22
Views
0
CrossRef citations to date
0
Altmetric
Research Article

A network bounded adjusted measure for dealing with dual-role factors and undesirable outputs in multi-stage systems

, &
Article: 2374290 | Received 02 Feb 2024, Accepted 25 Jun 2024, Published online: 18 Jul 2024

References

  • Akbarian, D. (2021). Network DEA based on DEA-ratio. Financial Innovation, 7(1), 73. https://doi.org/10.1186/s40854-021-00278-6
  • Avkiran, N. K., & McCrystal, A. (2012). Sensitivity analysis of network DEA: NSBM versus NRAM. Applied Mathematics and Computation, 218(22), 11226–11239. https://doi.org/10.1016/j.amc.2012.05.014
  • Banker, R. D., Charnes, A., & Cooper, W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
  • Beasley, J. E. (1990). Comparing university departments. Omega, 18(2), 171–183. https://doi.org/10.1016/0305-0483(90)90064-G
  • Charnes, A., Cooper, 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
  • Chen, X. D., Miao, Z., Wang, K. L., & Sun, C. W. (2020). Assessing eco-performance of transport sector: Approach framework, static efficiency and dynamic evolution. Transportation Research Part D: Transport and Environment, 85, 102414. https://doi.org/10.1016/j.trd.2020.102414
  • Chen, X., Wu, G., & Li, D. (2019). Efficiency measure on the truck restriction policy in China: A non-radial data envelopment model. Transportation Research Part A: Policy and Practice, 129, 140–154. https://doi.org/10.1016/j.tra.2019.08.010
  • Chodakowska, E., & Nazarko, J. (2017). Network DEA models for evaluating couriers and messengers. Procedia Engineering, 182, 106–111. https://doi.org/10.1016/j.proeng.2017.03.130
  • Cooper, W. W., Park, K. S., & Pastor, J. T. (1999). RAM: A range adjusted measure of inefficiency for use with additive models, and relations to other models and measures in DEA. Journal of Productivity Analysis, 11(1), 5–42. https://doi.org/10.1023/A:1007701304281
  • Cooper, W. W., Pastor, J. T., Borras, F., Aparicio, J., & Pastor, D. (2011). BAM: A bounded adjusted measure of efficiency for use with bounded additive models. Journal of Productivity Analysis, 35(2), 85–94. https://doi.org/10.1007/s11123-010-0190-2
  • Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-45283-8.
  • 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), 1103–1124. https://doi.org/10.1007/s00291-021-00649-6
  • Ebrahimnejad, A., & Amani, N. (2021). Fuzzy data envelopment analysis in the presence of undesirable outputs with ideal points. Complex & Intelligent Systems, 7(1), 379–400. https://doi.org/10.1007/s40747-020-00211-x
  • Ebrahimnejad, A., Tavana, M., & Mansourzadeh, S. M. (2015). An interactive MOLP method for solving output-oriented DEA problems with undesirable factors. Journal of Industrial and Management Optimization, 11(4), 1089–1110. https://doi.org/10.3934/jimo.2015.11.1089
  • Esfidani, S., Lotfi, F., Razavyan, S., & Ebrahimnejad, A. (2020). Efficiency changes index in the network data envelopment analysis with non-radial model. Asian-European Journal of Mathematics, 13(2), 2050031–17. https://doi.org/10.1142/S179355712050031X
  • Fare, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. https://doi.org/10.1016/S0038-0121(99)00012-9
  • Ghazi, A., & Lotfi, F. (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), 1947–1968. https://doi.org/10.1051/ro/2021162
  • 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
  • Izadikhah, M., Saen, R. F., & Ahmadi, K. (2017). How to assess sustainability of suppliers in the presence of dual-role factor and volume discounts? A data envelopment analysis approach. Asia-Pacific Journal of Operational Research, 34(3), 1740016. https://doi.org/10.1142/S0217595917400164
  • 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), 1–38. https://doi.org/10.4018/JGIM.298679
  • Jahanshahloo, G. R., Lotfi, F. H., Shoja, N., Tohidi, G., & Razavyan, S. (2005). Undesirable inputs and outputs in DEA models. Applied Mathematics and Computation, 169(2), 917–925. https://doi.org/10.1016/j.amc.2004.09.069
  • Kachouei, M., Ebrahimnejad, A., & Valami, H. B. (2020). A common-weights approach for efficiency evaluation in fuzzy data envelopment analysis with undesirable outputs: Application in banking industry. Journal of Intelligent & Fuzzy Systems, 39(5), 7705–7722. https://doi.org/10.3233/JIFS-201022
  • Kalantary, M., & Saen, R. F. (2019). Assessing sustainability of supply chains: An inverse network dynamic DEA model. Computers & Industrial Engineering, 135, 1224–1238. https://doi.org/10.1016/j.cie.2018.11.009
  • Khoshroo, A., Izadikhah, M., & Emrouznejad, A. (2021). Energy efficiency and congestion considering data envelopment analysis and bounded adjusted measure: A case of tomato production. Journal of Cleaner Production, 328, 129639. https://doi.org/10.1016/j.jclepro.2021.129639
  • Khoveyni, M., & Eslami, R. (2022). Merging two-stage series network structures: A DEA-based approach. OR Spectrum, 44(1), 273–302. https://doi.org/10.1007/s00291-021-00653-w
