Traditional Supply Chain Management Research Articles

LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS

The integration of artificial intelligence (AI) technologies into supply chain management has emerged as a crucial avenue for enhancing efficiency, agility, and responsiveness in modern business operations. This comprehensive review synthesizes current practices and future potentials of leveraging AI for supply chain optimization. Beginning with an overview of traditional supply chain management challenges, the review elucidates how AI solutions address these complexities by enabling predictive analytics, real-time visibility, and intelligent decision-making. The review delves into the diverse applications of AI across different stages of the supply chain, including demand forecasting, inventory management, logistics optimization, and supplier relationship management. Examples of AI-driven technologies such as machine learning, natural language processing, and robotic process automation are analyzed for their role in revolutionizing supply chain operations. Furthermore, the review highlights the transformative impact of AI on supply chain resilience, emphasizing its ability to mitigate disruptions, adapt to dynamic market conditions, and optimize resource allocation. The review also addresses critical considerations such as data privacy, ethical implications, and organizational readiness for AI adoption within supply chain contexts. Lastly, the review discusses future research directions and potential advancements in AI-enabled supply chain management, envisioning intelligent autonomous supply chains characterized by self-learning systems, collaborative ecosystems, and enhanced sustainability practices. In conclusion, this review underscores the pivotal role of AI in driving continuous innovation and competitive advantage within supply chain networks, while also emphasizing the importance of strategic planning and responsible implementation to harness its full potential.
 Keywords: AI, Supply Chain, Optimization, Practices, Review.

Reviewing the use of big data in supply chain optimization in the USA

This paper provides a succinct overview of the review conducted on the utilization of Big Data in supply chain optimization within the United States. The advent of Big Data analytics has revolutionized traditional supply chain management, offering unprecedented opportunities for enhancing efficiency, reducing costs, and improving overall operational performance. This comprehensive review examines the current state of Big Data applications in supply chain optimization, focusing specifically on the context of the United States. The review begins by outlining the fundamental role of Big Data in transforming supply chain processes. It delves into various aspects, including data collection, processing, and analysis, emphasizing their impact on decision-making and strategic planning. Notably, the study highlights real-world examples of successful Big Data implementations within the U.S. supply chain landscape, showcasing how companies have leveraged data-driven insights to streamline operations and gain a competitive edge. Furthermore, the paper explores the challenges associated with the adoption of Big Data in supply chain management. It addresses concerns related to data security, privacy, and the need for advanced technological infrastructure. Additionally, the review considers the organizational and cultural shifts required for successful integration, emphasizing the importance of a holistic approach to implementation. The paper concludes by pointing towards future trends and potential developments in the use of Big Data for supply chain optimization in the U.S. It underscores the evolving nature of technology and its continued impact on reshaping supply chain strategies. The insights derived from this review contribute to a deeper understanding of the current landscape, offering valuable implications for practitioners, researchers, and policymakers engaged in optimizing supply chain processes through the harnessing of Big Data analytics.

Influence of supply chain management on the sustainable construction industry in Algeria

The construction industry, a pivotal business sector facilitating physical infrastructure and equipment provision, holds a significant indirect influence on diverse industries. This study investigates the role of supply chain management in enhancing sustainable construction practices within the Algerian construction industry. The research delves into the relationship between traditional supply chain management and sustainable construction, employing a quantitative approach. Data collection involved a survey comprising 61 items, utilizing a five-point Likert scale, gathered through an online survey method targeting managers, supervisors, executives, and suppliers in the Algerian construction industry. With 237 participants from construction companies in Algeria, the study utilized Smart PLS for data analysis, confirming a positive relationship between traditional supply chain management and sustainable construction through partial least squares (PLS) path analysis. The findings provide valuable insights for future stakeholders, guiding employers, designers, manufacturers, contractors, and suppliers to enhance supply chain management practices for sustainable construction in Algeria. Consequently, this study offers significant results with practical and theoretical implications, contributing to the integration of sustainable supply chain management in Algerian construction. In summary, the research addresses the relationship challenges between traditional supply chain management and sustainable construction practices in Algeria.

