Kharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801A Systematic Literature Review on the Application of Industry 4.0 Technologies in Manufacturing Supply Chain Planning Phase274292296010.22034/ijsom.2025.110610.3259ENRefentse LydiaSelepeOperations Management ,Faculty of Management Sciences, Tshwane University of Technology0000-0002-3174-7444ThomasMunyaiDepartment of Operations Management, Faculty of Management Sciences, Tshwane University of TechnologyOlasumboMakindeDepartment of Quality and Operations Management, Faculty of Engineering and the Built Environment, University of JohannesburgJournal Article20241021Supply chain systems have become crucial in today’s highly competitive and ever-changing industrial environment; hence, effective management of supply chains is required to achieve operational excellence. Planning is the first stage of supply chain systems and is crucial to ensure overall optimization of the supply chain and business sustainability. With various business processes adopting industry 4.0 technologies for optimization, the supply chain system is not an exception. Also noting that, organizations based in the least developed and developing countries need more support in adopting 4IR technologies. Thus, the objective of the study is to investigate, through literature, the key 4IR technologies that have been applied within the supply chain planning phase of manufacturing organizations. A five-step systematic literature review was adopted to carry out the research. The steps included the identification and selection of a database, keywords development, and selection of inclusion and exclusion criteria through database filters and search categories. The findings of this systematic review revealed Industry 4.0 technologies that have been deployed in the supply chain planning phase of manufacturing organizations. These include Simulation, Machine Learning, Digital Twin, and Internet-of-things. While manufacturing supply chain planning departments are faced with myriads of operational challenges and constraints, the deployment of Industry 4.0 technologies serves as a potential solution towards promoting effective supply chain operations, thereby stimulating sustainable supply chain management. The results of this study serve as a revelation to Supply Chain Managers to identify the latest trends and gain insights into appropriate Industry 4.0 technologies that could be deployed to ensure effective supply chain planning.http://www.ijsom.com/article_2960_d1c373ab1570cfb9a7dbb53c186b37a2.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Blockchain Applications in Value Added Tax Refund: A Deep Learning-Based Dual-Stage SEM-ANN Analysis293317295910.22034/ijsom.2025.110332.3054ENThuy-Thanh ThiTranVinh University, Vinh City, VietnamTri-QuanDangHo Chi Minh City University of Foreign Languages-Information Technology0000-0003-3551-9198Luan-ThanhNguyenHo Chi Minh City University of Foreign Languages-Information Technology0000-0002-3118-0572Duc-Viet ThiDangPosts and Telecommunications Institute of Technology, PTIT, Tran Phu, Ha Dong, Hanoi, Vietnam0000-0002-4953-4906Journal Article20240123This study examines the determinants of businesses' readiness to implement blockchain technology for value-added tax (VAT) refunds. This study enhances Technology Acceptance Model 2 (TAM2) by incorporating the concept of perceived risk into the framework. This study utilized a two-stage approach that integrated Partial Least Squares Structural Equation Modeling (PLS-SEM) with Artificial Neural Network (ANN) predictive analytics to test the proposed hypotheses. The ANN technique was employed to identify and analyze the potential nonlinear effects within the model. A total of 175 self-administered questionnaires were used for the analysis. The study found that a significant relationship between TAM2s’ constructs and intention to use blockchain technology can markedly enhance the efficiency of VAT refund operations from a managerial standpoint. The theoretical implications of blockchain technology are substantial, as it introduces novel concepts of trust and accountability in tax interactions, disrupts traditional intermediaries, modifies the balance of information, and redefines contract enforcement.http://www.ijsom.com/article_2959_779efbd24d5a7e37ce8dc93e7c04d572.