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INDONESIA
International Journal of Supply Chain Management
Published by ExcelingTech
ISSN : 20513771     EISSN : 20507399     DOI : -
Core Subject : Science, Social, Engineering,
Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation
International Journal of Supply Chain Management (IJSCM) is a peer-reviewed indexed journal, ISSN: 2050-7399 (Online), 2051-3771 (Print), that publishes original, high quality, supply chain management empirical research that will have a significant impact on SCM theory and practice. Manuscripts accepted for publication in IJSCM must have clear implications for Supply chain managers based on one or more of a variety of rigorous research methodologies. IJSCM also publishes insightful meta-analyses of the SCM literature, conceptual/theoretical studies with clear implications for practice, comments on past articles, studies concerning the SCM field itself, and other such matters relevant to SCM.
Arjuna Subject : -
Articles 2,561 Documents
 253   254   255   256   257 
Reverse Supply Chain and Its Effect on Customer Satisfaction: A Comparative and SERVQUAL Analysis of Retail Practices Bajah, Jeff
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.v14i4.6334

Abstract

Reverse supply chain (RSC) operations have become increasingly critical for retail firms seeking to enhance sustainability, reduce costs, and retain customer loyalty. While traditional supply chain research emphasizes forward logistics, customer satisfaction in reverse logistics remains underexplored. This study investigates the relationship between RSC processes and customer satisfaction using qualitative semi-structured interviews with six U.S.-based supply chain professionals. It applies Qualitative Comparative Analysis (QCA) and the SERVQUAL model to analyze the configurations of RSC conditions that influence customer experience. Four key drivers emerged: return process efficiency, communication and transparency, employee competence, and alignment with customer expectations. A truth table developed using fuzzy set QCA 3.0 reveals five RSC condition combinations that consistently lead to high satisfaction. Customer communication and a hasslefree return process were necessary in all successful configurations. This study highlights best practices, including flexible return options, use of return metrics, staff training, and clear return policies. It contributes to the existing literature by reconceptualizing the reverse supply chain as not merely a cost recovery or operational function, but as a strategic service platform for generating competitive advantage in retail logistics. Further, this research offers a novel analytical framework capable of identifying multiple high-performance pathways rather than prescribing a one-size-fits-all solution. The emphasis on equifinality, or the possibility of different configurations leading to the same positive outcome, reflects the complexity and diversity of modern supply chain environments and aligns with the contemporary demands of supply chain managers.
Saudi Aramco: Circular Economy and Sustainability in the Oil and Gas Industry Eltayeb, Ahmed Y.
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.v14i4.6315

Abstract

This paper explores Saudi Aramco's commitment to sustainability and circular economy principles, highlighting key initiatives that enhance environmental performance and local content development [1]. Utilizing an integrated approach, the paper examines how Aramco implements strategies related to climate change, resource efficiency, and community engagement. The findings illustrate the company's significant contributions to job creation, GDP growth, and supply chain resilience. The paper argues that Aramco's efforts can serve as a model for other sectors aiming to achieve sustainable practices.
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.
Beyond Adoption: Stakeholders' Roles in the Diffusion of Sustainable Supply Chain Management - A Case Study Analysis Mourtaka, Samah
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.v14i4.6325

Abstract

This study examines the wide-ranging impact of companies' decisions to adopt Sustainable Supply Chain Management (SSCM) practices on their stakeholders and the subsequent diffusion of these practices across the stakeholder network. Drawing on game theory, the research investigates how stakeholder interactions and reciprocal influences contribute to the spread of sustainable practices within and beyond organizational boundaries. Through a qualitative, multiple case study approach involving three major Moroccan companies, the study employs triangulation and cross-case analysis to uncover the complex dynamics underlying SSCM implementation. The findings reveal that stakeholder relationships evolve into iterative, strategic interactions that not only reinforce sustainability adoption within individual firms but also catalyse broader diffusion across the supply chain ecosystem.The study contributes to SSCM literature by: (1) clarifying the mechanisms grounded in gametheoretical principles-that underpin sustainability diffusion, and (2) offering rare empirical insights from an emerging market context. By linking SSCM adoption to strategic stakeholder engagement, the research underscores its transformative potential for sustainable development. These insights are particularly valuable for policymakers, practitioners, and scholars seeking to leverage SSCM for broader societal impact.
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.
Application of Supply Chain Analytics in Agriculture: A Road to Sustainability Kumar, Sanjeev
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.v14i4.6335

