Area Of Supply Chain Management Research Articles

Exposition of techno-functional components of intelligent food supply chain: a review and future research agenda

Purpose The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps. Design/methodology/approach This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC. Findings This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies. Originality/value The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

A Topic Modeling Approach to Determine Supply Chain Management Priorities Enabled by Digital Twin Technology

Background: This paper examines scientific papers in the field of digital twins to explore the different areas of application in supply chains. Methods: Using a machine learning-based topic modeling approach, this study aims to provide insights into the key areas of supply chain management that benefit from digital twin capabilities. Results: The research findings highlight key priorities in the areas of infrastructure, construction, business, technology, manufacturing, blockchain, and agriculture, providing a comprehensive perspective. Conclusions: Our research findings confirm several recommendations. First, the machine learning-based model identifies new areas that are not addressed in the human review results. Second, while the human review results put more emphasis on practicality, such as management activities, processes, and methods, the machine learning results pay more attention to macro perspectives, such as infrastructure, technology, and business. Third, the machine learning-based model is able to extract more granular information; for example, it identifies core technologies beyond digital twins, including AI/reinforcement learning, picking robots, cybersecurity, 5G networks, the physical internet, additive manufacturing, and cloud manufacturing.

The effect of COVID-19 pandemic on the fruit juice industry: Insights from Türkiye

The COVID-19 pandemic has caused major problems in many areas of the world and has deeply affected many sectors and industries. The food and beverage industry is one of the industries that has been severely affected by the COVID-19 pandemic. This study aims to explore the impact of the pandemic on the Turkish fruit juice industry and the attitudes and behaviors of companies. In addition, the study seeks to identify the changes in the industry caused by the pandemic and discuss its long-term effects. The material used for the study consists of the data obtained from the surveys conducted among the companies producing fruit juices in Türkiye. The results show that the pandemic had a significant impact on companies' logistics activities, while supply activities were moderately affected. However, the effects of the pandemic on exports, sales, production, total profit, and R&D activities were comparatively limited. When comparing the pre-pandemic period with the first year of the COVID-19 pandemic, it was observed that some companies in the industry experienced declines in production, sales, exports, and overall profit, whereas others experienced increases in these metrics. These variations were not associated with company size or length of operation, suggesting that the impact of the pandemic on individual companies was unique. Interestingly, some companies reported positive effects from the pandemic, such as increased demand for certain products, new export markets, improved food safety practices, new suppliers and improved crisis management skills. However, the fruit juice industry in Türkiye was found to be vulnerable in the areas of logistics and supply chain management. The study suggests that companies should strengthen supply chain management, improve stock management, and create online marketing plans to reduce potential problems in future crises. Additionally, it contributes to the development of strategies to mitigate the impact of future pandemics or bottlenecks that may emerge in the future, thereby promoting the efficiency and sustainability of the fruit juice industry as a whole.

Machine Learning Technologies in the Supply Chain Management Research of Biodiesel: A Review

Biodiesel has received worldwide attention as a renewable energy resource that reduces greenhouse gas (GHG) emissions. Unlike traditional fossil fuels, such as coal, oil, and natural gas, biodiesel made of vegetable oils, animal fats, or recycled restaurant grease incurs higher production costs, so its supply chain should be managed efficiently for operational cost reduction. To this end, multiple machine learning technologies have recently been applied to estimate feedstock yield, biodiesel productivity, and biodiesel quality. This study aims to identify the machine learning technologies useful in particular areas of supply chain management by review of the scientific literature. As a result, nine machine learning algorithms, the Gaussian process model (GPM), random forest (RF), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor (KNN), AdaBoost regression, multiple linear regression (MLR), linear regression (LR). and multilayer perceptron (MLP), are used for feedstock yield estimation, biodiesel productivity prediction, and biodiesel quality prediction. Among these, RF and ANN were identified as the most appropriate algorithms, providing high prediction accuracy. This finding will help engineers and managers understand concepts of machine learning technologies so they can use appropriate technology to solve operational problems in supply chain management.

