Identifying the appropriate method of technology transfer in an automotive battery industry aimed at world-class manufacturing
Subject Areas :
Amir Hossein
Latifian
1
(Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Reza
Tavakoli Moghadam
2
(Faculty of Industrial Engineering, Technical Faculty, University of Tehran, Tehran, Iran)
mphammadali
keramati
3
(Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran)
Abstract :
Today, with the progress of science and the increasing trend in complexity of technological processes, cooperation between organizations is among their significant strategies and their public policies in technology development all around the world. So, success in the world today is obviously dependent on utilizing technology. Technology transfer is just one of the fields in implementation of technology management, which requires a broad and delicate vision. For this very reason, this research deals with recognizing and ranking the parameters influential in technology transfer in the automotive battery industry, to reach manufacturing world class. In the first part, effective indexes in assessing technology transfer methods in the automotive battery industry section were recognized and within the second part, Weighting coefficients related to any individual index were calculated through implementing fuzzy step-wise weight assessment ratio analysis (SWARA) decision-making method and then, in order to implement the proposed model, the methods of technology transfer were evaluated and their final prioritization was calculated utilizing the combined method of GRA-VIKOR relation analysis under the fuzzy environment .According to the results of the fuzzy step-wise weight assessment ratio analysis (SWARA) method, three influential factors in evaluation of technology transfer methods in the automotive battery industry were introduced as “he management style development”, “the strategic consequences” and “the cost effectiveness”. Finally, based on the results of the proposed method, the transfer method of “joint investment” was recognized as the most suitable technique for technology transfer in this industry, and through this method, all the managers and policy-makers can focus all theiractivities based on this system.
Kaimowitz, D., Making the link: Agricultural research and technology transfer in developing countries. 2019: CRC Press.
Bertsch, G.K., After the revolutions: East-West trade and technology transfer in the 1990s. 2019: Routledge.
Buzás, N., From technology transfer to knowledge transfer: an institutional transition, in: Linking industries across the world. 2019, Routledge. p. 109-124.
Günsel, A., Research on effectiveness of technology transfer from a knowledge based perspective. Procedia-Social and Behavioral Sciences, 2015. 207: p. 777-785.
Berry, N. (2000). Wcm Versus Strategic Trade-Offs. International Journal of Operations and Production Management, 34(12), 56-79.
Peter Poor, Marek Kocisko & Radoslav Krehel. (2016). World class manufacturing (WCM) modelas A tool for company managment. 27TH daaam international symposium on intelligent manufacturing and automation, p 386-390
R.G. Eccles, The Performance Measurement Manifesto, in: J. Holloway, J. Lewis, G. Mallory(Eds.), Performance Measurement and Evaluation, Sage Publications, London, 1995, pp. 5-14.
RCA, Tomorrow’s Company: The Role of Business in Changing World, Royal Society of Arts, Manufacturers and Commerce, London, 1994.
Jafari, M., P. Akhavan, and A. Rafiei, Technology Transfer Effectiveness in Knowledge-Based Centers Providing a Model Based on Knowledge Management. International Journal of Scientific Knowledge, 2014. 4(7).
Hsu, D.W., et al., Toward successful commercialization of university technology: Performance drivers of university technology transfer in Taiwan. Technological Forecasting and Social Change, 2015. 92: p. 25-39.
Dinmohammadi, A. and M. Shafiee, Determination of the most suitable technology transfer strategy for wind turbines using an integrated AHP-TOPSIS decision model. Energies, 2017. 10(5): p. 642.
Estep, J. and T. Daim. A framework for technology transfer potential assessment. in 2016 Portland International Conference on Management of Engineering and Technology (PICMET). 2016. IEEE.
Atkinson, P., et al., Technology Assessment: Patient-Centric Solutions for Transfer of Health Information, in Infrastructure and Technology Management. 2018, Springer. p. 245-269.
Distanont, A., O. Khongmalai, and P. Kritpipat, Factors affecting technology transfer performance in the Petrochemical Industry in Thailand: A Case study. WMS Journal of Management, 2018. 7(2): p. 23-35.
