Search Results (127)

This study proposes a fuzzy logic-based approach to better manage supply chain uncertainty and improve decision-making flexibility. The developed framework categorizes supply chain activities into procurement, production, distribution and reverse logistics and integrates Lean, Agile, Resilient, and Green (LARG) KPIs within a hierarchical structure. The tool was implemented using Microsoft Excel^TM to enhance usability for practitioners. To test its applicability, the model was applied to a real case study. The results show that lean and resilient practices are consistently well-established across all supply chain phases, while agility and green practices vary significantly depending on the operational area—particularly between internal function (i.e., production and reverse logistics) and external ones (i.e., procurement and distribution). These findings help to better understand how the LARG capabilities are distributed across the different operational areas of the supply chain and offer practical guidance for managers seeking targeted performance improvement. Although the numerical results are context-specific, the framework’s adaptability makes it suitable for diverse supply chain environments. Full article

This study presents a systematic literature review on the mathematical modeling of resilient and viable supply chains, grounded in the PRISMA methodology and applied to a curated corpus of 235 peer-reviewed scientific articles published between 2011 and 2025. The search strategy was implemented across four major academic databases (Scopus and Web of Science) using Boolean operators to capture intersections among the core concepts of supply chains, resilience, viability, and advanced optimization techniques. The screening process involved a double manual assessment of titles, abstracts, and full texts, based on inclusion criteria centered on the presence of formal mathematical models, computational approaches, and thematic relevance. As a result of the selection process, six thematic categories were identified, clustering the literature according to their analytical objectives and methodological approaches: viability-oriented modeling, resilient supply chain optimization, agile and digitally enabled supply chains, logistics optimization and network configuration, uncertainty modeling, and immune system-inspired approaches. These categories were validated through a bibliometric analysis and a thematic map that visually represents the density and centrality of core research topics. Descriptive analysis revealed a significant increase in scientific output starting in 2020, driven by post-pandemic concerns and the accelerated digitalization of logistics operations. At the methodological level, a high degree of diversity in modeling techniques was observed, with an emphasis on mixed-integer linear programming (MILP), robust optimization, multi-objective modeling, and the increasing use of bio-inspired algorithms, artificial intelligence, and simulation frameworks. The results confirm a paradigm shift toward integrative frameworks that combine robustness, adaptability, and Industry 4.0 technologies, as well as a growing interest in biological metaphors applied to resilient system design. Finally, the review identifies research gaps related to the formal integration of viability under disruptive scenarios, the operationalization of immune-inspired models in logistics environments, and the need for hybrid approaches that jointly address resilience, agility, and sustainability. Full article

In the shift toward sustainable and resource-efficient manufacturing, Artificial Intelligence (AI) is playing a transformative role in overcoming the limitations of traditional production scheduling methods. This study, based on a Systematic Literature Review (SLR), explores how AI techniques enhance Advanced Planning and Scheduling (APS) systems, particularly under finite-capacity constraints. Traditional scheduling models often overlook real-time resource limitations, leading to inefficiencies in complex and dynamic production environments. AI, with its capabilities in data fusion, pattern recognition, and adaptive learning, enables the development of intelligent, flexible scheduling solutions. The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. These AI-powered APS systems enhance scheduling accuracy, reduce lead times, improve resource utilization, and enable the proactive identification of production bottlenecks. Especially relevant in high-variability sectors like fashion, these approaches support Industry 5.0 goals by enabling agile, sustainable, and human-centered manufacturing systems. The findings have been highlighted in a structured framework for AI-based APS systems supported by metaheuristics that compares the Industry 4.0 and Industry 5.0 perspectives. The study offers valuable implications for both academia and industry: academics can gain a synthesized understanding of emerging trends, while practitioners are provided with actionable insights for deploying intelligent planning systems that align with sustainability goals and operational efficiency in modern supply chains. Full article

