Supply Chain Management In Industry Research Articles

Comparison of Alfamart and Indomaret Supply Chain Efficiency in Handling Consumer Demand in Indonesia

This study aims to provide a comparative analysis of the supply chain efficiency of two major retail chains in Indonesia, Alfamart and Indomaret, in handling consumer demand. The research focuses on key areas such as procurement, inventory management, distribution, and technology integration. Utilizing qualitative methods, including in-depth interviews with supply chain managers and document analysis, the study reveals that both companies have developed effective supply chain strategies. Alfamart is noted for its flexibility and speed of response, while Indomaret emphasizes stability and efficiency. The findings, supported by specific data on inventory turnover rates and distribution times, suggest that improved supply chain management can significantly impact product availability, customer service, and consumer satisfaction. Recommendations for both companies include optimizing logistics processes, adopting advanced technology, and enhancing collaboration with suppliers, aiming to reduce operational costs and increase consumer satisfaction. This study highlights the importance of continuous development and technology integration in supply chain systems to maintain a competitive edge in the retail market. By implementing tailored strategies, Alfamart and Indomaret can further improve their supply chain efficiency, thereby enhancing customer satisfaction and loyalty. References to relevant studies and journals support these conclusions, emphasizing the critical role of efficient supply chain management in the retail industry. The study's limitations and future research directions are also discussed to provide a comprehensive understanding of the topic.

Analyzing how COVID-19 moderates the relationship between organizational learning capabilities, technological innovation, supply chain management and enterprise performance in the automobile industry

PurposeThis study explored how COVID-19 moderated the relationship between organizational learning capabilities (OLCs), technological innovation (TI), supply chain management (SMC) processes and enterprise performance (EP). It aimed to give ideas on how organizations could change and do well during big disruptions.Design/methodology/approachDesign: A structured questionnaire served as the data collection tool, employing a stratified sampling technique. Partial least squares (PLS) was utilized for data processing. Information was gathered from the automobile industry in Xian, China, providing an in-depth understanding of how COVID-19 moderated the variables under examination.FindingsThe study discovered that COVID-19 changed how organizational learning, TI, SCM and EP interacted. Some organizations had trouble keeping up with learning and innovation, but others used them to make their SCM stronger, leading to better performance. Also, different effects of COVID-19 were seen in various industries and organizations.Practical implicationsThis study provided practical implications for managers, policymakers and practitioners. It emphasized fostering OLCs and TI as crucial for resilience during disruptions like COVID-19. Strategic investments in SCM were highlighted to mitigate disruptions and seize opportunities. Additionally, context-specific approaches were underscored for navigating pandemic-induced challenges.Originality/valueThis study enhanced existing literature by analyzing how COVID-19 moderated the link between organizational learning, TI, SCM and EP. Through diverse methodologies and organizational contexts, it offered fresh insights into dynamic organizational responses to disruptions, advancing both theoretical understanding and practical knowledge in the field.

Analyzing how COVID-19 moderates the relationship between organizational learning capabilities, technological innovation, supply chain management and enterprise performance in the automobile industry

PurposeThis study explored how COVID-19 moderated the relationship between organizational learning capabilities (OLCs), technological innovation (TI), supply chain management (SMC) processes and enterprise performance (EP). It aimed to give ideas on how organizations could change and do well during big disruptions.Design/methodology/approachDesign: A structured questionnaire served as the data collection tool, employing a stratified sampling technique. Partial least squares (PLS) was utilized for data processing. Information was gathered from the automobile industry in Xian, China, providing an in-depth understanding of how COVID-19 moderated the variables under examination.FindingsThe study discovered that COVID-19 changed how organizational learning, TI, SCM and EP interacted. Some organizations had trouble keeping up with learning and innovation, but others used them to make their SCM stronger, leading to better performance. Also, different effects of COVID-19 were seen in various industries and organizations.Practical implicationsThis study provided practical implications for managers, policymakers and practitioners. It emphasized fostering OLCs and TI as crucial for resilience during disruptions like COVID-19. Strategic investments in SCM were highlighted to mitigate disruptions and seize opportunities. Additionally, context-specific approaches were underscored for navigating pandemic-induced challenges.Originality/valueThis study enhanced existing literature by analyzing how COVID-19 moderated the link between organizational learning, TI, SCM and EP. Through diverse methodologies and organizational contexts, it offered fresh insights into dynamic organizational responses to disruptions, advancing both theoretical understanding and practical knowledge in the field.

