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Original Articles

Supply chains performance with undesirable factors and reverse flows: A DEA-based approach

, , &
Pages 125-135 | Received 16 Jan 2017, Accepted 21 Dec 2017, Published online: 05 Feb 2018

References

  • Amirteimoori, A., & Khoshandam, L. (2011). A data envelopment analysis approach to supply chain efficiency. Advances in Decision Sciences, 2011, 8.
  • An, Q., Chen, H., Wu, J., & Liang, L. (2015). Measuring slacks-based efficiency for commercial banks in China by using a two-stage DEA model with undesirable output. Annals of Operations Research, 235(1), 13–35.10.1007/s10479-015-1987-1
  • An, Q., Yan, H., Wu, J., & Liang, L. (2016). Internal resource waste and centralization degree in two-stage systems: An efficiency analysis. Omega, 61, 89–99.10.1016/j.omega.2015.07.009
  • Atici, K. B., & Podinovski, V. V. (2015). Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture. Omega, 54, 72–83.10.1016/j.omega.2015.01.015
  • Azadi, M., Jafarian, M., Farzipoor Saen, R., & Mirhedayatian, S. M. (2015). A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Computers & Operations Research, 54, 274–285.10.1016/j.cor.2014.03.002
  • Balfaqih, H., Nopiah, Z. M., Saibani, N., & Al-Nory, M. T. (2016). Review of supply chain performance measurement systems: 1998–2015. Computers in Industry, 82, 135–150.10.1016/j.compind.2016.07.002
  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.10.1016/0377-2217(78)90138-8
  • Chen, J. K., & Chen, I. S. (2011). Inno-Qual efficiency of higher education: Empirical testing using data envelopment analysis. Expert Systems with Applications, 38(3), 1823–1834.10.1016/j.eswa.2010.07.111
  • Chen, Y., Liang, L., & Yang, F. (2006). A DEA game model approach to supply chain efficiency. Annals of Operations Research, 145(1), 5–13.10.1007/s10479-006-0022-y
  • Chowdhury, H., & Zelenyuk, V. (2016). Performance of hospital services in Ontario: DEA with truncated regression approach. Omega, 63, 111–122.10.1016/j.omega.2015.10.007
  • Färe, R., & Grosskopf, S. (2003). Nonparametric productivity analysis with undesirable outputs: Comment. American Journal of Agricultural Economics, 85(4), 1070–1074.10.1111/1467-8276.00510
  • Färe, R., Grosskopf, S., Lovell, C. A. K., & Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach. The Review of Economics and Statistics, 71(1), 90–98.10.2307/1928055
  • Färe, R., Grosskopf, S., & Tyteca, D. (1996). An activity analysis model of the environmental performance of firms – Application to fossil-fuel-fired electric utilities. Ecological Economics, 18(2), 161–175.10.1016/0921-8009(96)00019-5
  • Haas, D. A., Murphy, F. H., & Lancioni, R. A. (2003). Managing reverse logistics channels with data envelopment analysis. Transportation Journal, 42(3), 59–69.
  • Hailu, A., & Veeman, T. S. (2001). Non-parametric productivity analysis with undesirable outputs: An application to the Canadian pulp and paper industry. American Journal of Agricultural Economics, 83(3), 605–616.10.1111/ajae.2001.83.issue-3
  • Hua, Z., Bian, Y., & Liang, L. (2007). Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach. Omega, 35(5), 578–587.10.1016/j.omega.2005.11.001
  • Kao, C. (2014). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1), 1–16.10.1016/j.ejor.2014.02.039
  • Khalili-Damghani, K., & Taghavifard, M. (2012). A three-stage fuzzy DEA approach to measure performance of a serial process including JIT practices, agility indices, and goals in supply chains. International Journal of Services and Operations Management, 13(2), 147–188.10.1504/IJSOM.2012.048828
  • Khodakarami, M., Shabani, A., Farzipoor Saen, R., & Azadi, M. (2015). Developing distinctive two-stage data envelopment analysis models: An application in evaluating the sustainability of supply chain management. Measurement, 70, 62–74.10.1016/j.measurement.2015.03.024
  • Korhonen, P. J., & Luptacik, M. (2004). Eco-efficiency analysis of power plants: An extension of data envelopment analysis. European Journal of Operational Research, 154(2), 437–446.10.1016/S0377-2217(03)00180-2
