ارزیابی کارایی سود فرآیندهای دو مرحله‌ای در حضور عوامل نامطلوب

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه ریاضی کاربردی، دانشکده علوم پایه، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران

2 استاد، گروه ریاضی کاربردی، دانشکده علوم پایه، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران

3 استاد، گروه ریاضی، دانشکده علوم پایه، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران

4 استادیار، گروه ریاضی کاربردی، دانشکده علوم پایه، واحدرشت، دانشگاه آزاد اسلامی، رشت، ایران

چکیده

مدیریت فرآیندهای تولیدی به منظور کاهش هزینه و افزایش درآمد و سود از عوامل مهم و ضروری برای رسیدن به موفقیت در امور اقتصادی و به‌دنبال آن رضایت مدیران و مشتریان است. در این راستا به ‌کارگیری یک روش مناسب به منظور بررسی عملکرد و مدیریت سیستم‌های پیچیده با ساختار شبکه‌ای امری مهم و ضروری به شمار می‌آید. تحلیل پوششی داده های شبکه ای یک روش برنامه ریزی ناپارامتری مناسب و موثر برای ارزیابی عملکرد واحدهای تصمیم گیرنده شامل چندین ورودی و خروجی می باشد که فرآیندهای داخلی را نیز در نظر می گیرد. در این تحقیق بر اساس تکنیک تحلیل پوششی داده ها با در نظر گرفتن نقش مناسب برای عوامل میانی فرآیندها و هم چنین فرض دسترسی پذیری ضعیف برای عوامل نامطلوب، کارایی سود سیستم هایی با ساختار شبکه ای دو مرحله ای در حضور عوامل نامطلوب مورد ارزیابی قرار می گیرد. به منظور شرح و تحلیل بیشتر روش پیشنهادی یک مطالعه کاربردی نیز ارایه می‌شود.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluating the profit efficiency of two-stage processes with undesirable outputs

نویسندگان [English]

  • Maryam Nematizadeh 1
  • Alireza Amirteimoori 2
  • Sohrab Kordrostami 3
  • Mohsen Vaez Ghasemi 4
1 PhD Student, Department of Applied Mathematics, Faculty of Basic Sciences, Rasht Branch, Islamic Azad University, Rasht, Iran
2 Professor, Department of Applied Mathematics, Faculty of Basic Sciences, Rasht Branch, Islamic Azad University, Rasht, Iran
3 Professor, Department of Mathematics, Faculty of Basic Sciences, Lahijan Branch, Islamic Azad University, Lahijan, Iran
4 Assistant Professor, Department of Applied Mathematics, Faculty of Basic Sciences, Vahdasht, Islamic Azad University, Rasht, Iran
چکیده [English]

The management of production processes in order to reduce costs and increase revenue and profits is one of important and essential factors to achieve success in economic affairs and then the satisfaction of managers and customers. In this regard, using an appropriate approach to evaluate the performance and to manage complex systems with network structure is important and necessary. Network Data Envelopment Analysis (NDEA) is a suitable and effective non parametric programming method for assessing the performance of decision-making units with multiple inputs and outputs, as well as taking into account internal processes. In this research, based on the DEA technique, considering the appropriate role for intermediate factors of processes as well as the weak disposability for undesirable factors, the efficiency of systems with a two - stage network structure in the presence of undesirable factors is evaluated. To further explain and analyze the proposed method, a case study is also examined.

کلیدواژه‌ها [English]

