TY - JOUR
T1 - A novel approach to assess sustainability of supply chains
AU - Kalantary, Majid
AU - Farzipoor Saen, Reza
N1 - Funding Information:
The authors would like to appreciate the constructive comments of Editor-in-Chief Professor Brandon Randolph-Seng and two anonymous Reviewers.
Publisher Copyright:
© 2021, Emerald Publishing Limited.
PY - 2021/9/3
Y1 - 2021/9/3
N2 - Purpose: This paper discusses how learning-by-doing (LBD) criterion can be used to evaluate the sustainability of supply chains. This paper assesses the impacts of teamwork on the LBD criterion. Besides, the effect of the internship of new labors on the LBD criterion is discussed. Design/methodology/approach: The repeat of a task leads to a gradual improvement in the efficiency of production systems. LBD occurs by accumulating knowledge and skills in multiple periods. LBD can be used to study changes in the efficiency. Efficiency can be improved by accumulating knowledge and skills. In this paper, the LBD criterion is projected on learning curve (LC) models. Furthermore, the LC models are fitted to the supply chains. Each supply chain may have a unique LC model. A minimum difference is set between the current performance of decision making unit (DMU) and the estimated performance of DMU based on DMU's LC. Hence, a point in which the LBD occurs is determined. Findings: This paper develops an inverse network dynamic data envelopment analysis (DEA) model to assess the sustainability of supply chains DMUs. Findings imply that the LBD criterion plays an important role in assessing the sustainability of supply chains. Furthermore, managers should increase the internships and teamwork to get more benefit from the LBD criterion. Originality/value: For the first time, this paper uses the LBD criterion to assess the sustainability of supply chains given the LC equations.
AB - Purpose: This paper discusses how learning-by-doing (LBD) criterion can be used to evaluate the sustainability of supply chains. This paper assesses the impacts of teamwork on the LBD criterion. Besides, the effect of the internship of new labors on the LBD criterion is discussed. Design/methodology/approach: The repeat of a task leads to a gradual improvement in the efficiency of production systems. LBD occurs by accumulating knowledge and skills in multiple periods. LBD can be used to study changes in the efficiency. Efficiency can be improved by accumulating knowledge and skills. In this paper, the LBD criterion is projected on learning curve (LC) models. Furthermore, the LC models are fitted to the supply chains. Each supply chain may have a unique LC model. A minimum difference is set between the current performance of decision making unit (DMU) and the estimated performance of DMU based on DMU's LC. Hence, a point in which the LBD occurs is determined. Findings: This paper develops an inverse network dynamic data envelopment analysis (DEA) model to assess the sustainability of supply chains DMUs. Findings imply that the LBD criterion plays an important role in assessing the sustainability of supply chains. Furthermore, managers should increase the internships and teamwork to get more benefit from the LBD criterion. Originality/value: For the first time, this paper uses the LBD criterion to assess the sustainability of supply chains given the LC equations.
KW - Data envelopment analysis (DEA)
KW - Dynamic data envelopment analysis (DDEA)
KW - Inverse data envelopment analysis (IDEA)
KW - Learning curve (LC)
KW - Learning-by-doing (LBD)
KW - Network data envelopment analysis (NDEA)
KW - Slacks-based measure (SBM) model
KW - Sustainable supply chain management (SSCM)
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U2 - 10.1108/md-04-2020-0484
DO - 10.1108/md-04-2020-0484
M3 - Article
AN - SCOPUS:85114195760
SN - 0025-1747
VL - 60
SP - 231
EP - 253
JO - Management Decision
JF - Management Decision
IS - 1
ER -