Global supply chains have faced unprecedented disruptions in recent years, ranging from the COVID-19 pandemic to geopolitical tensions and climate-induced shocks. These events have exposed structural vulnerabilities in operational models overly optimized for efficiency at the expense of resilience and sustainability. This conceptual paper proposes an integrated framework linking resilience enablers, post-pandemic operational strategies, and sustainability outcomes. Through a synthesis of the interdisciplinary literature across operations management, sustainability science, institutional theory, and organizational behavior, we develop typologies of operational responses—including agile, lean–green, circular, and decentralized models—and connect them to broader Sustainable Development Goals (SDGs). Drawing on systems thinking and the Triple Bottom Line framework, we present a conceptual model that outlines causal relationships between resilience drivers, adaptive operational strategies, and long-term sustainable performance. The paper further discusses policy implications for public and private sectors, offering insights for global sustainability governance. We conclude by outlining a research agenda to empirically test and refine the model through multi-method approaches. This study contributes to theory by reconceptualizing sustainable operations in the context of compound global disruptions and offers a normative direction for future scholarship and practice. Full article

Background: This study conceptualizes supply chain ambidexterity through two capabilities, supply chain adaptability and agility. Accordingly, it investigates the impact of supply chain adaptability and agility on green product innovation (GPI) and supply chain sustainability in Jordanian manufacturing firms. It also examines the mediating role of GPI in these relationships. The study is based on dynamic capabilities theory (DCT) as the theoretical foundation. Methods: A quantitative research approach was employed, with data collected from 346 supply chain managers using a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for analysis. Results: The findings reveal that supply chain adaptability does not directly influence sustainability but significantly enhances GPI, which positively impacts sustainability. Supply chain agility, however, directly and significantly improves both GPI and sustainability, highlighting its importance in achieving sustainable supply chain performance. Additionally, GPI mediates the relationship between supply chain ambidexterity and sustainability, reinforcing its role as a key enabler of eco-friendly supply chain management. These findings provide theoretical and managerial implications. Conclusions: The study extends DCT by confirming the role of GPI in linking supply chain ambidexterity to sustainability. Managers should prioritize agility, invest in sustainable products, and adopt green practices to enhance competitiveness. Full article

Lean manufacturing (LM) is one of the strongest tools used by manufacturing companies to improve and optimize their processes, making them more performant and agile. The current industrial revolution, or Industry 4.0, aims to give new momentum to manufacturing systems through various technologies, of which Blockchain is one of them. This technology has gained significant attention for its ability to enhance transparency, traceability, and data security within manufacturing and supply chain operations, representing a valuable opportunity to enhance lean manufacturing tools. Firstly, this paper presents what lean manufacturing is. After that, it explores how Industry 4.0 technologies influence LM. Then, it examines the impact of blockchain on LM, paving the way for lean 4.0 by presenting a case study concerning the Kanaban method in the automotive sector. Finally, the summary and future research direction will be presented. Full article

Digital twin technology has proven to be a transformative enabler for sustainable manufacturing by providing real-time virtual representations of physical assets and supply chain processes. This paper explores the integration of digital twins with agile supply chain strategies to improve the sustainability of manufacturing systems. By leveraging real-time data and advanced simulations, digital twins facilitate dynamic decision making, optimize resource utilization and reduce environmental impact. A case study is presented in which a digital twin is implemented with the aim of improving the responsiveness of agile supply chains and suggesting appropriate times for the delivery of components and the shipment of the final product, with the goal of minimizing the time components spend in warehouses. The analysis shows how digital twins improve clarity, adaptability and predictive capabilities, leading to greater efficiency and sustainability. The results show that the combination of digital twin technology and agile supply chain frameworks contributes significantly to resource optimization, emissions reduction and overall operational resilience. The proposed approach proves to be highly effective for various manufacturing environments, especially those that strive to balance efficiency and sustainability goals. Full article

