Complex Supply Chain Research Articles

A multi-stakeholder engagement framework for material-building-city synergy through circular transformation

Scholars, industrial stakeholders, and governmental institutions are developing the circular economy paradigm. However, the emergence of multiple perspectives has challenged its implementation. As the industry that is the biggest contributor to the negative impacts on the environment, the construction industry stakeholders are paving the way for more sustainable as well as circular and regenerative construction by considering all actors in the system. Yet, the construction industry has a complex supply chain that requires clear strategies and stakeholder engagement across materials, buildings, and cities for efficient flows in the supply chain. Nonetheless, there is a need for improvement in the engagement of construction stakeholders for circular transformation. Therefore, this study aims to develop a multi-stakeholder engagement framework through circular transformation to guide the decision-makers for circular city governance. It has identified critical success factors by considering the construction stakeholders. The framework includes strategies at the micro (material), meso (building), and macro (city) scales to strengthen the material-building-city synergy. It's a significant step toward advancing circular city governance by bridging the gap between theoretical understanding and practical implementation and establishing a robust engagement for material-building-city synergy. The study employs a systematic literature review to extract strategies and natural language processing to analyze the strategies by topic modeling and defines critical success factors for multi-stakeholder engagement at multiscale. The outcome introduces the REVERT framework, bridging resource, envisagement, validation, entity, regulation, and technology, to facilitate a seamless transition by material-building-city synergy advancing circular city governance.

Identification of Supply Chain Disruption Risks and Strategies in the Electric Vehicle Industry Based on Fuzzy Analytic Hierarchy Process (FAHP)

In recent years, the electric vehicle industry has witnessed unprecedented development opportunities. However, with rapid technological iterations and fluctuating market demands, the vulnerability and complexity of the electric vehicle supply chain have significantly increased the potential risk of supply chain disruptions. Against this backdrop, this study adopts the Fuzzy Analytic Hierarchy Process (FAHP) to systematically analyze the risks of supply chain disruptions in the electric vehicle industry. By constructing a judgment matrix through industry data surveys and expert scoring, and conducting consistency checks, the weights of various risk factors are determined. The study finds that technological quality risk, demand forecast deviation, and logistics disruption are the primary factors affecting the stability of the electric vehicle supply chain. Additionally, although the probability is relatively low, the potential destructiveness of exogenous risks is equally undeniable. Accordingly, the study will propose targeted management strategies to enhance the resilience of the new energy vehicle supply chain at both the enterprise and industry levels in response to these risks.

Visualizing Walmart's Supply Chain Management: A Case Study on Detailed Warehouse Management Practices

Supply chain management (SCM) plays a critical role in the success of modern businesses. Visualization techniques have become increasingly important in improving these processes. These methods have become increasingly significant in recent years, offering new ways to understand and optimize complex supply chain processes. This study focuses on how Walmart uses visualization in its supply chain management to boost efficiency and decision-making. This paper examines the integration of technologies like real-time tracking and data analysis into Walmart's practices, discussing both the advantages and challenges they bring. Walmart has embraced visualization technologies to streamline its SCM processes and make more informed decisions. Furthermore, the paper explores how visualization can help with inventory management, demand forecasting, and logistics optimization in Walmart's supply chain. Combined with relevant literature and case studies, it sheds light on how visualization enhances supply chain operations, offering insights for academics and industry professionals alike, that give good suggestions to the market.

Impact of Enterprise Supply Chain Digitalization on Cost of Debt: A Four-Flows Perspective Analysis Using Explainable Machine Learning Methodology

