Sustainability performance predictions in supply chains: grey and rough set theoretical approaches

• Published in: Annals of operations research Vol. 310; no. 1; pp. 171 - 200
• Main Author: Rajesh, R.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2022; Springer; Springer Nature B.V
• Subjects: Analysis; Business and Management; Combinatorics; Environmental sustainability; Indicators; Logistics; Operations research; Operations Research/Decision Theory; Performance prediction; Prediction models; Prediction theory; S.i.: Mim2019; Set theory; Supply chains; Sustainability; Theory of Computation; India; Rough set theory; Sustainable supply chains; Prediction models; Grey theory; Sustainability
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-020-03835-x

It is crucial for any supply chains to measure and monitor the sustainability performance indicators across three dimensions such as; economic, environmental, and social, to achieving sustainable competitiveness. We formulate a periodic prediction model based on grey theory and rough set theory to evaluate and predict the sustainability performances of supply chains. Here, a grey theory based prediction model is used in the first stage to estimating the predictors of the firms’ sustainability indicators, based on their performances in the past. A second stage assessment involves the analysis of the same using a rough set based prediction method to validating the results. A case evaluation for assessing the practical implications of the proposed methodology is also elaborated in this research. From the study, managers are recommended to make use of these prediction models into their supply chains to predicting the sustainability performances of their supply chains and to improve their performance for future.