  • Network data envelopment analysis
  • Two-stage network
  • Undesirable factors
  • Weak disposability
[1]    Charnes, A., Coopre, W.W., Rhodes, E., (1978). Measuring the efficiency of decision making units, European Journal of Operational Research, 2, pp 429-444.
[2]    Farrell, M. J., (1957). The measurement of production efficiency, Journal of the Royal Statistical Society 120. Series A, General, pp 253-281.
[3]    Färe, R., Grosskopf, S., Lovell, C. A. K., (1985). The measurement of efficiency of production, Kluwer-Nijhoff, Boston.
[4]    Ray, R. C., Kim, H. J., (1995). Cost efficiency in the US steel industry: A nonparametric analysis using data envelopment analysis, European Journal of Operational Research, 80, pp 654-671.
[5]    Tone, K., (2002). A strange Case of the Cost and Allocative Efficiencies in DEA, Journal of the Operation Research, Society 53, pp 1225-123.
[6]    Fukuyama, H., Weber, W. L., (2004). Economic inefficiency measurement of input spending when decision-making units face different input prices, Journal of the Operational Research Society, 55, pp 1102-1110.
[7]    Fukuyama, H., Weber, W. L., (2008). Japanese securities firms. Journal of Applied Economics, 11, pp 281-303.
[8]    Camanho, A. S., Dyson, R. G., (2008). A generalization of the Farell cost efficiency measure applicable to non-fully competitive settings, Omega: The International Journal of Management Science, 36, pp 147-162.
[9]    Sahoo, B. K., Mehdiloozad, M., Tone, K., (2014). Cost, revenue and profit efficiency measurement in DEA: A directional distance function approach, European Journal of Operational Research, 237(3), pp 921-931.
[10] Färe, R., Grosskopf, S., (2000). Network DEA, Socio-Economic Planning Sciences, 34, pp 35-49.
[11] 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, pp 418-429.
[12] Chen, Y., Cook, L. WD., Li, N., Zhu, J., (2009). Additive efficiency decomposition in two-stage DEA, European Journal of Operational Research, 196, pp 1170-1176.
[13] Liang, L., Cook, WD., Zhu, J., (2008). DEA models for two-stage processes: game approach and efficiency decomposition, Naval Research Logistics, 55, pp 643-53.
[14] Tone, K., Tsutsui, M., (2010). Dynamic DEA: a slacks-based measure approach, Omega, 38, pp 145-156.
[15] Kao C., (2014). Network data envelopment analysis: A review, European Journal of Operational research, 239, pp 1-16.
[16] Salari, M., Zandiyeh, M., (2016). Measuring the efficiency of internet shops using a multi stages Data Envelopment Analysis (DEA) model, IQBQ, 3(20), pp 127-151.
[17] Amirteimoori, A., Despotis, D. K., Kordrostami, S., Azizi, H., (2016). Additive models for network data envelopment analysis in the presence of shared resources, Transportation Research Part D, 48, pp 411-424.
[18] Taghavifard, MT., Maghsod, A., Mozafari, R., (2016). Management the managerial of Bank Branches: A Three-Stage DEA Analysis (In Melli Bank of Iran), MRDM, 2(1), PP 51-72.  
[19] Kolyaei, M., Azar, A., Amini, M., Rajabzadeh Gatari, A., (2016). Design of integerated mathematical model foe closed-loop supply chain. IQBQ, 20(1), PP 1-32.
[20] Lozano, S., Gutierres, E., Moreno, P., (2013). Network DEA approach to airports performance assessment considering undesirable outputs, Applied Mathematical Modelling, 37, pp 1665-1676.
[21] Maghbouli, M., Amirteimoori, A., Kordrostami, S., (2014). Two-stage network structures with undesirable outputs: A DEA based approach, Measurement, 48, pp 109-118.
[22] Wu, J., Zhu, Q., Ji, X., Chu, J., Liang, L., (2016). Two-stage network processes with shared resources and resources recovered from undesirable outputs, European Journal Operational Research, 251, pp 182-197.
[23] Lozano, S., (2011). Scale and cost efficiency analysis of networks of processes, Expert System with Applications, 38, pp 6612-6617.
[24] Banihashemi, S., Tohidi, G., (2013). Allocation efficiency in network DEA, International Journal of Data Envelopment Analysis, 1, pp 85-96.
[25] Hoseinzadeh, F., Zaker, E., (2020). Evaluation of cost-effictiveness and cost efficiency of network systems Case study: Bank branches, MRDM, 1, pp 22-42
[26] Banihashem, Sh., Sanei, M., Mohamadian Manesh, Z., (2013). Cost, revenue and profit efficiency in supply chain, African Journal of Business Management, 7, pp 4280-4287.
[27] Fukuyama, H., Matousek, R., (2017). Modeling bank performance: A network DEA approach, European Journal of Operational Research, 259, pp 721-732.
[28] Jahani Sayyad Noveiri, M., Kordrostami, S., Amirteimoori, A. R., (2017). Cost efficiency of closed-loop supply chain in the presence of dual-role and undesirable factors, Journal of New Research in Mathematics, 9, pp 5-16.
[29] Shephard R.W., (1970). Theory of Cost and Production functions, Princeton University Press.
[30] Kuosmanen, T., pp (2005). Weak disposability in nonparametric production analysis with undesirable outputs, American Journal of Agricultural Economics, 87, pp 1077-1082.