Sara Elzarka

Background: Global supply chains remain highly exposed to geopolitical instability affecting critical maritime chokepoints across the Middle East, including the Strait of Hormuz, Bab el-Mandeb and the Suez Canal. Disruptions in these corridors can reverberate through logistics networks, increase supply chain risk exposure and weaken trade continuity. Objectives: This study examines whether Saudi Arabia can function as a logistics stabilisation hub by connecting Red Sea gateways, Gulf ports, inland logistics corridors, energy logistics assets and digital logistics systems. Method: A structured survey of 300 logistics professionals was analysed using structural equation modelling. The model tested the relationships between geopolitical instability, maritime logistics disruptions, supply chain risk exposure, logistics stabilisation hub capability and supply chain stability. Results: Geopolitical instability increased maritime logistics disruptions, and maritime disruptions increased supply chain risk exposure. Supply chain risk exposure reduced global supply chain stability. Logistics stabilisation hub capability moderated the disruption–stability relationship and supported regional supply chain resilience. Conclusion: National logistics systems can reduce the destabilising effects of maritime chokepoint disruption when they provide multimodal redundancy, energy-logistics continuity and digital cargo visibility. Contribution: The study extends hub theory by framing logistics hubs as stabilisation infrastructure rather than only trade facilitation assets.

Background: Amid rising trade, urbanization, and carbon emissions in MENA countries, sustainable logistics faces major constraints. This study develops an enhanced Green Logistics Performance Index (GLPI) using min-max normalization and Principal Component Analysis (PCA) to integrate the World Bank's Logistics Performance Index (LPI) and Yale's Environmental Performance Index (EPI). The study uses fixed-effects panel regression on data from 20 MENA countries (2018-2024), identifies key drivers, and applies ARIMA and LSTM models for 2030 projections. The prior ratio-based GLPI suffered from scale sensitivity and volatility; this refined version provides improved stability and predictive utility for Green Supply Chain Management (GSCM). Methods: Panel data from 20 MENA countries (2018-2024) were analyzed. The enhanced GLPI normalizes and weights LPI and EPI scores via PCA. Fixed-effects regression identifies drivers, while ARIMA and LSTM enable scenario-based forecasting (baseline, optimistic, and pessimistic). Results: Renewable energy share positively influences GLPI, while trade openness has a negative effect. Projections indicate the regional GLPI will reach about 0.65 by 2030, with Saudi Arabia potentially achieving 25% higher under optimistic conditions. Conclusions: The refined GLPI advances GSCM theory by operationalizing triple bottom line trade-offs through a robust, predictive metric. It bridges descriptive limitations in prior literature, enabling forward-looking insights into sustainable logistics in emerging economies, with potential applicability beyond MENA.

Background: Supply chain management (SCM) research has expanded across the Middle East and North Africa (MENA), yet the field remains fragmented. Limited synthesis exists on how regional conditions shape research themes, theories, and methods. Methods: This study applies the PRISMA 2020 protocol to review SCM articles indexed in Scopus and Web of Science from January 2000 to March 2025. After screening and eligibility assessment, 512 peer-reviewed studies were retained. Bibliometric mapping and thematic coding were used to identify publication trends, research streams, theoretical lenses, and methodological patterns. Results: SCM research increased sharply after 2015, reflecting national diversification agendas, logistics reform, digitalization, and exposure to global supply chain disruptions. Three dominant streams were identified: resilience, sustainability, and digital transformation. Research output is concentrated in Saudi Arabia and the United Arab Emirates, while crosscountry comparative studies remain scarce. Empirical studies rely mainly on cross-sectional surveys and SEM-based analysis, with limited longitudinal, qualitative, mixed-method, and comparative work across the region. Conclusions: The study develops an integrative SCM capability framework linking regional structural conditions, capability development, and supply chain outcomes. The findings support managers and policymakers seeking resilient, sustainable, and digitally enabled supply chains, and define clear future research priorities for the MENA region.

