Operations Management Research最新文献

Players in the automotive industry have been adopting different strategies to remain competitive, including product and process innovation, Lean Manufacturing, and, more recently, Green Manufacturing. In this paper, we seek to explore the integration of Lean and Green manufacturing activities from the perspective of Operations Management and Operations Strategy. We carried out case studies at four Original Equipment Manufacturers and two first-tier suppliers in the automotive industry, examining their operations strategies, their Lean practices and their Green practices to discuss whether Lean and Green practices were integrated and aligned with companies' operations priorities. We found that companies have adopted different Operations Strategies considering operations competitive priorities, decision areas subjected to changes, and Lean and Green practices implemented. Cases analysed show different levels of Lean and Green Manufacturing adoption and different levels of integration of Lean practices and Green practices. The study indicates that the implementation of an operations strategy, with the addition of the Environment to the set of competitive priorities and involving the implementation of Lean and Green practices – or the implementation of Green practices in production systems that have already adopted Lean practices –, is a complex management task.

One of the most pressing concerns of patients is the timely delivery of required medicines at the appropriate time and location, as a lack of medicines can have a direct impact on their health. A multi-product and multi-period integer programming model is presented in this paper to design a pharmaceutical supply chain network with different layers: supplier, manufacturer, distributor, and customer. The proposed model's main goal is to maximize profits across the entire pharmaceutical supply chain. Revenues come from the sale of pharmaceuticals both domestically and internationally. Expenses include transportation, production, the procurement of materials, manufacturer establishment, distribution center establishment, inventory holding, medicines expiration, ordering, and loans. In the suggested model, import and export, customs tariffs, loans, and currencies are all presented. Environmental concerns about greenhouse gas emissions from transportation throughout the supply chain are also considered. A case study for the province of Fars is presented to evaluate the efficiency of the proposed model. While numerical results confirm the model's effectiveness, they also show that as the level of uncertainty increases, profitability decreases; however, profitability can be enhanced by carefully regulating characteristics such as fixed cost of manufacturer construction and fixed cost of distribution center construction.

As diseases, natural disasters, and man-made disruptions become more frequent and severe, enhancing the resilience of agri-food supply chain operations poses an increasing challenge.This study aims to identify and analyze the key capabilities and impact factors contributing to agri-food supply chain resilience (AFSCRE). By conducting a comprehensive literature review and engaging in expert consultations, fifteen significant capability factors were identified. We utilized the decision making trial and evaluation laboratory (DEMATEL) technique to determine and categorize AFSCRE factors into cause and effect groups. Subsequently, we employed interpretive structural modelling and a cross-impact matrix multiplication applied to classification (ISM-MICMAC) to establish interrelationships among these factors. The results indicated supply chain leadership is a fundamental factor for fostering AFSCRE, which is located at the bottom level of ISM hierarchy. Moreover, the study identifies the importance of government support in developing AFSCRE. The findings of this study can guide supply chain leaders and government officials to initiate targeted activities for improving resilience.

The startup industry is experiencing a dynamic and exciting time called Startup 5.0, where technology is quickly transforming how we conduct business, and startups are at the vanguard of this change. This study aims to model the enabling technologies influencing start-up 5.0. The enabling technologies that impact start-up 5.0 are modelled in this research using TISM and MICMAC analysis. According to the findings, key enabling technologies that are changing the technical landscape and opening up new opportunities for Startup 5.0 are Edge computing, complex adaptive systems, network slicing, and 6G and beyond. Fostering effective innovation and entrepreneurial activity within the startup ecosystem requires an understanding of the dynamic relationships among various technologies. Our findings have implications for government decision-makers, entrepreneurs, and investors who want to support Startup 5.0’s expansion. This study emphasizes how crucial it is to understand how enabling technologies interact in order to enable well-informed strategies for fostering innovation and long-term entrepreneurial endeavors in the dynamic startup environment.

Vendor credit line ((VCL)) is a common instrument to fund retailers with capital constraints, wherein a supplier extends credit for a retailer’s purchases and limits credit size for the sake of default risk. Our study investigates the operational and financial decisions in a supply chain consisting of a supplier and a capital-constrained retailer, wherein the supplier sets credit limits for the retailer’s ordering, and then examines the financing choice between (VCL) and bank loan. We derive the equilibrium credit limits, order quantity and financing mode and conclude that, the credit limits linearly increase with the capital level, and both credit limits and capital level are decisive to the order quantity and financing mode. In the illustrating examples, we identify the decision regions contingent on critical fractiles under different demand distributions (e.g., normal, uniform and exponential) and find the financing choice hinging on the supplier’s profit margin if the capital level stays low, otherwise (VCL) dominates. Finally, sensitivity analysis on key parameters is employed, suggesting that (VCL) is more preferable as the wholesale price increases or as the retail price and production cost decreases.