Optimization of logistics supply chain management model on consumer purchase anxiety disorder

BackgroundAnxiety refers to the intense, excessive, and persistent anxiety and fear in daily life, which will peak in a few minutes. Especially in online shopping, patients with anxiety will aggravate their anxiety because of the slow delivery of the traditional logistics supply chain management model. To reduce consumers’ anxiety, the network distribution system of logistics supply chain management mode is optimized.Subjects and MethodsThis study divided 200 patients with anxiety disorder in a city into a control group and an experimental group. In the experimental group, 100 patients used the optimized logistics supply chain management mode for online shopping. In contrast, in the control group, 100 patients used the traditional logistics supply chain management mode for online shopping. The study also used the self-rating anxiety scale (SAS) for psychological measurement and compared the SAS scores of the two groups of consumers for two months.ResultsThe data were analyzed by SPSS23.0. The SAS score of the experimental group was (1.63±0.23), and that of the control group was (1.81±0.59). The SAS scores of patients in the experimental group were better than those in the control group, and there were apparent differences between the two groups (P < 0.05).ConclusionsResearch on the choice of logistics supply chain management mode for online shopping optimizing its network distribution system can effectively shorten the online shopping distribution time and reduce consumers’ purchase anxiety.

Can blockchain technologies enhance environmental sustainable development goals performance in manufacturing firms? Potential mediation of green supply chain management practices

AbstractThe nexus between manufacturing firms and the green environment is unavoidable. It is merely due to the huge waste generation and greenhouse gas emissions resulting from large‐scale production and complex supply chain management processes involved in manufacturing firms. Continuation of the traditional business practices during Industry 4.0 made it impossible for the manufacturing firm to commit to green environmental practices and comply with environmental SDGs. At odd, it requires novel business strategies to ensure compliance of manufacturing firms with environmental sustainable development goals (SDGs). Blockchain is an ideal technology for delivering green environmental‐related information because it offers real‐time, shareable, and entirely transparent data kept on an immutable ledger that is accessible to members of a network. These green environmental‐related information received in real‐time through blockchain technology help in the transformation of the traditional supply chain management practices into a more green supply chain management practice. This green transformation ensures business compliance with environmental SDGs and that compliance is shared with multiple stakeholders through blockchain technology in real‐time, thus approving a positive mediating role of green supply chain management practices between blockchain technology and environmental SDGs performance. The proposed strategic framework through various propositions development will mainly offer policy insights toward (a) identifying novel antecedents of blockchain technology, (b) offering insights toward upgrading the traditional supply chain management framework into a green supply chain management framework, and (c) illuminating novel mediating role of green supply chain management practices between blockchain technology and environmental SDGs performance.

Sustainable Supply Chain Management Practices in the Dairy Industry: A Comparative Study of Leading Dairy Firms and Future Research Directives

The Indian dairy industry is one of the fastest growing industries in the world which employs millions of farmers directly and also participates more than five per cent in the economy as well. As the industry continues to expand there is a growing need to adopt sustainable practices in the supply chain to minimize negative impact on the environment and society and ensure viability. The present research aims at examining the supply chain management practices of the two leading dairy firms -Amul and Danone. The study relies primarily on secondary sources like peer-reviewed journals, authentic websites and reports. A case study-based approach has predominantly been used to compare two leading firms in the dairy industry with respect to sustainable practices across the supply chain. Key aspects such as the scale of dairy production, technology adoption, pricing, traditional supply chain management, artificial intelligence in sustainable supply chains and logistics management in select dairy firms have been critically reviewed for comparison purposes. The study identified the various problems and challenges being faced by the Indian dairy industry. The study found that Amul and Danone both have focused on sustainable and green practices. However, Danone’s ability to incorporate and enable technology has helped in improving efficiency across the supply chain making the chain sustainable. On the other hand, Amul lacked the adaptation of emerging technologies across its supply chain. The study suggested the exploration of artificial intelligence that might help in achieving a sustainable supply chain in Indian dairy firms.