The development of the supply chain’s outsourcing and globalization has intensified the requirement for sustainable transport. The evaluation of the transport providers’ maturity, which is crucial to all and any achievements in this context, is hampered by a myriad of factors ranging from the transport ecosystem complexity, self-contradictory and unverifiable data and the ceaseless march of modern technology. This study argues for an agile and smart approach to evaluate the maturity level of transport providers, particularly for high-risk areas like hazardous materials transport. Such models should include holistic analysis frameworks of all performance indicator measurement systems with their data collection methods and technology tools to be employed. The need to involve all stakeholders within the supply chain is said to require diverse collaboration. With regard to the solution, collaborative participation between transport providers and relevant institutions is vital to reduce the environmental impacts and improve the efficiency of the entire sector. Full article

Green supply chain integration (GSCI) has emerged as a significant technique for improving sustainable performance by promoting collaboration with supply chain partners and breaking down organizational barriers to utilize complementary resources. This study investigates the relationships among GSCI, supply chain agility (SCA), digital orientation (DO), and sustainable performance, grounded in the Natural Resource-Based View (NRBV) and Contingency Theory (CT), based on survey data from 288 Chinese pharmaceutical manufacturing enterprises. Using mediation, moderation, and moderated mediation analyses, the findings indicate that SCA serves as a mediator between GSCI and sustainable performance. Significantly, DO strengthens both the direct effect of SCA on sustainable performance and the overall mediating pathway; nevertheless, it does not substantially boost the association between GSCI and SCA. This study’s innovation lies in elucidating the significance of GSCI as a resource for sustainable performance within the pharmaceutical enterprises, while further delineating the pathways and contingent elements for achieving sustainable performance in a digital context. This study offers valuable implications for both academic research and managerial practice. Full article

In the past decade, extended reality (XR) has been introduced into healthcare due to several potential benefits, such as scalability and cost savings. As there is no comprehensive study covering all the factors influencing the selection of an XR system in the healthcare and medical domain, a Decision Support System is proposed in this paper to identify and rank factors impacting the performance of XR in this domain from an engineering design perspective. The proposed system is built upon the Supply Chain Operations Reference (SCOR) model supported by a literature survey and experts’ knowledge to extract and identify important factors. Subsequently, the factors are categorized into distinct categories, and their relative importance is specified by Analytic Network Process (ANP) models under a fuzzy environment. Two fuzzy approaches for the ANP models are compared, and the results are analyzed using statistical testing. The computational results show that the ranking agreement between the two fuzzy approaches is strong and corresponds to the fact that both approaches yield the same ranking of primary factors, highlighting the significance of reliability as the topmost factor, followed by responsiveness, cost, and agility. It is shown that while the top three important sub-factors are identical between the two approaches, their relative order is slightly varied. Safety is considered to be the most critical aspect within the reliability category in both approaches, but there are discrepancies in the rankings of accuracy and user control and freedom. Both approaches also consider warranty and depreciation costs as the least significant criteria. Full article

This study aims to examine how digital supply chain (DSC) dimensions—including digital performance measurement, information technology, digital suppliers, manufacturing, logistics and inventory, and digital client management—influence supply chain agility, and how agility subsequently impacts innovation performance within Moroccan industries. A cross-sectional quantitative research design was employed, collecting data via structured questionnaires from 634 supply chain professionals across sectors such as agri-food, textile, automotive, and aerospace in Morocco. Data were analyzed using structural equation modeling (SEM) with SmartPLS 4, evaluating direct and mediating relationships among variables. Results reveal that digital performance measurement, information technology, and logistics significantly enhance supply chain agility, which in turn strongly boosts innovation performance. Surprisingly, digital manufacturing negatively impacted agility, while digital suppliers and digital clients showed no significant direct effect. Theoretically, the study provides empirical evidence linking DSC dimensions to agility-mediated innovation performance, enriching dynamic capabilities and resource-based views. Practically, it advises managers to prioritize digital performance monitoring and IT integration to foster agility-driven innovation. This paper disaggregates digital supply chain dimensions, clarifying their distinct impacts on agility and innovation, thus addressing a research gap in digital transformation literature. Full article