Healthcare supply chains are increasingly required to achieve high levels of resilience while meeting growing sustainability and digital transformation demands. In Saudi Arabia, healthcare logistics systems face complex coordination challenges due to centralized procurement structures, large-scale public health operations, and rapidly evolving digital infrastructure. This study investigates how Artificial Intelligence (AI) and Physical Internet readiness influence the sustainability and resilience of healthcare supply chains by moderating the relationship between digital transformation barriers and supply chain performance. Using survey data collected from 619 healthcare supply chain professionals across Saudi Arabia, the study employs partial least squares structural equation modeling (PLS-SEM) to examine the relationships between digital transformation barriers, organizational resistance, and logistics performance. AI-PI readiness is modeled as a formative logistics capability because its dimensions, including AI-supported coordination, modular logistics infrastructure, interoperable data systems, and collaborative resource utilization, jointly form the capability. The study examines how this capability moderates the effects of digital transformation barriers on organizational resistance and sustainable healthcare supply chain performance. To evaluate the operational implications of these relationships, the empirical findings are integrated into an agent-based simulation model that examines system performance under disruption scenarios. The results show that technological and organizational constraints significantly hinder digital transformation in healthcare supply chains, while AI-PI capabilities moderate these effects by improving coordination efficiency and reducing systemic resistance. Simulation experiments further demonstrate that AI-enabled logistics architectures can enhance supply chain resilience while improving resource utilization and sustainability outcomes. The findings provide theoretical insights into the role of integrated logistics architectures in sustainable supply chain transformation and offer practical guidance for healthcare organizations seeking to develop digitally coordinated logistics networks aligned with national sustainability and healthcare modernization initiatives.

This paper focuses on Egyptian Customs clearance services and investigates the impact of the adoption of blockchain technology on the relationship between service quality and customer satisfaction. The five dimensions of the SERVQUAL model, including reliability, assurance, tangibles, empathy, and responsiveness, in conjunction with the Technology-Organization-Environment (TOE) framework of blockchain adoption, helped guide the collection of data from 401 employees in customs clearance operations. The results of Structural Equation Modeling (SEM) with AMOS indicated that the impact of service quality on customer satisfaction is significant (β = 0.495, p < 0.001), while that on the adoption of blockchain is (β = 0.801, p < 0.001). Moreover, the adoption of blockchain positively influences customer satisfaction (β = 0.410, p = 0.003). It was also confirmed that of the relationship between service quality and customer satisfaction (p < 0.001), the adoption of blockchain explains 73.9% of the variance in customer satisfaction (R² = 0.739). The results show that the integration of some blockchain technologies in customs operations can facilitate the service quality and customer satisfaction relationship by enhancing transparency, clearance times, and documentation error. Lastly, this study focuses on the pertinent literature of developing countries in the midst of digital transformation and offers valuable perspective for the Egyptian customs authorities concerned with improving current trade facilitation practices..

Background: Amid rising trade, urbanization, and carbon emissions in MENA countries, sustainable logistics faces major constraints. This study develops an enhanced Green Logistics Performance Index (GLPI) using min-max normalization and Principal Component Analysis (PCA) to integrate the World Bank's Logistics Performance Index (LPI) and Yale's Environmental Performance Index (EPI). The study uses fixed-effects panel regression on data from 20 MENA countries (2018-2024), identifies key drivers, and applies ARIMA and LSTM models for 2030 projections. The prior ratio-based GLPI suffered from scale sensitivity and volatility; this refined version provides improved stability and predictive utility for Green Supply Chain Management (GSCM). Methods: Panel data from 20 MENA countries (2018-2024) were analyzed. The enhanced GLPI normalizes and weights LPI and EPI scores via PCA. Fixed-effects regression identifies drivers, while ARIMA and LSTM enable scenario-based forecasting (baseline, optimistic, and pessimistic). Results: Renewable energy share positively influences GLPI, while trade openness has a negative effect. Projections indicate the regional GLPI will reach about 0.65 by 2030, with Saudi Arabia potentially achieving 25% higher under optimistic conditions. Conclusions: The refined GLPI advances GSCM theory by operationalizing triple bottom line trade-offs through a robust, predictive metric. It bridges descriptive limitations in prior literature, enabling forward-looking insights into sustainable logistics in emerging economies, with potential applicability beyond MENA.

This study addresses the critical problem of barriers hindering Green Supply Chain Management (GSCM) adoption in Egypt's petrochemical sector, a major economic driver that produces approximately 4.5 million tons annually but generates significant GHG emissions and hazardous waste. The objective is to identify, rank, and analyze the hierarchical relationships among internal and external barriers using a mixed-methods approach. This study focuses on the full petrochemical supply chain in Egypt, encompassing upstream (raw material sourcing), midstream (manufacturing/refining processes), and downstream (distribution, waste management, reverse logistics), with an emphasis on emission/waste reduction practices. Data were collected via a structured questionnaire from 400 employees in Egyptian petrochemical firms and analyzed using Interpretive Structural Modeling (ISM). The findings showed that internal impediments, such as a lack of corporate leadership and support (IB1), a critical shortage of resources (IB6), and the absence of green initiatives (IB5), serve as driving forces that exert a cascading influence over the external barriers, which include insufficient government support (EB1), a lack of markets for recycled materials (EB5), and human resources or expertise shortages (EB7). The study contributes to the existing literature on GSCM by incorporating international trends and specifically addressing Egyptian issues, including weak policies, difficult supply chains, high energy-intensive operations, and costly operations. The study suggests that sending clear messages from the top and providing financial incentives can help push the obstacles aside and guide the industry down the path of environmentally responsible operations.

