Assessing the sustainability of supply chains by dynamic network data envelopment analysis: a SCOR-based framework

Area of Science:

• Operations Research
• Supply Chain Management
• Sustainability Science

Background:

• Assessing supply chain sustainability is crucial in dynamic business environments.
• Traditional data envelopment analysis (DEA) models may face limitations with interval data and non-convex production technologies.
• The SCOR (Supply Chain Operations Reference) framework provides a standardized view of supply chain processes.

Purpose of the Study:

• To propose a novel dynamic network data envelopment analysis (DNDEA) model for evaluating supply chain sustainability.
• To address the challenge of interval data and potential violations of convexity in production technologies.
• To develop a DNDEA model based on the free disposal hull (FDH) approach within the SCOR framework.

Main Methods:

• Development of a DNDEA model incorporating the free disposal hull (FDH) approach.
• Application of the model to interval-valued data representing supply chain operations.
• Integration of the model within the context of the SCOR framework for standardized assessment.

Main Results:

• The proposed FDH-based DNDEA model consistently yields finite efficiency scores for supply chain sustainability assessment.
• The model enables the calculation of realistic benchmarks derived from actual operational data.
• A case study in the print industry demonstrates the model's validity and practical applicability.

Conclusions:

• The developed FDH-based DNDEA model offers a robust method for assessing supply chain sustainability, particularly with interval data.
• The model's ability to provide finite scores and actionable benchmarks enhances its utility for improving supply chain performance.
• This research presents the first DNDEA-FDH model tailored for the SCOR framework, offering a novel contribution to the field.