The Study of Key Success Factors for Transformation of Agricultural Biotechnology Industry in Taiwan Applies Fuzzy Theory and View of Value Chain Meng-Shiunn Lee, Associate Professor, Department of Business Administration, Chang Jung Christian University Jui-Ying Hung, Doctor Candidate, Business and Operations Management Graduate School, Chang Jung Christian University ABSTRACT The biotechnology industry currently is developing rapidly and expanding into multitudinous fields. Consequently, this investigation examines the case of the Taiwanese biotechnology industry to understand how different strategies can be applied by industries to create competitive advantage. This study performs the value chain construct (Porter, 1985) to devise concept indicators, and implements the Fuzzy Delphi Method expert questionnaire (FDM) for drafting strategic hierarchy structure. Next, this study uses the Fuzzy Analytic Hierarchy Process (FAHP) to derive the key success factors for biotechnology industry competition advantages in Taiwan. Finally, this study treats the most important and critical development strategy of the biotechnology industry in Taiwan based on the research results. Keywords: Biotechnology Industry, Competitive Advantage, Strategy, Key Success Factors INTRODUCTION In view of that Watson and Crick(1953) found the DNA double helix structure, biotechnology industry gaze at all of the world behind the information technology industry in 21st. Oliver(2001)stand that economic and social problems will solve to utilize the biotechnology and neo-materials science. Altogether the biotechnology industry is not only the technology revolution, but also leads the whole world economy to create astronomic economic business opportunities and benefits. Consequently, the biotechnology apply the agriculture fields attach importance gradually. Taiwan builds up from agriculture in early stage and obtains whole worlds affirm in breeding and improving the production of crop effectively. Nevertheless the agriculture in Taiwan faced with import pressure accelerated since join the World Trade Organization(WTO)2002. Consequently, the government employs the agriculture biotechnology to promote the competitions of agricultural in Taiwan. On the other hand, the estimation point out that the capacity of insecticides decrease, the yield advance and the cost of production reduce because of gene transaction in American agricultural based on the National center for Food and Agricultural Policy. Therefore, it will promote the applications and economic effective of agricultural in Taiwan if use the biotechnology to reform crop and exploit other purpose. The application of global oncoming biotechnology let the agriculture, medicine, food and green etc., integrate, application field of agricultural actions expand to achieve newly industry. And that these new technology, new application bring extensive development and profound effect on the basis of the economic value from biotechnology. The era of knowledge economy emphasize the positive effect of knowledge creation added-value and currency in technology development and industry extension. This shift of economic development is not only in high technology industry, but also in agricultural which protect in national policy. That will bring unprecedented opportunity in Taiwan s agricultural biotechnology if advance development between cross-field and non-cross field in agricultural biotechnology. In conclusion, this research aim at agricultural biotechnology industry and apply the viewpoint of value chain (Porter,1985)to integrate numerous scholars suggestions in agricultural biotechnology, then extract the key success factors to form concrete development policies in order that effect the agricultural biotechnology development in Taiwan. Furthermore, these differences between cross-field transaction and non-cross field transaction will provide the industrial circles and government departments to consult.
