Effective Supply Chain Management Research Articles

Optimization and Benefit Assessment of Production Supply Chain Networks Using Graph Neural Network Models

With the flourishing development of global economy, effective management of production supply chains is crucial for the competitiveness of enterprises. Optimizing supply chain networks can not only improve the efficiency of resource allocation but also enhance market responsiveness and systemic risk resistance. Traditional supply chain network optimization methods, focusing mostly on linear models and static analysis, fall short in addressing the growing complexity and dynamism. The emergence of Graph Neural Network (GNN) models in recent years has offered new opportunities to tackle non-linearity and structural dynamism in supply chain networks. However, existing research still faces methodological limitations in supply chain node relationship mining and benefit assessment. This study introduces an optimization and benefit assessment method for production supply chain networks based on GNNs. Firstly, by developing a node role type-aware graph neural network model, this paper achieves in-depth mining and optimization of node relationships within production supply chain networks. Secondly, a hierarchical factor analysis method is used to comprehensively assess the benefits of the production supply chain. This method can dynamically capture changes in node roles and relationships within the supply chain network, optimize the network structure, and provides a multidimensional, multilevel framework for benefit assessment. This study not only expands the application of GNN in the field of supply chain management but also provides a new analytical tool for the comprehensive assessment of supply chain benefits.

Strengthening Healthcare Supply Chains: A Comprehensive Strategy for Resilience in the Face of Natural Disasters

Effective and uninterrupted management of the healthcare supply chain and healthcare system preparedness for natural disasters (e.g., pandemics, earthquakes, forest fires, etc.) is essential to ensure that victims receive critical healthcare services and products with minimal disruption, even in the event of damage to transport and logistics infrastructure as a result of significant disasters. The article examines this issue using the example of Vital Health Systems, a prominent hospital system with multiple facilities across a wide region. The qualitative data for the study was collected through interviews and focus groups with key stakeholders in Vital Health Systems, including supply chain managers, procurement specialists, frontline staff, etc. The quantitative data for the study were based on reports, internal documentation and archival documents, industry reports, market research, government databases. Analysis of the supply chain resilience of Vital Health Systems to natural disasters was carried out using the PESTLE framework, based on which a comprehensive risk reduction strategy was proposed. This strategy, while rooted in theory, is highly practical and feasible, with measures to optimise stocks, creation of alternative transport routes and logistics networks, and use of technological solutions. Organisational and managerial proposals for minimising supply chain disruptions for Vital Health Systems in the event of natural disasters are based on the theory of transformational leadership, Denison’s organisational culture, Levitt’s diamond model, and McKinsey’s theory of strategic horizons. The role of healthcare professionals, supply chain managers, procurement specialists, and researchers in healthcare management and disaster preparedness is crucial in implementing these strategies.

Managing global supply chain teams: human resource strategies for effective collaboration and performance

This study examines the role of human resource (HR) strategies in enhancing collaboration and performance within global supply chains, an area of increasing importance in the context of globalized business operations. The primary objective is to identify and analyze current trends in HR practices that contribute to effective global supply chain management, focusing on adaptability, technological integration, sustainability, and ethical practices. Employing a systematic literature review and content analysis as its methodology, the study draws on academic journals, conference proceedings, and industry reports from databases such as Scopus, Web of Science, and Google Scholar. Key findings reveal that adaptability and flexible work arrangements, supported by digital HR technologies, are essential for operational resilience and employee engagement. The integration of sustainability and ethical considerations into HR practices is identified as crucial for maintaining competitive advantage and ensuring regulatory compliance. Furthermore, the development of cultural intelligence and inclusive leadership within global teams is highlighted as vital for fostering effective collaboration across diverse cultural landscapes. The study concludes that strategic HR management plays a pivotal role in navigating the challenges and leveraging the opportunities within global supply chains. Recommendations for practitioners emphasize the importance of continuous learning, embracing digital transformation, and integrating sustainability into HR practices. The study also outlines areas for further research, including the impact of emerging technologies on HR practices and the long-term effects of sustainable HR strategies on organizational performance. This research contributes valuable insights into optimizing HR strategies to enhance global supply chain collaboration and performance.

