooperative linkage in terms of joint R&D project to tap technological advantage of each other.

9.3.4 Industry-GRI Linkage

In order to maintain and strengthen the linkage, GRI should pay more attention on disseminating information and developing a competent staff including researchers and engineers. GRI should play an essential role in providing reliable and valuable information for Food Industry. On the other hand, GRI should keep in mind that its R&D cost should be cheap and quality of R&D result should be high. On the Industry side, industrial partner should be more tolerant in financing R&D projects in GRI and top management should more appreciate the technological linkage as an important engine for their development. Besides, both parties should concentrate more on provision of services and training activities that are cheapest ways in disseminating technology.

9.4Further Research Direction

Due to difficulty of collecting reliable data and time constraints, this study covers only food-processing industry of the Vietnamese production sector. Besides, secondary data was collected on some typical units in the food-processing industry. Thus, it is recommended that the model should be extended to the other industry and also to the nationwide production sector.

The research study just explores the assessment of the strength of University-Industry-GRI cooperation under the perspective from each unit. However, the survival of these linkages depends on not only each unit itself but also technology infrastructure (mentor, promoter, etc) of the country. Therefore, another research should be conducted to assess the strength of the Nation's technology infrastructure.

The proposed research study only applies one of methodologies to assess the linkages between R&D units and a specific industry. There are other available methods such as Delphi, critical (minimum) mass, successful factors, etc. Thus, the study would be more meaningful when combined with other methods.

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Appendix

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