International Journal of Information Engineering and Applications  
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Fuzzy Analytical Hierarchy Process Analysis for Evaluation of Impact Factors for Knowledge Hub
International Journal of Information Engineering and Applications
Vol.1 , No. 3, Publication Date: Aug. 2, 2018, Page: 132-144
1627 Views Since August 2, 2018, 319 Downloads Since Aug. 2, 2018
 
 
Authors
 
[1]    

James K. C. Chen, Department of Business Administration, College of Management, Asia University, Taichung, Taiwan R.O.C..

[2]    

Batchuluun Amrita, Department of Business Administration, College of Management, Asia University, Taichung, Taiwan R.O.C..

 
Abstract
 

This research evaluates key factors of Knowledge Hub comparing Silicon Valley of the United States, Hsinchu Science Park of Taiwan and National Information Technology Park of Mongolia. Accordingly, it determined the best matching factors of KH in developed and developing countries. This paper used 1) Analytical hierarchy process (AHP), and 2) Fuzzy analytical hierarchy process (FAHP). A total of 99 experts responded to the questionnaire from three countries. Result shows that innovation performance is the most important factor for KH by AHP method in both developed and developing countries. However, in accordance with FAHP analysis, absorptive capacity and learning environment are the most important factor for developed countries and regional development for the developing country. Consequently, KH becomes a cost effective and intermediary platform for academicians and entrepreneurs in developing countries, if they focus on absorptive capacity and learning environment to maintain regional development in the long–term.


Keywords
 

Knowledge Hub, Regional Development, Technology Knowledge, Innovation Performance, Absorptive Capacity, Learning Environment, FAHP


Reference
 
[01]    

Andersson, U., Dasi, A., Mudambi, R. & Pedersen, T. (2015). Technology, innovation and knowledge: The importance of ideas and international connectivity. Journal of World Business, 51 (1): 153-162. http://dx.doi.org/10.1016/j.jwb.2015.08.017.

[02]    

Audretsch, D. B. & Lehmann, E. E. (2005). Does the knowledge spillover theory of entrepreneurship hold for regions? Research Policy, 34 (8): 1191-1202.

[03]    

Badarch, D. (2004). Promoting business and technology incubation for improved competitiveness of small and medium – sized industries through application of modern and efficient technologies in Mongolia. United Nations Economic and Social Commission for Asia and the Pacific (ESCAP), 265-285.

[04]    

Callaert, J., Vervenne, J. B., Looy, B. V., Magermans, T., Song, X. & Jeuris, W. (2014). Patterns of Science – Technology Linkage. European Union: Luxembourg.

[05]    

Carayannis, E. G., Popescu, D., Sipp, C. & Stewart, McD. (2006). Technological learning for entrepreneurial development (TL4ED) in the knowledge economy (KE). Case studies and lessons learned. Technovation, 26 (4): 419-443.

[06]    

Casper, S. (2013). The spill-over theory reversed: The impact of regional economies on the commercialization of university science. Research Policy, 42 (8): 1313-1324.

[07]    

Chang, C. W., Wu, C. R. & Lin, H. L. (2009). Applying fuzzy hierarchy multiple attributes to construct an expert decision making process. Systems with Applications, 36 (4): 7363-7368. doi: 10.1016/j.eswa.2008.09.026.

[08]    

Chen, C. J., Wu, H. L., & Lin, B. W. (2006). Evaluating the development of high – tech industries: Taiwan’s science park. Technological Forecasting & Social Change, 73 (4): 452-465. doi: 10.1016/j.techfore.2005.04.003.

[09]    

Chen, Y. H., Lin, T. P., & Yen, D. C. (2014). How to facilitate inter-organizational knowledge sharing: The impact of trust. Information & Management, 51 (5): 568-578.

[10]    

Chyi, Y. L., Lai, Y. M. & Li, W. H. (2012). Knowledge spillovers and firm performance in the high-technology industrial cluster. Research Policy, 41 (3): 556-564.

[11]    

Cohen, W. & Levinthal, D. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35 (1): 128-152.

[12]    

Domenech, J., Escamilla, R., & Roig-Tierno, N. (2015). Explaining knowledge-intensive activities from a regional perspective. Journal of Business Research, 69 (4): 1301-1306.

[13]    

Etzkowitz, H., Webster, A., Gebhardt, C. h. & Terra, B. R. C. (2000). The future of the university and the university of the future: evolution of ivory tower to entrepreneurial paradigm. Research Policy, 29 (2000): 313-330.

[14]    

Erensal, Y. C., Oncan, T. & Demircan, M. L. (2006). Determining key capabilities in technology management using fuzzy analytic hierarchy process: A case study of Turkey. Information Sciences, 176 (18): 2755-2770. doi: 10.1016/j.ins.2005.11.004.

[15]    

Ewers, M. C. (2013). From knowledge transfer to learning: The acquisition and assimilation of human capital in the United Arab Emirates and the other Gulf States. Geoforum, 46 (May): 124-137. doi: 10.1016/j.geoforum.2012.12.019.