Supply Chain Management Optimization Based on Bigdata Analysis

Contemporarily, in the context of big data, enterprises need to continuously optimize and innovate the supply chain, change the traditional supply chain management process pattern as well as optimization the whole supply processes. These actions are able to strengthen the actual effect level of supply chain process operation and achieve more benefits for the enterprise. Under the background of big data, more information management technologies are widely used, and supply chain management needs to clarify the deficiencies in its own operation, and reengineer and adjust the deficiencies. This paper will systematically discusses the implementation of the state-of-art bigdata analysis techniques in SCM. According to the analysis and evaluations of the measures, the usage of advanced big data technology will help increase the cultivation and establishment of management talent resources, so as to optimize the supply chain management process. Overall, these results shed light on guiding further exploration of supply chain management optimization.

From Hype to Reality: Unveiling the Promises, Challenges and Opportunities of Blockchain in Supply Chain Systems

Blockchain is a groundbreaking technology widely adopted in industrial applications for improving supply chain management (SCM). The SCM and logistics communities have paid close attention to the development of blockchain technology. The primary purpose of employing a blockchain for SCM is to lower production costs while enhancing the system’s security. In recent years, blockchain-related SCM research has drawn much interest, and it is fair to state that this technology is now the most promising option for delivering reliable services/goods in supply chain networks. This study uses rigorous methods to review the technical implementation aspects of SCM systems driven by Blockchain. To ensure the security of industrial applications, we primarily concentrated on developing SCM solutions with blockchain capabilities. In this study, the unique qualities of blockchain technology have been exploited to analyze the main effects of leveraging it in the SCM. Several security metrics are utilized to validate and compare the blockchain methodologies’ effectiveness in SCM. The blockchain may alter the supply chain to make it more transparent and efficient by creating a useful tool for strategic planning and enhancing connections among the customers, suppliers, and accelerators. Moreover, the performance of traditional and blockchain-enabled SCM systems is compared in this study based on the parameters of efficiency, execution time, security level, and latency.

Drivers for Internet of Things (IoT) adoption in supply chains: Implications for sustainability in the post-pandemic era

As the post-COVID-19 pandemic era begins, the supply chain operating environment has transformed and faced disruptions. The Internet of Things (IoT) has emerged as one of the expedient technologies in the information technology domain, which solves the issues of traditional supply chain management (SCM) by providing resiliency, flexibility, and traceability. Despite the perceived advantages of IoT, it remains unknown what drivers are essential to adopt IoT in SCM. To achieve this aim, an integrated approach combining rough set theory and decision-making trial and evaluation laboratory (DEMATEL), that is rough strength relation analysis (RSRA) method, has been used to identify and investigate drivers of IoT adoption in SCM where drivers were analyzed according to their comparative importance based on expert opinions from industrial and academic backgrounds. A total of 14 drivers have been identified from the extensive literature review on previous IoT and SCM associated works, which were further analyzed to determine the most important drivers. The results show that “Efficient logistics systems”, “Business knowledge acumen”, and “Information safety assurance” are among the three most predominant driving factors. The findings may help practitioners implement IoT in supply chains to deal with disruptions, risks and vulnerabilities in the post-pandemic era.