  • Li, W. H., Li, Z. P., Liang, L., & Cook, W. D. (2017). Evaluation of ecological systems and the recycling of undesirable outputs: An efficiency study of regions in China. Socio-Economic Planning Sciences, 60, 77–86. https://doi.org/10.1016/j.seps.2017.03.002
  • Liu, W. B., Meng, W., Li, X. X., & Zhang, D. Q. (2010). DEA models with undesirable inputs and outputs. Annals of Operations Research, 173(1), 177–194. https://doi.org/10.1007/s10479-009-0587-3
  • Lozano, S., & Gutiérrez, E. (2014). A slacks-based network DEA efficiency analysis of European airlines. Transportation Planning and Technology, 37(7), 623–637. https://doi.org/10.1080/03081060.2014.935569
  • Majdi, M., Ebrahimnejad, A., & Azizi, A. (2023). Common-weights fuzzy DEA model in the presence of undesirable outputs with ideal and anti-ideal points: Development and prospects. Complex & Intelligent Systems, 9(6), 6223–6240. https://doi.org/10.1007/s40747-023-01030-6
  • Maleki, S., Ebrahimnejad, A., & Kazemi Matin, R. (2019a). Pareto–Koopmans efficiency in two-stage network data envelopment analysis in the presence of undesirable intermediate products and nondiscretionary factors. Expert Systems, 36(e12393), 1–20. https://doi.org/10.1111/exsy.12393
  • Maleki, S., Ebrahimnejad, A., & Kazemi Matin, R. (2019b). Two-stage network DEA with convex hull in intermediate products. Hacettepe Journal of Mathematics and Statistics, 48(1), 312–331. https://doi.org/10.15672/HJMS.2018.610
  • Maleki, S., & Kazemi Matin, R. (2019). A Russell-based model for estimating overall and divisional efficiency in two-stage production systems with sets of convex hulls in intermediate products. Sādhanā, 44(3), 69. https://doi.org/10.1007/s12046-019-1061-9
  • Mirhedayatian, S. M., Azadi, M., & Saen, R. F. (2014). A novel network data envelopment analysis model for evaluating green supply chain management. International Journal of Production Economics, 147, 544–554. https://doi.org/10.1016/j.ijpe.2013.02.009
  • Mo, R., Huang, H., & Yang, L. (2020). An interval efficiency measurement in DEA when considering undesirable outputs. Complexity, 2020, 1–12. https://doi.org/10.1155/2020/7161628
  • Nasseri, S. H., Ebrahimnejad, A., & Gholami, O. (2018). Fuzzy stochastic data envelopment analysis with undesirable outputs and its application to banking industry. International Journal of Fuzzy Systems, 20(2), 534–548. https://doi.org/10.1007/s40815-017-0367-1
  • Pastor, J. T., Aparicio, J., Alcaraz, J., Vidal, F., & Pastor, D. (2015). An enhanced BAM for unbounded or partially bounded CRS additive models. Omega, 56, 16–24. https://doi.org/10.1016/j.omega.2015.02.009
  • Rashidi, K., & Saen, R. F. (2015). Measuring eco-efficiency based on green indicators and potentials in energy saving and undesirable output abatement. Energy Economics, 50, 18–26. https://doi.org/10.1016/j.eneco.2015.04.018
  • Saen, R. F. (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/j.apm.2009.12.016
  • Shi, Y., Yu, A. Y., Higgins, H. N., & Zhu, J. (2021). Shared and unsplittable performance links in network DEA. Annals of Operations Research, 303(1-2), 507–528. https://doi.org/10.1007/s10479-020-03882-4
  • Song, W. J., Ren, J. W., Chen, C. H., Feng, C. X., Li, L. Q., & Ma, C. Y. (2024). A two-stage data envelopment analysis approach incorporating the global bounded adjustment measure to evaluate the efficiency of medical waste recycling systems with undesirable inputs and outputs. Sustainability, 16(10), 4023. https://doi.org/10.3390/su16104023
  • Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197(1), 243–252. https://doi.org/10.1016/j.ejor.2008.05.027
  • Wu, G., Zhu, C. X., Jiang, J. H., & Chen, X. D. (2022). Fuel consumption, vehicle quantities, and total factor inefficiency in China. Chinese Journal of Population, Resources and Environment, 20(2), 147–158. https://doi.org/10.1016/j.cjpre.2022.06.005
  • Yadollahi, A. H., Ebrahimnejad, A., & Kazemi Matin, R. (2022). Centralized resource reallocation in two-stage network structures with undesirable products. Computational and Applied Mathematics, 41(6), 228. https://doi.org/10.1007/s40314-022-01909-z
  • Yan, Q. Y., Zhao, F., Wang, X., Yang, G. L., Baležentis, T., & Streimikiene, D. (2019). The network data envelopment analysis models for non-homogenous decision making units based on the sun network structure. Central European Journal of Operations Research, 27(4), 1221–1244. https://doi.org/10.1007/s10100-018-0560-9
  • Yi, M., Peng, J., Zhang, L., & Zhang, Y. (2020). Is the allocation of medical and health resources effective? Characteristic facts from regional heterogeneity in China. International Journal for Equity in Health, 19(1), 89. https://doi.org/10.1186/s12939-020-01201-8
  • Zhao, T. Y., Xie, J. H., Chen, Y., & Liang, L. (2022). Coordination efficiency in two-stage network DEA: Application to a supplier–manufacturer sustainable supply chain. International Journal of Logistics Research and Applications, 25(4-5), 656–677. https://doi.org/10.1080/13675567.2021.1895976

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.