Modeling the Decision and Coordination Mechanism of Power Battery Closed-Loop Supply Chain Using Markov Decision Processes

With the rapid growth of the new energy vehicle market, efficient management of the closed-loop supply chain of power batteries has become an important issue. Effective closed-loop supply chain management is very critical, which is related to the efficient utilization of resources, environmental responsibility, and the realization of economic benefits. In this paper, the Markov Decision Process (MDP) is used to model the decision-making and coordination mechanism of the closed-loop supply chain of power batteries in order to cope with the challenges in the management process, such as cost, quality, and technological progress. By constructing the MDP model for different supply chain participants, this paper investigates the optimization strategy of the supply chain and applies two solution methods: dynamic programming and reinforcement learning. The case study results show that the model can effectively identify optimized supply chain decisions, improve the overall efficiency of the supply chain, and coordinate the interests among parties. The contribution of this study is to provide a new modeling framework for power battery recycling and to demonstrate the practicality and effectiveness of the method with empirical data. This study demonstrates that the Markov decision-making process can be a powerful tool for closed-loop supply chain management, promotes a deeper understanding of the complex decision-making environment of the supply chain, and provides a new solution path for decision-making and coordination in the supply chain.

Revolutionizing Supply Chain Management: Real-time Data Processing and Concurrency

In the contemporary business landscape, effective supply chain management (SCM) is paramount for organizations seeking to thrive amidst evolving market dynamics and heightened customer expectations. This research paper presents a pioneering approach to SCM that harnesses cutting-edge technologies, namely Kafka and Akka, to revolutionize data integration and decision-making processes. By leveraging Kafka as a robust distributed event streaming platform and Akka as a versatile toolkit for developing concurrent and distributed applications, our system facilitates seamless communication and coordination across diverse nodes within the supply chain network. This paper elucidates the intricacies of the proposed architecture, detailing the implementation methodology and performance evaluation metrics. Through a comprehensive examination, we demonstrate how our solution enhances supply chain visibility, fosters operational agility, and enables real-time responsiveness to market fluctuations and customer demands. Moreover, practical use cases exemplify the transformative impact of our approach on inventory management optimization, order fulfillment efficiency, and logistics optimization. Furthermore, we delve into the challenges encountered during implementation and deployment, offering insights into potential mitigative strategies. Finally, we outline avenues for future research, exploring emerging trends and opportunities in the realm of SCM empowered by Kafka and Akka technologies.

Co-creation of a novel approach for improving supply chain management for SARS-CoV-2 point of care diagnostic services in Mopani District, Limpopo Province: nominal group technique.

Effective supply chain management (SCM) of point-of-care (POC) tests for diseases like severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) requires active participation from diverse stakeholders, government entities, and regulatory bodies. The responsibility for overseeing various aspects of POC tests, including procurement, quality assurance, storage, inventory management, distribution, and human resource capacity, lies with national, provincial, and local levels of government. This study aimed to collaboratively develop an innovative approach to enhance SCM for SARS-CoV-2 POC diagnostic services in resource-limited settings, using the Mopani District in Limpopo province, South Africa, as a case study. Key stakeholders were invited to participate in an online workshop using purposive sampling. The study employed the nominal group technique (NGT) for data collection, which consisted of two phases. Phase 1 focused on identifying barriers in the supply chain of COVID-19 rapid tests, while phase 2 aimed to devise strategies to overcome the priority barriers identified in phase 1. Participants used a Likert scale of 1-5 to rank barriers and strategies, and an overall ranking score was calculated for each. The participants were provided with the results of the ranking exercise for their feedback. Eleven key stakeholders from national (n = 1), provincial (n = 4), and local government (n = 2) levels, research entities (n = 3), and non-governmental organizations (n = 1) took part in the study. Participants identified significant barriers in the supply chain, such as the availability of testing kits, unknown demand, information on SCM during a pandemic, methods of controlling stock, and procurement processes. Strategies suggested by key stakeholders included monitoring stock levels and optimizing stock visibility systems to improve test availability, enhancing information visibility and consistent data updates to address unknown demand and improve SCM during a pandemic, employing data capturing and digitization for effective stock control, and implementing demand planning and standardized procurement processes at the national level to enhance stock procurement. The successful collaboration with key stakeholders, facilitated by the NGT, resulted in the co-creation of a novel approach to enhance SCM for COVID-19 diagnostic services in resource-limited settings. This study holds the potential to support the provision of COVID-19 diagnostic services in such settings. A recommended follow-up study would assess the feasibility of implementing this approach.