A TOE-DCV approach to green supply chain adoption for sustainable operations in the semiconductor industry

Semiconductor industry plays a critical role for the global economy. Semiconductor industry provides various necessary technologies such as IoT, AI, modern fabrication technologies and so on to various industries including automotive industry, electronic and communication industry, healthcare industry, construction and building industry, space industry, and so on. However, semiconductor supply chain experiences various supply chain related risks and challenges because of its procedural complexities, global supply chain integrations, government policy and regulations, competitiveness, technological complexities, and so on. Not many studies available which investigated the risk, resilience, and complexities regarding green supply chain adoption by semiconductor industry. In this context, the objective of this study is to examine the risks, resilience, and complexities for managing the green supply chain adoption for higher sustainability in the semiconductor industry. Utilizing the TOE framework (Technology-Organization-Environment) and DCV (Dynamic Capability View), we developed a research model to achieve this purpose. Subsequently, this model was validated through structural equation modelling, involving 356 respondents affiliated with the semiconductor industry. This study highlights that technological risk aspects comprising of technological turbulence and risk, compatibility and complexity, organizational dynamic capabilities, and resilience along with appropriate policy and regulations could help successful adoption of green supply chain management in the semiconductor industry.

A REVIEW OF BLOCKCHAIN TECHNOLOGY'S IMPACT ON MODERN SUPPLY CHAIN MANAGEMENT IN THE AUTOMOTIVE INDUSTRY

Blockchain technology has emerged as a transformative force in various industries, including supply chain management within the automotive sector. This review examines the impact of blockchain on the automotive supply chain by analyzing 183 articles, focusing on its ability to enhance transparency, traceability, and efficiency. By providing a decentralized and immutable ledger, blockchain ensures real-time tracking of parts and components, thereby reducing the risk of counterfeit products and ensuring compliance with regulatory standards. The automation of transactions through smart contracts streamlines processes, reduces the need for intermediaries, and leads to substantial cost savings and faster delivery times. However, the implementation of blockchain also presents challenges such as scalability, interoperability with existing systems, high costs, and regulatory concerns. Addressing these challenges through future research and pilot projects is essential for unlocking the full potential of blockchain technology in revolutionizing supply chain management in the automotive industry. This review synthesizes current literature to provide a comprehensive understanding of both the benefits and challenges associated with blockchain implementation, highlighting its transformative potential and the necessary steps for successful adoption.

The role of digital transformation in achieving sustainable supply chain management in Industry 4.0: an editorial review perspective

ABSTRACT Before and aftermath of COVID-19 has created multiple waves of digital transformation adoption in supply chain management. The power of potential benefits is realised as a multitude however the transformation phases are not sustainable. This editorial special issue has edited papers of scholarly research contributions to the theory and practice of digital transformation aspects in the field of logistics and supply chain management. Based on the summary of each contribution and an extended literature review on the theme, this editorial paper proposes a novel framework that could facilitate the logistics industry at times of disruptive technologies when firms are struggling to cope with the challenges created due to the COVID-19 pandemic and the recovery.

