Input Estimation in Two-Stage Systems with Undesirable Outputs Based on Cost Efficiency

Subject Areas : International Journal of Data Envelopment Analysis

Zahra Shiri Daryani ¹ , Shabnam Razavyan ²

1 - Department of Mathematics, Islamic Azad University, South Tehran Branch, Tehran, Iran
2 - Department of Mathematics, Islamic Azad University, South Tehran Branch, Tehran, Iran

Received: 2021-07-09 Accepted : 2021-10-13 Published : 2021-11-01

Keywords:

References:

[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.

 

[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.

 

[3] Jahanshahloo, G. R., Lotfi, F. H., Shoja, N., Tohidi, G., & Razavyan, S. (2004a). The outputs estimation of a DMU according to improvement of its efficiency. Applied Mathematics and Computation, 147(2), 409–413.

 

[4] Hadi-Vencheh, A., Foroughi, A.A., (2006). A generalized DEA model for inputs/outputs estimation, Mathematical and Computer Modeling, 43, 447-457.

 

[5] 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, 1017–1023.

 

[6] Eyni, M., Tohidi, G., Mehrabian, S., (2016). 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.

 

[7] Ghiyasi, M., (2017b). Industrial sector environmental planning and energy efficiency of Iranian provinces, 142 (4), 2328-2339.

 

[8] An, Q., Liu, X., Li, Y., Xiong, B., (2019), Resource planning of Chinese commercial banking systems using two stage, PLoS ONE, 14 (6), e0218214.

 

[9] Hu, X., Li, J., Li, X., Cui, J., (2020). A revised inverse data envelopment analysis model based on radial models, Mathematics, 8, 803.

 

[10] Ghobadi, S. (2018). Inverse DEA using enhanced Russell measure in the presence of fuzzy data. Int. J. Ind. Math., 10, 165–180.

 

[11] Zhang, G., Cui, J., (2020), A general inverse DEA model for non-radial DEA, Computer and Industrial Engineering, 142.

 

[12] Emrouznejad, A.,Yang, G., Amin, G.R., (2019). A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries, Journal of the Operational Research Society, 70 (7), 1079-1090.

 

[13] Wegener, M., Amin, G.R., (2019). Minimizing greenhouse gas emissions using inverse DEA with an application in oil and gas, Expert Systems with Applications, 122, 369-375.

 

[14] Chen, Y., Chen, M., Li, T., (2021). China's CO2 emissions reduction potential: A novel inverse DEA model with frontier changes and comparable value. Energy Strategy Reviews, 38, 100762.

 

[15] Gattoufi, S., Amin, G. R., & Emrouznejad, A., (2014). A new inverse DEA method for merging banks. IMA Journal of Management Mathematics, 25(1), 73–87.

 

[16] Amin, G.R., Emrouznejad, A., Gattoufi, S., (2017). Minor and major consolidations in inverse DEA: Definition and Determination, Computers & Industrial Engineering 103, 193–200.

 

[17] Amin, G.R., Al-Muharrami, S., (2016). A new inverse data envelopment analysis model for mergers with negative data, MA Journal of Management Mathematics, 29 (2), 137–149.

 

[18] Hassanzadeh, A., Yousefi., S., Farzipour Saen, R., Seyed Hosseininia, S, S., (2018). How to assess sustainability of countries via inverse data envelopment analysis? Clean Technologies and Environmental Policy, 20, 29-40.

 

[19] Ghiyasi, M., Zhu, N., (2020). An inverse semi-oriented radial data envelopment analysis measure for dealing with negative data. IMA Journal of Management Mathematics, 31(4), 505-516.

 

[20] Soltanifar, M., Ghiyasi, M., Sharafi, H. (2022a). Inverse DEA-R models for merger analysis with negative data. IMA Journal of Management Mathematics, 00, 1-20.

 

[21] Amin, G.R., Al-Muharrami, S., Mehdi Toloo, M., (2019). A combined goal programming and inverse DEA method for target setting in mergers, Expert Systems with Applications, 115, 412-417.

 

[22] Amin, G. R., & Ibn Boamah, M. (2021). A two‐stage inverse data envelopment analysis approach for estimating potential merger gains in the US banking sector. Managerial and Decision Economics, 42(6), 1454-1465.

 

[23] Soltanifar, M., Ghiyasi, M., Emrouznejad, A., Sharafie, H., (2022b).  A Novel Model for Merger Analysis and Target Setting: A Csw-Inverse DEA Approach. Available at SSRN 4115552.

 

[24] Seiford, L.M., Zhu, J., (1999). Profitability and Marketability of the Top 55 US Commercial Banks.”Management Science, 45, 1270-1288.

 

[25] Farrell, M.J., (1957). The measurement of productive efficiency, Journal of the Royal Statistical Society Series A, 120 (3), 253 – 281.

 

[26] Wang, Q., Wu, Z., Chen, X., (2019). Decomposition weights and overall efficiency in a two-stage DEA model with shared resources, Computers & Industrial Engineering, 136, 135-148.

 

[27] Wang, Y., Pan, J.F., Pie, R.M., Yi, B. W., Yang, G. L., (2020). Assessing the technological innovation efficiency of China’s high-tech industries with a two-stage network DEA approach, Socio-Economic Planning Sciences, In Press.

 

[28] Lozano, S., (2011), Scale and cost efficiency analysis of networks of processes, Expert Systems with Applications, 38, 6612–6617.

 

[29] Shi, X., Li, Y., Emrouznejhad, A., Xie, J., Liang. L., (2017). Estimation of potential gains from bank mergers: a novel two stage cost efficiency DEA model, Journal of the operational research society, 68, 1045-1055.

 

[30] Shiri Daryani, Z., Tohidi, G., Daneshian, B., Razavyan, Sh., Hosseinzadeh Lotfi, F., (2021). Inverse DEA in Two-Stage Systems Based on Allocative Efficiency, Journal of Intelligent and Fuzzy Systems, 40, 591-603.

 

[31] Ghiyasi, M., (2017a). Inverse DEA based on cost and revenue efficiency, Computers & Industrial Engineering, 114, 258–263.

 

[32] Soleimani-Chamkhorami, Kh., Hosseinzade Lotfi, F., Jahanshahloo, G. R., Rostamy-Malkhalifeh, M., (2019a), Preserving cost and revenue efficiency through inverse data envelopment analysis models, Information Systems and Operational Research, 1-18.

 

[33] Soleimani-Chamkhorami, Kh., Hosseinzade Lotfi, F., Jahanshahloo, G. R., Rostamy-Malkhalifeh, M., (2019b), A ranking system based on inverse data envelopment analysis, Journal of Management Mathematics, 1-19.

 

[34] Kalantary, M., Farzipoor Saen, R., Toloie Eshlaghy, A., (2018a). Sustainability assessment of supply chains by inverse network dynamic data envelopment analysis, Scientia Iranica, 25(6), 3723-3743.

 

[35] Kalantary, M., Farzipoor Saen, R., Toloie Eshlaghy, A., (2018b). Assessing Sustainability of Supply Chains: An Inverse Network Dynamic DEA Model, Computers & Industrial Engineering, 135, 1224-1238.

 

[36] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429–444.

 

[37] Ghiyasi, M. (2015). On inverse DEA model: The case of variable returns to scale. Computers & Industrial Engineering, 87, 407–409.

 

[38] Steuer, R.E., (1986). Multiple Criteria Optimization: Theory, Computation, and Application. Krieger Publishing, Malabar, FL.