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Sustainability evaluation of transportation supply chains by common set of weights-network DEA and Shannon’s entropy in the presence of zero inputs

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Abstract

The transport industry is one of the main contributors to environmental pollutions. Sustainability evaluation of the transport industry helps companies to increase their awareness and leads to the right decisions. This study addresses the subject of sustainability for the transportation supply chain. Data envelopment analysis (DEA is a popular approach for efficiency evaluation. This work develops a common set of weights (CSW) model using two-stage network DEA and Shannon’s entropy. The proposed CSW model evaluates the sustainability of transportation supply chains in DEA context. The objective of this paper is to propose an integrated slack-based two-stage network DEA model with zero inputs and CSW analysis using Shannon’s entropy technique. To calculate the optimal weights, the Shannon entropy technique is used. To the best of the authors’ knowledge, there is no two-stage network DEA model based on Shannon’s entropy for evaluating the sustainability of transport companies when there are zero inputs. The proposed model can fully rank DMUs. In this study, optimal scores by different weights are obtained and can be applied in real-world problems. To demonstrate the applicability of the proposed approach, the sustainability of transportation supply chains is assessed.

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The authors would like to appreciate three anonymous Reviewers for their constructive comments.

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  1. Department of Management, Islamic Azad University, Dubai, United Arab Emirates

    Amirali Fathi

  2. Department of Operations Management & Business Statistics, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman

    Reza Farzipoor Saen

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  1. Amirali Fathi
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Fathi, A., Saen, R.F. Sustainability evaluation of transportation supply chains by common set of weights-network DEA and Shannon’s entropy in the presence of zero inputs. Environ Dev Sustain 26, 7999–8025 (2024). https://doi.org/10.1007/s10668-023-03046-x

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