This research uses the concepts of the fuzzy theory fuzzy Delphi method and fuzzy analytic hierarchical method as the analysis methods of the research. Then, the key success factors for transformation of agricultural biotechnology industry in Taiwan are filtered out. During the first stage, the fuzzy Delphi expert questionnaires are distributed to determine the group opinion of experts and scholars, as well as to establish the research framework and the various evaluation factors. During the second stage, fuzzy analytic hierarchical process expert questionnaires are administered to derive the weighted relationship between the various dimensions and the evaluation indicators. Finally, the key success factors for transformation of agricultural biotechnology industry in Taiwan are selected based on the research findings. LITERATURE REVIEW Agricultural biotechnology industry development in Taiwan Agricultural biotechnology is perform modern gene-engineering technology to add or omit some specific gene to obtain ideal situation, such as increase production, resist insect pest, bear unhealthy environment(drought-enduring, salty-enduring, cold-resistant)and advance nutrition components. Agricultural biotechnology apply in two industrial fields:the first field is combined the traditional breeding, examining, farming, epidemic prevention, fertilize and insecticides to upgrade output and quality of traditional agricultural;the second field is combined the application of newly biotechnology with agricultural, medicine, food and green gradually. According to the statement in White Paper of Biotechnology Industry in Taiwan(2006)that biotechnology apply in many fields and dispersal in agricultural, green and food industry. On the other hand, it will separate traditional Chinese medicine and biotechnology pharmacy from materials. The Council of Agricultural Executive Yuan divided agricultural biotechnology in Taiwan into 7 categories that accord to industrial characteristics and final productions, as (1)plant vaccine biotechnology,(2)aquatic products breeding biotechnology,(3)cattle and fowl biotechnology, (4)animal vaccine,(5)food biotechnology,(6)organism fertilize and(7)organism insecticide. Key success factor in enterprise transformation There are three key elements that the key success factor in enterprise transformation: people business aspects of macro competitiveness and financial resource (e.g., Bibeault 1982). Chen (1990) address the key success factor in transformation including industry trend analyze and control, relative specialized knowledge in upper and lower industry, good interpersonal relationship, successful capital management. Otherwise, it use FMCDM(Sun et. al, 2005and experts meeting to condense specialists suggestions and common sense to decide agricultural biotechnology potential products aspects that adaptive development in Taiwan. Then based on the result to dispose resource and make strategy. As the result reveal, the first condition is marketing channel capability and research innovation capability under the industrial capability that target industry with national competition; the second condition is relative regulations/prove completely and industry policy support from government under the policy and rule concept. Furthermore, Lee, Liu, Ting and Lin (2007)based on Porter s value chain viewpoint(1985) to indicate that key success factor in biotechnology industry in Taiwan as manufactured R&D innovation ability, manufactured quality control ability, product commercialization ability, technology R&D and innovation ability, technology R&D people quality nurturing ability and executive managers characteristics. Value chain Porter (1985) further pointed out that the competitive advantage originating from the value created by the enterprise for the clients, and the basic tool with which the enterprise would diagnose the competitive advantage and seek the improvement was the value chain model, as illustrated in Figure 1. As shown in the figure, the overall value presented by the value chain is composed of various value activities and margin. The so-called value activities refer to the detailed activities that are conducted on the layers of material and technique by the enterprise, and also the foundation for the enterprise to create valuable products for the clients.
Figure 1: Value chain Generally, industrial value chain will different from industry. But enterprises separate from their allocation with value chain activities, understand the added value proportions and determine the value chain position presently under industrial value chain. On the other hand, whether the value chain integrate vertical to interfere value chain and get the right added value. Altogether, it might hold trend and confront inner/outer environment change to hold together competition when agricultural biotechnology carry transformation out. Based on the upon literature result, it arrange some possible key success factors which effect agricultural biotechnology industry transformation and use as the viewpoint from Porter(1985) to analyze unique and excellent competitive advantages for considerate basis in transformation. Therefore, it develops the key success factor measure concepts in transformation: inbound & outbound logistic operations marketing & sales service human resource technology development and procurement & firm infrastructure(figure 2). Figure 2: key success factor measure concepts in agricultural biotechnology industry transformation based on value chain Key success factor(ksf) Daniel (1961) thinks that key success factors refer to important tasks that a business must do very well in order to succeed. These key areas are the key success factors. If a business wishes to sustain its growth, it needs to put more effort into managing these few key areas. Otherwise, it would be unable to achieve the expected goals. Boynton and Zmud (1984) point out that key success factors are matters that managers or businesses need to pay special and continuous attention to if they wish to succeed or obtain excellent results. This definition includes the key factors of the business s current and future operations and activities. This will enable business management to be more forward-looking and give a positive meaning to strategic planning. Hofer and Schendel(1985)indicate that key success factor is a flock of variables what managers counter with them affecting their competitive position in whole industry. Then, these key success factors separate from macro-environment, industry environment and enterprise three different levels and seven strategic planning processes.
