A dual model for selecting technology and technology transfer method using a combination of the Best-Worst Method (BWM) and goal programing

Document Type : Article

Authors

1 Department of Management and Business Engineering, School of Progress Engineering, Iran University of Science and Technology, Tehran, Iran

2 School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

Supplier selection is vital in the supply chain, with significant effects on the chain structure. Three important factors contribute to this process, namely, product/technology selection, selection of the technology/product transfer method, and supplier selection. In this study, after defining the influential criteria for these factors, the best-worst method (BWM) was employed for measuring the weights. Next, the three factors were incorporated into goal programming (GP) to minimize the cost and failure and maximize the level of service and environmental compliance. The results of the GP indicated the level of demand allocation to the supplier(s). Overall, the gray analytical network process (GANP) is used as the best decision-making method, and over the past four years, BWM has been applied in decision-making processes. Therefore, the GANP method was used to measure the weights of criteria. These weights were also incorporated into GP for comparison with the proposed combination. The results showed the superiority of BWM-GP over GANP-GP, given the reduced cost and failure, besides the increased level of service and environmental compliance.

Keywords


References:
1. Zack, M.H. "Developing a knowledge strategy", Calif. Manage. Rev., 41(3), pp. 125-145 (1999).
2. Garcia-Vega, M. and Huergo, E. "Trust and technology transfers", J. Econ. Behav. Organ., 142, pp. 92-104 (2017).
3. Motohashi, K. and Yuan, Y. "Productivity impact of technology spillover from multinationals to local firms: Comparing China's automobile and electronics industries", Res. Policy, 39(6), pp. 790-798 (2010).
4. Akhundzadeh, M. and Shirazi, B. "Technology selection and evaluation in Iran's pulp and paper industry using 2-filterd fuzzy decision making method", J. Clean. Prod., 142, pp. 3028-3043 (2017).
5. Danquah, M. "Technology transfer, adoption of technology and the efficiency of nations: Empirical evidence from sub Saharan Africa", Technol. Forecast. Soc. Change, 131 (December 2016), pp. 175-182 (2018). DOI: https://doi.org/10.1016/j.techfore.2017.12.007.
6. Klintenberg, P., Wallin, F., and Azimoh, L.C. "Successful technology transfer: What does it take?", Appl. Energy, 130, p. 807 (2014).
7. Jafarnezhad, A., Asgharizadeh, E., and Asemian, G. "Priority of technology transfer methods in oil drilling industry by using analysis network process (ANP)", Int. J. Learn. Dev., 3(5), pp. 15-25 (2013).
8. Shen, Y.C., Lin, G.T.R., and Tzeng, G.H. "Combined DEMATEL techniques with novel MCDM for the organic light emitting diode technology selection", Expert Syst. Appl., 38(3), pp. 1468-1481 (2011).
9. Abdullah, L. and Rahman, N.A.A. "Analytic network process for developing relative weight of wastewater treatment technology selection", Mod. Appl. Sci., 11(5), pp. 64-72 (2017).
10. Aliakbari Nouri, F., Khalili Esbouei, S., and  ntucheviciene, J. "A hybrid MCDM approach based on fuzzy ANP and fuzzy TOPSIS for technology selection", Informatica, 26(3), pp. 369-388 (2015).
11. Lee, A.H.I., Wang, W.M., and Lin, T.Y. "An evaluation framework for technology transfer of new equipment in high technology industry", Technol. Forecast. Soc. Change, 77(1), pp. 135-150 (2010).
12. Dou, Y., Zhu, Q., and Sarkis, J. "Evaluating green supplier development programs with a grey-analytical network process-based methodology", Eur. J. Oper. Res., 233(2), pp. 420-431 (2014).
13. Tuzkaya, U. and Yolver, E. "R&D project selection by integrated grey analytic network process and grey relational analysis: an implementation for home appliances company", J. Aeronaut. Sp. Technol., 8(2), pp. 35-41 (2015).
14. Lu, C., You, J.X., Liu, H.C., et al. "Health-care waste treatment technology selection using the interval 2- tuple induced TOPSIS method", Int. J. Environ. Res. Public Health, 13(6), p. 562 (2016).
15. Ic, Y.T. "An experimental design approach using TOPSIS method for the selection of computerintegrated manufacturing technologies", Robot. Comput. Integr. Manuf., 28(2), pp. 245-256 (2012).
16. Taghavifard, M., Rostami, M., Mahdi, S., et al. "A hierarchical fuzzy topsis model for evaluating technology transfer of medical equipment", Int. J. Acad. Res., 3(3), pp. 511-520 (2011).
