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Abstract
In recent years, data envelopment analysis (DEA) has been widely used to assess both efficiency and effectiveness. Accurate measurement of overall performance is a product of concurrent consideration of these measures. There are a couple of well-known methods to assess both efficiency and effectiveness. However, some issues can be found in previous methods. The issues include non-linearity problem, paradoxical improvement solutions, efficiency and effectiveness evaluation in two independent environments: dividing an operating unit into two autonomous departments for performance evaluation and problems associated with determining economies of scale. To overcome these issues, this paper aims to develop a series of linear DEA methods to estimate efficiency, effectiveness, and returns to scale of decision-making units (DMUs), simultaneously. This paper considers the departments of a DMU as a united entity to recommend consistent improvements. We first present a model under constant returns to scale (CRS) assumption, and examine its relationship with one of existing network DEA model. We then extend model under variable returns to scale (VRS) condition, and again its relationship with one of existing network DEA models is discussed. Next, we introduce a new integrated two-stage additive model. Finally, an in-depth analysis of returns to scale is provided. A case study demonstrates applicability of the proposed models.
Acknowledgements
Authors would like to appreciate three anonymous reviewers for their valuable suggestions and comments which improved this paper significantly.
Notes
1. Such a situation may occur in seasonal or periodic networks: the networks that change by seasonal effects or periodic variations.
Additional information
Notes on contributors
Mohsen Khodakarami
Mohsen Khodakarami is a scholar and consultant in the area of production and operation management (POM). He obtained his BSc in physics from Tabriz University in Iran. He also achieved his MSc in POM from Islamic Azad University – Karaj Branch in Iran. He has published a refereed paper in Clean Technologies and Environmental Policy.
Amir Shabani
Amir Shabani is a scholar and consultant in the area of production and operation management (POM). He obtained his BSc in industrial management from Islamic Azad University – Karaj Branch in Iran. He also achieved his MSc as a top student in POM from Islamic Azad University – Science and Research Branch in Iran. He has published several refereed papers in prestigious journals such as International Journal of Physical Distribution & Logistics Management, Clean Technologies and Environmental Policy, Applied Mathematical Modelling, International Journal of Integrated Supply Management, Benchmarkin: An International Journal, International Journal of Business Excellence and International Journal of Business Information Systems.
Reza Farzipoor Saen
Reza Farzipoor Saen is an associate professor in Department of Industrial Management, Islamic Azad University, Karaj Branch, Iran. In 2002, he obtained his PhD in industrial management from Islamic Azad University, Science and Research Branch in Iran. He has published over 125 refereed papers in many prestigious journals, such as Expert Systems with Applications, International Journal of Production Economics, Annals of Operations Research, Journal of the Operational Research Society, European Journal of Operational Research, Journal of Industrial and Management Optimisation, Applied Mathematics and Computation, Applied Mathematical Modelling, International Journal Advanced Manufacturing Technology, Asia-Pacific Management Review, etc. His research interests include operations research, data envelopment analysis, supply chain management and marketing research.