Key success factors will vary with the stage of the industry and the market. Therefore, business managers have to first identify the key success factors of the industry and invest the limited resources of the business on the key areas to build up the competitive advantage of the business. Generally, factor analysis, Delphi method, case study, and analytic hierarchical process can be used in the selection of key success factors (Saaty, 1980; Bullen and Rockart, 1981; Hofer and Schendel, 1985; He 1990). Because this research uses questionnaire surveys of experts and also due to the shortcomings of the traditional Delphi method and the analytic hierarchical process such as ambiguity in judgments, average, similarity in decision attributes, group decision, and inaccuracy(hwang and Lin, 1987;Hsu, 1998), this research uses fuzzy Delphi method and fuzzy analytic hierarchical process in fuzzy theory as the methodology for data analysis. This solves the problem of ambiguity produced in the process of measuring and evaluating criteria and accurately selects the key success factors for improving the competitive advantage of Taiwan s biotechnology industry transformation. RESEARCH METHOD Hierarchical Framework Taking into account the inputs from the literature review in section II and also using Porter (1985) s concept of value chain, this research establishes the preliminary hierarchical framework for the key success factors for transformation of agricultural biotechnology industry in Taiwan. This is used as the basis for the fuzzy Delphi questionnaire design and for selecting the evaluation criteria to facilitate subsequent empirical research. The final objective in the framework is the key success factors for transformation of agricultural biotechnology industry in Taiwan. The framework is then divided into three hierarchies, namely the main, secondary goals and 30 evaluation items. Research Target This research uses twice extending expert questionnaires as the basis for research analysis. The targets for the questionnaire survey are respondents who able to accept this type of questionnaire, respondents who have sufficient knowledge of the research question, and respondents who able to suit the schedule of the survey. The number of experts required for group decision-making problem is 5 to 7 according to Robbins (1994). However, this research bases on the database from agricultural biotechnology industry information net which set of biotechnology center in Taiwan to obtain objective and accurately measurement concepts. At the first stage it distributes 18 sets from operators and specialists in upon 7 fields of agricultural biotechnology industry of fuzzy Delphi expert questionnaires and effective questionnaire returned is 14. After that, it reports 16 survey targets for the fuzzy analytic hierarchical process expert questionnaires in the second stage who selected based on judgment sampling and effective questionnaire returned is 14. DATA ANALYSIS Select evaluation criteria- apply Fuzzy Delphi Method The threshold value calculated from the fuzzy Delphi method and EXCEL, separate from cross-domain and non-cross-domain are7.4 & 7.1. Based on the result, there are 7 evaluation criteria eliminated and keep 23 evaluation criteria as the possible success factors (comprising76.67% of the total number of evaluation criteria) in cross-domain section. On the other hand, there are 10 evaluation criteria eliminated and keep 20 evaluation criteria as the possible success factors (comprising 66.67% of the total number of evaluation criteria) in non-cross-domain section.based on the above selection results, this research builds the strategic hierarchical framework of success factors that might affect the competitive advantage of biotechnology industry transformation in cross-domain and non-cross-domain (Figure 3 and Figure 4).
