تعیین شاخص های کلیدی انتخاب فناوری با استفاده از تکنیک ترکیبی دلفی فازی و فرایندتحلیل سلسله مراتبی فازی
محورهای موضوعی : مدیریت صنعتیMilad Aghaee 1 , Reza Aghaee 2 , Mostafa Memarzadeh 3
1 - Ph.D. student in industrial management, Allameh Tabatabaei University, Tehran, Iran
2 - MSC of executive business administration, industrial management institute
3 - MSC of industrial management, Lecturer at Allameh Majlesi
کلید واژه: تحلیل مسیر, Analytical Hierarchy Process (AHP), نوآوری استراتژیک, ظرفیت جذب, یادگیری تعمدی, key technology selection criteria, FUZZY Delphi and Police Organization,
چکیده مقاله :
پس از بررسی های صورت گرفته در ادبیات مرتبط با افزایش ظرفیت نوآوری استراتژیک در بنگاه های دانش بنیان مشخص شد که عمده تمرکز محققان بر فرایند و شبکه های دانشی می باشد و کمتر بر رویکردهای کلان و راهبردی سازمان تأکید می شود. ساختار مطالعات بررسی شده و اطلاعات زمینه ای، محققان را به تفسیر مجدد ظرفیت جذب در خلال یک دیدگاه شناختی وا می دارد و اظهار می کند که مکانیسم های فراگیر تعمدی می تواند عملکردهای خاص تشخیص مجدد، تلفیق و بهره برداری از روش های نوین جهت قیمت گذاری را تحت تأثیر قرار دهد. پس از تحلیل داده ها با استفاده از تکنیک معادلات ساختاری اثر مکانیسم های یادگیری تعمدی جهت به رسمیت شناختن بر ظرفیت نوآوری استراتژیک تأیید نشد اما اثر مثبت مکانیسم های یادگیری تعمدی جهت جذب و بهره برداران بر ظرفیت نوآوری استراتژیک مورد تأیید واقع شد.
Technology has been an important element in service and production in which we have faced a great growth in different technological aspects. Today, many organizations, especially police organizations have no choice expect using technology for increasing productivity and service quality. In this way, many resources like financial, human and time resources consume that effective utilization of resources and investments on suitable technology have an important role in the achievement of technology. Thus, current research is aimed to recognize effective criteria on technology selection in police organization and present a systematic model for prioritizing them by FUZZY Delphi and FUZZY AHP technique. TO do so, the population of this research is experts of technology field in police organization in which 10 people were selected. The findings of this research are as three initiatives: 1- prioritization of fundamental criteria using FUZZY Delphi, 2- the refined criteria showed that technology selection criteria are not just inter-organizational criteria, but it encompasses external organizational criteria and 3- effective factors on technology selection for development are not only financial criteria, and there are other criteria like politics problems in which effects on technology selection. On the other hand, based on research results, the ranking of selecting technology in police organizations are as below: political problems, economic attractiveness, strategic attractiveness, value creation, practicality and technical knowledge and learning.
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1- Ahmadi, A.(1998). Application of Delphi method in determining and priorities the organization's strategic goals. Fifth Conference on Industrial Engineering student.
2- Azar,A., Rajabzade, A.(2003). Applied Decision (MADM approach). Tehran: Negah Danesh Publication.
3- Khalil, T.(2008). Technology management. Tehran: Publications of Cultural Research Office.
4- Fathi Vajargah, K.(2003). Training Needs Assessment (Patterns and Techniques). Tehran: Aeezh Publication.
5- Nasirzade,GH.(2000). Technology in enterprise service. Tehran: Industrial Management Institute Publication.
6- Abetti, P. (1989). Linking Technology and Business Strategy. Amacom Books, 45-80.
7- Achilladelis, B., & Antonakis, N. (2001). The dynamics of technological innovation: the case of the pharmaceutical industry. Research Policy, 535-588.
8- Awazu, Y. (2006). Managing technology alliances: The case for knowledge management. International Journal of Information Management, 484-493.
9- Bayazit, O. (2005). Use of AHP in decision-making for flexible manufacturing systems. Journal of Manufacturing Technology Management, 16.
10- Bellman, R., & Zadeh, L. (1970). Decision-making in a fuzzy environment management. Science, 17, 141–164.
11- Brown, S., Dennis, A., & Venkatesh, V. (2010). Predicting Collaboration Technology Use: Integrating Technology Adoption and Collaboration Research. Journal of Management Information Systems, 9-53.
12- Cantwell, J. (1992). The internalization of technological activity and its implications for competitiveness, in: O. Grandstrand, L. HakanSon, S. Sjolander (Eds.), Technology Management and International Business: Internationalisation of R&D and Technology. New York: Wiley.
13- Carlson, J., & Zmud, R. (1999). Channel expansion theory and the experiential nature of media richness perceptions. Academy of Management Journal, 153-170.
14- Chiesa, V. (1998). R&D Strategy and Organization. Series on Technology Management, 107-188.