  • Kuosmanen, T. (2005). Weak disposability in nonparametric production analysis with undesirable outputs. American Journal of Agricultural Economics, 87(4), 1077–1082.10.1111/j.1467-8276.2005.00788.x
  • Kuosmanen, T., & Kortelainen, M. (2005). Measuring eco-efficiency of production with data envelopment analysis. Journal of Industrial Ecology, 9(4), 59–72.10.1162/108819805775247846
  • Kwon, H. B., & Lee, J. (2015). Two-stage production modeling of large U.S. banks: A DEA-neural network approach. Expert Systems with Applications, 42(19), 6758–6766.10.1016/j.eswa.2015.04.062
  • Li, X. (2017). A fair evaluation of certain stage in a two-stage structure: Revisiting the typical two-stage DEA approaches. Omega, 68, 155–167.10.1016/j.omega.2016.07.002
  • Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of Operations Research, 145(1), 35–49.10.1007/s10479-006-0026-7
  • Mirhedayatian, S. M., Azadi, M., & Farzipoor Saen R. (2014). A novel network data envelopment analysis model for evaluating green supply chain management. International Journal of Production Economics, 147 Part B, 544–554.
  • Momeni, E., Tavana, M., Mirzagoltabar, H., & Mirhedayatian, S. M. (2014). A new fuzzy network slacks-based DEA model for evaluating performance of supply chains with reverse logistics. Journal of Intelligent & Fuzzy Systems, 27(2), 793–804.
  • Podinovski, V. V., & Kuosmanen, T. (2011). Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions. European Journal of Operational Research, 211(3), 577–585.10.1016/j.ejor.2010.12.003
  • Scheel, H. (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132(2), 400–410.10.1016/S0377-2217(00)00160-0
  • Seiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142(1), 16–20.10.1016/S0377-2217(01)00293-4
  • Shafiee, M., Hosseinzadeh Lotfi, F., & Saleh, H. (2014). Supply chain performance evaluation with data envelopment analysis and balanced scorecard approach. Applied Mathematical Modelling, 38(21–22), 5092–5112.10.1016/j.apm.2014.03.023
  • Shephard, R. W. (1970). Theory of cost and production functions. Princeton: Princeton University Press.
  • Tajbakhsh, A., & Hassini, E. (2015). A data envelopment analysis approach to evaluate sustainability in supply chain networks. Journal of Cleaner Production, 105, 74–85.10.1016/j.jclepro.2014.07.054
  • Tavana, M., Kaviani, M. A., Di Caprio, D., & Rahpeyma, B. (2016). A two-stage data envelopment analysis model for measuring performance in three-level supply chains. Measurement, 78, 322–333.10.1016/j.measurement.2015.10.023
  • Tyteca, D. (1997). Linear programming models for the measurement of environmental performance of firms – Concepts and empirical results. Journal of Productivity Analysis, 8(2), 183–197.10.1023/A:1013296909029
  • Wu, J., Zhu, Q., Chu, J., & Liang, L. (2015). Two-stage network structures with undesirable intermediate outputs reused: A DEA based approach. Computational Economics, 46(3), 455–477.10.1007/s10614-015-9498-3
  • Wu, J., Zhu, Q., Ji, X., Chu, J., & Liang, L. (2016). Two-stage network processes with shared resources and resources recovered from undesirable outputs. European Journal of Operational Research, 251(1), 182–197.10.1016/j.ejor.2015.10.049
  • Yang, F., Wu, D., Liang, L., Bi, G., & Wu, D. D. (2011). Supply chain DEA: Production possibility set and performance evaluation model. Annals of Operations Research, 185(1), 195–211.10.1007/s10479-008-0511-2
  • Yang, H., & Pollitt, M. (2010). The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants. Energy Policy, 38(8), 4440–4444.10.1016/j.enpol.2010.03.075
  • Zhou, Z., Wang, M., Ding, H., Ma, C., & Liu, W. (2013). Further study of production possibility set and performance evaluation model in supply chain DEA. Annals of Operations Research, 206(1), 585–592.10.1007/s10479-013-1365-9
  • Zhu, J. (2014). Quantitative models for performance evaluation and benchmarking: Data envelopment analysis with spreadsheets (Vol. 213). Basel: Springer.10.1007/978-3-319-06647-9

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