Extract key success factor- apply Fuzzy Hierarchy analysis method Based on the calculation method of the fuzzy analytic hierarchical process described above, and use EXCEL to deal with the expert questionnaires in stage two. First, the fuzzy positive reciprocal matrix is built using triangular fuzzy numbers as the basis for calculating the fuzzy weights. Next, based on the crisp values determined by the experts, consistency test on the matrix is conducted. The results indicate transformation between cross-domain and non-cross-domain that the C.I. and C.R. are both 0.1.This satisfies the acceptable limits of bias suggested by Saaty (1980), and indicate that expert opinions and judgments are consistent across all levels. In addition, looking from whole evaluation and analysis, the overall consistency ratio (C.R.H.) for transformation of cross-domain and non-cross-domain are 0.08 and 0.04, and this satisfies limit C.R.H<0.1, indicating that the configuration of the correlation between the hierarchies in the hierarchical framework built by this research is appropriate. Therefore, the hierarchical weight of each evaluation factor in its hierarchy can be analyzed their relative weights of the various factors in each hierarchy are calculated (also called local priority ). In addition, to understand the weight ratio of each hierarchical factor in the overall framework, global priority is further calculated. Finally, the results base on the absolute weights to precede synthetic value of priority ranking each hierarchy under the main goal of the success factors in agricultural biotechnology industry for transformation of cross-domain and non-cross domain ( table 1 and table 2). Figure 3: hierarchy structures of probably key success factor in cross-domain agricultural biotechnology industry transformation
Figure 4: hierarchy structures of probably key success factor in non-cross-domain agricultural biotechnology industry transformation Key success factor in cross-domain and non cross-domain transformation in agricultural biotechnology industry From the last column importance range in Table 1 learn that experts assume the key success factor of cross-domain transformation of 23 criteria items in the third level. With regard to the number of key success factors, this research consults the viewpoint of Daniel (1961) on key success factors in Management Information Crisis : Most industries usually have 3 to 6 key factors that underpin success. Therefore, this research selects the top six factors in the last column of table 1, importance ordering, as the success factors for transformation in cross-domain agricultural biotechnology industry. In order of their importance, they are Stable materials source, Control market need trend, Possessed new-type manufacturing equipment, Supporting capability from upper and lower industry, Integrated top middle and downstream manpower and Marketing promotion capability. From the last column importance range in Table 2 learn that experts assume the key success factor of non-cross domain transformation of 20 criteria items in the third level. With regard to the number of key success factors, this research consults the viewpoint of Daniel (1961) on key success factors in Management Information Crisis : Most industries usually have 3 to 6 key factors that underpin success. Therefore, this research selects the top six factors in the last column of table 6, importance ordering, as the success factors for transformation in non-cross domain agricultural biotechnology industry. In order of their importance, they are Build product technology system capability, Control intellectual property right capability, Integrity education system, Risk management of new product development, Nurture capability in technology, R&D members quality and Establish relative ordinance and rule.
Table 1: Weight analysis and importance range from cross-domain transformation KSFs The first hierarchy The second hierarchy The third hierarchy Criteria concept weight principle Inbound & outbound Logistics Primary activities Supported actives 0.5979 Operations Hierarchy weight Absolutely Importance weight range 0.2870 0.1716 4 0.4031 0.2410 1 Marketing & Sales Service 0.3099 0.1853 3 Technology development 0.4938 0.1985 2 0.4021 Human resource 0.3065 0.1233 5 Procurement & firm infrastructure Source: Sorted out by this research 0.1997 0.0803 6 Criteria principle Hierarchy Absolutely Importance weight weight range stable materials source 0.7739 0.1328 1 materials and manufactured goods storehouse management 0.2261 0.0388 15 Possessed new-type manufacturing equipment 0.2346 0.0566 3 Manufactured cycle shorten capability 0.1842 0.0444 8 Supporting capability from upper and lower industry 0.2244 0.0541 4 Customer-orientation products manufactured capability 0.1738 0.0419 11 Manufactured process quality and cost control capability 0.1830 0.0441 9 Marketing promotion capability 0.2652 0.0491 6 Control market need trend 0.3403 0.0631 2 Laid distribution channels capability 0.2254 0.0418 12 Product service after-selling capability 0.1691 0.0313 18 Control intellectual property right capability 0.1378 0.0274 19 Control key technology capability 0.2376 0.0472 7 Innovation applied and knowledge integrated 0.2016 0.0400 14 Build product technology system