Accelerating the African continental free trade area through optimization of digital supply chains

AbstractThe integration of e‐commerce into supply chain management (SCM) and logistics operations has greatly impacted the way these processes are executed. The Fourth Industrial Revolution (4IR) has disrupted traditional SCM and logistics business processes, making digitalization a crucial element for differentiation and competitiveness. The objective of this article was to investigate how the adoption of appropriate digital technologies could accelerate intra‐African trade in goods and services through the AfCFTA Agreement. The author employed a content analysis of the primary source documents, specifically the Protocol on Trade in Goods, available on the AfCFTA's website. The nine Annexes of the Protocol on Trade in Goods were evaluated against a digital supply chain (DSC) model adopted in this article. The results of the analysis showed that the supply chain and logistics processes of the AfCFTA's Protocol on Trade in Goods could be effectively identified and mapped to potential digital technologies through the adopted DSC framework. The practical implications of this study suggest that the AfCFTA could adopt a DSC framework as a guide in concluding negotiations on the Protocol on Digital Trade to harness the benefits of digital technologies. As the main contribution, this article provides a DSC framework that could be utilized to accelerate intra‐African trade through optimization of supply chain and logistics processes of the AfCFTA.

The Evolution from Traditional to Digital Supply Chain Management

The world of supply chain management (SCM) has been undergoing a seismic shift, transitioning from the traditional model to a futuristic digital avatar. The digital revolution, characterized by the Internet of Things (IoT), blockchain technology, and digital financial flows, is transforming how goods and services are manufactured, transported, and delivered, influencing various sectors, including the agri-food supply chain. Traditional SCM used to be linear and hierarchical, where each participant operated in silos with limited communication. The supply chain starts from raw material suppliers, followed by manufacturers, distributors, and retailers before reaching consumers. Such a system was characterized by inefficiencies, including information asymmetry, increased lead times, and lack of visibility.

Supply Chain Resources and Economic Security Based on Artificial Intelligence and Blockchain Multi-Channel Technology

With the rapid growth of social economy and the improvement of people's living standards, the logistics industry not only shows a trend of rapid development, but also faces various business risks. Therefore, supply chain management becomes particularly important. Strengthening supply chain management has become a general trend. The traditional cost-oriented supply chain management model has been unable to meet the requirements of modern enterprise development. Given that the changes in customer demand, production, and sales have not been considered, enterprise resources are easily wasted. How to build a new supply chain model driven by value and customer demand has become one of the problems that large enterprises must solve. The combination of artificial intelligence (AI) and blockchain technology (BT) can realize information sharing, risk sharing, data interaction, and other functions. Through smart contracts, the division of responsibilities among all roles in the supply chain is controlled, which makes the supply chain safer and more efficient. In this paper, the authors designed a new supply chain financial system model that can effectively reduce financial risks, improved the efficiency of capital use, and enhanced the competitiveness of enterprises. The authors compared the traditional supply chain management mode with the management mode under the combination of AI and BT. The supply chain resource and economic security management based on AI and blockchain multichannel technology was more efficient, the system security index was higher, and the internal employee satisfaction of the enterprise also increased by 5.98%. The simulation application system for the internet of things and edge computing has the characteristics of high real-time and scalability. By analyzing the differences between the internet of things and edge computing technologies in terms of device perception, communication mode, data processing, and processing performance, product manufacturing efficiency can be improved to a certain extent.

Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

RFID supply chain data deconstruction method based on artificial intelligence technology

Abstract Radio frequency identification (RFID) is a broad rapidly evolving skill in the past few years. It is characterized by non-contact identification, fast read and write speed, small label size, large data storage capacity, and other technical advantages. RFID technology for goods movement has completely changed the traditional supply chain management, greatly improved the operational efficiency of enterprises, and has become an important method for the development of supply chain logistics. This work mainly studies and analyzes the RFID supply chain, introduces the development and application of RFID supply chain sector technology, and discusses the operation of the supply chain in detail. Then, according to the existing RFID supply chain, a RFID supply chain artificial intelligence (AI) based approach to technology is proposed, and the data analysis of RFID supply chain is introduced in detail. In this work, through the research experiment of AI technology RFID supply chain data analysis, the experimental data show that there are several time-consuming links in the supply chain system. The time consumed in the AI RFID system is 9.9, 3.4, 3.5, and 29.9 min, respectively, while each link in the original system takes 13.4, 4.9, 4.9, and 34.9 min. It can be seen from the above data that the amount of time in each system link of the AI RFID supply chain system is less than that of the original supply chain system, which shortens the entire product passing cycle and greatly improves work efficiency.

