Lists
Lists
Detwal, Pankaj Kumar, Agrawal, Rajat, Samadhiya, Ashutosh, Kumar, Anil and Garza-Reyes, Jose Arturo (2024) Research developments in sustainable supply chain management considering optimization and industry 4.0 techniques: a systematic review. Benchmarking: an International Journal, 31 (4). pp. 1249-1269. ISSN 1463-5771
Purpose – The literature that is presently available on sustainable supply chain management (SSCM) combining Optimization and Industry 4.0 techniques falls short in its depictions of the recent developments, budding pertinent areas, and the importance of SSCM in the growth of industrial economies around the world. This article's main objective is to analyze current trends, highlight the latest initiatives, and perform a meta-analysis of the literature that is currently accessible in the SSCM area with a special focus on optimization and Industry 4.0 techniques. The paper also proposes a conceptual framework that will assist in illuminating how the ideas of optimization and Industry 4.0 may contribute to realizing sustainability in supply chains.
Design/methodology/approach – The proposed study systematically reviews 85 research publications published between 2010 and 2022 in referenced peer-reviewed journals in diverse fields, including engineering, business and management, services, and healthcare. Numerous categories are considered throughout the examination of the literature, including year-wise publications, prominent journals, type of research design, concerned industry, and research technique used.
Findings – The study demonstrates a deeper comprehension of the literature in the field and its evolution throughout numerous industry sectors, which is helpful for both practitioners and academics. The results from the content analysis highlight various future research opportunities in the domain.
Originality/value – This is one of the first research articles that have attempted to establish, analyse, and highlight the current trends and initiatives in the SSCM domain from an optimization and Industry 4.0 techniques viewpoint. The cluster-based future research propositions also enhance the novelty of the study.
Available under License Creative Commons Attribution Non-commercial 4.0.
Download (777kB) | Preview
 |
View Item |