Rising costs, complex supply chain management, and stringent regulations have created significant financial burdens on business sustainability, calling for new and rapid strategies to help enterprises transform. Supply chain digitalization (SCD) has emerged as a promising approach in the context of digitalization and globalization, with the potential to reduce an enterprise’s debt costs. Developing a strategic framework for SCD that effectively reduces the cost of debt (CoD) has become a key academic challenge, critical for ensuring business sustainability. To this end, under the perspective of four flows, SCD is deconstructed into four distinct features: logistics flow digitalization (LFD), product flow digitalization (PFD), information flow digitalization (IFD), and capital flow digitalization (CFD). To precisely measure the four SCD features and the dependent variable, COD, publicly available data from Chinese listed manufacturing enterprises such as annual report texts and financial statement data are collected, and various data mining technologies are also used to conduct data measurement and data processing. To comprehensively investigate the impact pattern of SCD on CoD, we employed the explainable machine learning methodology for data analysis. This methodology involved in-depth data discussions, cross-validation utilizing a series of machine learning models, and the utilization of Shapley additive explanations (SHAP) to explain the results generated by the models. To conduct sensitivity analysis, permutation feature importance (PFI) and partial dependence plots (PDPs) were also incorporated as supplementary explanatory methods, providing additional insights into the model’s explainability. Through the aforementioned research processes, the following findings are obtained: SCD can play a role in reducing CoD, but the effects of different SCD features are not exactly the same. Among the four SCD features, LFD, PFD, and IFD have the potential to significantly reduce CoD, with PFD having the most substantial impact, followed by LFD and IFD. In contrast, CFD has a relatively weak impact, and its role is challenging to discern. These findings provide significant guidance for enterprises in furthering their digitalization and supply chain development, helping them optimize SCD strategies more accurately to reduce CoD.

Bridging Supply Chain Complexity and Customization: An Exploration of SAP Segmentation in S/4HANA

Bridging Supply Chain Complexity and Customization: An Exploration of SAP Segmentation in S/4HANA

Evolutionary game theoretical approach for reducing carbon emissions in a complex supply chain organization

PurposeOur research explores the intricate behavior of low-carbon supply chain organizations in an ever-evolving landscape, emphasizing the profound implications of government-mandated low-carbon policies and the growing low-carbon market. Central to our exploration is applying a combined game theory model, merging Evolutionary Game Theory (EGT) with the Shapley Value Cooperative Game Theory Approach (SVCGTA).Design/methodology/approachWe establish a two-tier supply chain featuring retailers and manufacturers within this novel framework. We leverage an integrated approach, combining strategic Evolutionary Game Theory and Cooperative Game Theory, to conduct an in-depth analysis of four distinct low-carbon strategy combinations for retailers and manufacturers.FindingsThe implications of our findings transcend theoretical boundaries and resonate with a trinity of economic, environmental and societal interests. Our research goes beyond theoretical constructs to consider real-world impacts, including the influence of changes in government low-carbon policies, the dynamics of consumer sensitivities and the strategic calibration of retailer carbon financing incentives and subsidies on the identified ESS. Notably, our work highlights that governments can effectively incentivize organizations to reduce carbon emissions by adopting a more flexible approach, such as regulating carbon prices, rather than imposing rigid carbon caps.Originality/valueOur comprehensive analysis reveals the emergence of an Evolutionary Stability Strategy (ESS) that evolves in sync with the phases of low-carbon technology development. During the initial stages, our research suggests that manufacturers or retailers adopt low-carbon behavior as the optimal approach.

EXAMINING THE INTEGRATION OF INDUSTRY 4.0 TECHNOLOGIES IN MANUFACTURING

The integration of Industry 4.0 technologies is transforming manufacturing, enhancing efficiency, flexibility, and sustainability. This research paper explores the application of key technologies such as artificial intelligence (AI), the Internet of Things (IoT), and big data analytics in the sector. By analyzing a comprehensive dataset that includes supply chain metrics from major corporations like Apple, Amazon, and Google, the study examines the impact of Industry 4.0 practices on critical supply chain performance indicators, including inventory turnover ratio, lead time, and customer satisfaction. Industry 4.0 technologies are reshaping supply chain management (SCM) strategies such as lean manufacturing, agile SCM, and cross-docking. AI and block chain are shown to significantly enhance supply chain agility and resilience. Companies that integrate these technologies tend to have more streamlined operations, shorter lead times, and higher customer satisfaction rates. Environmental sustainability practices are becoming increasingly important as businesses strive for more eco-friendly manufacturing processes. The study finds that organizations employing agile supply chain practices and leveraging advanced technologies often demonstrate superior operational efficiency and financial performance. The integration of these technologies also introduces challenges, such as increased supply chain complexity and risk management concerns. This paper provides a comprehensive overview of how Industry 4.0 technologies are revolutionizing manufacturing and supply chain dynamics. It highlights the future trajectory of smart manufacturing and emphasizes the need for continued innovation to address emerging challenges. The research offers insights into how companies can adapt their supply chain strategies to thrive in the evolving landscape of digital transformation and automation.