17. Sharawat, K. and Dubey, S.K. "Diet recommendation for diabetic patients using MCDM approach", in Advances in Intelligent Systems and Computing, Springer Verlag, 624, pp. 239-246 (2018).
18. Kumar, S., Luthra, S., and Haleem, A. "Benchmarking supply chains by analyzing technology transfer critical barriers using AHP approach", Benchmarking an Int. J., 22(4), pp. 538-558 (2015).
19. Hu, W., Liu, G., and Tu, Y. "Wastewater treatment evaluation for enterprises based on fuzzy-AHP comprehensive evaluation: A case study in industrial park in Taihu Basin, China", Springerplus, 5(1), pp. 1-15 (2016).
20. Farshidi, S., Jansen, S., de Jong, R., et al. "A decision support system for software technology selection", J. Decis. Syst., 27(sup1), pp. 98-110 (2018).
21. Mokhtarzadeh, N., Mahdiraji, H., Beheshti, M., et al. "A novel hybrid approach for technology selection in the information technology industry", Technologies, 6(1), p. 34 (2018).
22. Rahimi, F., Goli, A., and Rezaee, R. "Hospital location-allocation in Shiraz using geographical information system (GIS)", Shiraz E Med. J., 18(8), pp. 1-8 (2017).
23. Amirghodsi, S., Bonyadi Naeini, A., and Roozbehani, B. "An integrated shannon-PAF method on gray numbers to rank technology transfer strategies", EMJ - Eng. Manag. J., 32(3), pp. 186-207 (2020).
24. Sahin, B. and Yip, T.L. "Shipping technology selection for dynamic capability based on improved Gaussian fuzzy AHP model", Ocean Eng., 136, pp. 233-242 (2017).
25. Mardani, A., Zavadskas, E.K., Streimikiene, D., et al. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency", Renew. Sustain. Energy Rev., 70, pp. 1298-1322 (2017).
26. Goker, N. and Karsak, E.E. "An improved common weight DEA-based methodology for manufacturing technology selection", in Lecture Notes in Engineering and Computer Science, Newswood Limited, 2226, pp. 864-869 (2016).
27. Ren, J. "Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory", Chemosphere, 191, pp. 747-760 (2018).
28. Van de Kaa, G., Kamp, L., and Rezaei, J. "Selection of biomass thermochemical conversion technology in the Netherlands: A best worst method approach", J. Clean. Prod., 166, pp. 32-39 (2017).
29. Rezaei, J., Kothadiya, O., Tavasszy, L., et al. "Quality assessment of airline baggage handling systems using SERVQUAL and BWM", Tour. Manag., 66, pp. 85-93 (2018).
30. Rezaei, J., Nispeling, T., Sarkis, J., et al. "A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method", J. Clean. Prod., 135, pp. 577-588 (2016).
31. Setyono, R.P. and Sarno, R. "Comparative method of Moora and CoprAs based on weighting of the best worst method in supplier selection at ABC mining companies in Indonesia", in 2019 International Conference on Information and Communications Technology, ICOIACT 2019, Institute of Electrical and Electronics Engineers Inc., pp. 354-359 (2019).
32. Xu, D., Li, W., Ren, X., et al. "Technology selection for sustainable hydrogen production: A multi-criteria assessment framework under uncertainties based on the combined weights and interval best-worst projection method", Int. J. Hydrogen Energy, 45(59), pp. 34396- 34411 (2020). DOI: https://doi.org/10.1016/j.ijhydene.2019.09.030. 33. Jafarzadeh Ghoushchi, S., Khazaeili, M., Amini, A., et al. "Multi-criteria sustainable supplier selection using piecewise linear value function and fuzzy best-worst method", J. Intell. Fuzzy Syst., 37(2), pp. 2309-2325 (2019).
34. Hendalianpour, A., Fakhrabadi, M., Zhang, X., et al. "Hybrid model of IVFRN-BWM and robust goal programming in agile and  flexible supply chain, a case study: Automobile industry", IEEE Access, 7, pp. 71481-71492 (2019).
35. Lee, J.W. and Kim, S.H. "Using analytic network process and goal programming for interdependent information system project selection", Comput. Oper. Res., 27(4), pp. 367-382 (2000).
36. Yurdakul, M. "Selection of computer-integrated manufacturing technologies using a combined analytic hierarchy process and goal programming model", Robot. Comput. Integr. Manuf., 20(4), pp. 329-340 (2004).
37. Feng, B., Fan, Z.P., and Li, Y. "A decision method for supplier selection in multi-service outsourcing", Int. J. Prod. Econ., 132(2), pp. 240-250 (2011).
38. Kannan, D., Khodaverdi, R., Olfat, L., et al. "Integrated fuzzy multi criteria decision making method and multiobjective programming approach for supplier selection and order allocation in a green supply chain", J. Clean. Prod., 47, pp. 355-367 (2013).
