TY - JOUR
T1 - Assessing the sustainability of transport supply chains by double frontier network data envelopment analysis
AU - Saen, Reza Farzipoor
AU - Karimi, Balal
AU - Fathi, Amirali
N1 - Funding Information:
Authors would like to appreciate the constructive comments of reviewers.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/6/20
Y1 - 2022/6/20
N2 - The transport industry is one of the main contributors to environmental pollution. Sustainable supply chain management (SSCM) is an essential subject in the transportation industry. Today, one of the important goals of organizations is to evaluate the sustainability of supply chain (SC) because assessing the efficiency of SCs helps organizations to enhance their awareness of performance and develop managerial strategies. Data envelopment analysis (DEA) is a common technique to assess the sustainability. The objective of this paper is to propose a Malmquist productivity index (MPI) based on network data envelopment analysis (NDEA) model in the presence of integer data, undesirable outputs, and non-discretionary inputs. The NDEA models deal with the internal structure of decision making units (DMUs). The MPI reflects the productivity change over time. The proposed model can fully rank DMUs. To prove the applicability of the proposed model, the sustainability of intercity passenger transportation is evaluated.
AB - The transport industry is one of the main contributors to environmental pollution. Sustainable supply chain management (SSCM) is an essential subject in the transportation industry. Today, one of the important goals of organizations is to evaluate the sustainability of supply chain (SC) because assessing the efficiency of SCs helps organizations to enhance their awareness of performance and develop managerial strategies. Data envelopment analysis (DEA) is a common technique to assess the sustainability. The objective of this paper is to propose a Malmquist productivity index (MPI) based on network data envelopment analysis (NDEA) model in the presence of integer data, undesirable outputs, and non-discretionary inputs. The NDEA models deal with the internal structure of decision making units (DMUs). The MPI reflects the productivity change over time. The proposed model can fully rank DMUs. To prove the applicability of the proposed model, the sustainability of intercity passenger transportation is evaluated.
KW - Double frontier
KW - Integer data
KW - Malmquist productivity index (MPI)
KW - Network data envelopment analysis (NDEA)
KW - Non-discretionary inputs
KW - Sustainability
KW - Transportation industry
KW - Undesirable outputs
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U2 - 10.1016/j.jclepro.2022.131771
DO - 10.1016/j.jclepro.2022.131771
M3 - Article
AN - SCOPUS:85128340331
SN - 0959-6526
VL - 354
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 131771
ER -