Fishy Forensics: FT-NIR and Machine Learning based authentication of Mediterranean Anchovies (Engraulis encrasicolus)

Seafood authentication and traceability is a challenging issue owing to its complex supply chain and fishing in international waters. NIR spectroscopy has been successfully used to authenticate food of animal and plant origin. In this study, FT-NIR was used to discriminate between Mediterranean anchovies (Engraulis encrasicolus) fished from Adriatic, Balearic, and Tyrrhenian Sea. The spectra were prepared using the standard normal variate (SNV) and the Savitzky-Golay 1st derivative, 2nd order (SG), as well as both together. The model was built, after outlier removal, with linear-support vector machine (L-SVM), polynomial-SVM (P-SVM), k-nearest neighbor (k-NN) and Random Forest (RF). Spectral preprocessing improved model classification accuracy for all algorithms. The data could not be put into groups by linear algorithms like L-SVM and k-NN because the NIR spectra were not linear and had many columns. Non-linear algorithms, P-SVM and RF when coupled with SG+SNV, successfully produced models with maximum robustness. P-SVM and RF models had 100% accuracy in training set and 95.7% and 95.5% accuracy in testing set, respectively and 95.2 and 95.1 accuracy in cross-validation set.

Agile Supply Chain Management In FashionIndustry

The fashion industry is one of the most globalized sectors, featuring a complex and widespread supply chain. Often, clothing is designed in one country, produced in another, and then distributed and sold across multiple international markets. This global scope and complexity necessitate an agile approach to supply chain management. Agile supply chains are engineered to be flexible, responsive, and adaptable, enabling companies to swiftly respond to shifts in consumer demands and market conditions. By adopting agile principles, fashion companies can more effectively navigate the intricacies of global operations, ensuring that products reach the appropriate markets at the right time, thereby sustaining competitiveness and meeting consumer expectations in a fast-paced industry

Temperature Excursion Management: A Tier-Based Approach for Commercial Oral Solid Dosage Forms

Temperature excursions during product storage, transportation, and handling can deteriorate product quality. Following a temperature excursion event, the impact of the event on the product quality should be evaluated to determine if the product can be used or if it needs to be discarded. Pharmaceutical companies are required to have defined procedures for managing temperature excursions and performing impact assessment after an excursion occurs. In an increasingly complex supply chain, it is vital to develop processes that can expedite the review of these events. A tier-based approach is presented for analyzing the impact of temperature excursion on commercial small molecule drug products intended to be stored at room temperature. Utilization of each of the three tiers is based on whether the excursion temperature and/or excursion duration are within a predetermined, product-specific, allowable range. The stress study temperature defines the allowable temperature range, while the allowable duration is determined using a mathematical approach outlined in this article. Tier 1, specific to the product, allows products to be dispositioned for use without further assessment when temperature excursion events fall within both the product-specific allowable excursion temperature and duration ranges. Tier 2 applies when the excursion temperature is within the allowable range, but the duration exceeds it. Lot-specific release data is used for impact assessment in this tier. Finally, Tier 3 utilizes Arrhenius extrapolation to predict the final degradation and perform the impact assessment when the excursion temperature surpasses the allowable temperature range.Graphical

Application Of FMEA Method In Halal Risk Determination On Halal Poultry Slaughtering Operations