Abstract

Every aspect of modern human living has now become significantly dependent on the use of data and analytics to reach optimum utility levels. Agriculture, modernized and mechanized over the ages, now makes judicious use of data analytics, particularly on aspects of agricultural supply chain, to improve efficiency. This article focuses on the merits of using supply chain analytics in agriculture. Global agricultural information can be organized and made universally accessible and useful. This article brings out how and why enormous volumes of data should be harnessed to effectively enhance agri SC in a sustainable manner, and benefit not just the customers but also the environment. This article establishes the rationale behind applying SC Analytics (SCA) in Agriculture and prepares the floor for further research on how volumes of agricultural data can be used effectively by corporate giants to implement Blockchain and Al technologies in agri SC.
A Study on the Mitigation of Global Supply Chain Disruptions Ghafli, Mohammad; Hussaien, Qassim Aba; Shaer, Ahmad
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.v14i4.6321

Abstract

Global supply chain disruptions pose significant challenges by unexpectedly interrupting the flow of materials and products across industries. Such disruptions; whether caused by natural disasters, geopolitical events, pandemics, or other shocks (may lead to substantial financial losses and operational instability). This paper examines key strategies for mitigating these risks in a neutral, cross-industry context. We explore how inventory optimization, refurbishment, circular economy principles, and sourcing diversification contribute to supply chain resilience. Research indicates that building redundancy (e.g., safety stocks, dual sourcing) and flexibility (e.g., alternate suppliers, adaptable production) can enhance continuity in the face of disruptions [1-3). Circular economy approaches such as remanufacturing, reuse of surplus materials, and extending material shelf-life emerge as complementary strategies that reduce dependence on newly sourced supplies [4,5]. Our findings synthesize examples from multiple sectors energy, manufacturing, healthcare, and logistics— to illustrate practical applications of these strategies and their effectiveness in improving resilience. The discussion addresses implementation challenges such as cost trade-offs, regulatory considerations, and stakeholder buy-in. The paper's contribution is a unified fourpillar conceptual model: redundancy, flexibility, circularity, and technological enablers; integrated from recent literature and translated into an actionable framework for practice.
An Effective Three-Echelon Reverse Supply Chain Strategic Alliance under Cap-and-Trade Regulation Lin, X. B.; Yu, J. C. P.
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.v14i4.6339

Abstract

In recent years, the booming industry has led to the extensive development of petrochemical energy, coupled with extensive deforestation, resulting in more serious global warming. Climatic anomalies around the world have made it an imperative for enterprises to effectively limit carbon emissions to protect the environment.In the study, we incorporate carbon emission reduction with implementing corporate social responsibility into a three-echelon reverse supply chain for used products. Assumed that carbon emission depends on sustainability level and the returns (used products) quality is stochastic. The optimization recycling models for both decentralized and centralized systems are formulated and then compared to each other. The results show that the centralized system can achieve higher profits and has lower carbon emissions.This study contributes by: (i) developing closed-loop supply chain models with recycler-manufacturerretailer interactions for reused products; (ii) incorporating both cap-and-trade regulation and green technology investment as emission-reduction mechanisms; (iii) modeling demand as dependent on price and technology level under decentralized and centralized structures; and (iv) providing comparative insights on profits, emissions, and sensitivity, with directions for multi-agent extensions.A computing software Maple 18 has been developed for this purpose and is implemented to derive the optimum decision for for each player. Numerical examples and sensitivity analyses are given to illustrate the results.
Economic Development Strategy Through Entrepreneurial Support: Case Study of Morocco Farissi, Aicha; Roudab, Noureddine
International Journal of Supply Chain Management Vol 14, No 5 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i5.6351

Abstract

This research delves deeply into the socioeconomic indicators and targeted population categories within the framework of the Jerada support fund management project, offering valuable insights into the unique challenges and opportunities in the region. The study goes beyond theoretical analysis by proposing practical solutions to Jerada's socioeconomic challenges, providing tangible and real-life responses. As a replicable model, this case study presents concrete and adaptable solutions, demonstrating how research can be translated into actionable strategies. Not only does this study inform the specific context of Jerada, but it also serves as a valuable model for similar territorial development initiatives in Morocco and beyond.
Predictive Analytics for Inbound Logistics: Optimizing Lead Times and Vendor Reliability Gupta, Vikas; Patro, Ravindra Kumar; Sharma, Aditya Kumar
International Journal of Supply Chain Management Vol 14, No 5 (2025): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v14i5.6348

Abstract

Lead time variability has significant impact on supply chain management (SCM) and is a critical factor that affects operational efficiency, cost management, and logistical aspects of a business. This coupled with vendor reliability is the key to quality assurance, waste reduction and cost rationalization. This article delves into the manner in which variations in lead time impact two important aspects of supply chain performance, lead time optimization and vendor management. The focus is on application of predictive analytics in this respect. The article underscores the strong potential that predictive analysis has in addressing the key threats and opportunities faced by modern supply chains. The key contribution of this research is addition to the pool of literature that covers the relatively less widely discussed areas - inbound logistics and the application of sophisticated modern technologies towards improvement of  supply chain visibility for enhancing efficiency of supply chain management. The article establishes that predictive analytics can be effectively used to facilitate data-driven decision-making in supplier management thus making decisions more proactive than reactive which significantly improves supply chain resilience.

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