The role of smart technologies in managing supply chain post pandemic: an exploratory scientific procedures and rationales for systematic literature review

Purpose The COVID-19 pandemic has brought unprecedented disruptions to global supply chains, compelling organizations to reevaluate their strategies for resilience and adaptability. In response, smart technologies (ST) have emerged as integral tools in post-pandemic supply chain management (SCM). This study aims to conduct an exploratory systematic literature review to comprehensively examine the evolving landscape of smart technology adoption in the context of SCM post-pandemic. Design/methodology/approach A systematic literature review has been conducted to examine the potential research contribution or directions in the field of ST and SCM. In total, 240 articles were shortlisted from the SCOPUS database in the chosen field of research. Bibliometric analysis was conducted by using VOSviewer to investigate the research trends in the area of SCM. Findings The review identifies key themes and trends, including supply chain resilience, digital transformation, enhanced visibility, predictive analytics and sustainability considerations. It explores the role of ST in fostering agility, transparency and risk mitigation within supply chains. Furthermore, eight clusters were identified to generate several thematic topics of ST in SCM. The results have evidenced a strong gap related to Industry 5.0 approaches for the supply chain field. A total of 240 publications, including journal articles, have been found in the literature. A total of 37 words, which were grouped in 8 clusters, have been identified in the data analysis. Research limitations/implications By synthesizing the current state of literature, this study provides valuable insights for practitioners, policymakers and researchers seeking to navigate the complexities of post-pandemic SCM in an increasingly digitized and interconnected world. The findings highlight the transformative potential of ST and offer a roadmap for further exploration in this critical domain. Originality/value In this paper, the development path of the field of ST in SCM during the pandemic and the research constructs are presented and potential research directions are based on the bibliometric method.

The Evolution of Dynamic Capabilities in OM

The dynamic capability view (DCV) has gained attraction in many areas of business administration. This article aims to analyze the evolution of the dynamic capability view (DCV) theory within the operations and supply chain field. In this article, we use author co-citation, term co-occurrence, and topic modeling techniques to uncover the evolution of DCV in operations and supply chain management areas. The analysis was performed on 166 peer-reviewed articles from the top four operations management (OM) journals. The study finds the prominent authors co-cited together along with the representative topics in these papers. Furthermore, newer topics, such as supply chain resilience and dynamic-based capabilities, such as data analytics capabilities, are gaining prominence. Finally, the future research agenda is discussed along with the limitations of the paper.

Multimodal logistics chains for international transportation of dangerous and perishable goods

The overview article delves into the critical area of emergency logistics and supply chain management. Analyzing research conducted by experts in the field, the authors explore the potential benefits and challenges associated with the use of multimodal and intermodal international transportation of dangerous and perishable goods, and assess the potential challenges as well as the importance of emergency logistics for disaster relief and recovery. It is noted that traditional unimodal transport systems may be insufficient for swift and efficient response to emergency situations, which makes the integration of multimodal and intermodal chains an increasingly attractive alternative. Emergency logistics play a key role in ensuring the uninterrupted flow of goods during crises and disasters, especially when it comes to dangerous and perishable goods. One of the purposes of this article is to highlight the importance of vehicle diversification during such disasters. Multimodal transport involves the use of several modes of transport, such as road, rail, sea and air, under the direction of one transport operator or several carriers that cooperate in a coordinated manner. On the other hand, such transportation involves the use of standardized containers that can be easily moved between different modes of transport, offering increased flexibility and cost-effectiveness. The article provides an overview of the challenges faced by emergency logistics and the potential problems when transporting dangerous and perishable goods. It emphasizes the importance of building robust supply chains that can withstand disruptions and provide rapid response to effectively mitigate risks. The need to increase the stability and efficiency of emergency logistics chains is emphasized. The study aims to shed light on which approach offers the best balance between timeliness, adaptability and overall efficiency in the international transport of hazardous materials and perishable goods. The article refers to case studies and real-world cases of emergency logistics operations where multimodal and intermodal transport systems have been successfully applied. These cases highlight their practicality and effectiveness in mitigating potential disasters and minimizing the negative impact of accidents such as spills, explosions or spoilage, and the consequences of war. The authors note the special relevance of multimodal container transportation of dangerous and perishable goods, especially during the war that Ukraine is waging against russian aggression, since in these conditions the principle of logistics “just in time” is most in demand, and modern containers allow to ensure complete safety, speed and accuracy, and in necessary cases, the secrecy of the delivery of goods in the conditions of hostilities and other emergency situations.

