1. OSCM Publications
  2. Volume 17, Issue 2, 2024

Volume 17, Issue 2, 2024

  1. A Bibliometric Analysis: Mapping the Evolution of Maritime Supply Chain Research Trends Across Academic Tides
    • Kazi Mohiuddin
    • Xuefeng Wang
    • Marufa Easmin Shormi
    • Mian Zafar
    • Mohammad Shamsu Uddin
    Abstract Full PDF Cite DOI: 10.31387/oscm0570421
    The maritime industry has been vital 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, and existing themes and address gaps within maritime supply chain publications. 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: 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.
    @article{kazimohiuddin-2024-1633,
  title={A Bibliometric Analysis: Mapping the Evolution of Maritime Supply Chain Research Trends Across Academic Tides},
  author={Kazi  Mohiuddin and Xuefeng  Wang and Marufa  Easmin Shormi and Mian  Zafar and Mohammad  Shamsu Uddin},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={182--196},
  doi={10.31387/oscm0570421}
}
    Kazi  Mohiuddin, Xuefeng  Wang, Marufa  Easmin Shormi, Mian  Zafar, Mohammad  Shamsu Uddin (2024). A Bibliometric Analysis: Mapping the Evolution of Maritime Supply Chain Research Trends Across Academic Tides. Operations and Supply Chain Management: An International Journal, 17(2), 182-196. https://doi.org/10.31387/oscm0570421
  2. Impact of Interactional Justice on Long-Term Orientation and Logistics Performance in the Supply Chain
    • Changjoon Lee
    • Young-Kyou Ha
    Abstract Full PDF Cite DOI: 10.31387/oscm0570422
    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.
    @article{changjoonlee-2024-1634,
  title={Impact of Interactional Justice on Long-Term Orientation and Logistics Performance in the Supply Chain},
  author={Changjoon  Lee and Young-Kyou  Ha},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={197--205},
  doi={10.31387/oscm0570422}
}
    Changjoon  Lee, Young-Kyou  Ha (2024). Impact of Interactional Justice on Long-Term Orientation and Logistics Performance in the Supply Chain. Operations and Supply Chain Management: An International Journal, 17(2), 197-205. https://doi.org/10.31387/oscm0570422
  3. Location-Routing Problem for Integrated Supply Chain Network Design with First and Last Mile: A Critical Literature Review
    • Rafael Arevalo-Ascanio
    • Annelies De Meyer
    • Roel Gevaers
    • Ruben Guisson
    • Wouter Dewulf
    Abstract Full PDF Cite DOI: 10.31387/oscm0570423
    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.
    @article{rafaelarevalo-ascanio-2024-1635,
  title={Location-Routing Problem for Integrated Supply Chain Network Design with First and Last Mile: A Critical Literature Review},
  author={Rafael  Arevalo-Ascanio and Annelies  De Meyer and Roel  Gevaers and Ruben  Guisson and Wouter  Dewulf},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={206--219},
  doi={10.31387/oscm0570423}
}
    Rafael  Arevalo-Ascanio, Annelies  De Meyer, Roel  Gevaers, Ruben  Guisson, Wouter  Dewulf (2024). Location-Routing Problem for Integrated Supply Chain Network Design with First and Last Mile: A Critical Literature Review. Operations and Supply Chain Management: An International Journal, 17(2), 206-219. https://doi.org/10.31387/oscm0570423
  4. Simulation-Based Optimization of Logistics Decisions under Horizontal Collaboration Following the Can-Order Policy
    • Shaza Hammoud
    • Rami As'ad
    • Mohamed Ben-Daya
    • Moncer Hariga
    Abstract Full PDF Cite DOI: 10.31387/oscm0570424
    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.