capability 0.2182 0.0433 10 Risk management of new product development 0.2048 0.0407 13 Integrity education system 0.3048 0.0376 16 Integrated top middle and downstream manpower 0.4368 0.0538 5 Nurture capability in technology R&D members quality 0.2584 0.0318 17 Capital accommodation capability 0.2230 0.0179 23 Establish relative ordinance and rule 0.2299 0.0185 22 Obtain biotechnology infrastructure capability 0.2422 0.0194 21 Build excellent policy of product proved system 0.3049 0.0245 20 Table 2: Weight analysis and importance range from non-cross domain transformation KSFs The first hierarchy The second hierarchy The third hierarchy Criteria Hierarchy Absolutely Importance Hierarchy Absolutely Importance concept weight Criteria principle principle weight weight range weight weight range Inbound & transportation management 0.2226 0.0140 19 outbound 0.3094 0.0631 5 order schedule planning capability 0.4249 0.0268 9 Logistics Materials stock control capability 0.3526 0.0222 10 Primary activities Supported actives 0.2038 0.7962 Operations Source: Sorted out by this research 0.2770 0.0565 6 Marketing & Sales Service 0.4136 0.0843 4 Technology development Human resource 0.5419 0.4314 1 0.2893 0.2303 2 Procurement & firm infrastructure 0.1688 0.1344 3 Possessed new-type manufacturing equipment 0.2535 0.0143 18 Supporting capability from upper and lower industry 0.3702 0.0209 12 Customer-orientation products manufactured capability 0.3763 0.0212 11 Marketing promotion capability 0.2034 0.0171 16 Control market need trend 0.2240 0.0189 14 Control product life cycle 0.2020 0.0170 17 Laid distribution channels capability 0.1243 0.0105 20 Product service after-selling capability 0.2462 0.0208 13 Control intellectual property right capability 0.3507 0.1513 2 Build product technology system capability 0.3679 0.1587 1 Risk management of new product development 0.2813 0.1214 4 Integrity education system 0.5942 0.1369 3 Nurture capability in technology R&D members quality 0.4058 0.0935 5 Government encouragement act 0.1347 0.0181 15 Capital accommodation capability 0.2925 0.0393 7 Establish relative ordinance and rule 0.3124 0.0420 6 Obtain biotechnology infrastructure capability 0.2604 0.350 8
CONCLUSION AND SUGGESTION This research through literature review edification and perform the Porte s(1985) viewpoint of value chain to draw up 30 potential success factors in agricultural biotechnology industry of cross-domain and non-cross domain transformation. Then, it builds elementary hierarchy structure to carry follow-up practical research out. It applies dual-triangular fuzzy number of fuzzy Delphi method subsequently to sieve criteria principles out. After sieving it retain 23 and 20 potential key success factors for transformation of cross-domain and non-cross-domain industry individually. Finally, key success factors sequence from cross-domain transformation by fuzzy hierarchy analysis method being stable materials source, control market need trend, possessed new-type manufacturing equipment, supporting capability from upper and lower industry, integrated top, middle and downstream manpower and marketing promotion capability. On the other hand, key success factors sequence from non-cross-domain transformation is build product technology system capability, control intellectual property right capability, integrity education system, risk management of new product development, nurture capability in technology, R&D members quality and establish relative ordinance and rule. It might respect the key success factors for transformation previously when agricultural biotechnology industry of cross-domain and non-cross-domain. Therefore, it will well for managers establish effective strategy planning and process enforcing. Even then the manager reach the decided goals effect and obtain persistence competition advantages in enterprise competitive environment. Agricultural biotechnology industry is the target in this research, including breeding sensing cultivating prevention fertilize insecticides and food. But it will suggest researchers aim at different fields to analyze the difference between each others key success factors when it transformation. REFERENCES Bibeault, B. D. (1982), Corporate Turnaround: How Managers Turn Losers into Winners, Boston: McGraw-Hill Book Company. Boynton & Zmud(1984), An Assessment of CriticalSuccess Factor, Sloan Management Review.Summer, pp.19-21. Bullen, V. L. & J. F.Rockart (1981), A Primer on Critical Success Factors, CISRND, 69. Daniel, D.R.(1961). Management Information Crisis. Harvard Business Review. 39(5):111-121. Hofer & Schendel (1985), Strategic Management and Strategic Marketing: What s Strategic About Either One?, New York: John Wiley and Sons. Lee, M.S., & Lu, S.I. (2006). The Study of Key Success Factors for Cross-domain Transformation of Agricultural Biotechnology Industry in Taiwan Applying view of value chain. Journal for SME Development. 2:53-87. Porter, M. E. (1985), Competitive Advantage, New York: The Free Press. Saaty, T. L., Rogers, P.C. & Pell, R. (1980), Portfolio Selection Through Hierarchies, Journal of Portfolio Management, pp.16-22. Sun, J.L., & Tsou, S.S. (2005). The Strategic Planning Science and Technology Program for Agricultural Biotechnology. Biotechnology Industry Study Centre.