Innovation in the dairy industry: forecasting cow cheese production with machine learning and deep learning models

This study focuses on the use of deep learning and machine learning models to forecast cow cheese production in Turkey. In particular, our research utilizes the LSTM (long short-term memory) model to forecast cow cheese production for the next 12 months by extensively utilizing deep learning and machine learning techniques that have not been applied in this field before. In addition to LSTM, models such as GRU (Gated Recurrent Unit), MLP (Multi-Layer Perceptron), SVR (Support Vector Regression), and KNN (K-Nearest Neighbors) were also tested, and their performances were compared using RMSE (Root Mean Square Error), MSE (Mean Squared Error), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error), and (Coefficient of Determination) metrics. The findings revealed that the LSTM model performed significantly better than the other models in terms of RMSE, MSE, MAE, and MAPE values. This result indicates that the LSTM model provides high accuracy and reliability in forecasting cow cheese production. This achievement of the model offers important applications in areas such as supply chain management, inventory optimization, and demand forecasting in the dairy industry.

A STUDY ON SUPPLIER EVALUATION PROCESS IN FOOTWEAR MANUFACTURING INDUSTRY

This study introduces an innovative supplier evaluation approach for footwear manufacturing by integrating the SCOR 4.0 model with machine learning techniques. The SCOR 4.0 model, combined with the Best Worst Method (BWM), provides a structured framework for evaluating suppliers across various dimensions. A Random Forest (RF) machine learning model is then used to classify and rank suppliers based on performance ratings. The results show that the RF algorithm effectively identifies suitable suppliers, with lower rejection scores indicating superior performance. This integration enhances supplier evaluation processes and offers valuable insights for supply chain management in the footwear industry. Key Words: Supplier evaluation, SCOR 4.0 model, Best-worst method (BWM), Random Forest (RF), Supplier Rejection score

The Negative Impact of ESG on the Australian Minerals Supply Chain

With the full implementation of the ESG standards in Australia, supply chain management in the mining industry faces challenges. This research utilized Mineral Resources Limited (MRL) as an example to discover how environmental (E), social (S), and governance (G) factors affect supply chain management. It applies MRL management costs and operations to analyze and integrate with the academic literature on ESG frameworks and supply chain management. It concludes with three points: Environmental management issues affect the delivery of minerals downstream in the supply chain, and an EMS system should be applied to manage them dynamically. Community cooperation and employment equity issues affect the cooperation and operation of mining businesses upstream of the supply chain, so the Community Engagement and Development Program (CEDP) system should be adopted to maintain community communication. Non-transparent governance issues affect both upstream operations and shake downstream investors' confidence. The Governance Enhancement and Compliance Programme (GECP) system can enhance decision-making transparency and compliance with governance policies. This research bridges the gap in negative ESG impacts on the mining industry. It proposes three new systems that serve as a model for future company adoption to cater to ESG standards.

Evaluation of critical success determinants to the implementation of additive manufacturing technology in the spare parts supply chain: a grey causal modelling approach

PurposeAdditive Manufacturing technology (AMT) is swiftly gaining prominence to induce automation and innovation in manufacturing systems. It holds immense potential to change supply chain dynamics by providing the possibility of printing objects on demand. This study thus formulates and analyzes the framework to incorporate AMT to handle the spare parts supply chain management (SPSCM) in capital-intensive industries by identifying and assessing the critical success factors (CSFs).Design/methodology/approachAssessment of the CSFs is performed using the novel Grey Causal Modeling method (GCM) with the objective of making SPSCM resilient and efficient. GCM conducts causal analysis by taking into consideration cause, effects, the objectives, and the situations.FindingsFindings indicate that; Logistics Lead Time (SD4), Time to manufacture (SD3), Management Support (SD11), and Risk Management (SD20) are the most prominent causal factor having a maximum impact when incorporating AMT in SPSCM. The results also reveal that the performance of manufacturing organizations that adopt AMT is substantially influenced by internal and external factors such as Management Support (SD11) and Government Regulations (SD16).Research limitations/implicationsThis research provides valuable information for getting the global spare parts supply chain equipped for the post-COVID age, where digital technologies such as AMT will be fundamental for bolstering supply chain resilience and efficiency.Originality/valueThis research proposes a framework for performance assessment when incorporating AMT in SPSCM. Study also demonstrates methodological application of novel Grey Causal Modelling technique using a real case in a spare parts manufacturing industry in India.

