یک روش تحلیل پوششی داده‌های شبکه‌ای برای ارزیابی زنجیره‌های تأمین و کاربرد آن در داروسازی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 استادیار، گروه ریاضی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران

2 استادیار، گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران

چکیده

تحلیل پوششی داده­ها یک تکنیک ناپارامتری بر مبنای برنامه­ریزی ریاضی برای ارزیابی عملکرد واحدهای تصمیم­گیرنده متجانس است. بسیاری از واحدها ساختار چندمرحله ای دارند که در آن خروجی یک مرحله به عنوان ورودی مرحله بعدی است. یک زنجیره تأمین، که شامل چندین عضو مانند تأمین کننده و تولیدکننده می­باشد، فرایند چندمرحله ای دارد. در این مقاله، برای نخستین­بار، روش­های شبکه­ای برای دستیابی به بیشترین میزان بهره­وری در زنجیره­های تأمین، که به صورت یک سیستم چندمرحله ای در نظر گرفته می­شوند، معرفی می­شود. مدل­های پیشنهادی با نگاه به ساختار درونی زنجیره تأمین ارتباط بین مراحل سازنده آن را لحاظ می­کند. چنین دیدگاهی مفاهیم مدیریتی را در جهت بهبود کارایی زنجیره تأمین و نیز بهره­وری هر عضو آن ارائه می­دهد.                        

کلیدواژه‌ها


[1] Färe, R.,  Primont, D.  (1984).Efficiency measures for multi plant firms. Operations Research Letters, 3و 257-260.

[2] Färe, R., Grosskopf, S. (2000).Network DEA. SOCIO ECON PLAN SCI, 34, 35-49.

[3] Wang, C.H., Gopal, R. & Zionts, S. (1997).Use of data envelopment analysis in assessing information technology impact on firm performance. Annals of Operations Research, 73, 191-213.

[4] Kao, C., Hwang, S-N.  (2008).Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research. 185 (1), 418–429.

[5] Chen, Y., Cook, W. D., Li, N., Zhu, J.  (2009). Additive efficiency decomposition in two-stage DEA. European Journal of Operational Research,196, 1170-1176.

[6] Yang, F., Wu, D., Liang, L., Bi, G.,  Wu, D.D.  (2011).Supply chain DEA: production possibility set and performance evaluation model. Annals of Operations Research, 185, 195-211.

[7] Paradi, J.C., Rouatt, S., Zhu, H.  (2011).Two-stage evaluation of bank branch efficiency using data envelopment analysis. Omega, 39(1), 99-109.

[8] Fukuyama, H, Mirdehghan, S. M.  (2012).Identifying the efficiency status in network DEA. European Journal of Operational Research,  220(1), 85-92.

[9] Amirteimoori, A.  (2013).A DEA two-stage decision processes with shared resources. Central European Journal of Operations Research, 21, 141-151.

[10] Liu, S-T.  (2014).Fuzzy efficiency ranking in fuzzy two-stage data envelopment analysis. Optimization Letters, 8(2), 633-652.

[11] Wang, K., Huang, W., Wu, J.,  Liu Y. N. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 3, 445-20.

[12] Sahoo, B. K., Zhu, J., Tone, K., Klemen, B. M. (2014).Decomposing technical efficiency and scale elasticity in two-stage network DEA. European Journal of Operational Research, 233(3), 584–594.

[13] Kao, C., & Hwang, S. N. (2011).Decomposition of technical and scale efficiencies in two-stage production systems. European Journal of Operational Research, 211,515–519.

[14] Lu, W-M, Kweh, Q. L., Huang, C-L. (2014). Intellectual capital and national innovation systems performance.  Knowledge-Based Systems, 71,  201–210.

[15] Liu, WB, Zhoua, ZB, Maa, CQ, Liu DB, Shen, WF. (2015).Two-stage DEA models with undesirable input-intermediate-outputs. Omega, 56, 74–87.

[16] Barros, C.P., Wanke, P. (2015).An analysis of African airlines efficiency with two-stage TOPSIS and neural networks Journal of Air Transport Management,44-45,  90-102.