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Solving The Capacitated Hybrid Vehicle Routing Problem Using a Random General Variable Neighborhood Search: Computational Experiments318335296110.22034/ijsom.2025.109882.2712ENAmiraBELHADJ AMMARModeling and Optimization for Decisional, Industrial and Logistic Systems Laboratory, Code: LR11ES44 , Faculty of Economics and Management, University of Sfax, Sfax, TunisiaMohamedCheikhModeling and Optimization for Decisional, Industrial and Logistic Systems Laboratory, Code : LR11ES44, Faculty of Economics and Management, University of Sfax,Sfax, TunisiaTaicir MoallaLoukilModeling and Optimization for Decisional, Industrial and Logistic Systems Laboratory, Code : LR11ES44,Faculty of Economics and Management, University of Sfax,Sfax, TunisiaJournal Article20230124Green logistics is developed due to the rise of the negative effect of logistics on the environment; and notably the transportation sector. To find advantageous solutions to both business and the environment, some governments require incorporating new environmental limits and objectives studying the vehicle routing problems. In this context, a particular NP-hard problem in this paper is studied called the Capacitated Hybrid Vehicle Routing Problem. We proposed an integer linear program for the capacitated case and we developed a Random General Variable Neighbourhood Search algorithm, which can handle the problem with a significant number of customers. We solved small instances with mutually the standard solver CPLEX and with our proposed algorithm. Outcomes show that our approach provided the same results for 55 % of the cases and superior solutions for 40 % of the instances compared to the results provided by CPLEX. In parallel, we modify a large set of benchmark instances proposed in previous works by introducing the product demand of each customer and we solve it by the Random General Variable Neighbourhood Search algorithm. Results of numerical testing show that our method delivers the best-known solutions in computation times of just 3 seconds on average.http://www.ijsom.com/article_2961_3e60e09c222f206c725385f53d7e567c.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Supply Chain Management 4.0 Research Area Maturity: A Systematic Literature Review336363296210.22034/ijsom.2025.110532.3206ENHosseinGhodrati AbbassiTehran, Daneshjoo blvd0009-0008-0273-9905MasoodRabiehShahid Beheshti University, Shahid Shahriari Square, Evin, Tehran, Iran Postal Code: 1983969411; Telephone: +98 (21) 224316440000-0001-6572-6118AbbassRezaei PandariTarbiat modaress university, Tehran< Iran.MahdiEsmaeiliFaculty of Management and Accounting, Allameh Tabataba&#039;i University, Tehran, Iran0000-0001-5623-2925Journal Article20240816Driven by the Fourth Industrial Revolution, organizations are increasingly striving to gain competitive advantages through the adoption of information and communication technologies. Among the various organizational domains affected by this transformation, the supply chain stands out as one of the most critical in highly competitive environments. Consequently, both academic and industrial researchers have consistently devoted considerable attention to the study of supply chains.<br />With the advent of Industry 4.0 technologies, a new paradigm known as Supply Chain Management 4.0 has emerged. In response to the growing prominence of this concept, the present study aims to review existing experiences and scholarly research related to Supply Chain Management 4.0. To achieve this objective, a bibliometric analysis was conducted to assess the maturity of research in this field and to identify opportunities for future investigation. The literature was systematically reviewed using the Systematic Literature Review approach. Articles published between 2011 and 2025 were retrieved from nine online databases, resulting in a final selection of 157 articles for bibliometric analysis.<br />The findings of the bibliometric study—highlighting a dispersed group of contributing authors, a limited number of dedicated journals, weak author collaboration networks, frequent use of exploratory research methods, and a narrow focus on specific keywords—suggest that Supply Chain Management 4.0 remains in the early maturity stages of research area.http://www.ijsom.com/article_2962_3b2d8f129ae2f408f2153cd9ce663043.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Sustainable Tire Closed-Loop Supply Chain Design under Uncertain Return and Demand364395295810.22034/ijsom.2024.109939.2759ENMojtabaFarrokhAssistant Professor, Department of Information technology and Operations Management, Kharazmi University, Iran, Tehran.RezaYousefi ZenouzLecturer in Business Analytics, Queen’s University Belfast, Belfast, UKAboozarJamalniaThe business school, Edinburgh Napier University, Edinburgh, UKMastanehAsadiMSc, Operations Research, Kharazmi University, Iran, Tehran.Journal Article20230225Each year, millions of tires that have reached their end of life are either buried or burned, both of which harm the environment through polluting the air and groundwater. Companies need to consider their social responsibility, including employment and regional development, and the environmental impact of their activities when making strategic and operational decisions. This study addresses the closed-loop supply chain (CLSC) design problem with regard to the dimensions of sustainability. The options of retreading, recycling, and energy recovery, along with the use of green technologies are considered to minimize environmental impacts. The proposed decision approach uses Life cycle assessment (LCA)-based