Cheng, A.-C. Exploring technology transfer of innovation process in the new materials. in 2018 IEEE 9th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT). 2018. IEEE.
Kraujalienė, L., Comparative analysis of multicriteria decision-making methods evaluating the efficiency of technology transfer. Business, Management and Education, 2019. 17(1): p. 72-93.
Lavoie, J.R. and T. Daim, Technology transfer assessment: An integrated approach, in: R&D Management in the Knowledge Era. 2019, Springer. p. 439-460.
Maludin, S., et al., Strategic choice of technology transfer in Indonesia. Jurnal Aplikasi Bisnis dan Manajemen (JABM), 2019. 5(1): p. 163.
Lafuente, E. and J. Berbegal-Mirabent, Assessing the productivity of technology transfer offices: an analysis of the relevance of aspiration performance and portfolio complexity. The Journal of Technology Transfer, 2019. 44(3): p. 778-801.
Amini, E., et al., Affecting factors of knowledge-based companies using fuzzy AHP model, Case study Tehran University Enterprise Park. Journal of the Knowledge Economy, 2020. 11(2): p. 574-592.
Zadeh, L.A., Information and control. Fuzzy Sets, 1965. 8(3): p. 338-353.
Wu, H.-Y., G.-H. Tzeng, and Y.-H. Chen, A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Systems with Applications, 2009. 36(6): p. 10135-10147.
Yao, J.-S. and K. Wu, Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets and Systems, 2000. 116(2): p. 275-288.
Ansari, Z.N., R. Kant, and R. Shankar, Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 2020: p. 1-22.
Yadav, G., et al., Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study. International Journal of Production Research, 2018. 56(18): p. 6259-6278.
Keršuliene, V., E.K. Zavadskas, and Z. Turskis, Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 2010. 11(2): p. 243-258.
Kou, G., et al., Pairwise comparison matrix in multiple criteria decision making. Technological and economic development of economy, 2016. 22(5): p. 738-765.
Kou, G., Y. Peng, and G. Wang, Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Information Sciences, 2014. 275: p. 1-12.
Agarwal, S., R. Kant, and R. Shankar, Evaluating Solutions to Overcome Humanitarian Supply Chain Management Barriers: A Hybrid Fuzzy SWARA–Fuzzy WASPAS Approach. International Journal of Disaster Risk Reduction, 2020: p. 101838.
Kaimowitz, D., Making the link: Agricultural research and technology transfer in developing countries. 2019: CRC Press.
Bertsch, G.K., After the revolutions: East-West trade and technology transfer in the 1990s. 2019: Routledge.
Buzás, N., From technology transfer to knowledge transfer: an institutional transition, in: Linking industries across the world. 2019, Routledge. p. 109-124.
Günsel, A., Research on effectiveness of technology transfer from a knowledge based perspective. Procedia-Social and Behavioral Sciences, 2015. 207: p. 777-785.
Berry, N. (2000). Wcm Versus Strategic Trade-Offs. International Journal of Operations and Production Management, 34(12), 56-79.
Peter Poor, Marek Kocisko & Radoslav Krehel. (2016). World class manufacturing (WCM) modelas A tool for company managment. 27TH daaam international symposium on intelligent manufacturing and automation, p 386-390
R.G. Eccles, The Performance Measurement Manifesto, in: J. Holloway, J. Lewis, G. Mallory(Eds.), Performance Measurement and Evaluation, Sage Publications, London, 1995, pp. 5-14.
RCA, Tomorrow’s Company: The Role of Business in Changing World, Royal Society of Arts, Manufacturers and Commerce, London, 1994.
Jafari, M., P. Akhavan, and A. Rafiei, Technology Transfer Effectiveness in Knowledge-Based Centers Providing a Model Based on Knowledge Management. International Journal of Scientific Knowledge, 2014. 4(7).
Hsu, D.W., et al., Toward successful commercialization of university technology: Performance drivers of university technology transfer in Taiwan. Technological Forecasting and Social Change, 2015. 92: p. 25-39.
Dinmohammadi, A. and M. Shafiee, Determination of the most suitable technology transfer strategy for wind turbines using an integrated AHP-TOPSIS decision model. Energies, 2017. 10(5): p. 642.