    @article{shazahammoud-2024-1636,
  title={Simulation-Based Optimization of Logistics Decisions under Horizontal Collaboration Following the Can-Order Policy},
  author={Shaza  Hammoud and Rami  As'ad and Mohamed  Ben-Daya and Moncer  Hariga},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={220--235},
  doi={10.31387/oscm0570424}
}
    Shaza  Hammoud, Rami  As'ad, Mohamed  Ben-Daya, Moncer  Hariga (2024). Simulation-Based Optimization of Logistics Decisions under Horizontal Collaboration Following the Can-Order Policy. Operations and Supply Chain Management: An International Journal, 17(2), 220-235. https://doi.org/10.31387/oscm0570424
  5. Optimizing Procurement Strategies for Diverse Product Segments: A Case Study in Pharmaceutical Supply Chain Management
    • Kaoutar Douaioui
    • Rachid Oucheikh
    • Othmane Benmoussa
    Abstract Full PDF Cite DOI: 10.31387/oscm0570425
    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.
    @article{kaoutardouaioui-2024-1637,
  title={Optimizing Procurement Strategies for Diverse Product Segments: A Case Study in Pharmaceutical Supply Chain Management},
  author={Kaoutar  Douaioui and Rachid  Oucheikh and Othmane  Benmoussa},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={236--252},
  doi={10.31387/oscm0570425}
}
    Kaoutar  Douaioui, Rachid  Oucheikh, Othmane  Benmoussa (2024). Optimizing Procurement Strategies for Diverse Product Segments: A Case Study in Pharmaceutical Supply Chain Management. Operations and Supply Chain Management: An International Journal, 17(2), 236-252. https://doi.org/10.31387/oscm0570425
  6. The Role of Supply Chain Transparency in the Relation between Supply Chain Analytics Capabilities and Firm Performance
    • Murat Cemberci
    • Sumeyye Cicek Vural
    • Cemil Celik
    • Elif Canbaz
    Abstract Full PDF Cite DOI: 10.31387/oscm0570426
    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 participants 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.
    @article{muratcemberci-2024-1638,
  title={The Role of Supply Chain Transparency in the Relation between Supply Chain Analytics Capabilities and Firm Performance},
  author={Murat  Cemberci and Sumeyye  Cicek Vural and Cemil  Celik and Elif  Canbaz},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={253--263},
  doi={10.31387/oscm0570426}
}
    Murat  Cemberci, Sumeyye  Cicek Vural, Cemil  Celik, Elif  Canbaz (2024). The Role of Supply Chain Transparency in the Relation between Supply Chain Analytics Capabilities and Firm Performance. Operations and Supply Chain Management: An International Journal, 17(2), 253-263. https://doi.org/10.31387/oscm0570426
  7. Healthcare Supply Chain Disruption Risks
    • Fatima Ahmad
    • Abdulrahim Shamayleh
    • Abdelkader Daghfous
    • Inas Al Khatib
    • Ghufran Al Salloum
    • Salma Elabed
    Abstract Full PDF Cite DOI: 10.31387/oscm0570427
    The healthcare sector stands as a cornerstone of every nation’s economy, while playing a vital role in fostering the health and wellbeing of populations. Numerous studies have addressed the effective management of healthcare supply chains to ensure optimal healthcare provision. Implementing efficient strategies not only reduces costs but also enhances quality, efficiency, and adaptability. However, the COVID-19 pandemic has exposed significant shortcomings in Healthcare Supply Chain (HSC) risk management strategies. This pandemic has shown that the HSC was unprepared for such disruption and that the traditional supply chain risk strategies followed are restrictive in tackling long-term global pandemic disruptions. To contribute to the current research on this topic, we introduce a framework that identifies and comprehends disruption risks, their origins, and impacts. Through a thorough literature review and interviews with HSC specialists, risks are identified and prioritized using Bayesian Belief Networks (BBN). The findings of this study seek to provide HSC decision-makers with valuable insights into the primary risks associated with HSC disruptions, paving the way for the development of effective mitigation strategies.