[16]    

Felsenstein, D. (1994). University – related science parks –‘seedbeds’ or ‘enclaves’ of innovation. Technovation, 14 (2): 93-110. DOI: 10.1016/0166-4972(94)90099-X.

[17]    

Fu, X., Pietrobelli, C. & Soete, L. (2011). The role of foreign technology and indigenous innovation in the emerging economies: Technological change and catching-up. World Development, 39 (7): 1204-1212. doi: 10.1016/j.worlddev.2010.05.009.

[18]    

Guo, B. & Guo, J. J. (2011). Patterns of technological learning with in the knowledge systems of industrial clusters in emerging economies: Evidence from China. Technovation, 31 (2-3): 87-104. doi: 10.1016/j.technovation.2010.10.006.

[19]    

Hallin, C. & Holmstrom Lind, C. (2012). Revisiting the external impact of MNCs: An empirical study of the mechanisms behind knowledge spillovers from MNC subsidiaries. International Business Review, 21 (2): 167-179. doi: 10.1016/j.ibusrev.2010.12.003.

[20]    

Harbi, S., Amamou, M. & Anderson, A. (2009). Establishing high-tech industry: the Tunisia ICT experience. Tecnovation, 29 (6-7): 465-480. doi: 10.1016/j.technovation.2008.11.001.

[21]    

Hsieh, H. N., Hu, T. Sh., Chia, P. Ch., & Liu, Ch. Ch. (2014). Knowledge patterns and spatial dynamics of industrial districts in knowledge cities: Hsinchu, Taiwan. Expert Systems and Applications, 41 (12): 5587- 5596. doi: 10.1016/j.eswa.2014.02.009.

[22]    

Hsinchu Science Park. (2015). An introduction to the Hsinchu Science Park. Retrieved from http://www.sipa.gov.tw/english/home.jsp

[23]    

Huang, C. C. & Chu, P. Y. (2011). Using the fuzzy analytic network process for selecting technology R&D projects. International Journal of Technology Management, 53 (1): 89-115. http://dx.doi.org/10.1504/IJTM.2011.037239

[24]    

Iammarino, S. & McCannc, P. h. (2006). The structure and evolution of industrial clusters: Transactions, technology and knowledge spillover. Research Policy, 35 (7): 1018-1036.

[25]    

Isaak, R. (2009). From collective learning to Silicon Valley replication: The limits to synergistic entrepreneurship in Sophia Antipolis. Research in International Business and Finance, 23 (2): 134-143. doi: 10.1016/j.ribaf.2008.03.006.

[26]    

Lai, H. C. & Shyu, J. Z. (2005). A comparison of innovation capacity at science parks across the Taiwan Strait: the case of Zhangjiang High-Tech Park and Hsinchu Science-based Industrial Park. Technovation, 25 (7): 805-813.

[27]    

Lau, A. K. W. & Lo, W. (2015). Regional innovation system, absorptive capacity and innovation performance: An empirical study. Technological Forecasting & Social Change, 92 (March): 99-114.

[28]    

Lee, J., Park, J. G. & Lee, S. (2015). Raising team social capital with knowledge and communication in information systems development projects. International Journal of Project Management, 33 (4): 797-807.

[29]    

Leisyte, L. (2011). University commercialization policies and their implementation in the Netherlands and the United States. Science and Public Policy, 38 (6): 437-448.

[30]    

Lin, S. h. (2015). Are ivory towers truly ivory? Knowledge spillovers and firm innovation. Journal of Economics and Business, 80 (July-Aug): 21-36.

[31]    

Martin–de Castro, G. (2015). Knowledge management and innovation in knowledge-based and high-tech industrial markets: The role of openness and absorptive capacity. Industrial Marketing Management, 47 (May): 143-146.

[32]    

Martini, L., Tjakraatmadja, J. H., Anggoro, Y., Pritasari, A. & Hutapea, L. (2012). Triple Helix Collaboration to Develop Economic Corridors as Knowledge Hub in Indonesia. Procedia – Social and Behavioral Sciences 52 (2012): 130-139.

[33]    

Mattar, Y. (2008). Post-industrialism and Silicon Valley as models of industrial governance in Australian public policy. Telematics and Informatics, 25 (4): 246-261.

[34]    

Mikhailov, L. (2002). Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega, 30 (5): 393-401. doi: 10.1016/S0305-0483(02)00052-X.

[35]    

National Information Technology Park of Mongolia. (2015). Introduction and activities. Retrieved from: http://itpark.mn/eng/?page_id=13.

[36]    

OECD (Organization for Economic Cooperation and Development). (2010). The OECD innovation strategy: getting a head start on tomorrow. Executive summary: 9-15.

[37]    

Ooms, W., Werker, C., Caniëls, M. C. J. & Bosch, H (2015). Research orientation and agglomeration: Can every region become a Silicon Valley? Technovation, 45-46 (November-December): 78-92.

