Role In Supply Chain Management Research Articles

A fuzzy multi-objective optimization model for sustainable healthcare supply chain network design

Healthcare supply chains play a crucial role, which enables the implementation of optimization strategies that have rapidly emerged as highly effective means for improving the overall structure of pharmaceutical and healthcare supply chains.. In the healthcare industry, parameters such as increasing the quality of service, as well as optimizing costs, environmental, and social factors play a unique role in supply chain management. To improve the healthcare supply chain network, this study proposed a novel optimization model to optimize multiple objectives, including minimizing the total costs and environmental impacts, while maximizing the social factors by creating jobs simultaneously. To address the effects of uncertain parameters, a fuzzy optimization method alongside the multi-objective gray wolf optimizer (MOGWO), non-dominated sorting genetic algorithm II (NSGA-II), multi-objective differential evolution algorithm (MODEA), and ε-constraint are applied to optimize the model. Also, a case study of the pharmaceutical industry demonstrates the model's efficacy in a real-life context. The numerical results show the MOGWO manages to create high-quality Pareto solutions with a good spread at the Pareto boundary within a short time compared to the ε-constraint approach. Further, it has shown a more robust performance compared to MODEA and NSGA-II, indicating the efficiency of MOGWO, among other solution methods and other objective indicators.

Management accounting and control, supply chain resilience and healthcare performance under disruptive impact

PurposeBuilding supply chain (SC) resilience has become a priority for many organizations, following a global increase in disruptive events. While management accounting and control (MAC) systems play a supportive role in supply chain management (SCM) decisions, little is known about the contributions offered to resilience decisions in service organizations. The purpose of this study is to examine the performance implications of MCS's impact on proactive and reactive resilience of healthcare supply chains.Design/methodology/approachThis study conducted a survey of 127 public health managers via structural equation modeling. The partial least squares version 3.3.3 was used.FindingsThe results show a statistically positive impact of MAC dimensions on proactive and reactive resilience, which in turn impacts the quality, delivery speed and cost effectiveness of the health SC. However, the integration dimension had an insignificant effect on reactive resilience but a positive effect on proactive resilience.Research limitations/implicationsThis study examined the performance implications of MAC system dimensions and proactive and reactive resilience on operational performance in health SCs, using empirical data from only one country. Thus, generalizing the findings to include other jurisdictions may be impossible.Practical implicationsHealthcare managers in public health facilities should embrace the four MAC dimensions (except the integrated dimension in reactive resilience) to support information generation in SC resilience decisions.Originality/valuePerhaps, the first to provide preliminary empirical evidence on the interactive effect of proactive and reactive resilience and MAC dimensions in terms of broad scope, timeliness, integration and aggregation on health SC operational performance under disruption, in the context of an emerging economy.

The Impact of Production and Operations Management Practices in Improving Organizational Performance: The Mediating Role of Supply Chain Integration

While prior research has consistently established a significant link between production and operations management (POM) practices and organizational financial performance (OFP) across various contexts, the mechanisms driving this connection remain unclear. This study addresses this gap by examining the mediating role of supply chain management (SCM) integration in the relationship between POM practices and OFP within manufacturing firms. Drawing on established theories and concepts such as the resource-based view (RBV) of firm and operation strategies, this study employed a quantitative research design. Survey data were collected from 209 managers in Jordanian manufacturing firms and analyzed using structural equation modeling (SEM). The results confirmed a positive and significant association between POM practices and both SCM integration and OFP. Furthermore, SCM integration partially mediated the impact of POM practices on OFP, thereby underscoring its role in transmitting positive effects to financial performance. This research contributes to the field by integrating POM practices with SCM integration and by elucidating the mechanisms through which these practices influence financial performance in Jordanian manufacturing firms. Through this, our understanding of these relationships for practitioners and researchers alike is enhanced.

Overview of Logistics Finance Theories

Logistics finance is of great significance in helping companies bail out. Not only that, different models of logistics financial business types also have different impacts on business risks. This article starts from logistics finance, expounds its role and significance in the modern economic system, subdivides logistics financial business into three aspects: logistics settlement finance, logistics warehouse receipt finance and logistics credit finance, and analyzes their role in supply chain management and the key role in the financial field, and further in-depth research on the risks faced by the logistics financial field. It is hoped to provide in-depth insights to practitioners and decision-makers in the field of logistics finance and help them better understand and manage the risks associated with it to ensure the sustainable development and successful implementation of logistics finance business.