The world has encountered numerous global crises, including epidemics, military conflicts, and economic collapse. Innovative digital technologies, such as Industry 4.0 (I4.0), can undoubtedly help improve industries’ operations during critical times. The dairy industry has seen an increment in technological adoption in the last few years. Adopting cutting-edge technologies is regarded as more feasible as compared to existing practices. The advancements achieved through the white revolution became game changers for the Indian dairy industry, establishing it as a top producer. The key challenges faced by the Indian dairy industry include safety, quality, transparency, and sustainability. The Indian dairy sector needs a revolution to address these challenges, and digital technologies can play a big role. This study critically demonstrates the emergence of technological transformations in the Indian dairy industry. A conceptual framework, White Revolution 2.0, which indicates the digital revolution, is introduced. This proposed framework presents the three dimensions of White Revolution 2.0, i.e., technological dimension, external factors, and applications of I4.0. The proposed framework will significantly improve dairy operations by effectively addressing the identified challenges throughout every aspect of the dairy industry. The findings indicate that adopting the proposed concept can ensure effective supply chain integration and a sustainable future for the dairy industry by integrating all the stakeholders. Practical implementation of this concept includes improvements in food safety, security, and quality sustainably. This study will assist practitioners and researchers in understanding the fundamentals and necessity of the White Revolution 2.0 and can serve as a roadmap for integrated dairy digitalization.

The recent increase in food contamination, corruption, and child labor in the agricultural industry has prompted attention to sustainable supply chain management (SSCM). Although some companies try to solve these problems through blockchain technology, there are many barriers to adopting blockchain technology for the SSCM, especially in the agriculture supply chain of emerging economies. Through literature review, this paper first constructs a two-level barrier framework, 4 main barriers, and 22 sub-barriers to adopt blockchain technology for the SSCM. Then, we propose a novel hierarchical group Decision Making Trial and Evaluation Laboratory (DEMATEL) based on probability hesitant fuzzy sets (P-HFS) to prioritize those barriers and identify the influence relationship among them. Through an empirical case in the cocoa supply chain of Ghana, the results of the proposed method showed that the Intra-organizational barrier is the most significant main barrier, while the system barrier is the most influential barrier with the highest net effect value. The most significant sub-barriers are lack of management commitment and support in intra-organizational sub-barriers, lack of customer awareness and tendency in inter-organizational sub-barriers, security challenges in system-related sub-barriers, and lack of industry involvement in ethical and safe practices in external sub-barriers, respectively. Interestingly, those most significant sub-barriers are also the most influential factors in other sub-barriers. These findings help managers and policymakers to prioritize their efforts and resources in addressing the barriers in some emerging economies in Africa.

Abstract

Scheduling problems are a fundamental aspect of various industries, wherein the effective allocation of resources and time management play a crucial role in optimizing operational processes. These problems can arise in any industry that requires the scheduling of resources, from manufacturing to healthcare and transportation. Despite the extensive scope of service system scheduling problems in the literature, research has yet to examine the bibliometric variables in this area. Based on bibliometric criteria, this research offers a picture of the structure, evolution, and potential future directions of studies on scheduling in service systems. With the application of the bibliometric analysis software VOSviewer and CiteSpace, 1991 publications related to service scheduling were identified from the Web of Science database between 1982 and 2023 and used in the analysis of this paper. This review used several bibliometric approaches, such as performance analysis and a scientific mapping of service scheduling. Several bibliometric variables, such as h-index, productivity, and citations, were included in the performance evaluation. Science mapping has used co-citations, bibliographic coupling, and the concurrency of keywords. Also, this paper introduces a novel and comprehensive framework for classifying scheduling models in service systems based on their characteristics. The highly cited implementation papers in the literature have demonstrated that scheduling problems in health care have been heavily utilized in the scholarly literature. This review which is the first bibliometric analysis in the service scheduling field provides a summary reference for scholars entering the subject for future research.

Digital Twin (DT) is a technology platform that is revolutionizing the supply chain digitization process by creating virtual representations of physical systems. Agro-food supply chain (AFSC) is one of the most important supply chains that can be made more efficient by widespread adoption of DT. However, the adoption and implementation of DT in AFSC is very limited due to various hindrances. Thus, it is imperative to identify and analyze the DT barriers thoroughly; and subsequently, develop strategies to overcome the dominant barriers for the successful implementation of DT in AFSC. This study identifies the barriers to DT implementation through a literature review and experts’ opinions. The interaction amongst the barriers is captured using the “Weighted Influence Non-linear Gauge System (WINGS)” method. Lack of technology infrastructure, technology immaturity, and high capital investment emerge as the dominant causal barriers. Furthermore, to overcome the identified barriers, a framework based on a triple helix approach is suggested. The findings of the study will be useful for government agencies, policymakers, agricultural institutions, and agro-food industry stakeholders to eliminate the obstacles to the successful implementation of DT in AFSC.