| تعداد نشریات | 49 |
| تعداد شمارهها | 1,278 |
| تعداد مقالات | 11,036 |
| تعداد مشاهده مقاله | 22,775,277 |
| تعداد دریافت فایل اصل مقاله | 15,396,671 |
A Two-Stage Network DEA Model Under Hybrid Disposability Technology: An Application to Healthcare Centers | ||
| Control and Optimization in Applied Mathematics | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 04 خرداد 1405 اصل مقاله (467.71 K) | ||
| نوع مقاله: Applied Article | ||
| شناسه دیجیتال (DOI): 10.30473/coam.2026.75411.1330 | ||
| نویسندگان | ||
| Javad Gerami* 1؛ Alireza Alireza Davoodi2 | ||
| 1Department of Mathematics, Shi.C., Islamic Azad University, Shiraz, Iran | ||
| 2Department of Mathematics, Ne.C., Islamic Azad University, Neyshabur, Iran | ||
| چکیده | ||
| Two-stage network Data Envelopment Analysis (DEA) models under variable returns to scale (VRS) suffer from a well-known pitfall: efficiency score decomposition and frontier projection can be mutually inconsistent, undermining both the theoretical foundations and practical interpretability of the results. A further limitation is the universal assumption of strong disposability for all inputs and outputs, which is unrealistic when variables are structurally or statistically interdependent—as is common in healthcare settings. This paper addresses both issues simultaneously by developing a novel two-stage network DEA model under hybrid disposability (HD) technology, which allows selective strong or weak disposability for subsets of closely related inputs, intermediate measures, and outputs. We formally derive the efficiency decomposition and frontier projection under HD technology, establish theoretical consistency between the envelopment and multiplier forms, and prove that the proposed model yields Pareto-efficient targets. The model captures synergistic scale effects across stages and preserves structural dependencies between them, thereby providing a more realistic representation of multi-stage production systems. The practical relevance and advantages of the proposed framework are demonstrated through an empirical case study involving 32 Iranian healthcare centers operating under a two-stage network structure with interdependent variables. | ||
تازه های تحقیق | ||
| ||
| کلیدواژهها | ||
| Data envelopment analysis؛ Two-stage network DEA؛ Hybrid disposability؛ Variable returns to scale؛ Efficiency decomposition؛ Frontier projection؛ Healthcare performance evaluation | ||
| مراجع | ||
|
[1] Banker, R.D., Charnes, A., & Cooper, W.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 [2] 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 [3] Chen, Y., Cook, W.D., Li, N. & Zh, J. (2009). “Additive efficiency decomposition in two-stage DEA”. European Journal of Operational Research, 196(3), 1170–1176. https: //doi.org/10.1016/j.ejor.2008.05.011 [4] Chen, Y., Cook, W. D., & Zhu, J. (2010). “Deriving the DEA frontier for two-stage processes”. European Journal of Operational Research, 202(1), 138–142. https://doi. org/10.1016/j.ejor.2009.05.012 [5] Chen, Y., Cook, W. D., Kao, C., & Zhu, J. (2013). “Network DEA pitfalls: Divisional efficiency and frontier projection under general network structures”. European Journal of Operational Research, 226(3), 507–515. https://doi.org/10.1016/j.ejor.2012. 11.021 [6] Chen, L., & Wang, Y.-M. (2025). “Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale”. European Journal of Operational Research, 322(1), 157–170. https://doi.org/10.1016/j.ejor.2024.10.011 [7] Chu, J., Zhu, J. (2021). “Production scale-based two-stage network data envelopment analysis”.European Journal of Operational Research, 294(1), 283–294, https://doi.org/ 10.1016/j.ejor.2021.01.020 [8] Dar, K. H., & Raina, S. H. (2024). “Public healthcare efficiency in India: Estimates and determinants using two-stage DEA approach”. Evaluation and Program Planning, 106, Article 102472. https://doi.org/10.1016/j.evalprogplan.2024.102472 [9] Deng, G., Pan, Y., Feng, C., & Liang, L. (2024). “The efficiency of residency training and health outcomes in China: Based on two-stage DEA and cluster analysis”. Socio-Economic Planning Sciences, 96, Article 102057. https://doi.org/10.1016/ j.seps.2024.102057 [10] Ding, T., Zhang, Y., Zhang, D., et al. (2023). “Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs”. Socio-Economic Planning Sciences, 87, Article 101582. https://doi.org/10. 1016/j.seps.2023.101582 [11] Emrouznejad, A., Yang, G. L., & Zhang, W. G. (2018). “A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016”. Socio-Economic Planning Sciences, 61, 4–8. https://doi.org/10.1016/j.seps.2017.01.008 [12] Färe, R., Grosskopf, S., Lovell, C.A.K. (1985). “The measurement of efficiency of production”.Springer Dordrecht. https://doi.org/10.1007/978-94-015-7721-2 [13] Førsund, F.R., Sarafoglou, N. (2002). “On the origins of data envelopment analysis”. Journal of Productivity Analysis, 17(1–2), 23–40. https://doi.org/10.1023/A: 1013519902012 [14] Gearhart, R. S., Michieka, N. M. (2018). “A comparison of the robust conditional order-m estimation and two-stage DEA in measuring healthcare efficiency among California counties”. Economic Modelling, 73, 395–406. https://doi.org/10.1016/j. econmod.2018.04.015 [15] Gerami, J., Kiani Mavi, R., Farzipoor Saen, R., & Kiani Mavi, N. (2023). “A novel network DEA-R model for evaluating hospital services supply chain performance”. Annals of Operations Research, 324(1–2), 1041–1066. https://doi.org/10.1007/ s10479-020-03755-w [16] Guo, C., Zhang, J., Zhang, L. (2020). “Two-stage additive network DEA: Duality, frontier projection and divisional efficiency”. Expert Systems with Applications, 157, Article 113478. https://doi.org/10.1016/j.eswa.2020.113478 [17] 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 [18] Kao, C. (2018). “A classification of slacks-based efficiency measures in network data envelopment analysis with an analysis of the properties possessed”. European Journal of Operational Research, 270(3), 1109–1121. https://doi.org/10.1016/j.ejor.2018. 