Role of Supply Chain Management in Quality of Healthcare Services

Healthcare organizations in Haryana (Kurukshetra) face many supply chain management challenges that can be addressed through effective operational and management decisions. The aim of this paper is to examine the supply chain management of healthcare quality in developing countries, particularly in rural healthcare in Haryana (Kurukshetra), and to consider demographic variables such as gender, age, education level and healthcare experience. Design and Hypothesis Testing Approach Distributed 500 questionnaires to determine the impact of aspects of supply chain management on the quality of health services. 27 of his seven procurement officers and administrative staff in Kurukshetra Haryana. The primary method was to collect data from 73 rural health managers and procurement managers to identify the quality and size of health services. The results of our study show that a combination of timely delivery of health products, specifications, level of health product providers and safety in the rural health sector of Haryana (Kurukshetra) is related to the quality of health services. The scope of this article focuses on employing appropriate human resources and highly trained professionals in supply chain departments to improve the quality of health services in the supply chain. As a practical contribution, this article can help healthcare supply chain managers and organizations do their jobs better or create a competitive advantage by addressing the issues and challenges facing individual healthcare managers, organizations and their partners.

Exploring sustainability management control system and eco-innovation matter sustainable financial performance: The role of supply chain management and digital adaptability in indonesian context

This research delves into the intricate dynamics of sustainable financial performance, driven by the interplay between Sustainable Management Control Systems (SMCS) and Eco-Innovation. Additionally, it evaluates the pivotal mediating roles of Supply Chain Management (SCM) and Digital Adaptability within this relationship, specifically within the context of Indonesian companies. Employing a survey methodology via carefully designed questionnaires, responses were collected from managerial representatives of the companies. The results underscore the significance of most hypotheses, revealing a notable influence of SMCS and eco-innovation on sustainable financial performance. However, some hypotheses regarding the mediating role of SCM and digital adaptability exhibit mixed outcomes. These findings emphasize the essential roles of SCM and digital adaptability in amplifying the effects of SMCS and eco-innovation on sustainable financial performance. Nevertheless, the intricate interdependencies suggest the presence of other influential factors affecting the relationship between digital adaptability and sustainable financial performance, warranting further exploration. The study's limitations include its focus on Indonesian organizations, reliance on self-reported data with response bias potential, cross-sectional design lacking causality establishment, and unexplored alternative mediating variables. This study enriches managerial decision-making and contributes valuable insights to sustainability management, especially in Indonesia, opening new avenues for academic research and inquiry.

Inventory Control Model of Beef for Rendang Products

The definition and function of inventory management reveal the importance of modern industry in formulating policies that regulate the supply of raw materials, semi-finished products, and finished products. Unfortunately, most companies fail to consider the characteristics of their raw materials when determining inventory strategies. Raw materials that are perishable are those that consider their service life and storage time. Inventory management plays a crucial role in supply chain management, especially for perishable raw materials, such as food products. PT X, a food business in Padang, experienced difficulty in meeting the demand for rendang products due to a lack of raw materials. Therefore, this study aims to develop an inventory management model that takes into account the perishable raw materials' expiration time. The model development consists of three stages: model development design, inventory model formulation, and model testing. The proposed model resulted in a storage time interval of five days and an optimal order quantity of 34 kg of meat with a safety stock of 14 kg. Implementing this model led to lower total inventory costs for PT X than the actual conditions of the company. The total inventory cost obtained using this model is Rp279,797,822. This study emphasizes the importance of considering the characteristics of raw materials in determining inventory strategies to optimize inventory management effectively and efficiently. The study's findings can serve as a reference for other food businesses encountering similar inventory management challenges in the perishable food industry.

Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets

Supplier selection process plays a vital role in supply chain management and is the most important variable in its success. With increasing environmental considerations, organizations must consider sustainability considerations and economic goals to protect the environment. Furthermore, the destructive effects of disruptions on the supply chain performance of companies have prompted organizational experts to pay special attention to the concept of resilience. This study developed an integrated approach based on the extended version of Multi-Criteria Decision-Making (MCDM) methods in a spherical fuzzy (SFS) environment to address sustainable and resilient IoT supplier selection. In the proposed approach, the main criteria (i.e., resilience, and sustainability) have been used in the supplier selection process. Then, these criteria are weighted using the developed SFS-Best-Worst Method (BWM), which reduces uncertainty in pairwise comparisons. In the next step, the 14 selected IoT suppliers are evaluated and prioritized by applying SFS-mulTi-noRmalization mUlti-Distance aSsessmenT (TRUST) that considers a multi-normalization algorithm to reduce subjectivity in normalized data. The results of this study shows that the pollution control and risk-taking sub-criteria are placed in the first and second priorities, respectively. The comparison of the results of the SFS-TRUST with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.