COVID-19 and Supply Chain Disruption Management: A Behavioural Economics Perspective and Future Research Direction

The COVID-19 pandemic has been one of the most severe disruptions to normal life, impacting how businesses operate. The academic literature in the areas of supply chain and operations management has been trying to explain how this has affected decision-making in businesses. However, the existing literature has predominantly overlooked organisational culture and behavioural economic theories. This paper contends that considering the decisions made in supply chain disruption management involve groups and the individuals within them, the relevance of behavioural economic concepts becomes paramount. As such, the objective of this paper is to conduct an integrative literature review, utilising the purposive sampling method to explore the dearth of academic work connecting behavioural economic theories and organisational culture to supply chain disruption management. Additionally, the paper aims to offer guidelines for future research in this domain. Enhancing our comprehension of these domains concerning supply chain disruption management would empower firms to better anticipate their parties’ decisions, refine their decision-making models, and cultivate stronger relationships with suppliers and customers.

Difference Between Corporate Logistics Management and Defense Logistics Management

Logistics Management basically starts from logistics management for war. To go to war, you must have good logistics management in order to win the war. Along with the times, logistics management has evolved to be used for a company. Against this background, the title of this study is the difference between corporate logistics management and defense logistics management. The research methodology used in this study is a literature review. The conclusion of this study is that Logistics management in companies with logistics management in defense has the same outline. Basically, logistics management focuses on maintenance planning, workforce and personnel, supply support, equipment support and testing, equipment training and education, technical documentation, computer facilities, contracts, negotiation and Transfer of Storage, Space, Stability and Maintenance. Meanwhile, logistics management in defense focuses on the main areas of logistics and supply chain management in the context of sustainability, inventory management, resilience, procurement, information systems and crisis response.

The advance of non-digital-currency application with blockchain

With the vigorous development of blockchain technology, its decentralization, privacy, convenience, and other characteristics make it shine in the financial field. Today, blockchain technology has gradually been widely integrated into government, the Internet of Things, supply chain management, healthcare, and other areas. It can change the traditional centralized data management model and provide distributed and decentralized data storage and management methods. This method has higher security, transparency, and reliability, which can solve the problems existing in traditional data management methods and improve the efficiency and reliability of data management. In the meantime, using new technologies also brings many practical problems to solve. These include insufficient technology maturity, privacy concerns, and volatile legal and regulatory policies. This paper delves into these real-world scenarios and summarizes some recommendations. This will give a greater understanding of the principles and characteristics of blockchain technology, promote the popularization of blockchain technology, have a more comprehensive understanding of the use of blockchain technology in different fields, and provide valuable research materials for researchers in related fields in the future.

Analysis of the Impact of Big Data and Artificial Intelligence Technology on Supply Chain Management

Differentiated production and supply chain management (SCM) areas benefit from the IoT, Big Data, and the data-management capabilities of the AI paradigm. Many businesses have wondered how the arrival of AI will affect planning, organization, optimization, and logistics in the context of SCM. Information symmetry is very important here, as maintaining consistency between output and the supply chain is aided by processing and drawing insights from big data. We consider continuous (production) and discontinuous (supply chain) data to satisfy delivery needs to solve the shortage problem. Despite a surplus of output, this article addresses the voluptuous deficiency problem in supply chain administration. This research serves as an overview of AI for SCM practitioners. The report then moves into an in-depth analysis of the most recent studies on and applications of AI in the supply chain industry. This work introduces a novel approach, Incessant Data Processing (IDP), for handling harmonized data on both ends, which should reduce the risk of incorrect results. This processing technique detects shifts in the data stream and uses them to predict future suppressions of demand. Federated learning gathers and analyzes information at several points in the supply chain and is used to spot the shifts. The learning model is educated to forecast further supply chain actions in response to spikes and dips in demand. The entire procedure is simulated using IoT calculations and collected data. An improved prediction accuracy of 9.93%, a reduced analysis time of 9.19%, a reduced data error of 9.77%, and increased alterations of 10.62% are the results of the suggested method.