Blockchain-Based Lean Supply Chain: A Simulation Approach

This paper aims to propose a model based on blockchain and cloud computing technologies to support lean production techniques for industrial supply chain management, evaluating how the combination of these technologies provides improvement in the chain performance. The literature review contextualizes the state of the art in studies related to the application of blockchain technology to lean manufacturing processes, as well as identifies research gaps in this field. Besides, this study models and simulates an architecture based on both the Hyperledger Fabric network and a virtual machine in the cloud environment, assessing its applicability and performance in the industrial supply chain. The analysis addresses lean aspects identified as research gaps, including integration of stakeholders in the collaborative production of customized products, conditions of flexibility and adaptability to demand variations, coordinated relationship of networks involving small and medium-sized enterprises, and behavior of various players acting simultaneously and consensually. The proposed model reveals a decentralized and nonlinear information sharing concept that demonstrates a logic of simultaneous participation of all players involved in the supply chain. The low costs and processing times identified in the simulation indicate the robustness of the system even in transactions involving a large number of companies and a large amount of data. This architecture offers an integration solution between stakeholders to support operational processes, providing insights for researchers and specialists in the adoption of innovative, reliable and inclusive information technologies for companies of different sizes or levels of development, with a focus on lean manufacturing, reduction in resource consumption and cost reduction. The developed model, which combines blockchain and cloud computing technologies applied to stages of lean production systems, presents a differentiated solution on the planning of integrated production systems, indicating the differential in this work.

Implementing RPA to optimize supply chain and inventory management in the pharmaceutical industry

Implementing RPA to optimize supply chain and inventory management in the pharmaceutical industry

Collaborative Eco-Industrial networks: A study on environmental resilience

Collaborative Eco-Industrial networks (EINs) are partnerships of companies and industry participants that promote sustainable activities. To optimize resource usage, lessen their influence on the environment and foster innovation, share knowledge, resources and technological advancements. Through collaboration and synergy, these networks promote an industrial ecosystem that is more sustainable and favorable to the environment. The creation of EIN is examined in the review as a crucial component, with an emphasis on closed-loop logistics and Industrial Symbiosis (IS). This study examines the significance of collaborative EINs to environmental resilience by utilizing concepts from 30 investigations in 2017-2023. The review addresses the idea of collaborative EINs and the design components of environmental impact focusing on real-world examples. It introduces the concept of collaborative EINs and a case study of a large company collaborating with partners to establish a recycling-focused EIN. The review emphasizes the importance of EINs in sustainable practices and the need for agility and resilience in supply chain (SC) management in Industry 4.0. It includes metrics relevant to the COVID-19 pandemic to evaluate the economic and environmental effects of EINs. This review concludes that collaborative EIN connections improve supply chain agility and resilience, creating a more environmentally conscious and sustainable industrial landscape.

Digitalization in Supply Chain are Changing the Dynamics of Business

This research paper provides an indepth study on the field of automation and digitalization in supply chain management (SCM) in the textile industry. The study, which compares traditional methods with digital methods, aims to shed light on the development of technology in this field.

Integrating accounting models with supply chain management in the aerospace industry: A strategic approach to enhancing efficiency and reducing costs in the U.S

