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

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

扫码查看
原文链接
  • NETL
  • NSTL
  • Emerald Group Publishing
Purpose - Reverse 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/approach - In 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.Findings - Nine 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 Al-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 capability have no mediation.Practical implications - The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.Originality/value - Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs' CE performance.

Artificial intelligenceReverse logisticsCircular economy performanceAI-based circular economy

Subhodeep Mukherjee、Ramji Nagariya、K. Mathiyazhagan、Manish Mohan Baral、M.R. Pavithra、Andrea Appolloni

展开 >

GITAM School of Business, GIT AM (Deemed to be University), Visakhapatnam, India

School of Business and Management, CHRIST University, Bengaluru, India

Thiagarajar School of Management, Madurai, India

GITAM School of Business, GITAM (Deemed to be University), Visakhapatnam, India

Rajahkshmi School of Business, Chembarambakkam, Chennai, India

Department of Management and Law, University of Rome Tor Vergata, Rome, Italy

展开 >

2024

10.1108/IJLM-03-2023-0102

The international journal of logistics management

The international journal of logistics management

ISSN：0957-4093
年,卷(期)：2024.35(6)
  • 144