Editorial

The agri-food systems around the world are faced with the challenges from unprecedented short-term shocks and long-term supply and demand shifts. The need for transformation towards more sustainable and resilient agri-food systems has thus risen to the centre of attention of agribusiness industry and policy decision makers. Technological innovations in the areas of supply chain management, environmental protection, and nutrition improvement have a potential of playing an important catalytic role in such systematic transformations. This special issue includes 11 research articles examining a range of strategic and technological solutions aimed at facilitating the resilience and sustainability of agri-food systems to shocks such as COVID-19, pest infestations, trade restrictions, shifting diets and consumer preferences, armed conflicts, and extreme weather events. The research findings and insights provide implications for a wide range of food and agribusiness stakeholders including managers and policy makers.

Blockchain Technology Adoption Effect Onknowledge Management State of the Art Survey

The International Journal of Managing Value and Supply Chains ( IJMVSC ) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of value and supply chain management. The journal provides a platform to disseminate new ideas and new research, advance theories, and propagate best practices in the management of value and supply chain management, looking across both product and service-based businesses. This will include works based in service management, logistics and distribution, operations management, process management, flow control, and customer service. The journal offers a forum in which academics, consultants, and practitioners in a variety of fields can exchange ideas to further research and improve practices in all areas of business. The International Journal of Managing Value and Supply Chains ( IJMVSC ) seek to establish new collaborations, new best practices, and new theories in the management of both product and service-based organizations around the world.

Authorization or encroachment: Effects of channel encroachment on decisions and performance in software service supply chains

At present, plenty of software developers not only sell their software to client firms through downstream service integrators, but also vend it to clients directly. However, little research has been investigated software developers' channel encroachment in the area of software service supply chain (SSSC) management. In this study, we examine a SSSC with a developer, an integrator, and client firms. Clients can either purchase software from the integrator at high prices and with accessorial pre-sale services, or procure it directly from the developer at low prices but with no pre-sale services. After purchasing software, clients can also purchase the extended warranty service (EWS) from the developer. We investigated the two cooperation modes, i.e., the “Authorization” (marked as mode A) and the “Authorization + direct sales” (marked as mode E), and analyzed effects of the developer's channel encroachment on equilibrium decisions of SSSC members and on SSSC performance. It is shown that both the sensitivity of clients to the EWS price and the EWS cost cannot affect the software pricing decision of the integrator in the mode A, but those can affect that in the mode E. Furthermore, when the EWS cost is high, although the developer can obtain the software authorization revenue, the software sales revenue, and the EWS sales revenue (in the mode E), its channel encroachment will unexpectedly cause its own profit to decline. We also find that if the developer participates in the competition with low intensity, its encroachment is detrimental to both parties; only when the developer participates in the competition with high intensity and has a low-cost advantage, its encroachment can increase its own profit, but it may reduce the profit of the integrator and lead to a decrease in the total SSSC profit. However, we are surprised to find that if the developer participates in the competition with high intensity and its EWS cost is high, its channel encroachment not only increases the integrator's profit but also the total SSSC performance.

Supply chain management and optimization in transportation logistics

Supply chain management and optimization in transportation logistics

The Vehicle Routine Problem : Applications and Research Perspectives

This is an expository article about the Vehicle Routing Problem, which is an important problem in the area of supply chain management. The purpose of this article is to draw the attention of potential researchers towards this problem. Even though the problem is heavily researched, there is plenty of scope for more research on this problem because many new versions of the problem keep emerging. After introducing the problem, the article provides a mathematical formulation of the problem, an illustrative example, and a brief literature survey. Then a number of di¤erent versions of the problem which are of practical interest have been discussed. Finally, the article ends with a short discussion on the scope of future research on this problem.

Internet of Things (IoT)—blockchain-enabled pharmaceutical supply chain resilience in the post-pandemic era

During the COVID-19 pandemic, the current operating environment of pharmaceutical supply chain (PSC) has rapidly changed and faced increasing risks of disruption. The Internet of Things (IoT) and blockchain not only help enhance the efficiency of PSC operations in the information technology domain but also address complex related issues and improve the visibility, flexibility, and transparency of these operations. Although IoT and blockchain have been widely examined in the areas of supply chain and logistics management, further work on PSC is expected by the public to enhance its resilience. To respond to this call, this paper combines a literature review with semi-structured interviews to investigate the characteristics of PSC, the key aspects affecting PSC, and the challenges faced by PSC in the post-pandemic era. An IoT—blockchain-integrated hospital-side oriented PSC management model is also developed. This paper highlights how IoT and blockchain technology can enhance supply chain resilience and provides a reference on how PSC members can cope with the associated risks.

