Industrial Management Studies

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

Memorandum of Understanding between the Quarterly and the Iranian Management Sciences Association

Article Writing Guide

Files

Reviewer 1402

Reviewer 1401

Reviewer 1400

Consultants

Publons

Determining the efficiency of decision-making units using the technique of data envelopment analysis in the presence of dual-role performance factors

Document Type : Research Paper

Authors

1 Department of Mathematics, Islamic Azad University, Sirjan Branch, Sirjan, Iran

2 Associate Professor, Faculty of Administrative Sciences and Economics Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

3 Master of Industrial Engineering, Faculty of Administrative Sciences and Economics, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

Abstract

Data Envelopment Analysis (DEA) is an approach based on mathematical programming for the relative evaluation of decision-making units treated as similar yet distinct production systems. In this approach, the performance of each unit is characterized by describing the transformation of specific inputs into specific outputs. Traditional DEA models assume that the role of each performance factor is clearly defined. However, in some real-world problems, certain factors might be identified as dual-role factors depending on the evaluation nature or the decision-makers' perspective. These factors can play the role of both input and output, or even be considered neutral in assessing the units' performance. In the current paper, to determine the status of dual-role factors and calculate the efficiency of DMUs, two new linear programming models, based on the concept of deviation in the efficiency constraint and a common set of weights, are suggested. The main advantages of the proposed models are significantly reducing the computations and iterations required to solve the model, and involving all DMUs to determine the role of factors. To assess the performance of the proposed models, a data set for the evaluation of eighteen suppliers in the presence of two inputs, three outputs, and two dual-role factors has been employed. The obtained results showed that, compared to other models, the proposed models are computationally more efficient, and the role determination and evaluation of the units, based on the obtained weights from these models, are better aligned with the expectations of decision-makers

