Inverse Data Envelopment Analysis Models for Inputs/Outputs Estimation in Two-Stage Processes

Authors

DOI:

https://doi.org/10.31181/dmame8120251091

Keywords:

Data Envelopment Analysis (DEA), Inverse DEA, Two-Stage Structure, Middle Products, Window DEA

Abstract

Considering the interior of decision-making units (DMUs) is essential when evaluating a system's performance in the practical and real-world circumstances. Knowing what happens inside a DMU allows a more accurate study of relevant process. It identifies the efficiency, and inefficiency of the sub-units in the system being evaluated. This study focuses on two-stage inverse data envelopment analysis (DEA) problems. In these problems, a portion of the outputs from the first period is used as inputs in the second stage. For this purpose, several models are offered to address the input/output estimation problem, in which decision makers should deal with intermediate products and shared and non-shared inputs in a two-stage system. Furthermore, the proposed models are examined using a window DEA because of the importance of assessing repetitive processes in some two-stage systems. Next, an Iranian bank is considered as a case study to further elucidate using the presented models. Finally, we present a conclusion and suggestions for further research.

Downloads

Download data is not yet available.

References

Charnes, A., Cooper, W. W. & Rhodes, E. (1978). Measuring the efficiency of decision-making units, Eur. J. Oper. Res., 2, 429-444. https://doi.org/10.1016/0377-2217(78)901388.

Wei, Q., Zhang, J., & Zhang, X. (2000). An inverse DEA model for inputs/outputs estimate, Eur. J. Oper. Res., 121, 151-163. https://doi.org/10.1016/S0377-2217(99)00007-7.

Hadi-Vencheh, A., Foroughi, A. A., & Soleimani-damaneh, M. (2008). A DEA model for resource allocation, Econ. Model., 25, 983-993. https://doi.org/10.1016/j.econmod.2008.01.003.

Izadikhah, M., Tavana, M., & Di Caprio, D. & Santos-Arteaga, F. J. (2018). A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs, Expert Syst. Appl., 99, 213-230. https://doi.org/10.1016/j.eswa.2017.11.005.

Jianfeng, M. A. (2015). A two - stage DEA model considering shared inputs and free intermediate measures, Expert Syst. Appl., 42, 4339-4347. https://doi.org/10.1016/j.eswa.2015.01.040.

Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies data envelopment analysis, J. Manag. Sci., 30, 1078 - 1092. https://doi.org/10.1287//mnsc.30.9.1078.

Byrnes, P., Färe, R., & Grosskopf, S. (1984). Measuring productive efficiency: an application to Illinois strip mines, J. Manag. Sci., 30, 671-68. https://doi.org/10.1287/mnsc.30.6.671.

Kao, C. (1995). Some properties of Pareto efficiency under the framework of data envelopment analysis, Int. J. Syst. Sci., 26, 1549-1558. https://doi.org/10.1080/00207729508929118.

Charnes, A., Cooper, W. W., Golany, B., Halek, R., Klopp, G., Schmitz, E., & Thomas, D. (1986). Two phase data envelopment analysis approach to policy evaluation and management of army recruiting activities: Tradeoffs between joint services and army advertising, The University of Texas, Texas.

Lewis, H. F., Mallikarjun, S., & Sexton, T. R. (2013). Unoriented two - stage DEA: The case of the oscillating intermediate products, Eur. J. Oper. Res., 229, 529 – 539. https://doi.org/10.1016/j.ejor.2013.02.058.

Wang, K., Huang, W., Wu, J., & Liu, Y. N. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA, Omega, 44, 5-20. https://doi.org/10.1016/j.omega.2013.09.005.

Färe, R., & Grosskopf, S. (1996). Productivity and intermediate products: A frontier approach, Econ. Lett., 50, 65-70 https://doi.org/10.1016/0165-1765(95)00729-6.

Chen, Y., Cook, W. D., & Zhu, J. (2010). Deriving the DEA frontier for two-stage processes, Eur. J. Oper. Res., 202, 138-142. https://doi.org/10.1016/j.ejor.2009.05.012.

Liang, L., Cook, W. D., & Zhu, J. (2008). DEA models for two ‐ stage processes: Game approach and efficiency decomposition, NRL, 55, 643-653. https://doi.org/10.1002/nav.20308.

Chen, Y., Cook, W. D., Li, N., & Zhu, J. (2009). Additive efficiency decomposition in two-stage DEA, Eur. J. Oper. Res., 196, 1170-1176. https://doi.org/10.1016/j.ejor.2008.05.011.

Du, J., Liang, L., Chen, Y., Cook, W. D., & Zhu, J. (2011). A bargaining game model for measuring performance of two-stage network structures, Eur. J. Oper. Res., 210, 390-397. http://dx.doi.org/10.1016/j.ejor.2010.08.025.

Yu, Y., Shi, Q. F., & Song, J. (2013). A note on some alternative DEA models for two-stage process, Expert Syst. Appl., 40, 4268-4269. http://dx.doi.org/10.1016/j.eswa.2013.01.022.

Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non- life insurance companies in Taiwan, Eur. J. Oper. Res., 185, 418 - 429. https://doi.org/10.1016/j.ejor.2006/j.ejor.2006.11.041.