Moving from the Traditional Practices to the Green Era

As environmental issues have become of prime importance, green supply chain management (GSCM) has become a proactive approach for industries to improve their environmental performance and develop a competitive advantage. GSCM has been widely implemented by different industrial sectors to minimize the environmental impact of their supply chain activities, such as waste generation and pollution. Nowadays, industries are seeking to convert their traditional supply chain management (TSCM) to (GSCM) due to concerns about environmental sustainability and to improve their overall performance, develop a competitive advantage, and gain a brand image. This paper started with an interest in understanding the factors that lead companies to convert their traditional practices to more environmentally friendly activities. Many theories in the literature were employed to explore the topic of GSCM; three theories have been observed to be the vital theoretical pillars within the GSCM literature namely, institutional theory, stakeholder theory, and resource-based view theory. These theories will be discussed in this paper. The aim of reviewing these theories is to understand the transition process from TSCM into GSCM. Additionally, the transition from TSCM to GSCM is associated with tensions that may arise as companies still prioritize the economic goals over the environmental dimensions. This paper will investigate the potential tensions and conflicts GSCM barriers may cause between various stakeholders. Therefore, the goal of this paper is to explore what the pressures are for companies to implement green supply chain management, what drives or prevents companies from adopting GSCM. To accomplish this task, literature is reviewed, focusing on theories, tensions, drivers, and barriers that are related to the field of GSCM.

A Comprehensive Review of the Integration of Blockchain Technology in Supply Chain Management

This paper reviews the concept of Supply Chain Management (SCM) and provides an introduction to the use of blockchain technology in SCM. SCM involves the coordination and control of operations related to the production and delivery of goods and services to clients. The traditional SCM model has been facing challenges, including a lack of transparency, inefficiency, and increased costs. Blockchain technology offers a promising solution to these challenges by providing a secure, decentralized, and transparent platform for the management of supply chain operations. This paper highlights the key features of blockchain technology and how it can be applied in the SCM business model. The use of blockchain can improve the efficiency of supply chain processes, reduce costs, increase transparency, and enhance trust among supply chain partners. The paper also discusses the challenges and limitations of implementing blockchain in SCM and provides recommendations for future research.

Green supply chain management, risk-taking, and corporate value—Dual regulation effect based on technological innovation capability and supply chain concentration

With the promotion of carbon-peak and carbon-neutral strategies and the increase in green awareness, green development is gradually gaining attention, and the green supply chain management (GSCM) derived from traditional supply chain management is gradually becoming a path to promote green development. At the same time, enterprise, as an important source of pollution, how to consider social responsibility, such as environmental protection, in the process of ensuring efficiency improvement has become an important issue. To study the impact of green supply chain management on enterprise value and its path of action, this paper examines the impact of green supply chain management on enterprise value, explores the moderating effect of the risk-taking level, and further analyzes the dual moderating effect played by technological innovation capability and supply chain concentration. Based on the micro data of 131 Chinese listed enterprises from 2014 to 2021, a panel-regression model is used to illustrate how green supply chain management affects enterprise value, and the results show that: 1) green supply chain management can promote enterprise value; 2) the level of risk-taking strengthens the promoting effect of green supply chain management on enterprise value enhancement; and 3) the technological innovation capability negatively regulates the moderating effect of risk-taking, while the supply chain concentration positively regulates the moderating effect of risk-taking. The research results of this paper enrich the path of the effect of implementing of green supply chain management on enterprise value enhancement, i.e., the process of green supply chain management to enhance enterprise value is regulated by the level of enterprise risk-taking, while technological innovation capability and supply chain concentration will also regulate the level of enterprise risk-taking and thus promote enterprise value enhancement. This research not only extends the research perspective and enriches the existing research, but also provides a theoretical basis for enterprises to implement green supply chain management to promote value enhancement and improve the level of green supply chain management implementation and the green development of enterprises.

