List of Forthcoming Journals

The journals in the list below have been accepted for publication in Operations and Supply Chain Management: An International Journal. We are currently in the process of assigning each of these entries into our upcoming issue. Once published, you can access the corresponding article for free through our repository. Please feel free to contact us via Contact Us page or our email for any inquiries.

1. Location-Routing Problem for integrated supply chain network design with first and last mile: A critical literature review

Rafael Arevalo-Ascanio (University of Antwerp, Prinstraat 13, 2000 Antwerpen, Belgium),
Annelies De Meyer (MooV, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium),
Roel Gevaers (University of Antwerp, Prinstraat 13, 2000 Antwerpen, Belgium),
Ruben Guisson (MooV, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium),
Wouter Dewulf (University of Antwerp, Prinstraat 13, 2000 Antwerpen, Belgium)

Supply chain management includes strategic, tactical, and operational decisions for long, medium, and short-term planning. Strategic decisions, such as network design, and operational decisions, such as last-mile routing, have mutual implications. Therefore, modelling them separately can lead to sub-optimal solutions. The integrated modelling of these decisions has been addressed as a location routing problem (LRP). This paper aims to identify the solution strategies and methods to solve the LRP, as well as related challenges and research opportunities based on a critical literature review. The findings reveal that 46% of the reviewed publications have adopted a multistage modelling approach to address the LRP, sequentially tackling strategic and operational decisions. Moreover, in addition to the challenge of modelling diverse decision levels, the LRP models need to incorporate variables such as time windows, delivery failure rates, demand density, etc. Five research opportunities are proposed: i) modelling the first and last mile with a strategic approach when making strategic network decisions, ii) integrating environmental and social objectives into the modelling framework, iii) applying the solution methods and algorithms to complex real-world cases, iv) exploring competitive and cooperative models in LRP, and v) evaluating the use of emerging technologies.

2. Central Hospital Location and Distribution Planning Using Integrated Kmeans and Vehicle Routing Algorithm in the Healthcare Chain

Kasin Ransikarbum (Ubonratchathani University, Thailand),
Duangpun Singkarin (Mahidol University, Thailand),
Wirachchaya Chanpuypetch (Chiang Mai University, Thailand),
Jirawan Niemsakul (Sripatum University, Thailand)

A healthcare chain (HC) involves interrelated activities inclusive of medicine manufacturing, storage, and last-mile distribution to drug retailers and users. Major decision-makers in the HC are also interrelated, in which proper management and planning for logistics activities are required to enhance efficiency and effectiveness. In this study, we first investigate the optimal locations of central hospitals using the K-means algorithm at the midstream of the healthcare chain for long-term planning. Next, we assess the distribution plan of medical supplies by integrating the capacitated vehicle routing problem (CVRP) model with a limited time planning horizon, in which the total economic aspect is evaluated for the short-term plan. Then, our integrated framework is applied to a case study of existing hospitals in Thailand to verify and validate model functionalities. We then examine both locational and distribution plans and present our findings using the geographic information system (GIS). The sensitivity analysis is further performed to evaluate the clustering classification scheme for central hospitals and to evaluate the impact on healthcare logistics plans.

3. The Role of Supply Chain Transparency in the Relation Between Supply Chain Analytics Capabilities and Firm Performance

Murat Cemberci (Y?ld?z Technical University, Turkey),
Sumeyye Cicek (Y?ld?z Technical University, Turkey),
Cemil Celik (Dinçer Lojistik A.?.),
Elif Canbaz (Dinçer Lojistik A.?.)

Ever-increasing data change the business environment with a great acceleration. This unavoidable data growth brings uncertainties and causes heavy pressure on firms. In this context, supply chain analytics have much more attention in order to manage data in the field of supply chain management. Despite the growing interest in analytics capabilities, the studies are in its early stages. The current study investigated the role of supply chain transparency in the relation between supply chain analytics capabilities and firm performance. The data was gathered via survey from 100 participant from different companies and the PLS-SEM was used in order to investigate theoretical framework. The results indicate that enhanced supply chain analytic capabilities have positive impacts on the firm performance and the supply chain transparency positively moderates this relationship.

