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Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance

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  • Chang, Dong-Shang
  • Liu, Wenrong
  • Yeh, Li-Ting

Abstract

The effect of organizational learning, which results in continuous improvement of organizational performance over time, has been widely discussed. The cumulative learning effect may form as a source of intellectual capital. Thus far, the static data envelopment analysis (DEA) model has not been used to examine the longitudinal learning effect. Therefore, a two-stage approach is developed together with the estimation of a latent learning effect using time-series data; the estimated learning effect is then used as an input in the DEA Slacks-Based Measure (SBM) model. The proposed DEA SBM model can be used to investigate the efficiency of the organizational learning effect of Municipal Solid Waste (MSW) recycling systems.

Suggested Citation

  • Chang, Dong-Shang & Liu, Wenrong & Yeh, Li-Ting, 2013. "Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance," European Journal of Operational Research, Elsevier, vol. 229(2), pages 496-504.
  • Handle: RePEc:eee:ejores:v:229:y:2013:i:2:p:496-504
    DOI: 10.1016/j.ejor.2013.01.026
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    References listed on IDEAS

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    1. B. K. Sahoo & K. Kerstens & K. Tone, 2012. "Returns to growth in a non parametric DEA approach," Post-Print hal-00684430, HAL.
    2. Avkiran, Necmi K. & Rowlands, Terry, 2008. "How to better identify the true managerial performance: State of the art using DEA," Omega, Elsevier, vol. 36(2), pages 317-324, April.
    3. Mahlberg, Bernhard & Sahoo, Biresh K., 2011. "Radial and non-radial decompositions of Luenberger productivity indicator with an illustrative application," International Journal of Production Economics, Elsevier, vol. 131(2), pages 721-726, June.
    4. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    5. Yang, Wen-Hua & Chand, Suresh, 2008. "Learning and forgetting effects on a group scheduling problem," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1033-1044, June.
    6. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    7. Kuo, Wen-Hung & Yang, Dar-Li, 2006. "Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1184-1190, October.
    8. Lee, S & Courtney, J. F. & O'Keefe, R. M., 1992. "A system for organizational learning using cognitive maps," Omega, Elsevier, vol. 20(1), pages 23-36, January.
    9. Chang, Dong-Shang & Yang, Fu-Chiang, 2011. "Assessing the power generation, pollution control, and overall efficiencies of municipal solid waste incinerators in Taiwan," Energy Policy, Elsevier, vol. 39(2), pages 651-663, February.
    10. Dyckhoff, H. & Allen, K., 2001. "Measuring ecological efficiency with data envelopment analysis (DEA)," European Journal of Operational Research, Elsevier, vol. 132(2), pages 312-325, July.
    11. Knox Lovell, C. A., 1995. "Measuring the macroeconomic performance of the Taiwanese economy," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 165-178, April.
    12. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    13. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    14. Yang, Xiaopeng & Morita, Hiroshi, 2013. "Efficiency improvement from multiple perspectives: An application to Japanese banking industry," Omega, Elsevier, vol. 41(3), pages 501-509.
    15. Fioretti, Guido, 2007. "The organizational learning curve," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1375-1384, March.
    16. Anthony J. Dibella & Janet M. Gould, 1996. "Understanding Organizational Learning Capability," Journal of Management Studies, Wiley Blackwell, vol. 33(3), pages 361-379, May.
    17. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    18. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    19. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    20. Olav Sorenson, 2003. "Interdependence and Adaptability: Organizational Learning and the Long--Term Effect of Integration," Management Science, INFORMS, vol. 49(4), pages 446-463, April.
    21. Ferdinand K. Levy, 1965. "Adaptation in the Production Process," Management Science, INFORMS, vol. 11(6), pages 136-154, April.
    22. Hsu, Chin-Chun & Pereira, Arun, 2008. "Internationalization and performance: The moderating effects of organizational learning," Omega, Elsevier, vol. 36(2), pages 188-205, April.
    23. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    24. Sengupta, Jati K., 2000. "Quality and efficiency," Economic Modelling, Elsevier, vol. 17(2), pages 195-207, April.
    25. Kao, Chiang, 2009. "Efficiency measurement for parallel production systems," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1107-1112, August.
    26. Sarkis, Joseph & Cordeiro, James J., 2001. "An empirical evaluation of environmental efficiencies and firm performance: Pollution prevention versus end-of-pipe practice," European Journal of Operational Research, Elsevier, vol. 135(1), pages 102-113, November.
    27. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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    1. repec:gam:jsusta:v:9:y:2017:i:12:p:2241-:d:121575 is not listed on IDEAS
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Guyot, Alexis & Doumpos, Michael & Zopounidis, Constantin, 2016. "A novel multi-attribute benchmarking approach for assessing the financial performance of local governments: Empirical evidence from FranceAuthor-Name: Galariotis, Emilios," European Journal of Operational Research, Elsevier, vol. 248(1), pages 301-317.

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