Document Type : Research Article
Authors
1 No 17,8th alley, varze street, West ferdos boulivard, Tehran
2 Applied mathematics, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran
Abstract
In the process of evaluating the Decision Making Units, two factors of efficiency and production size can be used. When the production size of a unit is not optimal, its Returns To Scale (RTS) determines that changing the resources in another
direction would enhance its productivity. In most previous research, RTS is considered to be increasing or decreasing, and frontier analysis is used to determine it. The concept of RTS in Network Data Envelopment Analysis (DEA) is so interesting. In this paper a method based on Most Productive Scale Size (MPSS) in several steps is developed, in addition to determining that RTS of units for each unit in directional manner, the shortest changes in resources for achieving the right size for network production is also obtained. In this approach, the computational complexity, and the ambiguity in units RTS is not present.
Keywords
[2] Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M., and Zhu, J. (2004). Returns to scale in different dea models. European Journal of Operational Research, 154(2):345{362.
[3] Banker, R. D. and Maindiratta, A. (1986). Piecewise loglinear estimation of efficient production surfaces. Management Science, 32(1):126{135.
[4] Banker, R. D. and Thrall, R. M. (1992). Estimation of returns to scale using data envelopment analysis. European Journal of operational research, 62(1):74{84.
[5] Dellnitz, A. and Rodder, W. (2019). Severe aws of returns to scale in data envelopment analysis. Available at SSRN 3349177.
[6] Fare, R. and Grosskopf, S. (1997). Intertemporal production frontiers: with dynamic dea. Journal of the operational research society, 48(6):656{656.
[7] Fare, R., Grosskopf, S., and Lovell, C. K. (1985). The measurement of efficiency of production, volume 6. Springer Science & Business Media.
[8] Lee, H.-S. (2021). Efficiency decomposition of the network dea in variable returns to scale: An additive dissection in losses. Omega, 100:102212.
[9] Liang, L., Cook, W. D., and Zhu, J. (2008). Dea models for two-stage processes: Game approach and efficiency decomposition. Naval Research Logistics (NRL), 55(7):643{653.
[10] Mehdiloozad, M., Sahoo, B. K., and Roshdi, I. (2014). A generalized multiplicative directional distance function for efficiency measurement in dea. European Journal of Operational Research, 232(3):679{688.
[11] Seiford, L. M. and Zhu, J. (1999). An investigation of returns to scale in data envelopment analysis. Omega, 27(1):1{11.
[12] Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3):498{509.
[13] Wei, Q. and Yan, H. (2004). Congestion and returns to scale in data envelopment analysis. European Journal of operational research, 153(3):641{660.
[14] Yang, G.-l., Rousseau, R., Yang, L.-y., and Liu, W.-b. (2014). A study on directional returns to scale. Journal of Informetrics, 8(3):628{641.
)