Decision support framework for inventory management combining fuzzy multicriteria methods, genetic algorithm, and artificial neural network

Decision support tools, within the Industry 4.0 perspective, have increasingly impacted different operations and supply chain management (OSCM) areas, such as inventory management. Within the digital transformation era, multicriteria decision-making (MCDM) and machine learning (ML) can be used to improve inventory management decisions. Despite their importance, the literature lacks empirical studies involving advanced solutions that combine both approaches to support practitioners in real-life settings. This is especially relevant for maintenance, repair, and operation (MRO) inventories, which usually present several SKUs with irregular demand patterns and difficult forecasting. Therefore, this study proposes a decision support framework for inventory management, combining MCDM and ML approaches, and applies it to a railway logistics operator to assist its MRO inventory management decision-making process. The first stage of the framework consists of applying a hybrid MCDM method that combines fuzzy logic with the analytic hierarchy process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methods to rank and select SKUs according to importance and criticality. Once the most critical SKUs are revealed, a second stage of the framework is introduced to forecast the demand for these SKUs through an ML model, which combines a genetic algorithm and an artificial neural network (GA-ANN). Research findings point to a considerable improvement in the accuracy of the demand forecast for SKUs compared to the previous forecast by the company, and the forecasting methods support vector machine (SVM) and exponential smoothing. The results of the combined approaches are consolidated into a management dashboard, which improves the agility and quality of the analyzed company's decision-making process in inventory management. Therefore, practitioners can also take stock of the proposed framework as a semi-automatic management artefact to enhance decision-making from a digital transformation view in a vital area of OSCM.

Transactional leadership and its effect on supply chain management in manufacturing SMEs

The continued lacklustre performance of small and medium enterprises (SMEs) in South Africa has brought the quest for lasting solutions. One of the options available is to tap into the areas of leadership and supply chain management (SCM) as potential sources of SME growth.
 This study analysed the link between transactional leadership and SCM in manufacturing SMEs in South Africa. The research constructs included transactional leadership, supply chain execution (SCE), and performance.
 The research was conducted in Gauteng, North-West and the Free State provinces. Furthermore, the study focused on established manufacturing SMEs, registered with the Small Enterprise Development Agency (SEDA).
 A quantitative research approach using a correlational design was used. 411 SME owners, managers and professional employees participated in the study.
 Management by exception exerted a positive effect on SCE. In turn, SCE positively impacted customer service (CS) but did not affect supplier performance.
 The impact of transactional leadership on the execution of SCM in manufacturing SMEs is minimal and is demonstrated through management by exception. Effective implementation of SCM in these businesses is essential for optimising CS.

Improving environmental sustainability in agri-food supply chains: Evidence from an eco-intensity-based method application

Focal companies in food supply chains face increasing pressure to produce food sustainably and lower the environmental impact across their supply chain (SC). Although governance mechanisms to manage suppliers and sub-suppliers have been established, focal companies in the food sector still lack effective tools to capture the actual environmental sustainability performance of their multi-tier SCs, which could support them to decrease the environmental impact associated to their products.This work thus aims to showcase how assessing the environmental sustainability performance of a multi-tier food SC made up by SMEs can support decisions in order to drive evidence-based green improvements in the SC operations. A low-input eco-intensity-based multicriteria performance assessment method was applied to a bread SC, adopting a longitudinal case study design, to evaluate its applicability for decision-making in an operating context.Following the identification of environmental hotspots along the SC, targeted green operational improvements were implemented within individual organisations, resulting in a decrease of the eco-intensity values both at the targeted SC tiers and at the overall SC level. These results demonstrated that the method was able to support the improvement of the SC environmental performance.This work is the first longitudinal study in the multi-tier green supply chain management (GSCM) area. It contributes to the multi-tier food GSCM and GSCM performance assessment fields by demonstrating how the integration of environmental sustainability performance assessment methods and SC governance mechanisms can effectively support across time the deployment of GSCM within food SCs, while adopting an indirect SC management approach. Finally, the application of the method within a supply chain consisting of SMEs, inexperienced in sustainability assessment, demonstrates its potential to achieve SC-wide sustainability assessment and contributes to the wider GSCM field by providing insights on the implementation of GSCM in supply chains dominated by SMEs.