How Does Supply Chain Information Disclosure Relate to Corporate Investment Efficiency? Evidence from Chinese-Listed Companies

Supply chain information disclosure is a vital factor for corporate investment efficiency and can signal a corporation’s long-term sustainable development. However, little attention has been paid to its significance. In this paper, we investigate how supply chain information disclosure affects corporate investment decisions. Using a sample of Chinese-listed firms, we find that firms that disclose nonfinancial information are more likely to have a high level of investment efficiency. We also identify the mechanism underlying the effect by examining the mediating effect of financial constraints and agency costs. Increasing a firm’s supply chain information disclosure can improve its investment efficiency by reducing its financial constraints and agency costs. We further find that this positive impact is more pronounced for non-state-owned enterprises (non-SOEs) and firms located in regions with a high degree of marketization. Our findings imply that supply chain information disclosure plays an important role in corporate investment efficiency and sustainable development. Our study emphasizes the importance of nonfinancial information disclosure, contributing to the literature investigating the role of supply chain management in corporate decision-making on sustainable development.

Financing and Supply Chain Operations Resilience and Juxtaposing: The Role of Finance in Improving the Supply Chain in the COVID-19 Pandemic Environment

Amidst the renewed quest for supply chain resiliency, finance outgrows its traditional role in B2B; instead, finance position itself to become a more integrated partner in supply chain management activities. Areas such as global trade management and supply chain risk management are fluid areas for finance to flourish, coupled with increasing demands for finance to take a more active role in supply chain management. The global supply chain has experienced several disruptions, such as the COVID-19 pandemic, extreme climate change-induced events, natural disasters, conflict, financial crises, recessions, shortages of raw materials for manufacturing, and macroeconomic imbalances; however, futuristic disruptions are already projected by several stakeholders in the logistics and transport sector. Hence, companies must concentrate on building their resilience to all manner of supply chain disruptions. The initial motive of firm management to increase leverage and engage in financial goods is diminished when the economic dilemma of supply chain value is resolved; by so doing, the internal financial situations could facilitate the advancement of enterprise value. Keywords: supply chain, financial service innovations, distribution dimension, COVID-19 DOI: 10.7176/EJBM/15-7-01 Publication date: April 30 th 2023

Internet of Things (IoT) in Supply Chain Management: Challenges, Opportunities, and Best Practices

The advent of the Internet of Things (IoT) has ushered in a transformative era in supply chain management, revolutionizing the way organizations monitor, analyze, and optimize their operations. This comprehensive survey paper explores the multifaceted landscape of IoT applications in supply chain management, shedding light on the challenges, opportunities, and best practices that define this technological paradigm shift. The paper delves into the fundamental principles of IoT, elucidating how sensor-laden devices, real-time data streams, and advanced analytics empower organizations with unprecedented visibility and control across their supply chains. It systematically examines IoT applications in key supply chain domains, including inventory management, asset tracking, cold chain monitoring, predictive maintenance, route optimization, and waste reduction. Each application is scrutinized for its role in enhancing efficiency, reducing costs, ensuring product quality, and advancing sustainability. Furthermore, this paper addresses the challenges inherent in implementing IoT within supply chains, such as data security, interoperability, scalability, and regulatory compliance. It underscores the importance of change management and workforce development in harnessing the full potential of IoT and presents a roadmap for best practices to overcome these obstacles. The paper culminates in a forward-looking exploration of future trends and innovations in the IoT-driven supply chain landscape. By offering a comprehensive overview of IoT's role in supply chain management, this paper equips practitioners, researchers, and decision-makers with a holistic understanding of the transformative power of IoT, empowering them to navigate the complexities, seize opportunities, and implement best practices that will define the future of supply chain management.

