Evaluating approaches using the Grey-TOPSIS for sustainable supply chain collaboration under risk and uncertainty

Abstract

Purpose

Collaboration methods are unique strategies that can help organizations hedge against external and internal supply chain risks without stressing their relationships with supply chain partners. However, selecting the most appropriate collaboration method from a given set of strategies is a multifaceted challenge. This paper aims to address this issue.

Design/methodology/approach

The decision maker's dilemma of fighting data uncertainty in input parameters to check the efficacy of a given collaboration or mitigation approach is tackled by the integration of Grey theory with the technique for order of preference by similarity to ideal solution (TOPSIS) method. The proposed technique is applied and tested for an Indian diesel generator-set manufacturer to identify the most apposite set of sustainable collaboration strategies.

Findings

The results showed that when a firm is bidding for different horizontal collaboration strategies across its supply chain system technology and resource-sharing-centered collaboration strategies are the prominent option. In the case of the company's vertical collaboration deployment, the focus should be kept on information sharing to achieve impactful collaboration. The outcome of the analysis helped the Indian manufacturer to adopt transparent order and production information sharing with its regional distributors and core suppliers within its supply chain.

Originality/value

This study demonstrates from a methodological perspective the successful application of the Grey-TOPSIS approach that effectively captures data uncertainty. It also integrates sustainability parameters in collaboration strategy criteria selections.

Citation

Prakash, S., Kumar, S., Soni, G., Jain, V., Dev, S. and Chandra, C. (2023), "Evaluating approaches using the Grey-TOPSIS for sustainable supply chain collaboration under risk and uncertainty", Benchmarking: An International Journal, Vol. 30 No. 9, pp. 3124-3149. https://doi.org/10.1108/BIJ-05-2022-0319