Intertwining green SCM- and agile SCM-based decision-making framework for sustainability using GIVTFNs

Abstract

Purpose Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM. Design/methodology/approach DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment. Findings The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment. Research limitations/implications The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success. Originality/value To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.

Guest editorial: Emerging trends in supply chain engineering towards global sustainability

“…Application of AHP and G-TOPSIS for prioritizing capabilities and related practices for a mature and resilient supply chain during disruption Echefaj et al (2022) Capturing cross-border logistics for analysis and improvement Bandaranayake et al (2022) Modelling the drivers of responsiveness of automotive supply chain using an integrated fuzzy DEMATEL-ISM approach Sathyan et al (2022) Can circular healthcare economy be achieved through implementation of sustainable healthcare supply chain practices? Empirical evidence from Indian healthcare sector Vishwakarma et al (2022) Analysis of performance of COVID-19 vaccine supply chain in India Nagarajan et al (2022) Improving the waste to energy supply chain through increased overall equipment effectiveness Wijesinghe and Illankoon (2022) Intertwining green SCM-and agile SCM-based decision-making framework for sustainability using GIVTFNs Sahu et al (2022) The effect of supplier sustainability risk management strategies on supply chain performance Silva et al (2023) Planning of a distribution network utilizing a heterogeneous fixed fleet with a balanced workload Hettiarachchi et al (2023) Identifying the key influencing factors for the growth of air cargo demand Karunathilake and Fernando (2023) Artificial intelligence an enabler for sustainable engineering decision making in uncertain environment: a review and future propositions Wankhede et al (2023) Achieving sustainability through multifaceted green functions in manufacturing Rashid et al (2024aRashid et al ( , 2024b Role of information processing and digital supply chain in supply chain resilience through supply chain risk management Rashid et al (2024aRashid et al ( , 2024b JGOSS 17,2 Sathyan et al (2022) identified seventeen drivers for enhancing supply chain responsiveness and among them, the critical drivers are strategic decision-making, demand forecasting accuracy, advanced manufacturing systems and data integration tools. This integrated methodology will benefit the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness.…”

“…This OEE and productivity will have a direct impact on their supply chain engineering. Sahu et al (2022) developed a decision-support framework for identifying dominating measures in SCM. The degree of similarity approach and distance approach under the extent boundaries of GIVTFNs, are implicated in data analytics.…”

“…Green SCM (GSCM) is one of the key concepts in sustainability. It was identified that “sustainable packaging” under the traits of GSCM had the best performance compared to other sustainability methods (Sahu et al , 2022).…”