15- Chiesa, V.; Manzini, R.; Tecilla, F. (2000). Selecting Sourcing Strategies for Technological Innovation. International Journal of Operations & Production Management, 1017-1037.
16- Choudhury, A., Shankar, R., & Tiwari, M. (2006). Consensus-based intelligent group decision-making model for the selection of advanced technology. Decision Support Systems 42, 1776– 1799.
17- Coldrick, S., Longhurst, P., Ivey, P., & Hannis, J. (2005). An R&D options selection model for investment decisions. Technovation, 185-193.
18- Da Silveira, G., & Cagliano, R. (2006). The relationship between interorganizational information systems and operations performance. International Journal of Operations & Production Management, 232-281.
19- Daft, L. (2006). The New Era of Management. International Student Edition.
20- Daft, R., & Lengel, R. (1986). Organizational information requirements, media richness and structural design. Management Science, 554-571.
21- Daim, T., & Kocaoglu, D. (2008). Exploring technology acquisition in Oregon, Turkey and in the U.S. electronics manufacturing companies. Journal of High Technology Management Research, 45-58.
22- Dussauge, P., Hart, S., & Ramanatsoa, B. (1992). Strategic technology management. New York: Wiley.
23- Erensal, Y., Oncan, T., & Demircan, M. (2006). Determining key capabilities in technology management using fuzzy analytical hierarchy process: A case study of Turkey. Information Sciences, 2755-2770.
24- Evans, A., Strezov, V., & Evans, T. (2009). Assessment of sustainability indicators for renewable energy technologies. Renewable and Sustainable Energy Reviews, 1082-1088.
25- Farooq, S., & O’Brien, C. (2010). Risk calculations in the manufacturing technology selection process. Journal of Manufacturing Technology Management, 28-49.
26- Gimenez, G. (2006). Investment in new technology: modeling the decision process. Technovation, 345-350.
27- Granstrand, O. (2004). The economics and management of technology trade: Towards a pro-licensing era? International Journal of Technology Management, 209-240.
28- Gregory, M. (1995). Technology management: a process approach, Proc. IME. B. J. Eng. Manufact, 347-355.
29- Hader, H. (1995). Delphi and cognitions psychology. ZUMA, 13.
30- Hänninen, S., & Kauranen, I. (2007). Product innovation as micro strategy. International Journal of Innovation and Learning, 425-443.
31- Hemmert, M. (2004). The Influence of Institutional Factors on the Technology Acquisition Performance of High-Tech Firms: Survey Results from Germany and Japan. Research Policy, 1019-1039.
32- Hemphill, T. (2006). Economic considerations in cooperative research and development agreements (CRADA): The case of Taxol, NIH, and technology transfer. Technology in Society, 321-331.
33- Herps, M., van Mal, H., & Halman, I. (2003). The Process of Selecting Technology Development Project: A Practical Framework. University of Technology.
34- Ho, W. (2008). Integrated analytic hierarchy process and its applications – A literature review. European Journal of Operational Research, 211-228.
35- Hsieh, T.-Y., Lu, S.-T., & Tzeng, G.-H. (2004). Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 22, 573–584.
36- Hsu, Y., Lee, C., & Kreng, V. (2010). The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Expert Systems with Applications, 419-425.
37- Husain, Z., Sushil, & Pathak, R. (2002). A technology management perspective on collaborations in the Indian automobile industry: a case study. J. Eng. Technol. Manage, 167-201.
38- Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G., Tatsuta, R., & Mieno, H. (1993).The max–min Delphi method and fuzzy Delphi method via fuzzy integration. Fuzzy Sets and Systems, 55, 241–253.
39- Kasvi, J., Vartiainen, M., & Hailikari, M. (2003). Managing knowledge and knowledge competences in projects and project organisations. International Journal of Project Management, 571-582.
40- Keogh, W., Stewart, V., & Taylor, J. (2001). Developing strategies for growth in HTSFs: looking beyond survival in an increasingly competitive marketplace, in: During, W., Oakey, R. (Eds.), New Technology-Based Firms in the New Millenium. London: Pergamon Press.
41- Kim, B. (2003). Managing the transition of technology life cycle. Technovation, 372-381.
42- Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzy logic – Theory and application. New Jersey: Prentice-Hall Inc.
43- Kulak, O., Kahraman, C., Öztayși, B., & Tanyaș, M. (2005). Multi-attribute information technology project selection using fuzzy axiomatic design. The Journal of Enterprise Information, 275-288.
44- Laarhoven, P., & Pedrycz, W. (1983). A fuzzy extension of Sati’s priority theory. Fuzzy Sets and System, 11, 229–241.
45- Landeta , J. (2006). Current validity of the Delphi method in social sciences. Technological Forecasting & Social Change, 467-482.
46- Langley, A., Mintzberg, H., Pitcher, P., Posada, E., & Saint-Macary, J. (1995). Opening up decision making: the view from the black stool. Organization Science, 260-279.
47- Laurie, D. (2001). Venture Catalyst. New York: McGraw-Hill.