This concept paper proposes the integration of accounting models with supply chain management in the aerospace industry as a strategic approach to enhancing efficiency and reducing costs in the United States. The aerospace sector faces numerous challenges, including complex supply chains, stringent regulatory requirements, and cost pressures. By combining accounting principles with supply chain management strategies, this approach aims to optimize operations, improve financial transparency, and foster collaboration among stakeholders. Key objectives of this initiative include streamlining financial processes, enhancing decision-making capabilities, and mitigating risks associated with supply chain disruptions. By leveraging accounting models such as activity-based costing, lean accounting, and performance measurement systems, organizations can gain insights into cost structures, identify inefficiencies, and allocate resources effectively across the supply chain. Moreover, integrating accounting with supply chain management enables real-time monitoring of financial performance metrics, enabling timely interventions and adjustments to achieve strategic goals. This approach also facilitates better coordination between finance and operations teams, leading to improved communication, alignment of objectives, and ultimately, enhanced organizational performance. In the context of the aerospace industry, where precision, reliability, and cost-efficiency are paramount, this integrated approach offers significant benefits. It enables companies to optimize inventory management, minimize waste, and identify opportunities for cost savings throughout the supply chain. Additionally, by fostering a culture of continuous improvement and data-driven decision-making, organizations can adapt more effectively to market dynamics and gain a competitive edge. This concept paper outlines the theoretical framework and practical implications of integrating accounting models with supply chain management in the aerospace industry. Through case studies, best practices, and implementation strategies, it provides a roadmap for organizations to embrace this strategic approach and realize its full potential in enhancing efficiency and reducing costs in the U.S. aerospace sector.

SUSTAINABLE SUPPLY CHAIN MANAGEMENT IN THE MEDICAL INDUSTRY: A THEORETICAL AND PRACTICAL EXAMINATION

Sustainable Supply Chain Management (SSCM) has emerged as a critical paradigm in the modern healthcare landscape, aiming to reconcile the often conflicting objectives of environmental stewardship, social responsibility, and economic viability within medical supply chains. This paper offers a comprehensive theoretical and practical exploration of SSCM within the context of the medical industry. Six keywords - sustainability, supply chain management, healthcare, environmental stewardship, social responsibility, economic viability - encapsulate the essence of this examination. The introduction sets the stage by highlighting the growing importance of sustainability in healthcare operations and the unique challenges faced by the medical sector in achieving sustainable supply chains. It underscores the significance of integrating environmental, social, and economic considerations into the fabric of medical supply chain management practices. The subsequent sections delve into various facets of SSCM in the medical industry. They address key components such as reducing carbon footprint and waste, fostering social responsibility through ethical sourcing practices, and striking a balance between sustainability objectives and cost efficiency. Regulatory frameworks and compliance requirements specific to healthcare supply chains are also explored, emphasizing the need for alignment with evolving sustainability standards. Technological innovations play a pivotal role in driving sustainability in medical supply chains, with advancements in data analytics, blockchain, and IoT enabling enhanced visibility, traceability, and efficiency. Moreover, collaboration and partnerships among stakeholders are deemed essential for fostering sustainable practices across the healthcare ecosystem. Drawing from real-world case studies, the paper illustrates successful implementations of SSCM principles in the medical industry, showcasing best practices and lessons learned. Finally, it prognosticates future trends and challenges, anticipating continued emphasis on sustainability amidst evolving market dynamics and regulatory landscapes. In sum, this theoretical and practical examination underscores the imperative for sustainable supply chain management in the medical industry, offering insights and strategies to navigate the complex interplay of environmental, social, and economic factors in healthcare logistics.
 Keywords: Sustainability, Supply Chain Management, Healthcare, Environmental Stewardship, Social Responsibility, Economic Viability.

Identification of practices in sustainable supply chain management for the food industry

El artículo que se presenta a continuación tiene como objetivo identificar las prácticas implementadas en la gestión de la cadena de suministro sostenible de empresas de la industria alimenticia a nivel internacional. Para su desarrollo metodológico se realizó una revisión de una muestra de documentos científicos que permitió la identificación de prácticas por medio de las técnicas de análisis del discurso y de análisis reticular, a fin de evidenciar las múltiples relaciones entre las dimensiones y las categorías asociadas a lagestión de la cadena de suministro sostenible. Los resultados contribuyen a la compresión de la sostenibilidad en los aspectos productivos asociados al ámbito económico, social y ambiental, y aportan a la trasferencia de conocimiento científico a los empresarios, investigadores y encargados de la producción en una industria que se enfrenta a un entorno competitivo,caracterizado por las exigencias en trazabilidad e inocuidad, los cambios en las demandas de los consumidores y la seguridad alimentaria