Blok Zincir Uygulamaları ile Kapalı Döngü Tedarik Zincirinde Bilgi Yönetiminin Değeri

Purpose: Rapidly developing information technology increases expectations for obtaining much more efficient structures by providing accurate, sufficient and secure information sharing in supply chains as well as in many other fields. Traceability is a critical element in supply chain management, especially in security-sensitive sectors such as food, medicine, etc. Blockchain is a decentralized record platform that provides traceability, transparency and security, and it shows promise in alleviating traditional supply chain management problems and making a positive contribution. This article aims to improve the relevant literature by revealing the level of impact of blockchain technology on supply chain management.Methodology: First of all, a traditional closed-loop supply chain (CLSC) network was designed and modeled. Then, the main model was developed by creating four more scenarios for different applications of the blockchain technology to the existing model and the application results were analyzed.Findings: This paper demonstrated the implementation of blockchain technology in forward and reverse flows activities coordination for effective and efficient supply chain management, and the resulting gains by developing appropriate models through explanatory scenarios. The implications showed that blockchain technology could significantly reduce supply chain costs.Originality: While blockchain technology is gaining attention, there are very few studies focused on its integration into the supply chain. Apart from the applications in the field of finance, the most important contribution and originality of the study is the application of the blockchain to CLSC from different aspects as partial, full, only forward flow and only reverse flow.

Green Supply Chain Practices: Toward A Sustainable Industry Development

As environmental consciousness is growing, organizations are required to implement environmental-friendly practices, and to develop sustainable strategies not just for the health of the environment but also for sustaining the industry for the future. Today consumers value organizations that go green and are willing to pay a price premium for sustainable goods. Then, it is an incumbent need for the industry to integrate sustain ability concepts into its traditional supply chain management. The industry is a driving force behind sustainable development, where industry 4.0 is set to be a critical enabler. Nevertheless, to foster sustainable development of the industry, there is a need for applying uniform standards in environmental management to reduce the consumption of renewable resources and develop productive ways of reusing and recycling the used/waste resources. This paper, theoretical by nature, explores the impact of Green Supply Chain Practices (GSCP) on accelerating industry-related targets of Sustainable Development Goal (SDG) 9 on building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation. Based on the literature review, conceptual interlinkages between the targets of SDG 9 and those SDGs that address issues of social, economic, and environmental goals, are studied in the context of GSCP. This work provides an understanding of the impact of green practices on the achievement of the SDGs.

Construction of Supply Chain Security Management Model for Information and Communication Technology Based on the Internet of Things and Cloud Computing

At the level of enterprise supply chain security management, with the rise of network technology big data technology methods such as the Internet of Things (IoT) and cloud computing, it has had a multi-level impact on its supply chain management mode, including operation mode, operation mode, and security management mode. The traditional supply chain management model is based on old-fashioned communication methods and manual intervention for judgment and processing. Information and communication technology has advantages such as immediacy and strong correlation. Based on this, this article applies the data interconnection technology of the Internet of Things to the construction of supply chain management models and combines it with efficient algorithms of cloud computing. This article also explores the construction of supply chain security management models from the perspectives of participants, activity modes, module operations, and conducts data comparisons based on them. The experimental results show that in the running tests of the model, its average accuracy is about 89.60%, and the prediction accuracy of benefits is as high as 98.48%. In stability testing, it is also evident that the average stability of the model after multiple iterations is about 96.02%. Research has shown that the Internet of Things and cloud computing technology have great application potential in the construction of supply chain security management, which can provide enterprises with more effective supply chain security management tools.