Yu, M. M., & Fan, C. K. (2006). Measuring the cost effectiveness of multimode bus transit in the presence of accident risks, Transp. Plan. Technol., 29, 383-407. https://doi.org/10.1080/03081060600917728.

Chen, Y., Du, J., Sherman, H. D., & Zhu, J. (2010). DEA model with shared resources and efficiency decomposition, Eur. J. Oper. Res., 207, 339-349. https://doi.org/10.1016/j.ejor.2010.03.031.

Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation, Ann. Oper. Res., 145, 35-49. DOI: 10.1007/s10479-006-0026-7.

Chen, Y., Cook, W. D., & Zhu, J. (2014). Network DEA pitfalls: Divisional efficiency and frontier projection. In Data envelopment analysis, Springer, 31-54. https://doi.org/ 10.1016/j.ejor.2012.11.021.

Castelli, L., Pesenti, R., & Ukovich, W. (2010). A classification of DEA models when the internal structure of the decision-making units is considered, Ann. Oper. Res., 173, 207-235. DOI 10.1007/s10479-008-0414-2.

Fukuyama, H., & Weber, W. L. (2010). A slacks-based inefficiency measure for a two-stage system with bad outputs, Omega, 38, 398-409. DOI: 10.1016/j.omega.2009.10.006.

Liu, J. S., Lu, L. Y., & Lu, W. M. (2016). Research fronts in data envelopment analysis, Omega, 58, 33-45. https://doi.org/10.1016/j.omega.2015.04.004.

Cook, W. D., Liang, L., & Zhu, J. (2010). Measuring performance of two - stage network structures by DEA: A review and future perspective, Omega, 38, 423-430. https://doi.org/10.1016/j.omega.2009.12.001.

Zha, Y., & Liang, L. (2010). Two - stage cooperation model with input freely distributed among the stages, Eur. J. Oper. Res., 205, 332-338. http://dx.doi.org/10.1016/j.ejor.2010.01.010.

Yu, Y., & Shi, Q. (2014). Two - stage DEA model with additional input in the second stage and part of intermediate products as final output, Expert Syst. Appl., 41 (2014), 6570-6574. http://dx.doi.org/10.1016/ j.eswa.2014.05.021.

Zhang, X. S., & Cui, J. C. (1999). A project evaluation system in the state economic information system of china an operations research practice in public sectors, Int Trans Oper Res, 6, 441- 452. http://dx.doi.org/10.1111/j.1475-3995-1999.tb00166.x.

Jahanshahloo, G. R., Vencheh, A. H., Foroughi, A. A., & Matin, R. K. (2004). Inputs/outputs estimation in DEA when some factors are undesirable, Appl. Math. Comput., 156, 19-32. http://dx.doi.org/10.1016/S0096-3003(03)00814-2.

Jahanshahloo, G. R., Lotfi, F. H., Shoja, N., Tohidi, G., & Razavyan, S. (2004). Input estimation and identification of and identification of extra inputs in inverse DEA models, Appl. Math. Comput., 156, 427-437. http://dx.doi.org/10.1016/j.amc.2003.08.001.

Jahanshahloo, G. R., Soleimani-Damaneh, M., & Ghobadi, S. (2015). Inverse DEA under inter- temporal dependence using multiple-objective programming, Eur. J. Oper. Res., 240, 447- 456. http://dx.doi.org/10.1016/j.ejor.2014.07.002.

Ghobadi, S., & Jahangiri, S. (2015). Inverse DEA: review, extension and application, Int J Inf Technol Decis Mak., 14, 805-824. http://dx.doi.org/10.1142/S0219622014500370.

Ghiyasi, M. (2017). Inverse DEA based on cost and revenue efficiency, CAIE, 114, 258 - 263. http://dx.doi.org/10.1016/j.cie.2017.10.024.

Cook, W. D., & Hababou, M. (2001). Sales performance measurement in bank branches, Omega, 29, 299 - 307. https://doi.org/10.1016/S0305-0483(01)00025-1.

Charnes, A., & Cooper, W. W. (1962). Programming with linear fractional functionals, Nav. Res. Logist. Q. 9, 181- 186. http://dx.doi.org/10.1002/nav.3800090303.

Jahanshahloo, G. R., Soleimani-Damaneh, M., & Reshadi, M. (2006).On Pareto (dynamically) efficient paths, Int. J. Comput. Math. 83, 631-635. https://doi.org/10.1080/00207160601056099.

Emrouznejad, A., & Thanassoulis, E. (2005). A mathematical model for dynamic efficiency using data envelopment analysis, Appl. Math. Comput., 160, 363-378. https://doi.org/10.1080/00207160601056099.

Ehrgott, M. (2005). Multicriteria optimization, Springer Science & Business Media, 491. https://doi.org/10.1007/3-540-27659-9.

Published

2024-08-16

How to Cite

Moradi, H., Hosseinzadeh Lotfi, F., & Rostamy-Malkhalifeh, M. (2024). Inverse Data Envelopment Analysis Models for Inputs/Outputs Estimation in Two-Stage Processes. Decision Making: Applications in Management and Engineering, 8(1), 82–107. https://doi.org/10.31181/dmame8120251091