Pharmaceutical retail supply chain responses to the COVID-19 pandemic

AbstractIn the wake of the COVID-19 pandemic, the importance of resilient supply chain and operations management in the pharmaceutical industry has intensified. A particular challenge has been the timely adaptation to rapid fluctuations in the business environment to cope with disruptions and ensure the adequate supply of medical equipment and pharmaceuticals. In this study, we perform a simulation-based analysis of pandemic-triggered impacts on pharmaceutical supply chains in Germany with the aim of examining supply chain response to the COVID-19 pandemic. To accomplish this, we build a digital supply chain model using a hybrid approach that combines case study analysis and discrete-event simulation implemented in anyLogistix. Based on the results, we propose a specific response action plan for the pharmaceutical industry that can be deployed in response to severe disruptions and pandemic-like crises. We also offer a resilience framework for the post-pandemic environment as a guideline for strategic decision-making.

Green supply chain management practices and implementation in the construction industry

This study aims to define and describe Green Supply Chain Management (GSCM) in the construction industry. GSCM is one of the most critical initiatives for integrating environmental factors into supply chain management. It aids in the reduction of carbon emissions and the improvement of organizational environmental performance. As a result, most construction organizations have included GSCM in their strategic planning. Barriers and problems are predicted to exist in the execution or operational process of GSCM in construction or building firms, as in the case of radical innovations. As a result, organizations must identify any potential hurdles to GSCM implementation and develop strategies for achieving success. This study undertakes a complete literature evaluation on GSCM procedures to address the difficulties of establishing a conceptual framework. According to the data, the biggest weaknesses or disorders to applying GSCM canister are divided into five categories: expertise, information and facts, funds, contract out, administration, and supervision. Moreover, uppermost managing commitment, variated in present strategies and know-hows, expanded consciousness of harmless to the ecosystem matters, preparing and instruction, and executing effective materials and waste administration frameworks are systems to improve GSCM performances in building organizations. To successfully implement GSCM in construction firms, the provided framework can be used to recognize the crucial mechanisms of GSCM and self-assessment of obstacles and policies.

Enhancing third-party logistics providers partnerships: An approach through the D.L.A.R.C.S supply chain paradigm

The effective selection of third-party logistics providers (3PLs) is crucial for achieving optimal supply chain performance. This study addresses the challenge of 3PL selection by adopting the comprehensive Digital, Lean, Agile, Resilient, Circular, and Sustainable (D.L.A.R.C.S) supply chain paradigm, which encompasses dimensions vital for managing modern supply chains, including digital, lean, agile, resilient, circular, and sustainable aspects. Recognising the interconnectedness of these dimensions, this paradigm emphasises their collective importance in enhancing supply chain operations. Utilising fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) and BWM (Best Worst Method) techniques, the study evaluates and ranks 3PLs based on their performance within these dimensions. The analysis reveals pivotal criteria such as purchasing price, transportation cost, removal of wastes, service costs, reduction in costs, and crisis and risk management as paramount considerations in the 3PL selection process. These criteria not only provide specific insights but also serve as a foundation for a data-driven approach to decision-making. This research, beyond offering strategic alignment insights for outsourcing, contributes substantively to the broader discourse on supply chain management. The methodology employed in this study integrates diverse dimensions, offering a robust framework for 3PL selection, thereby enhancing operational efficiency and sustainability across industries. The findings offer valuable insights for tyre manufacturers seeking to optimise their logistics operations within the D.L.A.R.C.S. framework, contributing to the advancement of supply chain management in the tyre industry and beyond.