    @article{fatimaahmad-2024-1639,
  title={Healthcare Supply Chain Disruption Risks},
  author={Fatima  Ahmad and Abdulrahim  Shamayleh and Abdelkader  Daghfous and Inas  Al Khatib and Ghufran  Al Salloum and Salma  Elabed},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={264--283},
  doi={10.31387/oscm0570427}
}
    Fatima  Ahmad, Abdulrahim  Shamayleh, Abdelkader  Daghfous, Inas  Al Khatib, Ghufran  Al Salloum, Salma  Elabed (2024). Healthcare Supply Chain Disruption Risks. Operations and Supply Chain Management: An International Journal, 17(2), 264-283. https://doi.org/10.31387/oscm0570427
  8. The Impact of COVID-19 on Industry 4.0 Adoption: An Emerging Economy Perspective
    • Said Usman
    Abstract Full PDF Cite DOI: 10.31387/oscm0570428
    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. To address these challenges, 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 organizations, 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 the 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. Based on these findings, the study recommends that companies in emerging economies invest in infrastructure, training and development, seek government support, address data privacy and security concerns, and plan for the long-term implications of Industry 4.0 adoption. This research, anchored in a robust dataset, provides valuable insights into the role of Industry 4.0 technologies in enhancing supply chain resilience in emerging economies during the COVID-19 pandemic and the challenges that companies in these economies may face in implementing these technologies.
    @article{saidusman-2024-1640,
  title={The Impact of COVID-19 on Industry 4.0 Adoption: An Emerging Economy Perspective},
  author={Said  Usman},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={284--298},
  doi={10.31387/oscm0570428}
}
    Said  Usman (2024). The Impact of COVID-19 on Industry 4.0 Adoption: An Emerging Economy Perspective. Operations and Supply Chain Management: An International Journal, 17(2), 284-298. https://doi.org/10.31387/oscm0570428
  9. Central Hospital Location and Distribution Planning Using Integrated K-Means and Vehicle Routing Algorithm in the Healthcare Chain
    • Kasin Ransikarbum
    • Duangpun Kritchanchai
    • Wirachchaya Chanpuypetch
    • Jirawan Niemsakul
    Abstract Full PDF Cite DOI: 10.31387/oscm0570429
    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.
    @article{kasinransikarbum-2024-1641,
  title={Central Hospital Location and Distribution Planning Using Integrated K-Means and Vehicle Routing Algorithm in the Healthcare Chain},
  author={Kasin  Ransikarbum and Duangpun  Kritchanchai and Wirachchaya  Chanpuypetch and Jirawan  Niemsakul},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={299--315},
  doi={10.31387/oscm0570429}
}
    Kasin  Ransikarbum, Duangpun  Kritchanchai, Wirachchaya  Chanpuypetch, Jirawan  Niemsakul (2024). Central Hospital Location and Distribution Planning Using Integrated K-Means and Vehicle Routing Algorithm in the Healthcare Chain. Operations and Supply Chain Management: An International Journal, 17(2), 299-315. https://doi.org/10.31387/oscm0570429
  10. A Review of Models for Dependency of Risks: Extension and Applications to Supply Chains
    • Leila Morteza Beigi
    • Elkafi Hassini
    • Narges Soltani
    Abstract Full PDF Cite DOI: 10.31387/oscm0570430
    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.
    @article{leilamortezabeigi-2024-1642,
  title={A Review of Models for Dependency of Risks: Extension and Applications to Supply Chains},
  author={Leila  Morteza Beigi and Elkafi  Hassini and Narges  Soltani},
  journal={Operations and Supply Chain Management: An International Journal},
  year={2024},
  volume={17},
  number={2},
  pages={316--329},
  doi={10.31387/oscm0570430}
}
    Leila  Morteza Beigi, Elkafi  Hassini, Narges  Soltani (2024). A Review of Models for Dependency of Risks: Extension and Applications to Supply Chains. Operations and Supply Chain Management: An International Journal, 17(2), 316-329. https://doi.org/10.31387/oscm0570430
Other links