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Challenges of Implementing Reverse Logistics in Small and Medium Enterprises (SMEs) Al-Huzaili, Sami Ahmed Faraj; Mokhtar, Ahmad Irdha Bin; Muhamat, Madya Razaleigh Bin
International Journal of Supply Chain Management Vol 14, No 4 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i4.6331

Abstract

Reverse coordination is an essential component of sustainable supply chain management, enabling businesses to recover value from returned products while minimizing environmental impact. While large corporations have increasingly integrated reverse coordination into their operations, small and medium enterprises (SMEs) often face considerable barriers that hinder implementation. This study explores the key challenges SMEs encounter in adopting reverse coordination, using a qualitative methodology that combines secondary data analysis with semi-structured interviews conducted with logistics managers from ten SMEs across diverse sectors.The findings reveal six primary obstacles: financial constraints, lack of technical expertise, inadequate infrastructure, weak regulatory pressure, low customer awareness, and organizational resistance to change. These barriers are interconnected and reflect both internal limitations and external systemic factors. Despite these challenges, the research underscores the strategic potential of reverse logistics for SMEs, including cost savings, regulatory compliance, improved customer satisfaction, and new revenue opportunities.The study concludes with practical recommendations to support SMEs in overcoming these challenges highlighting the need for government incentives, targeted training, affordable technologies, collaborative logistics networks, and enhanced customer engagement. Addressing these issues through coordinated efforts can help SMEs realize the full value of reverse logistics and contribute to a more circular and sustainable economy.
The Role of Artificial Intelligence in Enhancing Procurement Processes and Supply Chains Al-Huzaili, Sami Ahmed Faraj; Mokhtar, Ahmad Irdha Bin; Muhamat, Madya Razaleigh Bin
International Journal of Supply Chain Management Vol 14, No 4 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i4.6328

Abstract

The integration of Artificial Intelligence (AI) into procurement and supply chain management has significantly transformed traditional operations by enhancing efficiency, resilience, and decision- making. As businesses increasingly adopt AI-driven solutions, procurement processes and supply chain functions have evolved to become more automated, data-driven, and responsive to market dynamics. This study conducts a systematic literature review (SLR) to explore the role of AI in optimizing procurement processes and improving overall supply chain performance. The research examines key AI technologies, including machine learning, predictive analytics, robotic process automation (RPA), and natural language processing (NLP), highlighting their applications in procurement, logistics, and risk management. Findings suggest that AI enhances supplier selection, automates procurement workflows, improves demand forecasting, and strengthens supply chain resilience, particularly in response to disruptions such as the COVID-19 pandemic. By leveraging AI, organizations can minimize operational inefficiencies, enhance real-time decision- making, and improve supply chain sustainability. Despite its numerous benefits, the study identifies key challenges hindering widespread AI adoption in procurement and supply chains. These challenges include high implementation costs, data security concerns, workforce resistance to AI-driven automation, and the complexity of integrating AI with existing systems. Addressing these barriers requires strategic investments in AI infrastructure, enhanced data governance, and workforce training initiatives to ensure smooth AI adoption. The study concludes that while AI presents transformative opportunities for procurement and supply chains, businesses must develop comprehensive AI strategies to maximize its potential. Future research should focus on overcoming adoption barriers, improving AI-driven decision-making frameworks, and exploring emerging innovations to further enhance procurement and supply chain efficiency.