39. Li, D.F. and Wan, S.P. "Fuzzy linear programming approach to multiattribute decision making with multiple types of attribute values and incomplete weight information", Appl. Soft Comput. J., 13(11), pp. 4333- 4348 (2013).
40. Hamurcu, M. and Eren, T. "A hybrid approach of analytic hierarchy process-topsis and goal programming for electric automobile selection", in In The 2018 International Conference of the African Federation of Operational Research Societies (AFROS 2018). (https://www.mendeley.com/catalogue/d7a57- 562-0c75-3fd5-8ba7-ca025faac965/, 2018), p. 2.
41. Lin, R., Man, Y., Lee, C.K.M., et al. "Sustainability prioritization framework of biorefinery: A novel multi-criteria decision-making model under uncertainty based on an improved interval goal programming method", J. Clean. Prod., 251, p. 119729 (2020).
42. Vahidi, F., Torabi, S.A., and Ramezankhani, M.J. Sustainable supplier selection and order allocation under operational and disruption risks", J. Clean. Prod., 174, pp. 1351-1365 (2018).
43. Sarkar, S., Pratihar, D.K., and Sarkar, B. "An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company", J. Manuf. Syst., 46, pp. 163-178 (2018).
44. Hendalianpour, A., Fakhrabadi, M., Sangari, M.S., et al. "A combined benders decomposition and lagrangian relaxation algorithm for optimizing a multi-product, multi-level omni-channel distribution system", Sci. Iran., Transactions on Industrial Engineering (E), 29(1), pp. 355-371 (2022). DOI: https://dx.doi.org/10.24200/sci.2020.53644.3349.
45. Mazdeh, M.M., Ali Shafia, M., Bandarian, R., et al. "An ISM approach for analyzing the factors in technology transfer", Decis. Sci. Lett., 4(3), pp. 335- 348 (2015).
46. Kharat, M.G., Raut, R.D., Kamble, S.S., et al. "The application of Delphi and AHP method in environmentally conscious solid waste treatment and disposal technology selection", Manag. Environ. Qual. an Int. J., 27(4), pp. 427-440 (2016).
47. Montazeri, M.M. and Najjartabar-Bisheh, M. "Optimizing technology selection for power smart grid systems: A case study of Iran power distribution industry (IPDI)", Technol. Econ. Smart Grids Sustain. Energy, 2(1), p. 6 (2017).
48. Rezaei, J. "Best-worst multi-criteria decision-making method", Omega, United Kingdom, 53, pp. 49-57 (2015).
49. Pamucar, D., Petrovic, I., and Cirovic, G. "Modification of the best-worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers", Expert Syst. Appl., 91, pp. 89-106 (2018).
50. Wan Ahmad, W.N.K., Rezaei, J., Sadaghiani, S., et al. "Evaluation of the external forces affecting the sustainability of oil and gas supply chain using best worst method", J. Clean. Prod., 153, pp. 242-252 (2017).
51. Rezaei, J. "Best-worst multi-criteria decision-making method: Some properties and a linear model", Omega, United Kingdom, 64, pp. 126-130 (2016).
52. Razmi, J., Sangari, M.S., and Ghodsi, R. "Developing a practical framework for ERP readiness assessment using fuzzy analytic network process", Adv. Eng. Softw., 40(11), pp. 1168-1178 (2009).
53. Sarkis, J. and Sundarraj, R.P. "Factors for strategic evaluation of enterprise information technologies", Int. J. Phys. Distrib. Logist. Manag., 30, pp. 196-220 (2000).
54. Lin, J.J. and Wei, Y.H. "Assessing area-wide bikeability: A grey analytic network process", Transp. Res. Part A Policy Pract., 113, pp. 381-396 (2018).
55. Deng, J.L. "Control problems of grey systems", Syst. Control Lett., 1(5), pp. 288-294 (1982).
56. Opricovic, S. and Tzeng, G.H. "Defuzzification within a multicriteria decision model", Int. J. Uncertainty, Fuzziness Knowledge-Based Syst., 11(5), pp. 635-652 (2003).
57. Deng, J.L. "Introduction to grey system theory", J. grey Syst., 1(1), pp. 1-24 (1989).
58. Sarkis, J., Hasan, M.A., and Shankar, R. "Evaluating environmentally conscious manufacturing barriers with interpretive structural modeling", in Environmentally Conscious Manufacturing VI, SPIE, 6385, p. 638508 (2006).
59. Fontela, E. and Gabus, A. "The DEMATEL observer", DEMATEL 1976 Report (1976).
60. Gabus, A. and Fontela, E. "World problems, an invitation to further thought within the framework of DEMATEL", Battelle Geneva Res. Cent., pp. 1-12 (1974).
61. Amirghodsi, S., Bonyadi Naeini, A., and Makui, A. "An integrated delphi-DEMATEL-ELECTRE method on gray numbers to rank technology providers", IEEE Trans. Eng. Manag., 69(4), pp. 1348-1364 (2022).DOI: https://doi.org/10.1109/TEM.2020.2980127.
62. Saaty, T., Decision Making with Dependence and Feedback: The Analytic Network Process, RWS Publications (1996).