[17] Chao, C-M, Yu, M-M, Wu, H-N. (2015).An application of the Dynamic Network DEA Model: The case of banks in Taiwan. Journal of Emerging Markets Finance and Trade, 51.

[18] Hu, J-L, Yu, H-E. (2015).Risk, Capital, and Operating Efficiency: Evidence from Taiwan’s Life Insurance Market. Journal of Emerging Markets Finance and Trade, 51(1), 121-132.

[19] Chen, M-J, Chiu, Y-H, Jan, Ch., Chen, Y-C, Liu, H-H. (2015).Efficiency and Risk in Commercial Banks – Hybrid DEA Estimation. Journal of Emerging Markets Finance and Trade, 44, 3.

[20] Kumar A.,  Mukherjee K.,  Adlakha A. (2015). Dynamic performance assessment of a supply chain process: A case from pharmaceutical supply chain in India. Business Process Management Journal, 21(4), 743-770.

[21] Yu, M-M, Chen, L-H, Hsiao, B.(2016). Dynamic performance assessment of bus transit with the multi-activity network structure. Omega, 60, 15-25.

[22] Fukuyama, H, Weber, W L., Xia, Y. (2016).Time substitution and network effects with an application to Nano biotechnology policy for US universities. Omega,  60, 34-44.


[23] Gulati, R., Kumar, S. (2017). Analysing banks’ intermediation and operating efficiencies using the two-stage network DEA model: The case of India, International Journal of Productivity and Performance Management. 66, 4, 500-516.

[24] Chao, C-M, Yu, M-M, Lee, U-T,  Hsiao, B. (2016). Measurement of Banking Performance in a Dynamic Multi-activity Network Structure: Evidence from Banks in Taiwan. Journal of  Emerging Markets Finance and Trade , 53(4),786-805.

[25] Fukuyama, H. and Matousek, R. (2016). Modeling Bank Performance: A Network DEA Approach. European Journal of Operational Research, 259 (2). 721-732.

[26]  Chorfi, Z., Benabbou L., Berrado A. (2016). An experimental approach for dimensioning healthcare supply chains. Intelligent Systems: Theories and Applications, 11th International Conference on  Logistics Operations Management, 1-6.

[27] Koushki, F. (2017). Modeling Dynamic Production Systems with Network Structure. Iranian Journal of Mathematical Sciences and Informatics, 12(1), 13-26.

[28] Lin, R., Chen, Z., Hu, Q., Li Z. (2017). Dynamic network DEA approach with diversification to multi-period performance evaluation of funds. OR Spectrum, 39(3), 821-860.

[29] Shokri Kahi, V., Yousefi, S., Shabanpour, H., Farzipoor Saen, R. (2017). How to evaluate sustainability of supply chains? A dynamic network DEA approach. Industrial Management & Data Systems, 117(9):1866-1889.

[30] Tone, K., Tsutsui, M. (2014). Dynamic DEA with network structure: a slacks-based measure approach. Omega, 42(1): 124-131.

[31] Zhou Z., Lin L., Xiao H., Ma Ch., Wu Sh. (2017). Stochastic network DEA models for two-stage systems under the centralized control organization mechanism. Computers & Industrial Engineering, 110, 404-412.

[32] Galagedera,  D. U. A., Roshdi,  I., Fukuyama,  H., & Zhu,  J. (2018). A new network DEA model for mutual fund performance appraisal: An application to U.S. equity mutual funds. Omega. 77, 168-179

[33] Li, H., Chen Ch., Cook, W.D., Zhang, J., Zhu, J. (2018). Two-stage network DEA: Who is the leader?. Omega. 24(C), 15-19.

[34] Banker, R. D, & Thrall, R. M.  (1992).Estimation of returns to scale using data envelopment analysis. European Journal of Operational Research. 1002,  62, 74–84.

[35] Banker, R. D.  (1984).Estimating most productive scale size using data envelopment analysis. European Journal of Operational Research, 17, 35–44.

[36] Charnes, A, Cooper, W.W, Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.