48- Lee, H., Kim, C., Cho, H., & Park, Y. (2009). An ANP-based technology network for identification of core technologies: A case of telecommunication technologies. Expert Systems with Applications, 894-908.
49- Lee, J., & Kim, S. (2001). An integrated approach for interdependent information system project selection. Int. J. Proj. Manag, 111–118.
50- Lee, S., Kang, S., Park, E., & Park, Y. (2008). Applying Technology Road-Maps in Project Selecting and Planning. International Journal of Quality & Reliability Management, 39-51.
51- Lefebvre, L., Langley, A., Harvey, J., & Lefebvre, E. (1992). Exploring the strategy–technology connection in small manufacturing firms. Production and Operations, 269−285.
52- Lehtimäki, T., Simula, H., & Salo, J. (2009). Applying knowledge management to project marketing in a demanding technology transfer project: Convincing the industrial customer over the knowledge gap. Industrial Marketing Management, 228-236.
53- Leseure, M., & Brookes, N. (2004). Knowledge management benchmarks for project management. Journal of Knowledge Management, 103-116.
54- Liu, H., & Jiang, Y. (2001). Technology transfer from higher education institutions to industry in China: nature and implications. Technovation, 175–188.
55- Lucheng, H., Xin, L., & Wenguang, L. (2010). Research on emerging technology selection and assessment by technology foresight and fuzzy consistent matrix. 77-89.
56- Mahmoodzadeh, S., & Shahrabi, J. (2007). "Project Selection by Using Fuzzy AHP and TOPSIS Technique". Proceedings of World Academy of Science. Engineering and Technology.
57- McAdam, R., Keogh, W., Galbraith, B., & Laurie, D. (2005). Defining and improving technology transfer business and management processes in university innovation centres. Technovation, 1418-1429.
58- Noorderhaben, N. (1995). Strategic decision making. UK: Addison-Wesley.
59- Patterson, K., Grimm, C., & Corsi, T. (2003). Adopting new technologies for supply chain management. Transportation Research Part E, 95–121.
60- Peças, P., Ribeiro, I., Folgado, R., & Henriques, E. (2009). A Life Cycle Engineering model for technology selection: a case study on plastic injection moulds for low production volumes. Journal of Cleaner Production, 846-856.
61- Phaal, R., Farrukh, C., & Probert, D. (2001). Technology management process assessment: A case study. International Journal of Operations and Production Management, 1116-1132.
62- Phaal, R., Farrukh, C., & Probert, D. (2006). Technology management tools: concept, development and application. Technovation, 336–344.
63- Prajogo, D., & Sohal, A. (2006). The integration ofTQMand technology/R&D management in determining quality and innovation performance. international journal of management science, 296-312.
64- Reinsch, N., & Beswick, R. (1990). Voice mail versus conventional channels: A cost minimization analysis of individuals’ preferences. Academy of Management Journal, 801-816.
65- Saaty, T.L. (1980). The Analytical Hierarchy Process. New York: McGraw-Hill.
66- Schweizer, L. (2005). Knowledge transfer and R&D in pharmaceutical companies: A case study. J. Eng. Technol. Manage, 315–331.
67- Shehabuddeen, N., Probert, D., & Phaal, R. (2006). From theory to practice: challenges in operationalising a technology selection framework. Technovation, 324-335.
68- Shen, Y. C., Chang, S. H., Lin, G., & Yu, H. C. (2010). A hybrid selection model for emerging technology. Technological Forecasting & Social Change, 151-166.
69- Shen, Yung-Chi; Lin, Grace T.R.; Tzeng, Gwo-Hshiung. (2011). Combined DEMATEL techniques with novel MCDM for the organic light emitting diode technology selection. Expert Systems with Applications, 1468-1481.
70- Short, J., Williams, E., & Christie, B. (1976). The Social Psychology of Telecommunications. London: John Wiley.
71- Siegel, D., Waldman, D., Atwater, L., & Link, A. (2004). Toward a model of the effective transfer of scientific knowledge from academicians to practitioners: qualitative evidence from the commercialization of university technologies. J. Eng. Technol. Manage, 115-142.
72- Siriram, R., & Snaddon, D. (2005). Verifying links in technology management, transaction processes and governance structures. Technovation, 321-337.
73- Stacey, G., & Ashton, W. (1990). A structured approach to corporate technology strategy. Int. J. Technol. Manage, 389-1407.
74- Stewart, R. (2008). A framework for the life cycle management of information technology projects: ProjectIT. International Journal of Project Management, 203-212.
75- Sung, T. (2009). Technology transfer in the IT industry: A Korean perspective. Technological Forecasting & Social Change, 700–708.
76- Swamidass, P., & Kotha, S. (1998). Explaining manufacturing technology use, firm size and performance using a multidimensional view of technology. Journal of Operations Management, 23-37.
77- Takayama, M., & Watanabe, C. (2002). Myth of market needs and technology seeds as a source of product innovation — an analysis of pharmaceutical new product development in an anti-hypertensive product innovation. Technovation, 353-362.
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