BEYOND EFFICIENCY: SMART TECHNOLOGIES DRIVING ENVIRONMENTAL AND OPERATIONAL SUSTAINABILITY IN E-COMMERCE LOGISTICS

Abstract

Abstract Introduction: E-commerce supply chains are under unprecedented pressure to deliver speed, efficiency, and sustainability. Smart automation and robotics are widely used; however, research in this area remains fragmented, focusing mainly on economic and environmental benefits while neglecting social sustainability. This study aims to address these gaps by examining how digital technologies can advance the economic, environmental, and social sustainability in the rapidly evolving world of e-commerce logistics. Purpose: This research examines how smart automation and robotics contribute to economic, environmental, and social sustainability within e-commerce supply chains, addressing gaps in both theory and practice. Methodology: This study employs a dual-method approach, combining bibliometric analysis with a systematic literature review (SLR). An initial total of 432 records was retrieved from Scopus, Google Scholar, and Web of Science. Following screening, deduplication, and quality assessment, the dataset was refined to 45 peer-reviewed studies (20 from Scopus, 15 from Google Scholar, and 10 from Web of Science). Guided by PRISMA 2020, the review identifies thematic clusters. It synthesises evidence on how smart automation promotes sustainability in e-commerce supply chains, framed by the Triple Bottom Line and ResourceBased View. Results: The research findings confirm that automation technologies, such as AI forecasting, robotic process automation, and IoT-enabled traceability, offer significant efficiency gains, cost reductions, and quantifiable environmental benefits, including energy optimisation and carbon reduction. However, social outcomes, including workforce reskilling and equity, frequently remain insignificant and underdeveloped. Barriers include high costs, limited interoperability, and regulatory fragmentation. Implications: The research enhances our understanding of existing knowledge by clarifying how smart automation enhances economic and environmental performance while also revealing a persistent disregard for social sustainability. For leaders, the findings point to the need for effective governance, ethical oversight of AI, and workforce transformation. For policymakers, establishing coherent standards and inclusive frameworks is critical for guaranteeing that automation delivers balanced and sustainable outcomes.