The genetic algorithm and BP neural network in financial supply chain management under information sharing

AbstractIn today's global business competition environment, the significant changes in the market environment make it very difficult for supply chain enterprises to gain a place in the fierce market only by their strength. This article will do the following research work to effectively play the role of supply chain management. First, the concepts, and characteristics, related applications of supply chain information sharing (IS) and genetic algorithm back propagation (GABP) neural networks, are expounded. Then, the feasibility of applying BP neural network (BPNN) to evaluate supply chain IS is analysed. Next, the assessment indicator system for IS is constructed from four aspects: IS infrastructure, IS member characteristics, IS content, and the quality of supply chain enterprises. Finally, the principle and algorithm of BPNN are analysed, the network model is constructed, the BPNN process based on GA is designed, and every step in the process is explained in detail. The sample input is provided for the network model by obtaining and sorting data. The supply chain IS assessment model based on the GABP neural network is constructed. The results show that the assessment model of supply chain IS based on the GABP neural network has high accuracy, and the highest network accuracy reaches 95.01%, which proves that the assessment model based on BPNN has certain advantages for the supply chain IS of the financial industry.

Manipulating Supply Chain Demand Forecasting With Targeted Poisoning Attacks

Demand forecasting (DF) plays an essential role in supply chain management, as it provides an estimate of the goods that customers are expected to purchase in the foreseeable future. While machine learning techniques are widely used for building DF models, they also become more susceptible to data poisoning attacks. In this article, we study the vulnerability of targeted poisoning attacks for linear regression DF models, where the attacker controls the behavior of forecasting models on a specific target sample without compromising the overall forecasting performance. We devise a gradient-optimization framework for targeted regression poisoning in white-box settings, and further design a regression value manipulation strategy for targeted poisoning in black-box settings. We also discuss some possible countermeasures to defend against our attacks. Extensive experiments are conducted on two real-world datasets with four linear regression models. The results demonstrate that our attacks are very effective, and can achieve a high prediction deviation with control of less than 1% of the training samples.

Effects of Supply Chain Visibility on Supply Chain Performance in Ghana Health Service: The Case of Kumasi Metro Health Directorate

The integration of supply chain visibility has become very necessary in today’s corporate world. For quality health delivery system to be realised, the critical role of supply chain management cannot be overlooked. This study, which is more of quantitative study examined the effects of supply chain visibility on supply chain performance of Ghana health service. The study used Kumasi Metro Health Directorate as the case study and employed questionnaire to collect data. Both descriptive and inferential statistics were utilized to analyze the data gathered from the study area. Additionally, mean and standard deviation as well as frequencies and percentages were the main descriptive statistics used. Regression analysis was conducted to establish the effect of SCV on SCP. It was revealed that most respondents have a fair idea of the strategies being used to implement supply chain visibility in Kumasi Metro Health directorate. The study identified exchanging or sharing of information, use of asset status knowledge and improved electronic dissemination as SCV measures employed at Kumasi Metro Health Directorate. The findings also revealed that technological constraints, lack of synergy between automated systems and manual operations, inconsistencies in the flow of data between stakeholders, lack of communication between staff and management and budget constraint were noted as some of the bottlenecks that impede the smooth implementation of SCV in the Kumasi Metro Health Directorate. It was also found that Supply Chain Visibility has a positive effect on the supply chain performance of Kumasi Metro Health directorate. It is therefore recommended that Kumasi Metro Health directorate adopt effective networking programs as the basis for enhancing supply chain efficiency and performance.

The role of supply chain management in entrepreneurial activities and product innovation on SMEs performance

The purpose of this research is to provide practical and theoretical insights about how small and medium enterprises (SMEs) adapt and further develop entrepreneurial activities, product innovation and SME business performance This study used a quantitative method using a questionnaire for data collection. The research data developed by distributed online questionnaires by social media. The number of samples used was 230 respondents using a purposive sampling technique. Partial Least Square (PLS) is used for data processing by SartPLS 4.0. Based on the results of data analysis it is concluded that entrepreneurial competence has a significant effect on business performance and entrepreneurial competence has a significant effect on product innovation. Product innovation has also a significant effect on the performance of SME businesses.

Developing trust among players in a vendor-managed inventory model for random demand under environmental impact.

Retailers play a vital role in supply chain management because they deal directly with consumers. Occasionally, retailers may cover the entire system's statistics and not disclose these data to the manufacturer. Therefore, asymmetry is generated in the data throughout the system. The main motive of this research was to prevent unreliability throughout the system using a vendor-managed inventory policy. This research shows that by applying a cap and trade policy, the total carbon emitted from the production and transportation sectors can be controlled in the atmosphere. Finally, numerical and sensitivity analyses, along with pictorial representations of various parameters, are performed to examine the optimal results of this study. In addition, the retailer's lead time demand for items is assumed to be random rather than fixed and follows uniform and normal distribution functions. Under these two distribution functions, the optimal retailer lot size, service provided by the retailer to customers, and retailer reorder points are assessed. Furthermore, an evaluation of the total carbon released from an environmental viewpoint is illustrated using numerical findings. The numerical results show that this research is 50.24% more economically beneficial than the methods used in previous studies, whereas the mean value of demand follows a uniform distribution.