[38]    

Park, B. I. (2011). Knowledge transfer capacity of multinational enterprises and technology acquisition in international joint ventures. International Business Review, 20 (1): 75-87.

[39]    

Perkmann, M., Neely, A. & Walsh, K. (2011). How should firms evaluate success in university- industry alliances? A performance measurement system. R&D Management, 41 (2): 202–216. doi: 10.1111/j.1467-9310.2011.00637.x.

[40]    

Ruismäki, H., Salomaa, R. L. & Ruokonen, I. (2015). Minerva Plaza - a new technology-rich learning environment. Procedia - Social and Behavioral Sciences, 171 (January): 968 – 981. doi: 10.1016/j.sbspro.2015.01.216.

[41]    

Saaty, R. W. (1980). “The Analytic Hierarchy Process.” McGraw-Hill, New York.

[42]    

Saaty, R. W. (1986). The Analytical hierarchy process - what it is and how it is used. Mathematical modelling, 9 (3-5): 161-176. doi: 10.1016/0270-0255(87)90473-8.

[43]    

Saaty, R. W. (1990). How to make a decision: The Analytical Hierarchy process. European Journal of Operational research, 48 (1): 9-26. doi: 10.1016/0377-2217(90)90057-I.

[44]    

Saaty, R. W. (1994). How to make a decision: the analytic hierarchy process. Interfaces, 24 (6): 19–43. http://dx.doi.org/10.1287/inte.24.6.19.

[45]    

Saxenian, A. & Hsu, J. Y. (2001). The Silicon Valley –Hsinchu connection: Technical Communities and Industrial upgrading. Industrial and Corporate Change, 10 (4): 893-920. doi: 10.1093/icc/10.4.893.

[46]    

Schmidt, S. (2015). Balancing the spatial localization ‘Tilt’: Knowledge spillovers in process of knowledge intensive services. Geoforum, 65 (October), 374-386.

[47]    

Seppanen, R., Blomqvist, K. & Sundqvist, S. (2007). Measuring inter-organizational trust—a critical review of the empirical research in 1990–2003. Industrial Marketing Management, 36 (2): 249-265. doi: 10.1016/j.indmarman.2005.09.003.

[48]    

Tang, Y., Sun, H., Yao, Q., & Wang, Y. (2014). The selection of key technologies by the silicon photovoltaic industry based on the Delphi method and AHP (analytic hierarchy process): case study of China. Energy, 75: 474-482. doi: 10.1016/j.energy.2014.08.003.

[49]    

Tödtling, F., Lehner, P. & Kaufmann, A. (2009). Do different types of innovation rely on specific kind of knowledge interactions? Tecnovation, 9 (1): 59-71.

[50]    

Tzeng, G. H. & Huang, J. J. (2011). Multiple Attribute Decision Making: Methods and Applications. United States of America: CRC Press.

[51]    

Valtolina, S., Barricelli, B. R. & Dittrich, Y. (2012). Participatory knowledge-management design: A semiotic approach. Journal of Visual Languages and Computing, 23 (2): 103-115. doi: 10.1016/j.jvlc.2011.11.007.

[52]    

Van Geenhuizen, M. & Ye, Q. (2014). Responsible innovators: open networks on the way to sustainability transitions. Technological Forecasting & Social Change, 87 (September): 28-40. http://dx.doi.org/10.1016/j.techfore.2014.06.001.

[53]    

Van Wyk, R. J. (2010). Technology assessment for portfolio managers. Technovation, 30 (4): 223-228. doi: 10.1016/j.technovation.2009.06.005.

[54]    

Walker, R. M., Chen, J. & Aravind, D. (2015). Management innovation and firm performance: An integration of research findings. European Management Journal, 33 (5): 407-422. doi.org/10.1016/j.emj.2015.07.001.

[55]    

Wang, Y. M., & Chin, K. S. (2011). Fuzzy analytic hierarchy process: A logarithmic fuzzy preference programming methodology. International Journal of Approximate Reasoning, 52 (4): 541-553. doi: 10.1016/j.ijar.2010.12.004.

[56]    

Yang, C. H., Motohashi, K. & Chen, J. R. (2009). Are new technology – based firms located on science parks really more innovative? Evidence from Taiwan. Research Policy, 38 (1): 77-85. doi: 10.1016/j.respol.2008.09.001.

[57]    

Yingnan, D., Yuduo, L. & Xiongfei, Q. (2012). Spatial knowledge spillovers: New 3-Zone Interaction Engineering. Systems Engineering Procedia, 3 (2012): 307-311.

[58]    

Youtie, J. & Shapira, Ph. (2008). Building an innovation hub: A case study of the transformation of university roles in regional technological and economic development. Research Policy, 37 (8): 1188-1204. doi: 10.1016/j.respol.2008.04.012.

[59]    

Zadeh, A. (1965). Fuzzy sets. Information and control, 8: 338-353.

[60]    

Zahra, S. & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27 (2): 185-203.





 
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