Effective hydrogen supply chain management framework considering nonlinear multi-stage process uncertainties

The large amount of carbon emitted due to industrial development is posing serious climate change. Under these circumstances, hydrogen energy is being used as a major energy source and is attracting attention as an alternative energy to fossil fuels, characterized by high carbon emissions. While the use of hydrogen has the obvious benefit of a low carbon footprint, the hydrogen production process possesses a high carbon footprint difference depending on the source of utilized electricity. This study considers several situations arising in an electrolysis-based hydrogen supply chain network (HSCN). A multi-stage stochastic programming (SP) is modeled to consider the uncertainty of demand and transportation capacity generated in HSCN. Moreover, a typical stochastic model has a chain rule between the decision variables resulting from nonlinearity and uncertainty, and these features make it difficult to derive an effective solution. Thus, in this study, a new methodology, Weighted Scenario Sample Average Approximation (WSSAA), is proposed to derive an effective solution for the multistage SP model considering various scenarios under the hydrogen supply chain. While a general stochastic programming approach fails to generate feasible solutions with volatile HSCN uncertainties, the proposed WSSAA framework provides feasible decisions considering multiple scenarios. The effectiveness of the proposed model applied with WSSAA is demonstrated through comparative experiments over the models used in existing studies.

Food safety in consumer relations: the influence of personal values

Purpose: The aim of this article is to analyze the relationship between food safety and personal values in light of consumer behavior theory. Method: In this theoretical essay, this relationship is examined through a discussion on how consumers' subjective perceptions are influenced by their personal values in various contexts involving food safety. Findings: The debate addresses social, cultural, economic and environmental factors, considering that values are shaped through the interaction of these variables. By outlining their positioning strategies based on segments of values that are relevant to consumers, organizations are more likely to evoke favorable attitudes towards product acquisition. This includes considering external factors because they shape the formation of personal values and thus influence individuals' choices related to food and their perception of food safety. Originality: This work enriches the theory of personal values in the field of consumer behavior related to food safety by exploring the complex interplay between personal, cultural and market values. Considering personal values as a central element, the analysis presented provides insights for the development of more targeted marketing actions, effective public policies and food supply chain management approaches that meet consumers' expectations in terms of food safety.

Penerapan Supply Chain Management di PT Nippon Indosari Corpindo Tbk

This research discusses the application of Supply Chain Management (SCM) at PT Nippon Indosari Corpindo Tbk., one of the leading companies in the bakery industry in Indonesia. Focusing on enhancing operational efficiency and reducing production costs, this study explores how PT Nippon Indosari Corpindo Tbk. integrates advanced technology and Supply Chain Management strategies to maintain product quality while minimizing losses. Through the use of the Just In Time (JIT) concept, Advanced Planning & Optimization (APO) tool, and Radio Frequency Identification (RFID), the company has successfully improved inventory management, expedited distribution, and maximized customer satisfaction. The research findings show that effective SCM implementation has reduced the bullwhip effect, increased transparency in the flow of raw materials and finished products, and supported the sustainability of the company's operations. Thus, this study provides important insights into the benefits of SCM in the food and beverage industry, especially for companies operating on a large scale with dynamic market demands