This study investigates the effects of the mediations of economic utility and moderation of perceived risk on supply chain performance as determined by the organization factors (innovation, organizational culture, and employee motivation) in the Egyptian Fast-Moving Consumer Goods (FMCG) Industry. Although previous research has identified an excess of factors affecting supply chain performance, limited were the studies trying to establish relationships among those factors, especially in emerging economies. Thus, a quantitative approach was adopted, using a structured questionnaire, which was distributed to 382 FMCG supply chain professionals in Egypt. Data were analyzed using structural equation modeling (SEM) to test relations between the hypothesized variables. The results provide evidence that innovation and employee motivation have a positive impact on supply chain performance; organizational culture, however, has no significant impact. Economic utility partially mediates this relationship, of which time utility is by far the strongest mediator. Furthermore, perceived risk moderates the effects of innovation and organizational culture on supply chain performance, thus creating a necessity for risk management. Such information will benefit supply chain managers through considering organizational agility, time-efficient utility drivers, and risk reduction strategies. This research adds to the literature by providing a broad framework integrating organizational factors, economic utility, and perceived risk within supply chain performance systems in developing markets. Full article

Background: In today’s complex and rapidly changing global markets, supply chain resilience (SCR) has become critical for businesses aiming to maintain continuity and competitive advantage. Disruptions and challenges in the supply chain will always exist; therefore, preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. Methods: Digital twins (DTs) provide a comprehensive view of product performance, enabling companies to adopt an end-to-end approach to product management. To maximize product and service value, supply chains must also be managed holistically. Results: Therefore, companies will need smarter strategies to balance inventory costs, availability and lead times. The optimal setup of suppliers, manufacturing, logistics and stock locations will ensure high service levels and meet customer expectations. Additionally, supply chains must be resilient, and capable of maintaining performance during disruptions and adapting to demand changes. Conclusions: This paper aims to provide a comprehensive review of the state of the art in digital twin applications within supply chains, focusing on their role in improving visibility, agility and decision-making. This paper explores how digital twins might integrate with emerging technologies such as IoT, AI and blockchain, fostering a more adaptive and robust supply chain ecosystem. Full article

Artificial intelligence (AI) and smart automation are revolutionizing the global supply chain ecosystem at an accelerated pace, providing tremendous potential for resilience, innovation, efficacy, and profitability. This paper examines how AI, machine learning (ML), and robotic process automation (RPA) influence supply chain operations to adjust to the risks and vulnerabilities. It focuses on how AI and other relevant technologies will enhance forecasting to predict actual demand, expedite logistics, increase warehouse efficiency, and promote instantaneously making decisions. This study utilizes thematic analysis to find AI-driven supply chain applications, including logistics optimization, forecasting demand, and risk mitigation, among 383 peer-reviewed articles (2017–2024). It provides a strategic framework for dealing with vulnerabilities, operational excellence, and resilient solutions. Additionally, the research investigates how AI contributes to supply chain resilience by predicting disruptions and automating risk mitigation strategies. This paper identifies critical success factors and challenges in adopting intelligent automation by analyzing real-world industry implementations. The findings will propose a strategic framework for organizations aiming to leverage AI to achieve operational excellence, agility, and real-time information flow for effective decision-making. Full article

In today’s dynamic and uncertain environment, supply chains are increasingly vulnerable to disruptions that can negatively impact operational efficiency, cost management, and customer satisfaction. Ensuring supply chain resilience and continuity has become a critical challenge for businesses. This review addresses the pressing issue of supply chain risk management by evaluating cutting-edge solutions that enhance visibility, agility, and responsiveness. Through a comprehensive analysis of literature from 2009 to 2024, sourced from Web of Science, Scopus, and Google Scholar, this study identifies key methodologies, technologies, and frameworks designed to mitigate supply chain risks. The findings of the study highlight the revolutionary potential of IoT sensors, machine learning algorithms, and digital twins for proactive risk assessment and mitigation, offering a pathway to safeguard supply networks in the face of uncertainty. Full article