A New Inverse DEA Method for Input Estimation and Efficiency Improvement in Network Systems by a Two-Stage Structure

Authors

https://doi.org/10.48314/jidcm.v1i2.69

Abstract

Inverse Data Envelopment Analysis (InvDEA) is a helpful tool for estimating the inputs/outputs of Decision-Making Units (DMUs) in order to achieve an unchanged efficiency score. This paper first provides an InvDEA method for input estimation in the two-stage network systems when the efficiency score of all units is fixed. Then, an InvDEA method is developed in order to improve the efficiency of all DMUs. Finally, a case study is presented to show the capabilities of the proposed methods.

Keywords:

Data envelopment analysis, Inverse data envelopment analysis, Network data envelopment analysis, Two-stage network, Input estimation, Efficiency improvement

References

  1. [1] Wei, Q., Zhang, J., & Zhang, X. (2000). An inverse DEA model for inputs/outputs estimate. European journal of operational research, 121(1), 151–163. https://doi.org/10.1016/S0377-2217(99)00007-7
  2. [2] Yan, H., Wei, Q., & Hao, G. (2002). DEA models for resource reallocation and production input/output estimation. European journal of operational research, 136(1), 19–31. https://doi.org/10.1016/S0377-2217(01)00046-7
  3. [3] Jahanshahloo, G. R., Hosseinzadeh Lotfi, F., Shoja, N., Tohidi, G., & Razavyan, S. (2004). The outputs estimation of a DMU according to improvement of its efficiency. Applied mathematics and computation, 147(2), 409–413. https://doi.org/10.1016/S0096-3003(02)00734-8
  4. [4] Lertworasirikul, S., Charnsethikul, P., & Fang, S. C. (2011). Inverse data envelopment analysis model to preserve relative efficiency values: The case of variable returns to scale. Computers & industrial engineering, 61(4), 1017–1023. https://doi.org/10.1016/j.cie.2011.06.014
  5. [5] Eyni, M., Tohidi, G., & Mehrabeian, S. (2017). Applying inverse DEA and cone constraint to sensitivity analysis of DMUs with undesirable inputs and outputs. Journal of the operational research society, 68(1), 34–40. https://doi.org/10.1057/s41274-016-0004-7
  6. [6] Amin, G. R., Al-Muharrami, S., & Toloo, M. (2019). A combined goal programming and inverse DEA method for target setting in mergers. Expert systems with applications, 115, 412–417. https://doi.org/10.1016/j.eswa.2018.08.018
  7. [7] Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management science, 45(9), 1270–1288. https://doi.org/10.1287/mnsc.45.9.1270
  8. [8] 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. https://doi.org/10.1016/j.ejor.2006.11.041
  9. [9] 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/10.1016/0377-2217(78)90138-8

Downloads

Published

2025-06-21

Issue

Vol. 1 No. 2 (2025): Journal of Intelligent Decision and Computational Modelling (JIDCM)

Section

Articles

How to Cite

Tohidi, G. . (2025). A New Inverse DEA Method for Input Estimation and Efficiency Improvement in Network Systems by a Two-Stage Structure. Journal of Intelligent Decision and Computational Modelling, 1(2), 138-147. https://doi.org/10.48314/jidcm.v1i2.69

Similar Articles

You may also start an advanced similarity search for this article.