The Mediating Role of Supply Chain Management between Social Media Networks and Service Quality

The Mediating Role of Supply Chain Management between Social Media Networks and Service Quality

Evaluating green supply chain performance based on ESG and financial indicators

To reduce carbon emission and enhance social development simultaneously, “Environmental, Social and Governance” (ESG) plays a significant role in supply chain management. The study collected 2,400 financial data and ESG performance of 200 companies from the Clean 200 list of global public companies from 2019 to 2021. It aimed to: 1) evaluate green supply chain performance based on financial indicators and corporate’s ESG performance; 2) use the entropy weight method (EWM) to determine the weight of ESG elements in green supply chain; 3) validate this ESG-based green supply chain performance using real world examples. The results showed that operational performance had the highest weight, followed by environmental performance, and profitability ranked the last. The results suggested that managers should focus more on the governance and environment rather than emphasizing short-term financial benefits. It contributes to the literature by incorporating ESG to evaluate green supply chain performance, which is the first of its kind. The results would be beneficial when people wish to select supply chain partners. They are also conducive to companies’ managers and listed companies when they submit financial reports that need to report ESG performance.

Spherical Linear Diophantine Fuzzy TOPSIS Algorithm for Green Supply Chain Management System

Enhancing competitive pressure is one of the most significant roles of supply chain management. The competitive environment and customer perception have shifted in favour of an ecological mentality. As a result, green supplier selection (GSS) has emerged as a critical problem. The challenge of green supplier selection striving for agility, durability, ecological sensitivity, leanness, and sustainability is tackled in this paper. In terms of recycling applications, environmental applications, carbon footprint, and water consumption, the environmental parameters evaluated in GSS and traditional supplier selection differ. Because of the form of the problem, a resolution is defined, which comprises an algorithm entrenched in the spherical linear Diophantine fuzzy sets (SLDFSs) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. Before discussing the approach of the SLDF model, some background information on SLDF sets is provided. To assure the uniqueness of this robust extension, different operations on SLDFSs are described, along with some concise interpretations to help the reader comprehend these ideas. A robust TOPSIS approach has been utilized in the issue of GSS by taking into consideration the multicriteria decision-making (MCDM) technique particularly useful in several areas, like analyzing and choosing traditional and environmental conventionalities. Due to linguistic criteria and the inability to assess all criteria, the fuzzy technique must be used with the TOPSIS method to lessen the consequences of instability and ambiguity. The spherical linear Diophantine fuzzy TOPSIS approach is employed, as it simplifies the evaluation of decision-makers and criteria. The hybrid technique resulting from integrating the SLDFS and TOPSIS is extremely successful in selecting which provider is more suited among the alternatives established on the criteria set by the order of significance, and this method may also be incorporated into similar issues.

Supplier Selection through Multicriteria Decision-Making Algorithmic Approach Based on Rough Approximation of Fuzzy Hypersoft Sets for Construction Project

The suppliers play a significant role in supply chain management. In supplier selection, factors like market-based exposure, community-based reputation, trust-based status, etc., must be considered, along with the opinions of hired experts. These factors are usually termed as rough information. Most of the literature has disregarded such factors, which may lead to a biased selection. In this study, linguistic variables in terms of triangular fuzzy numbers (TrFn) are used to manage such kind of rough information, then the rough approximations of the fuzzy hypersoft set (FHS-set) are characterized which are capable of handling such informational uncertainties. The FHS-set is more flexible as well as consistent as it tackles the limitation of fuzzy soft sets regarding categorizing parameters into their related sub-classes having their sub-parametric values. Based on these rough approximations, an algorithm is proposed for the optimal selection of suppliers by managing experts’ opinions and rough information collectively in the form of TrFn-based linguistic variables. To have a discrete decision, a signed distance method is employed to transform the TrFn-based opinions of experts into fuzzy grades. The proposed algorithm is corroborated with the help of a multi-criteria decision-making application to choose the best supplier for real estate builders. The beneficial facets of the put forward study are appraised through its structural comparison with few existing related approaches. The presented approach is consistent as it is capable to manage rough information and expert’s opinions about suppliers collectively by using rough approximations of FHS-set.