4. Simulation-Based Optimization of Logistics Decisions under Horizontal Collaboration Following the Can-Order Policy

Shaza Hammoud (American University of Sharjah, United Arab Emirates),
Rami As'Ad (American University of Sharjah, United Arab Emirates),
Mohamed Ben-Daya (American University of Sharjah, United Arab Emirates),
Moncer Hariga (American University of Sharjah, United Arab Emirates)

In today's competitive and environmentally conscious business landscape, companies constantly seek more efficient ways to conduct their daily operations. Horizontal Logistics Collaboration (HLC), in which firms at the same supply chain level share resources such as trucks and information, has proven effective in achieving synchronized deliveries, optimizing transport equipment usage, and reducing carbon footprint. This study implements HLC between two neighboring companies ordering different products from the same supplier. The study adopts the can-order policy, employing three threshold values to define each company's ordering policy and potential joint orders. To better reflect real-world operational aspects, a simulation-based optimization approach is employed, allowing experimentation with various realistic scenarios. The developed model assumes stochastic demand and lead time for both companies and assesses the benefits of HLC from both economic and environmental standpoints, one at a time. Computational experiments consistently demonstrate cost savings through collaboration, especially when both companies are similar with low unit holding costs. From an environmental standpoint, adopting the collaborative model can reduce carbon emissions by up to 27%, particularly when both companies are identical and have low demand and low products' weight. Statistical analysis using paired t-tests confirms the significant differences in cost and carbon emissions after implementing HLC

5. A Bibliometric Analysis: Mapping the Evolution of Maritime Supply Chain Research Trends Across Academic Tides

Kazi Mohiuddin (Shanghai Maritime University),
Xuefeng Wang (Shanghai Maritime University),
Marufa Easmin Shormi (Khulna University),
Mian Gohar Rahman Zafar (Shanghai Maritime University),
Mohammad Shamsu Uddin (Islamic University of Technology )

The maritime industry has been a vital player in facilitating and enabling economic development and global trade. Although the industry and its supply chain are not new concepts, they have gained significant attention from academic researchers over the past decade. As a result, numerous scholarly explorations and investigations have been published. This study aims to analyze publication trends, scientific impact, existing themes, and address gaps within the maritime supply chain publications. To do this, a bibliometric method is applied to 382 articles extracted from two popular databases, Scopus and Web of Science. The study uncovered a growing focus on the maritime supply chain, with particular attention given to maritime logistics. The literature revealed several recurring themes, such as blockchain integration, supply chain risk management, and green logistics. However, there is still a need for more empirical investigation into sustainable performance, especially in areas like the green maritime supply chain. Future studies should expand on existing conceptual explorations and incorporate empirical investigations. The findings have two main benefits: they provide researchers with opportunities for further investigation and enable policymakers and port authorities to monitor global maritime supply chain trends and progress. By doing so, they can learn from others' initiatives and improve their current practices.

6. A Review of Models for Dependency of Risks: Extension and Applications to Supply Chains

Leila Morteza Beigi (School of Computational Sciences and Engineering, McMaster University, Canada),
Elkafi Hassini (DeGroote School of Business, McMaster University, Canada),
Narges Soltani (DeGroote School of Business, McMaster University, Canada)

Today’s highly integrated supply chains are exposed to various types of risks that disrupt the normal flow of goods or services within a supply chain network. Since most of these individual risks are interconnected, a mitigation strategy to tackle one risk may result in the exacerbation of another. Given that the occurrence of one risk may cause a chain reaction, an important question arises: how to model risk dependencies in a supply chain and what factors are relevant in measuring supply chain dependencies? In the financial insurance literature, risk dependencies have been modeled using two approaches : (i) random variables, and (ii) copulas. This paper first reviews these studies to understand the dependency factors and their sources. Then, these models are extended for predicting and mitigating supply chain risks under dependencies. Finally, those models are applied to different supply chain network configurations.

