Artificial intelligence-based reverse logistics for improving circular economy performance: a developing country perspective

作者：Subhodeep Mukherjee, Ramji Nagariya, K. Mathiyazhagan, M. Baral, M. Pavithra, Andrea Appolloni · 发表于：International Journal of Logistics Management · 年份：2024 · DOI：10.1108/ijlm-03-2023-0102 · 被引用次数：47

PurposeReverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.Design/methodology/approachIn this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.FindingsNine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical c...