A digital twin-enabled digital spare parts supply chain

An efficient and effective spare parts supply chain management is crucial to ensure highly available production systems. However, achieving such a spare parts supply chain management is challenging due to the intrinsic characteristics of spare parts. Traditional spare parts supply chains (TSPSCs) adopt large spare parts inventories to tackle such intrinsic characteristics, with disadvantages in terms of high inventory costs. Recently, Additive Manufacturing (AM) has shown breakthrough potential, allowing the transition from TSPSCs to digital spare parts supply chains (DSPSCs), where spare parts are no longer stored in large amounts but are stored digitally and produced only when needed. However, despite DSPSCs benefits, a complete transition from TSPSCs to DSPSCs is still far from becoming reality. Indeed, hindering such a transition is a lack of expertise in three main areas, i.e. how to design, operate, and control and monitor a DSPSC. With this position paper, we envision how a digital twin (DT) could overcome these issues, enabling a full transition to a DSPSC. Moreover, this work further concretely suggests how such a DT could be developed, providing the basis for developing both the theoretical and practical knowledge necessary to render DSPSCs a reality.

Research on Inventory Control Method Based on Demand Response of Power Big Data

The supply chain functions as a complex web, interconnecting various stakeholders such as suppliers, manufacturers, wholesalers, retailers, and ultimately, end consumers. Central to effective supply chain management is the meticulous handling of inventory, a critical factor influencing both cost efficiency and service excellence throughout the entire network. The management of inventory within this context extends beyond the confines of individual enterprises, bearing significance across the entirety of the supply chain. Consequently, achieving optimal performance necessitates a cohesive, holistic approach to management, aligning with the overarching objectives of the system. Through dynamic data analysis of multiple types of power materials, a dynamic inventory control model for power materials is constructed to achieve optimal adjustment of inventory management. Ultimately, a multi-granularity inventory control method based on big data analysis of power warehousing is constructed, which effectively improves inventory management efficiency and reduces logistics management costs for enterprises. Through big data analysis of power material warehousing, the characteristics of power material demand are excavated, and a classification method for power material demand is constructed to achieve an overall inventory control strategy for power materials. The implementation results show that the controlled inventory can better meet the changing demand, thereby improving inventory management efficiency. The multi-granularity inventory control method based on big data mining of warehousing combines inventory and multi-objective optimization theories, proves the applicability and feasibility of the proposed method, effectively improves inventory management efficiency, reduces logistics management costs for enterprises, and provides practical guidance and decision-making reference for improving the intensive management level of power production and maintenance materials.

Empirical Examination of the Relationship between Supply Chain Effectiveness and a Company’s Overall Success

The relationship between the effective management of supply chains and overall organizational success is not fully explained in the literature. The differences in the effectiveness of supply chains as well as the corporate social responsibility (CSR) of supply chain companies in North America, Europe, and Asia Pacific are not broadly studied. This article attempts to bridge that gap in the literature using data from the Gartner Supply Chain Group, Brand Finance, American Consumer Satisfaction Index, and Bloomberg Finance. Pertinent statistical tools including multiple regression, ANOVA, t-tests, and chi-square tests were utilized in the study. SCM top performers were found to have higher customer satisfaction than their industry counterparts; supply chain variables used currently do not have a statistically significant impact on the overall success of those companies; North American companies have experienced significantly higher supply chain effectiveness than their counterparts in Europe and Asia Pacific; and European supply chain companies are significantly ahead of companies in America and Asia in the area of CSR. The findings can help managers in companies to benchmark with their global peers. The main contribution of this research is that it demonstrates the value of supply chain effectiveness while underscoring the need for further research to link supply chain effectiveness with organizational performance. Supply chain managers need to explore operational or internal process metrics that have a more significant impact on overall company success.

Analysis Of Ship Main Engine Procurement Process In The Shipyard Industry Using Supply Chain Operation Reference Method (SCOR) (Case Study: PT XYZ)

As a sector playing a crucial role in ship construction and repair, the shipbuilding industry faces significant challenges in material procurement, where materials constitute 50-70% of the total project cost. One of the materials requiring paramount attention is the ship's main engine. Effective supply chain management is critical to enhancing efficiency and effectiveness in the procurement process of ship engines. However, supply chain performance measurement research, especially in ship engine procurement, still needs to be improved. Therefore, this study aims to identify relevant performance metrics, analyze critical performance indicators, and provide recommendations based on the SCOR (Supply et al.) framework to improve ship engine procurement. The research results present 24 metrics distributed into four performance attributes based on SCOR 12.0, with 22 selected metrics aligned with the company's context. Analysis using the AHP method indicates that the reliability attribute has the highest weight (0.296), with the metric "Percentage of procurement received on time as per request" being the top priority (weight 0.143). This study provides a holistic view of crucial aspects of the ship engine procurement supply chain, supporting companies in enhancing their performance in the procurement process.