Estep, J. and T. Daim. A framework for technology transfer potential assessment. in 2016 Portland International Conference on Management of Engineering and Technology (PICMET). 2016. IEEE.
Atkinson, P., et al., Technology Assessment: Patient-Centric Solutions for Transfer of Health Information, in Infrastructure and Technology Management. 2018, Springer. p. 245-269.
Distanont, A., O. Khongmalai, and P. Kritpipat, Factors affecting technology transfer performance in the Petrochemical Industry in Thailand: A Case study. WMS Journal of Management, 2018. 7(2): p. 23-35.
Cheng, A.-C. Exploring technology transfer of innovation process in the new materials. in 2018 IEEE 9th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT). 2018. IEEE.
Kraujalienė, L., Comparative analysis of multicriteria decision-making methods evaluating the efficiency of technology transfer. Business, Management and Education, 2019. 17(1): p. 72-93.
Lavoie, J.R. and T. Daim, Technology transfer assessment: An integrated approach, in: R&D Management in the Knowledge Era. 2019, Springer. p. 439-460.
Maludin, S., et al., Strategic choice of technology transfer in Indonesia. Jurnal Aplikasi Bisnis dan Manajemen (JABM), 2019. 5(1): p. 163.
Lafuente, E. and J. Berbegal-Mirabent, Assessing the productivity of technology transfer offices: an analysis of the relevance of aspiration performance and portfolio complexity. The Journal of Technology Transfer, 2019. 44(3): p. 778-801.
Amini, E., et al., Affecting factors of knowledge-based companies using fuzzy AHP model, Case study Tehran University Enterprise Park. Journal of the Knowledge Economy, 2020. 11(2): p. 574-592.
Zadeh, L.A., Information and control. Fuzzy Sets, 1965. 8(3): p. 338-353.
Wu, H.-Y., G.-H. Tzeng, and Y.-H. Chen, A fuzzy MCDM approach for evaluating banking performance based on Balanced Scorecard. Expert Systems with Applications, 2009. 36(6): p. 10135-10147.
Yao, J.-S. and K. Wu, Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets and Systems, 2000. 116(2): p. 275-288.
Ansari, Z.N., R. Kant, and R. Shankar, Evaluation and ranking of solutions to mitigate sustainable remanufacturing supply chain risks: a hybrid fuzzy SWARA-fuzzy COPRAS framework approach. International Journal of Sustainable Engineering, 2020: p. 1-22.
Yadav, G., et al., Hybrid BWM-ELECTRE-based decision framework for effective offshore outsourcing adoption: a case study. International Journal of Production Research, 2018. 56(18): p. 6259-6278.
Keršuliene, V., E.K. Zavadskas, and Z. Turskis, Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 2010. 11(2): p. 243-258.
Kou, G., et al., Pairwise comparison matrix in multiple criteria decision making. Technological and economic development of economy, 2016. 22(5): p. 738-765.
Kou, G., Y. Peng, and G. Wang, Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Information Sciences, 2014. 275: p. 1-12.
Agarwal, S., R. Kant, and R. Shankar, Evaluating Solutions to Overcome Humanitarian Supply Chain Management Barriers: A Hybrid Fuzzy SWARA–Fuzzy WASPAS Approach. International Journal of Disaster Risk Reduction, 2020: p. 101838.
Mardani, A., et al., A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments. Applied Soft Computing, 2017. 57: p. 265-292.
Rezaei, J., Best-worst multi-criteria decision-making method. Omega, 2015. 53: p. 49-57.
Rezaei, J., Best-worst multi-criteria decision-making method: Some properties and a linear model. Omega, 2016. 64: p. 126-130.
Kuo, M.-S. and G.-S. Liang, Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 2011. 38(3): p. 1304-1312.
Li, N. and H. Zhao, Performance evaluation of eco-industrial thermal power plants by using fuzzy GRA-VIKOR and combination weighting techniques. Journal of Cleaner Production, 2016. 135: p. 169-183.
Chen, C.-T., Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 2000. 114(1): p. 1-9.