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Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing

Author

Listed:
  • Serkan Gumus

    (Turkish Military Academy, Ankara, Turkey)

  • Gokhan Egilmez

    (University of New Haven, CT, USA)

  • Murat Kucukvar

    (Istanbul Sehir University, Istanbul, Turkey)

  • Yong Shin Park

    (UGPTI, North Dakota State University, Fargo, ND)

Abstract

In this paper, the effect of weighting strategies on sustainability performance assessment is addressed. Eco-efficiency is used as the main metric for sustainability performance evaluation. An integrated input-output life cycle assessment (LCA) and multi criteria decision making (MCDM) approach is employed. The US manufacturing sectors’ LCA results are used in conjunction with the proposed MCDM framework to perform the eco-efficiency evaluation of 276 US manufacturing sectors. Five environmental impact categories are considered as the negative factors, namely: greenhouse gas emissions, energy use, water withdrawal, hazardous waste generation and toxic releases into air and the economic output of each manufacturing sector is considered to be the positive output. To study the overall impact of different weighting strategies; twenty weighting scenarios are designed. Five pairs of weights considered for the overall economic versus environmental impacts along with four specific weighting strategies based on Harvard, SAB, EPP and Equal weighting for each pair. According to the results of the statistical analysis, it is concluded that the weighing strategies applied to the overall environmental impacts and economic outputs cause statistically significant differences in the eco-efficiency scores.

Suggested Citation

  • Serkan Gumus & Gokhan Egilmez & Murat Kucukvar & Yong Shin Park, 2016. "Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(4), pages 616-628, April.
    • Handle: RePEc:pal:jorsoc:v:67:y:2016:i:4:p:616-628
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    Citations

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    Cited by:

    1. Song, Malin & Zheng, Wanping & Wang, Shuhong, 2017. "Measuring green technology progress in large-scale thermoelectric enterprises based on Malmquist–Luenberger life cycle assessment," Resources, Conservation & Recycling, Elsevier, vol. 122(C), pages 261-269.
    2. Debdip Khan & Ranjan Kumar Gupta, 2024. "Production optimization with the maintenance of environmental sustainability based on multi-criteria decision analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 19425-19442, August.
    3. Roger Chapman Burk & Richard M. Nehring, 2023. "An Empirical Comparison of Rank-Based Surrogate Weights in Additive Multiattribute Decision Analysis," Decision Analysis, INFORMS, vol. 20(1), pages 55-72, March.
    4. K. Graff & C. Lissak & Y. Thiery & O. Maquaire & S. Costa & B. Laignel, 2019. "Analysis and quantification of potential consequences in multirisk coastal context at different spatial scales (Normandy, France)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(2), pages 637-664, November.
    5. Kucukvar, Murat & Haider, Muhammad Ali & Onat, Nuri Cihat, 2017. "Exploring the material footprints of national electricity production scenarios until 2050: The case for Turkey and UK," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 251-263.
    6. Svetlana Ratner & Andrey Lychev & Aleksei Rozhnov & Igor Lobanov, 2021. "Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis," Mathematics, MDPI, vol. 9(18), pages 1-21, September.
    7. Liu, Conghu & Gao, Mengdi & Zhu, Guang & Zhang, Cuixia & Zhang, Pan & Chen, Jianqing & Cai, Wei, 2021. "Data driven eco-efficiency evaluation and optimization in industrial production," Energy, Elsevier, vol. 224(C).
    8. Maria Julia Xavier Belem & Milton Vieira Junior & Giovanni Mummolo & Francesco Facchini, 2021. "An AHP-Based Procedure for Model Selection for Eco-Efficiency Assessment," Sustainability, MDPI, vol. 13(21), pages 1-21, November.
    9. Puertas, Rosa & Guaita-Martinez, José M. & Carracedo, Patricia & Ribeiro-Soriano, Domingo, 2022. "Analysis of European environmental policies: Improving decision making through eco-efficiency," Technology in Society, Elsevier, vol. 70(C).
    10. Maria del Mar Casanovas-Rubio & Bernat Vinolas, 2024. "New method for assigning cardinal weights in multi-criteria decision-making: the constant weight ratio method," Operational Research, Springer, vol. 24(2), pages 1-33, June.
    11. Konstantinos N. Konstantakis & Panagiotis T. Cheilas & Ioannis G. Melissaropoulos & Panos Xidonas & Panayotis G. Michaelides, 2023. "Supply chains and fake news: a novel input–output neural network approach for the US food sector," Annals of Operations Research, Springer, vol. 327(2), pages 779-794, August.
    12. Dyckhoff, Harald & Souren, Rainer, 2022. "Integrating multiple criteria decision analysis and production theory for performance evaluation: Framework and review," European Journal of Operational Research, Elsevier, vol. 297(3), pages 795-816.

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