List of Forthcoming Journals

Abstract:
This study examines public sector operations in supplier management as applied to public-sector procurement in a developing country (South Africa (SA)) to delineate practices that have a salutary impact on the performance of the public sector supply chain. Based on the largest survey conducted in this context (333 Supply Chain Management (SCM) public sector professionals in SA), analysis was conducted using descriptive and inferential statistics, and hypotheses were tested using Structural Equation Modelling. Results indicate that three SCM practices (collaboration, innovation, and integration) exert a significant positive influence on supplier performance. Further, supplier performance exerted a significant positive influence on supply chain resilience. Managerial implications of the findings are discussed, especially practices that deserve attention to improve the performance of suppliers and how supplier performance can be harnessed to enhance resilience of public sector supply chains in developing economies.

Abstract:
Efficiently managing blood production and inventory is critical for achieving an adequate blood supply. Due to the complexity of blood components, optimizing their production and inventory levels, particularly during blood shortages, is challenging. This paper proposes a dynamic approach for blood component production-inventory optimization that considers transshipment, hierarchical substitution, crossmatching, and age. The hierarchical substitution in this study refers to the substitution of blood components due to heterogeneous demands rather than for ABO group compatibility as previously studied. In clinical practice, component substitution is more commonly utilized than ABO compatible substitution. Such a challenging problem is formulated as a multi-objective optimization problem where the shortage rate, system cost, and average storage age are the objectives to be optimized. To address this complex model, an improved whale optimization algorithm is proposed. Numerical experiments are presented to validate the efficiency of the model and demonstrate that transshipment and substitution effectively mitigate blood component shortages.

Abstract:
Despite extensive research on logistics service quality, a significant gap remains in frameworks that concurrently capture both provider and customer perspectives. This paper aims to validate a logistics service quality framework that integrates the perspectives of both logistics service providers and customers, addressing the limitations of traditional models that consider these perspectives in isolation. A two-stage analysis, involving exploratory and confirmatory factor analyses, is conducted to identify and examine the key dimensions of logistics service quality from both stakeholder perspectives. To demonstrate the framework’s applicability, a case study is carried out in the Philippines. The findings highlight critical dimensions such as location, timeliness, tracking, and service recovery. Notably, this is the first study to unify provider and customer viewpoints in assessing logistics service quality, offering a more holistic understanding that can better align services with the expectations and goals of all parties involved.

Abstract:
In the wake of post-COVID-19 shifts in consumer behavior and competitive pressures, assessing supply chain relationships among South African SMEs has become increasingly critical. Key relational dimensions enhance cost-efficiency and business performance, but they vary across sectors due to the distinct nature of products and services. To explore the extent of these differences, this study surveyed 396 SMEs using convenience sampling. Factor analysis and Bayesian regression modelling were employed to evaluate and compare the strength of supply chain relationships across sectors. The analysis reveals that trust and communication are perceived as slightly stronger in all sectors, with manufacturing showing a slightly weaker strength and agriculture having a relatively stronger score strength. The quality dimension varies significantly across sectors, with agriculture leading in product quality strength, followed closely by wholesale and transport, while manufacturing trails behind. Flexibility is also slightly stronger for most sectors, with the agriculture sector leading, while the manufacturing sector lags. Commitment is slightly strong across all sectors, with manufacturing lag again and other sectors showing. Construction exhibits consistently weaker strengths across all four dimensions of the logistics relationship.

Abstract:
Spare parts management is a persistent operational challenge, often constrained by long lead times, high inventory costs, and frequent supply chain disruptions. Digital spare parts (DSP), enabled by additive manufacturing and digital technologies, provide a promising alternative through localized production and demand-driven supply. Yet, successful DSP adoption requires more than technological readiness; it depends on a systemic understanding of the ecosystem of enablers that shape both economic and operational viability. This study develops and empirically validates a structural model of DSP ecosystem readiness in the United Arab Emirates, an emerging economy pursuing industrial diversification. Data were collected from 162 industry professionals across energy, manufacturing, healthcare, automotive, and aerospace sectors. Using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), the study examines the interdependencies among 13 critical ecosystem factors. Findings show that infrastructure readiness, cost management, vendor support, customization capability, and quality assurance significantly and positively influence DSP adoption. In contrast, material availability, scalability, and industry readiness demonstrate counterintuitive negative effects, while sustainability and risk management exhibit no significant direct impacts. The results highlight the complex interplay of economic and operational drivers, providing an empirically grounded framework for decision-making and offering actionable insights for managers and policymakers.

Abstract:
The Cluster-Led coordination approach enhances humanitarian aid distribution by centralising coordination, addressing critical gaps, and fostering partnerships. In this study, we explore the challenges of implementing a cluster-led coordination approach in humanitarian aid distribution during armed conflicts. Additionally, we explore the factors that influence humanitarian actors’ intention to use of a decision-support tool (DST) to optimise humanitarian aid distribution planning within this approach. Qualitative research through semi-structured interviews with humanitarian cluster coordinators and focal points in Palestine and Syria is employed. We identify key challenges in implementing a cluster-led approach to humanitarian aid distribution, while also highlighting the potential advantages and barriers of adopting a Decision Support Tool (DST). Our study offers novel insights into the barriers of implementing the cluster-led coordination approach for humanitarian aid distribution during human-made disasters, as well as intention to use the decision-support tools (DSTs) within this approach. It highlights key areas for future research, including the long-term impacts of such approaches, the integration of advanced technologies, and the role of DSTs in strengthening supply network resilience and response efforts. These findings are critical for refining humanitarian aid distribution strategies, enhancing humanitarian logistics coordination, and fostering resilient humanitarian networks in human-made disasters contexts.