MAPPING THE LANDSCAPE OF ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN MANAGEMENT: A BIBLIOMETRIC ANALYSIS

Industry 4.0 concepts and technologies, which focus on interconnectivity, digitalization, and automation, are critical to the long-term success of both micro and macroeconomic entities. Artificial Intelligence (AI) has emerged as a critical enabler for effective Supply Chain Management (SCM) within this framework. This research study conducts a thorough examination of the current literature to investigate the role of AI in SCM. The study attempts to identify research trends, appraise the present state of knowledge, and provide insights on management implications through a systematic review and the use of bibliometric analytic methodologies. The management implications of this study provide light on the potential benefits and possibilities that AI may provide to SCM operations. The research findings provide firms with the means to improve their supply chain operations, elevate decision-making processes, and achieve a competitive advantage in the changing business landscape by properly using the potential of AI.

The mediating role of perceived competitive advantage on the relationships between green supply chain management practices and operational performance: evidence from Bangladeshi manufacturing firms

Purpose Effective green supply chain management (GSCM) has become a potentially valuable tool of securing competitive advantage and improving operational performance (OP) as competition is no longer exists between the firms but within green supply chains. The aim of this empirical study is to determine the link between GSCM practices (GSCMPs) and OP within the manufacturing sector of Bangladesh mediated by perceived competitive advantage (PCA). GSCMPs were divided into three further dimensions: green eco-design (GED), green supply chain partnering (GSCP) and internal green orientation (IGO).Design/methodology/approach The study selected 376 individuals as respondents who work as the top-level managers and the members of the Board of Directors at different Bangladeshi manufacturing firms through purposive sampling. A partial least square-based structural equation modeling (PLS-SEM) was utilized to identify the relationships between the three dimensions of, GSCMPs, and the single dependent variable, OP.Findings The study identified that two factors, GED and GSCP, have significant positive relationships with OP. On the other hand, another factor, IGO has a statistically insignificant relationship with OP. Regarding the mediating effects, the study identified that PCA can fully mediate the insignificant relationship between IGO and OP, and partially mediate the significant relationship between GSCP and OP. On the contrary, PCA has no mediating effect on the relationship between GED and OP.Originality/value This empirical study is an effort that examined the role of GSCMPs on the OP in the Bangladeshi manufacturing context. It is believed that this empirical investigation will prompt future theoretical studies and empirical experiments to enrich academia. Further, the findings of this study can serve as foundational guidance for policymakers and/or managers studying the formulation and implementation of GSCMP-related policies and strategies.

Exploring critical internal enablers to SMEs export performance: evidence from Qatar

This study seeks to provide a contextualized and nuanced understanding of what constitutes internal enablers among small and medium-sized enterprises (SMEs) in support of their export activities in international markets. We unpacked a unique set of critical enablers that can be cultivated as the internal impetus for enhancing the export performance of SMEs in a less-researched emerging market, Qatar. The study employs a qualitative approach for collecting, analyzing, and interpreting data, which were collected through in-depth interviews with 20 SMEs managers from 11 manufacturing sub-sectors. A thematic analysis of our data reveals five key internal enablers needed for better export performance. These comprise employees with networking skills, effective supply chain management, product diversification, digitalization, and market intelligence capabilities. This research offers empirical insights into what enables non-hydrocarbon manufacturing SMEs to enhance their export performance.

