Modeling the pressures for sustainability adoption in the Indian automotive context. (15th March 2022) - Mathivathanan, Deepak; Agarwal, Vernika; Mathiyazhagan, K.; Saikouk, Tarik; Appolloni, Andrea
Abstract: Sustainable excellence can be achieved by including sustainable supply chain management (SSCM) practices within the existing practices of industries. However, in developing countries such as India, industries, in general, are less willing to modify their existing traditional supply chain activities without pressures or motivations, which is the case in the automotive industries. The literature on SSCM pressure by the various stakeholders is limited in the Indian context. To fill this void in the literature, the present study examines the pressure for the adoption of sustainability in Indian supply chains, particularly in the context of the automotive industry. The automotive sectors to implement SSCM were identified from the literature review and the relationships among the elements were established using contextual, relationship-based, total interpretive structural modeling (TISM). The pressures were subjected to Matrice d'Impacts Cross-impact Matrix multiplication Applied to Classification (MICMAC) analysis to classify the different groups of pressures based on their driving powers and dependence. The developed TISM model was further assessed by a different group of industry experts to ensure its validity. The findings inferred that government regulations, the special benefits of social and environmental certifications, and the interests of the foreign investor in sustainable product development, are the most influential pressures for SSCM adoption in Indian automotive component manufacturing industries. Highlights: Identified 11 individual pressure elements for SSCM implementation in Indian automotive component manufacturing industries. Determined interrelationships between the identified pressures using pairwise comparison. Developed a performance model for the pressures of SSCM using the TISM approach. Validated the developed model with the help of domain experts. Classified the different groups of pressures based on MICMAC analysis.