04.036 [19] Khushalani, J., & Ozcan, Y. A. (2017). “Are hospitals producing quality care efficiently? An analysis using dynamic network data envelopment analysis (DEA)”. Socio-Economic Planning Sciences, 60, 15–23. https://doi.org/10.1016/j.seps.2017.01.009 [20] Kuosmanen, T. (2005). “Weak disposability in nonparametric productivity analysis with undesirable outputs”. American Journal of Agricultural Economics, 87(4), 1077–1082. https://doi.org/10.1111/j.1467-8276.2005.00788.x [21] Lim, S., & Zhu, J. (2019). “Primal-dual correspondence and frontier projections in twostage network DEA models”. Omega, 83, 236–248. https://doi.org/10.1016/j. omega.2018.06.005 [22] Mehdiloozad, M., & Podinovski, V. V. (2018). “Nonparametric production technologies with weakly disposable inputs”. European Journal of Operational Research, 266(1), 247– 258. https://doi.org/10.1016/j.ejor.2017.09.030 [23] Mehdiloo, M., & Podinovski, V. V. (2019). “Selective strong and weak disposability in efficiency analysis”. European Journal of Operational Research, 276(3), 1154–1169. https://doi.org/10.1016/j.ejor.2019.01.064 [24] Michali, M., Emrouznejad, A., Dehnokhalaji, A., & Clegg, B. (2023). “Subsampling bootstrap in network DEA”. European Journal of Operational Research, 305(2), 766–780. https://doi.org/10.1016/j.ejor.2022.06.022 [25] Patrizii, V. (2020). “On network two-stages variable returns to scale DEA models”. Omega, 97, Article 102084. https://doi.org/10.1016/j.omega.2019.06.010 [26] Paramanik, A. R., Sarkar, S., & Sarkar, B. (2023). “A two-stage improved base point slacks-based measure of super-efficiency for negative data handling”. Computers and Operations Research, 150, Article 106057. https://doi.org/10.1016/j.cor.2022. 106057 [27] Pham, M. D., & Zelenyuk, V. (2019). “Weak disposability in nonparametric production analysis: A new taxonomy of reference technology sets”. European Journal of Operational Research, 274(1), 186–198. https://doi.org/10.1016/j.ejor.2018.09. 019 [28] Podinovski, V. V., Wu, J., & Argyris, N. (2024). “Production trade-offs in models of data envelopment analysis with ratio inputs and outputs: An application to schools in England”. European Journal of Operational Research, 313(1), 359–372. https://doi.org/10. 1016/j.ejor.2023.08.019 [29] Roshdi, I., Mahdiloo, M., Arjomandi, A., & Margaritis, D. (2023). “On second order cone programming approach to two-stage network data envelopment analysis”. European Journal of Operational Research, 309(2), 953–956. https://doi.org/10.1016/j.ejor. 2023.02.022 [30] Pourmahmoud, J., Abbasi, A., Ghaffari-Hadigheh, A. (2025). “Network data envelopment analysis and uncertainty in decision-making: A three-Stage model based on Liu’s uncertainty theory”. Control and Optimization in Applied Mathematics, 10(2), 103-133. https://doi.org/10.30473/coam.2025.73893.1293 [31] Shi, X., Wang, L., & Emrouznejad, A. (2023). “Performance evaluation of Chinese commercial banks by an improved slacks-based DEA model”. Socio-Economic Planning Sciences, 90, Article 101702. https://doi.org/10.1016/j.seps.2023.101702 [32] 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 [33] Tone, K., & Tsutsui, M. (2014). “Dynamic DEA with network structure: A slacks-based measure approach”. Omega, 42(1), 124–131. https://doi.org/10.1016/j.omega. 2013.03.002 [34] Yang, L., Chen, S., Chiu, Y., et al. (2024). “Reassessment of industrial eco-efficiency in China under the sustainable development goals: A meta two-stage parallel entropy dynamic DDF-DEA model”. Journal of Cleaner Production, 447, Article 141275. https://doi.org/10.1016/j.jclepro.2024.141275 [35] Zhao, T., Xie, J., Chen, Y., et al. (2022). “Coordination efficiency for general two-stage network system”. RAIRO-Operations Research, 56(6), 3801–3815. https://doi.org/ 10.1051/ro/2022180 [36] Zhang, M., Li, W., Zhang, L., et al. (2023a). “A Pearson correlation-based adaptive variable grouping method for large-scale multi-objective optimization”. Information Sciences, 639, Article 118737. https://doi.org/10.1016/j.ins.2023.02.055 [37] Zhang, X. Q., Xia, Q., Wei, F. Q. (2023b). “Efficiency evaluation of two-stage parallel series structures with fixed-sum outputs: An approach based on SMAA and DEA. Expert Systems with Applications, 227, Article 120264. https://doi.org/10.1016/j.eswa. 2023.120264 [38] Zhu, J. (2022). “DEA under big data: Data enabled analytics and network data envelopment analysis”. Annals of Operations Research, 309(2), 761–783. https://doi.org/ 10.1007/s10479-020-03668-8 | ||
|
آمار تعداد مشاهده مقاله: 9 تعداد دریافت فایل اصل مقاله: 5 |
||