Keywords

Main Subjects

References
  1. Afsharian, M., Ahn, H., & Neumann, L. (2016). Generalized DEA: an approach for supporting input/output factor determination in DEA. Benchmarking, 23(7). https://doi.org/10.1108/BIJ-07-2015-0074.
  2. Azadi, M., & Farzipoor Sean, R. (2011). A new chance-constrained data envelopment analysis for selecting third-party reverse logistics providers in the existence of dual-role factors. Expert Systems with Applications, 38(10), 12231–12236. https://doi.org/10.1016/‌­eswa.2011.04.001.
  3. Azadi, M., & Saen, R. F. (2012). Developing a worst practice DEA model for selecting suppliers in the presence of imprecise data and dual-role factor. International Journal of Applied Decision Sciences, 5(3). https://doi.org/10.1504/IJADS.2012.047671
  4. Azadi, M., Shabani, A., & Farzipoor Saen, R. (2014). A new Russell model for selecting suppliers. International Journal of Integrated Supply Management, 9(1–2). https://doi.org/10.1504/­2014.064354
  5. Azadi, M., Mirhedayatian, S. M., Saen, R. F., Hatamzad, M., & Momeni, E. (2017). Green supplier selection: A novel fuzzy double frontier data envelopment analysis model to deal with undesirable outputs and dual-role factors. International Journal of Industrial and Systems Engineering, 25(2). https://doi.org/10.1504/IJISE.2017.081516
  6. Beasley, J. E. (1990). Comparing university departments. Omega, 18(2), 171–183, https://doi.org/10.1016/0305-0483(90)90064-G
  7. Beasley, J. E. (1995). Determining Teaching and Research Efficiencies. Journal of the Operational Research Society, 46(4), 441–452, https://doi.org/10.2307/2584592.
  8. Charnes, A., Cooper, W.W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429-444, https://doi.org/10.1016/03772217(78)90138-8
  9. Chaghooshi, A. J., Jafarzadeh, A. H., & Mahdiloo, M. (2012). Selecting the best flexible manufacturing system supplier in the presence of dual-role factors: A decision model based on the Worst Practice Frontier DEA and Common Set of Weights. World Applied Sciences Journal, 17(7).
  10. Chen, W. C. (2014). Revisiting dual-role factors in data envelopment analysis: Derivation and implications. IIE Transactions (Institute of Industrial Engineers), 46(7), 653–663 https://doi.org/10.1080/0740817X.2012.721943
  11. Chen, W. C. (2021). On performance evaluation with a dual-role factor. Annals of Operations Research, 304(1–2). https://doi.org/10.1007/s10479-021-04102-3
  12. Cook, W. D., Green, R. H., & Zhu, J. (2006). Dual-role factors in data envelopment analysis. IIE Transactions (Institute of Industrial Engineers), 38(2), 105–115. https://doi.org/10.1080/07408170500245570
  13. Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software (2nd edi.). Springer US. https://doi.org/10.1007/978-0-387-45283-8
  14. Ding, J., Dong, W., Bi, G., & Liang, L. (2015). A decision model for supplier selection in the presence of dual-role factors. Journal of the Operational Research Society, 66(5), 737–746. https://doi.org/10.1057/jors.2014.53
  15. Ebrahimi, B. (2020). Efficiency measurement to identify the best efficient unit in the presence of dual-role factors. International Journal of Applied Decision Sciences, 13(1). ­https://doi.org/10.1504/­2020.10020424
  16. Ebrahimi, B., Tavana, M., Kleine, A., & Dellnitz, A. (2021). An epsilon-based data envelopment analysis approach for solving performance measurement problems with interval and ordinal dual-role factors. OR Spectrum, 43(4). https://doi.org/10.1007/s00291-021-00649-6
  17. Eydi, A., & Rastgar, S. (2022). A DEA model with dual-role factors and fuzzy data for selecting third-party reverse logistics provider, case study: Hospital waste collection. Ain Shams Engineering Journal, 13(2), 101561. https://doi.org/10.1016/J.ASEJ.2021.07.011
  18. Farell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society, Series A (General), 120(3), 253-290, https://doi.org/10.2307/2343100
  19. Farzipoor Saen, R. (2010). Restricting weights in supplier selection decisions in the presence of dual-role factors. Applied Mathematical Modelling, 34(10), 2820–2830. https://doi.org/10.1016/­apm.2009.12.016
  20. Geng, C., Wang, Q., & E, H. (2019). Application of Fuzzy Bilateral Boundary DEA Model in Selection of Energy-Saving and Environmental Protection Enterprises. Transactions of Nanjing University of Aeronautics and Astronautics, 36(2). https://doi.org/10.16356/j.1005-1120.2019.02.010
  21. Ghasem, N., Kashan, A. H., & Najafi, S. E. (2024). Evaluating Supply Chains Based on the Novel Network Data Envelopment Analysis Model. Journal of Advanced Manufacturing Systems, 23(1). https://doi.org/10.1142/S0219686724500069
  22. Ghazi, A., & Lotfi, F. H. (2022). Weight restrictions for the DEA model in the presence of dual-role factors: An application to the Iranian banking sector. RAIRO - Operations Research, 56(3). https://doi.org/10.1051/ro/2021162
  23. Ghiyasi, M., & Cook, W. D. (2021). Classifying dual role variables in DEA: The case of VRS. Journal of the Operational Research Society, 72(5), 1183–1190. https://doi.org/10.1080/01605682.2020.1790309
  24. Izadikhah, M., Saen, R. F., & Ehsanifar, M. (2022). A Modified-Range Directional Measure for Assessing the Sustainability of Suppliers by DEA/UTASTAR. Journal of Global Information Management, 30(8). https://doi.org/10.4018/jgim.298679
  25. Kumar, A., Jain, V., & Kumar, S. (2014). A comprehensive environment friendly approach for supplier selection. Omega (United Kingdom), 42(1), 109–123. https://doi.org/10.1016/j.omega.2013.04.003
  26. Lee, K.-H., & Farzipoor Sean, R. (2012). Measuring corporate sustainability management: A data envelopment analysis approach. International Journal of Production Economics, 140(1), 219–226. https://doi.org/10.1016/j.ijpe.2011.08.024
  27. Li, F., Deng, L., Li, L., Cheng, Z., & Yu, H. (2020). A two-stage model for monitoring the green supplier performance considering dual-role and undesirable factors. Asia Pacific Journal of Marketing and Logistics, 32(1). https://doi.org/10.1108/APJML-02-2019-0110
  28. Mahdiloo, M., Noorizadeh, A., & Saen, R. F. (2013). A new model for suppliers ranking in the presence of both dual-role factors and undesirable outputs. International Journal of Logistics Systems and Management, 15(1). https://doi.org/10.1504/IJLSM.2013.053240
  29. Noorizadeh, A., Mahdiloo, M., & Saen, R. F. (2012). A new approach for considering a dual-role factor in data envelopment analysis. International Journal of Operational Research, 14(2). https://doi.org/10.1504/IJOR.2012.046645
  30. Sadeghi, S. A. H., Ahmady, N., & Ahmady, E. (2012). Technology selection in the presence of fuzzy data and dual-role factors. International Journal of Advanced Manufacturing Technology, 62(5–8), 801–811. https://doi.org/10.1007/s00170-011-3818-0
  31. Shabani, A., Torabipour, S. M. R., & Farzipoor Saen, R. (2011). Container selection in the presence of partial dual-role factors. International Journal of Physical Distribution and Logistics Management, 41(10). https://doi.org/10.1108/09600031111185257
  32. Su, Y., & Sun, W. (2018). Sustainability evaluation of the supply chain with undesired outputs and dual-role factors based on double frontier network DEA. Soft Computing, 22(16). https://doi.org/10.1007­/s00500-018-3240-8
  33. Talluri, S., & Baker, R. C. (2002). Production, Manufacturing and Logistics A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3), 544-558. https://doi.org/10.1016/S0377-2217(01)00277-6
  34. Toloo, M., & Barat, M. (2015). On considering dual-role factor in supplier selection problem. Mathematical Methods of Operations Research, 82(1), 107–122. https://doi.org/10.1007/s00186-015-0507-z
  35. Toloo, M., Keshavarz, E., & Hatami-Marbini, A. (2018). Dual-role factors for imprecise data envelopment analysis. Omega, 77, 15–31. https://doi.org/10.1016/j.omega.2017.05.005
  36. Azizi, H., Jafari Shaerlar, A., & Farzipoor Saen, R. (2015). A new Approach for Considering a Dual-Role Factor in Supplier Selection Problem: DEA with efficient and inefficient frontiers. Research in Production and Operations Management, 6(2), 129-144.
Industrial Management Studies
Volume 22, Issue 73
September 2024
Pages 143-184
Files
Share
How to cite
Statistics