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

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Journal of the Operational Research Society

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.

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Authors and Affiliations

  1. Turkish Military Academy, Ankara, Turkey

    Serkan Gumus

  2. University of New Haven, CT, USA

    Gokhan Egilmez

  3. Istanbul Sehir University, Istanbul, Turkey

    Murat Kucukvar

  4. UGPTI, North Dakota State University, Fargo, ND

    Yong Shin Park

Authors
  1. Serkan Gumus
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  2. Gokhan Egilmez
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  3. Murat Kucukvar
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  4. Yong Shin Park
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Correspondence to Gokhan Egilmez.

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Gumus, S., Egilmez, G., Kucukvar, M. et al. Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing. J Oper Res Soc 67, 616–628 (2016). https://doi.org/10.1057/jors.2015.88

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