Abstract:
This study develops a fairness-oriented police duty scheduling framework minimizing perceived workload imbalances among officers. A Mixed Integer Programming (MIP) model is used for fairness-aware scheduling, incorporating officer-perceived workload into optimization. The model follows Taiwan's regulations mandating balanced rest/duty times—specifically the '12-hour duty, 8-hour break' rule, requiring at least eight consecutive daily rest hours and limiting night shifts to under 4 hours. Workload intensities, derived via Analytic Hierarchy Process (AHP) from Taiwanese police survey data, capture officers' subjective duty intensity perceptions. Personalized weights are embedded in the model which minimizes deviations in assigned duty workloads from the average across all officers for equitable distribution. Computational testing using CPLEX on Taiwanese police scenarios (35 & 40 officers, varying duty/rest hours) finds optimal solutions within hours, confirming its practical applicability. A repeated-measures ANOVA shows that reducing daily working hours from 12 to 10 lowers officers’ weekly perceived workload because they work fewer shifts, while workload per shift does not change significantly. The length of the daily rest period (6 or 8 hours) has no significant effect.

Abstract:
Hazardous materials logistics remains one of the most disruption-sensitive domains in modern supply chains, where failures at storage–transport interfaces can escalate into cascading safety, environmental, and operational consequences. Although prior research has advanced risk identification and resilience conceptualization, structured decision-support mechanisms for prioritizing mitigation strategies under multiple conflicting criteria at safety-critical interfaces remain scarce. This study develops and empirically applies an integrated multi-criteria decision framework combining the Best–Worst Method (BWM) and PROMETHEE II to prioritize risk mitigation strategies for ammunition loading–unloading operations at a maritime depot operated by the Indonesian Navy. BWM derives consistency-controlled criteria weights under a linear programming formulation, while PROMETHEE II generates dominance-based rankings using a linear preference function applied to expert-elicited performance scores. Nine domain experts, organized into three structured group deliberation sessions, provide pairwise comparison inputs and decision matrix scores for five mitigation alternatives evaluated across six criteria. The resulting weight structure assigns 77.5% of total importance to Safety, Security, and Regulatory Compliance, reflecting expert consensus on the primacy of systemic risk control at this interface. Integrated Security System Enhancement achieves complete pairwise dominance and ranks first, followed by Automated Equipment and Integrated Risk Management in the positive net flow tier, while Training and Certification and Specialized Cranes fall in the negative tier. Oneat-a-time sensitivity analysis confirms full ranking stability across all perturbation scenarios. The study demonstrates a transparent, auditable prioritization instrument for high-reliability logistics environments, with framework transferability to civilian dangerous goods supply chains discussed under explicit boundary conditions.

Abstract:
Designing sustainable supply chains requires firms to simultaneously balance economic performance, environmental responsibility, and social inclusion. Strategic network design decisions—such as facility location, supplier engagement structure, capacity allocation, and energy sourcing—directly influence emissions, employment distribution, and inclusive development outcomes. However, managers lack integrated decision-support frameworks that quantitatively evaluate trade-offs among profitability, renewable energy adoption, and inclusive sourcing strategies at the network level. This study develops a multi-objective supply chain network design framework that jointly optimizes economic profit, environmental emissions, and social utility. The model integrates renewable energy investment decisions and inclusive supplier development within a unified planning structure. A real-world agro-industrial case study demonstrates how alternative network configurations generate distinct trade-offs across the three sustainability pillars. Results show that inclusive sourcing can enhance social performance and profitability up to critical capacity thresholds, while renewable energy adoption becomes economically viable under specific demand and reputation conditions. The findings provide actionable insights for supply chain managers seeking to design sustainable and inclusive production networks without sacrificing competitiveness.

Abstract:
Indonesia is vulnerable to natural disasters, which frequently disrupt ground transportation infrastructure and hinder humanitarian aid distribution. In such conditions, drone-based logistics offers a promising alternative for last-mile delivery to affected areas. This study proposes an integrated optimization framework for humanitarian drone logistics that combines a multi-objective Facility Location Problem (FLP) and a Vehicle Routing Problem (VRP). The FLP determines the optimal locations of drone stations to maximize service coverage while minimizing infrastructure and operational costs. The VRP, solved using a modified Simulated Annealing (SA) algorithm, optimizes pickup-and-delivery routes with multi-trip capability under drone capacity, distance, and operational time constraints. The framework is evaluated using data from the 2022 Cianjur earthquake in Indonesia. Results show that 19 strategically located drone stations can achieve 94.7% service coverage, serving 403 out of 489 demand points. While the strategic model estimates a requirement of 59 drones, operational routing optimization reduces the daily fleet to 32 drones, representing a 46% reduction and yielding a daily operational cost of approximately IDR 4.2 million. The findings demonstrate that integrated strategic–operational optimization significantly enhances the efficiency and feasibility of drone-based humanitarian logistics, supporting more responsive and cost-effective disaster relief operations.

Abstract:
Three-station production lines without intermediate buffers are analyzed using the holding-time model. This model allows the analysis to be performed for service times at two end stations having phase-type (PH) distribution and the middle station having an arbitrary distribution. Such choices of distribution produce a system of linear algebraic equations with closed-form solutions for cumulative distribution functions (CDFs) of variables in the system of equations and the interdemand time. When all stations have PH-distributed service times, closure properties of PH distribution can be employed to provide closed-form formulas for CDFs of other variables that are not in the system of equations, including the interdeparture time.