Background: Supply chain management (SCM) research has expanded across the Middle East and North Africa (MENA), yet the field remains fragmented. Limited synthesis exists on how regional conditions shape research themes, theories, and methods. Methods: This study applies the PRISMA 2020 protocol to review SCM articles indexed in Scopus and Web of Science from January 2000 to March 2025. After screening and eligibility assessment, 512 peer-reviewed studies were retained. Bibliometric mapping and thematic coding were used to identify publication trends, research streams, theoretical lenses, and methodological patterns. Results: SCM research increased sharply after 2015, reflecting national diversification agendas, logistics reform, digitalization, and exposure to global supply chain disruptions. Three dominant streams were identified: resilience, sustainability, and digital transformation. Research output is concentrated in Saudi Arabia and the United Arab Emirates, while cross-country comparative studies remain scarce. Empirical studies rely mainly on cross-sectional surveys and SEM-based analysis, with limited longitudinal, qualitative, mixed-method, and comparative work across the region. Conclusions: The study develops an integrative SCM capability framework linking regional structural conditions, capability development, and supply chain outcomes. The findings support managers and policymakers seeking resilient, sustainable, and digitally enabled supply chains, and define clear future research priorities for the MENA region.

Background: Amid rising trade, urbanization, and carbon emissions in MENA countries, sustainable logistics faces major constraints. This study develops an enhanced Green Logistics Performance Index (GLPI) using min-max normalization and Principal Component Analysis (PCA) to integrate the World Bank’s Logistics Performance Index (LPI) and Yale’s Environmental Performance Index (EPI). The study uses fixed-effects panel regression on data from 20 MENA countries (2018–2024), identifies key drivers, and applies ARIMA and LSTM models for 2030 projections. The prior ratio-based GLPI suffered from scale sensitivity and volatility; this refined version provides improved stability and predictive utility for Green Supply Chain Management (GSCM). Methods: Panel data from 20 MENA countries (2018–2024) were analyzed. The enhanced GLPI normalizes and weights LPI and EPI scores via PCA. Fixed-effects regression identifies drivers, while ARIMA and LSTM enable scenario-based forecasting (baseline, optimistic, and pessimistic). Results: Renewable energy share positively influences GLPI, while trade openness has a negative effect. Projections indicate the regional GLPI will reach about 0.65 by 2030, with Saudi Arabia potentially achieving 25% higher under optimistic conditions. Conclusions: The refined GLPI advances GSCM theory by operationalizing triple bottom line trade-offs through a robust, predictive metric. It bridges descriptive limitations in prior literature, enabling forward-looking insights into sustainable logistics in emerging economies, with potential applicability beyond MENA.

This study addresses the critical problem of barriers hindering Green Supply Chain Management (GSCM) adoption in Egypt’s petrochemical sector, a major economic driver that produces approximately 4.5 million tons annually but generates significant GHG emissions and hazardous waste. The objective is to identify, rank, and analyze the hierarchical relationships among internal and external barriers using a mixed-methods approach. This study focuses on the full petrochemical supply chain in Egypt, encompassing upstream (raw material sourcing), midstream (manufacturing/refining processes), and downstream (distribution, waste management, reverse logistics), with an emphasis on emission/waste reduction practices. Data were collected via a structured questionnaire from 400 employees in Egyptian petrochemical firms and analyzed using Interpretive Structural Modeling (ISM). The findings showed that internal impediments, such as a lack of corporate leadership and support (IB1), a critical shortage of resources (IB6), and the absence of green initiatives (IB5), serve as driving forces that exert a cascading influence over the external barriers, which include insufficient government support (EB1), a lack of markets for recycled materials (EB5), and human resources or expertise shortages (EB7). The study contributes to the existing literature on GSCM by incorporating international trends and specifically addressing Egyptian issues, including weak policies, difficult supply chains, high energy-intensive operations, and costly operations. The study suggests that sending clear messages from the top and providing financial incentives can help push the obstacles aside and guide the industry down the path of environmentally responsible operations.