7. Impact of Interactional Justice on Long-term Orientation and Logistics Performance in the Supply Chain

Changjoon Lee (College of Business Administration, University of Ulsan, Republic of Korea),
Young-Kyou Ha (Department of International Trade and Logistics, Chung-Ang University, Republic of Korea )

The aim of this study is to empirically analyze the impact of justice on long-term orientation and logistics performance in the relationships between firms within the supply chain. Specifically, justice is categorized into distributive justice, procedural justice, and interactional justice. This study particularly concentrates on interactional justice, which pertains to the quality of interpersonal treatment. To investigate their correlation, a survey was conducted among employees working in departments related to supply chains in South Korea, resulting in a total of 350 valid questionnaire responses. Subsequently, the hypotheses were assessed using structural equation modeling with SPSS 18.0 and AMOS 18.0. The findings of the study are as follows: The subfactors of interactional justice, such as interpersonal justice and informational justice, both had a positive impact on long-term orientation. Furthermore, long-term orientation positively influenced logistics performance. Based on the aforementioned results, the following conclusions can be drawn: Long-term orientation among firms in the supply chain plays a pivotal role in enhancing logistics performance. Given that the perception of justice heightens the likelihood of such long-term orientation, firms in the supply chain must take this relationship into careful consideration.

8. Optimizing Procurement Strategies for Diverse Product Segments: A Case Study in Pharmaceutical Supply Chain Management

Douaioui Kaoutar (FST SETTAT, Morocco),
Rachi Oucheikh (Lund University, Lund, Sweden),
Othmane Benmoussa (Euromed University of Fes, UEMF, Morocco)

Selecting the most suitable procurement strategy is crucial to the efficient management of supply chain operations and the prevention of stock shortages. Nevertheless, when dealing with a wide variety of products, this task becomes an intricate challenge. While traditional and advanced procurement tools are available, applying them across such diverse product ranges is often impractical. This research is dedicated to determining distinct procurement strategies tailored to each product cluster. These strategies will be designed to accommodate the technical and financial constraints specific to each cluster. To address the optimization challenges associated with clustering algorithms, especially within complex search spaces, metaheuristic algorithms are considered as promising solutions. In this paper, Accelerated Particle Swarm Optimization (APSO) is harnessed for its exploratory capabilities, and Teaching Learning Based Algorithms (TLBO) are leveraged for their high exploitation competence. This innovative approach effectively combines the strengths of both algorithms, ensuring optimal clustering solutions in an efficient manner. The suggested approach outperforms the accuracy of the well-known metaheuristics including Grey Wolf Optimizer and the Whale Optimization Algorithm. This methodology successfully identifies five major clusters and assigns the appropriate procurement strategy to each cluster. The selection of a suitable procurement strategy for each product cluster significantly enhances overall procurement performance. This study introduces a powerful approach to assist managers in adapting procurement strategies for different product clusters. This approach has been implemented within organizations specializing in pharmaceutical freight and holds potential applicability across various product types. This innovation has the capacity to significantly impact and enhance global procurement performance.

9. The Impact of Covid-19 on Industry 4.0 Adoption: An Emerging Economy Perspective

Said Usman (University of Roehampton, United Kingdom)

The disruptions that Covid-19 precipitated on the world economy made it hard for companies to maintain their operations and achieve sustainable supply chain management. In order to correct this situation, companies had to leverage a new set of resources. This study, employing a desk-based qualitative research approach, investigated how Covid-19 drove companies to adopt Industry 4.0 technologies in their supply chain management, and how these technologies, including artificial intelligence and the Internet of Things, in turn drove supply chain resilience among firms in emerging countries. Through a comprehensive review of scholarly articles and publications from various organisations, the study employed the triangulation method to ensure the validity and reliability of the findings. The data collection adhered to specific criteria, including relevance, credibility, and publication date post-2020, aligning with the period when the COVID-19 pandemic began. Through a content analysis of these diverse data sources, mainly capturing sentiments of industry players, three main findings emerged. First, the adoption of Industry 4.0 technologies has had a significant impact on the resilience of supply chain management in emerging economies during the COVID-19 pandemic. Second, the characteristics of emerging economies, such as limited infrastructure and a lack of technological proficiency, significantly influence the effectiveness of Industry 4.0 in enhancing supply chain resilience. Third, the long-term implications of Industry 4.0 adoption on supply chain resilience in emerging economies post-COVID-19 are multifaceted, encompassing both positive and negative effects.