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Comparing eco-efficiency with productive efficiency: Addressing the dimensionality issue

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  • Chen, Chien-Ming
  • Wang, Hui

Abstract

One important strategic question in sustainable operations is how explicitly internalizing the societal impact of undesirable outputs (UO) would affect a company's relative competitiveness: the discrepancy between eco-efficiency and productive efficiency. This paper presents a DEA approach to evaluating the impact of considering UO on productive efficiency. The main challenge to be overcome is that the two models have different dimensionalities: the eco-efficiency model additionally considers UO and thus is endowed with higher dimensionality. Prior research suggested that the added dimensionality alone can inflate the overall efficiency score. Thus, comparing the eco-efficiency directly with productive efficiency scores would create biased results. Moreover, the model should allow a firm's eco-efficiency to be higher or lower than its productive efficiency, depending on its relative UO performance. This paper proposes an approach to addressing these issues. More generally, our approach applies to studies that compare efficiency scores from models with different dimensions. We included several numerical examples for illustration.

Suggested Citation

  • Chen, Chien-Ming & Wang, Hui, 2024. "Comparing eco-efficiency with productive efficiency: Addressing the dimensionality issue," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1170-1179.
  • Handle: RePEc:eee:ejores:v:313:y:2024:i:3:p:1170-1179
    DOI: 10.1016/j.ejor.2023.09.001
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    References listed on IDEAS

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Pastor, Jesus T. & Lovell, C.A. Knox & Aparicio, Juan, 2020. "Defining a new graph inefficiency measure for the proportional directional distance function and introducing a new Malmquist productivity index," European Journal of Operational Research, Elsevier, vol. 281(1), pages 222-230.
    3. Charles, Vincent & Aparicio, Juan & Zhu, Joe, 2019. "The curse of dimensionality of decision-making units: A simple approach to increase the discriminatory power of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 279(3), pages 929-940.
    4. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528, Decembrie.
    5. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    6. Bansal, Pooja & Kumar, Sunil & Mehra, Aparna & Gulati, Rachita, 2022. "Developing two dynamic Malmquist-Luenberger productivity indices: An illustrated application for assessing productivity performance of Indian banks," Omega, Elsevier, vol. 107(C).
    7. Yun Zhang & Robert Bartels, 1998. "The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand," Journal of Productivity Analysis, Springer, vol. 9(3), pages 187-204, March.
    8. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    9. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    10. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    11. Rolf Färe & Shawna Grosskopf, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1070-1074.
    12. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    13. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    14. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    15. Tang, Christopher S. & Zhou, Sean, 2012. "Research advances in environmentally and socially sustainable operations," European Journal of Operational Research, Elsevier, vol. 223(3), pages 585-594.
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