social indicators to model its social impacts, along with the use of eco-indicator 99 as a method of assessing environmental impacts. The developed mathematical model turns out to be a multi-objective, mixed-integer linear programming (MOMILP) model that considers population density and unemployment rate in the social dimension. The model is solved using the Lp-metric method and CPLEX solver. A scenario-based approach is used to address the uncertainty in demand and the return of worn-out tires. The results show to which extent considering social sustainability, along with uncertainties in demand and return, impacts location and technology selection decisions in the tire CLSC design problem. Besides, the economic and environmental dimensions are also affected when considering social indicators, because of relocation and changes in the distances between the various supply chain centers, which in turn results in changes in costs and pollutant emissions.http://www.ijsom.com/article_2958_b91b1facf3b3a7890177f02ac188f14c.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Preliminary Framework for Lean Supply Chain Integration Assessment Index in the Healthcare Sector396430296310.22034/ijsom.2025.110756.3365ENMARWANHFEDAFaculty of Mechanical Engineering, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaAzanizawatiMa’aramFaculty of Mechanical Engineering, Universiti Teknologi Malaysia, Johor Bahru, MalaysiaMuhdMaulanaFaculty of Mechanical Engineering, Universiti Teknologi Malaysia, ,Johor Bahru, MalaysiaAhmadAdnanFaculty of Mechanical Engineering, Universiti Teknologi MARA (UiTM), Pasir Gudang, MalaysiaJournal Article20250404Healthcare providers face the formidable challenge of providing high-quality treatment without passing the costs on to their patients. Rising hospital inventory costs in recent years have highlighted the critical importance of developing a more efficient healthcare supply chain management (SCM) system. Despite the importance and the potential of lean supply chain applications in the healthcare sector, extensive development is necessary for the successful adaptation of lean integration across the supply chain network. There have been very few comprehensive frameworks of all the critical success factors (CSF) that enable lean-supply chain integration (LSCI) for healthcare. Only a few studies provided an index for lean-related activities in the healthcare context. The objective of this paper is to propose a obtain the critical success factors in lean-supply chain integration for healthcare and develop an LSCI assessment index to measure. The paper used a systematic literature review of recent studies on critical success factors of lean supply chain in healthcare. The results of the review enabled the development of the proposed LSCI assessment index based on the identified CSF of supply chain and lean implementation in the healthcare context. The index is divided into categorical factors related to organization, supply, patients, technology, and lean implementation. The expert validation process involved feedback from 20 academics and experts with expertise in Lean Supply Chain Management and healthcare operations, ensuring the questionnaire's comprehensiveness and relevance. The pilot reliability study with experts assessed the questionnaire's reliability using Cronbach's Alpha, demonstrating acceptable consistency for the research variables.http://www.ijsom.com/article_2963_b887d8d5e65ac4dec3934028fe23ad72.pdfKharazmi UniversityInternational Journal of Supply and Operations Management2383-135912320250801Designing A Sustainable Closed Loop Supply Chain Network under Uncertainty: A Robust Possibilistic Programming Approach431463295510.22034/ijsom.2025.109454.2415ENSeyed AliTorabiProfessor,
Department of Industrial Engineering College of Engineering University of TehranEsmaeilAkhondi BajeganiDepartment of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.Journal Article20211214This paper studies a comprehensive multi-objective closed loop supply chain network design problem by considering economic performance, environmental impacts, and social responsibilities as the most important concerns of a supply chain’s stakeholders. Due to the unavailability of historical data, all uncertain parameters are represented as fuzzy numbers based on the subjective knowledge of experts. A novel multi-objective mixed integer programming model is developed to formulate the problem. Furthermore, a robust possibilistic counterpart model is derived to generate robust solutions under epistemic uncertainty of parameters. Because of the multi-objective nature of the problem an NSGA-II algorithm is designed to yield Pareto-optimal solutions. A case study in the automotive industry is provided to validate the developed model and its solution method. Finally, several sensitivity analyses are carried out to determine the impact of critical parameters.http://www.ijsom.com/article_2955_b44afe91b8a427a6be2078cc89bd6f9b.pdf