Optimising Energy Efficiency through Effective Supply Chain Management: A Comparative Study

Energy Efficiency (EE) is a crucial resource for social and financial development, benefiting everyone through EE developers in society. Encouraging energy problem alignment with corporate company goals increases productivity, profitability, quality, and cost reductions. EE is an essential benefit for organizations, not merely a minor concern. Most companies, particularly Small and Medium Enterprises (SMEs), need help adopting EE measures and even encounter opposition. Funding and awareness (particularly of life cycle cost impacts) are the biggest obstacles. One way weaker organizations might overcome such constraints and improve EE is from the Supply Chain (SC) perspective. Since most EE studies and practical strategies concentrate on single-firm energy usage, this article examines peer-reviewed journal articles on EE incorporation in SC development and oversight to identify research needs. Several literature evaluations have focused on sustainability or Supply Chain Management (SCM), but none have addressed EE. First, this article explains how energy usage in SCM improves systemic EE. Then, a study technique is developed, and the selected publications are examined and classed by their methodologies.

Implementation of Green Supply Chain Management Practices

This research investigates the barriers to effective Green Supply Chain Management (GSCM) practices, focusing on the critical roles of environmental awareness, financial constraints, and regulatory compliance in organizations. It utilizes a mixed-methods approach, combining quantitative data from structured questionnaires with qualitative insights from expert interviews and case studies. The study begins with a comprehensive literature review to frame the hypotheses, followed by empirical data collection to evaluate these hypotheses. The findings are analyzed using statistical methods, including hypothesis testing and regression analysis, and are further enriched with expert opinions. Cronbach’s Alpha values are used to assess the reliability of measurement instruments for various factors, including Environmental Awareness, Financial Constraints, and Regulatory Compliance. The research culminates in presenting actionable strategies and recommendations for overcoming identified barriers, thereby promoting the adoption of GSCM practices in industries, particularly in the context of organizational culture and regulatory environments. The research aims to provide actionable recommendations based on validated hypotheses and case study findings to enhance the adoption of GSCM practices in underdeveloped nations.

Analisis Rantai Pasok Ketersediaan Bahan Baku Produk Pertanian Jenis Beras dengan Metode Supply Chain Operations Reference

Supply chain management affects the availability, sufficiency, and quality of raw material inventory. With effective supply chain management, the inventory will always be well-maintained, meeting the needs and demands when required, especially at UD. Fajar Samudra. The purpose of this research is to understand the supply chain management regarding raw material inventory at UD. Fajar Samudra using a descriptive qualitative research method that addresses in more detail the specific and in-depth issues studied at UD. Fajar Samudra. In qualitative research, the population and sample are referred to as informants (company executives, warehouse managers, and the three largest suppliers at UD. Fajar Samudra). The research results indicate that the supply chain management at UD. Fajar Samudra shows that the supply chain management has not been able to meet the raw material inventory due to several issues in the field. These issues include inadequate procurement of raw materials due to the selection of rice types that do not match the requirements, damaged rice quality due to distribution processes, and unfulfilled quantity needs or demands, leading to dissatisfaction among consumers, as measured by the Supply Chain Operations Reference (SCOR) performance metrics. The advice that can be given to UD. Fajar Samudra is to make improvements by conducting forecasting based on historical sales data, engaging suppliers that implement management information systems, and implementing line balancing to enhance production strategies.

Practices and strategies for global sourcing and supply chain management: a Pareto analysis and MOORA a mixed method approach

Purpose This study aims to identify and prioritize the key practices and strategies for effective global sourcing and supply chain management (SCM). Design/methodology/approach The study uses a combination of Pareto analysis and multi-objective optimization based on ratio analysis research methodology to analyze and establish the relationships among the identified key practices and strategies. Pareto analysis enables organization to prioritize organizational efforts and resources by focusing on the most critical factors. Findings The study shows that the “eco-friendly sourcing strategy”, “lean manufacturing” and “tool cost analysis” are the top critical practices and strategy variables for global sourcing and SCM, whereas the “risk management”, “procurement strategy” and “leverage digital solutions” are the critical practices and strategy variables. Research limitations/implications The findings of this research can also assist organizations in making informed decisions to optimize their global sourcing and supply chain operations. Originality/value By using these methods, this research paper gives valuable insights into the critical practices and strategies that can enhance efficiency, mitigate risks and drive success in global sourcing and SCM. The subjects and elements this study identified will serve as a framework and suggestions for further theoretical investigation and real-world implementations.