The importance of halal slaughtered chicken has become crucial in the era of globalization and complex supply chains. The rising awareness among Muslim communities regarding the integrity of slaughtered chicken products has led to a focus on adhering to halal compliance standards and Islamic law. This study aims to qualitatively analyze the halal risk points in chicken slaughtering operations, by using the Failure Mode and Effect Analysis (FMEA) method, in order to identify potential halal risks and ensure the integrity of halal chicken products. This qualitative study uses a analysis approach by examining secondary sources including journals, articles, guidelines and standards related to halal slaughtering process. In this study, seven Halal Risk Points (HRP) have been identified in the entire halal slaughtering process of broilers. Based on the results of the risk assessment through the FMEA method, each determined HRP will be assessed based on the severity, occurrence and detection rating scale. The final result of this study found that only six HRPs have a Risk Priority Number (RPN) value that exceeds 100. Therefore, corrective action recommendations are proposed to prevent any halal non-compliance from occurring on the process involved. Overall, the FMEA framework in this study is a new approach in guaranteeing the integrity of chicken slaughter products and is able to have a positive impact on the halal chicken slaughter industry players and also the implementers of the halal management system.

Advancing food safety standards through technology integration and policy development

Food safety is a critical global concern, directly impacting public health, economic stability, and international trade. With the complexity of modern food supply chains and the rising incidence of foodborne illnesses, traditional food safety measures are often insufficient to address the growing risks. This review explores how integrating advanced technologies and developing robust policies can significantly enhance food safety standards. Technological innovations, including the Internet of Things (IoT), blockchain, artificial intelligence (AI), and automation, offer promising solutions for real-time monitoring, traceability, and predictive analytics in food production and distribution. IoT and sensors enable constant monitoring of environmental conditions like temperature and humidity, while blockchain ensures transparency and traceability across supply chains. AI and machine learning are transforming food safety by predicting contamination risks and optimizing inspection processes, while robotics and automation reduce human error in food processing plants. Alongside technological advancements, policy development plays a crucial role in reinforcing food safety standards. Global harmonization of food safety regulations, stronger enforcement mechanisms, and public-private partnerships are essential for ensuring widespread compliance. Incorporating technology into regulatory frameworks is key to addressing new challenges and maintaining food safety across borders. Governments must also prioritize consumer education and awareness through policies that leverage technology platforms to promote food safety knowledge. Case studies demonstrate the successful application of these technologies in sectors like dairy and meat processing, showcasing the potential for broader industry adoption. However, challenges such as high implementation costs, regulatory lag, and data security concerns remain. This review argues that a synergistic approach combining technological integration with forward-thinking policy development is essential for advancing global food safety standards and safeguarding public health in the future.

Optimizing supply chain networks using mixed integer linear programming (MILP)

Mixed Integer Linear Programming (MILP) has emerged as a powerful tool for optimizing complex supply chain networks. This paper explores the theoretical foundations of MILP, including the integration of integer variables and advanced solution techniques such as branch-and-bound and branch-and-cut algorithms. Through detailed modeling of production planning, network design, and transportation logistics, MILP enables companies to achieve significant cost reductions and operational efficiencies. We present case studies from retail, manufacturing, and pharmaceutical sectors to illustrate the practical applications of MILP. These examples demonstrate how MILP optimization can lead to reductions in production and inventory costs, improved customer satisfaction, and enhanced service levels. The findings underscore the value of MILP in addressing the multifaceted challenges of modern supply chain management.

Building Resilient Supply Chains with Intelligent Automation

Building Resilient Supply Chains with Intelligent Automation represents a transformative approach to modern supply chain management, focusing on optimizing operations through the integration of advanced technologies, data analytics, and process automation. In an increasingly complex and competitive global market, these solutions offer a framework to enhance efficiency, transparency, and responsiveness across the entire supply chain from procurement to final delivery. This paper explores the core components of Intelligent Automation, including data integration, supply chain visibility, inventory and demand management, and process automation. However, implementing these systems also presents challenges such as overcoming data silos, managing supply chain complexity, and ensuring regulatory compliance. This study aims to provide a comprehensive understanding of Intelligent Automation in supply chains, emphasizing their benefits, challenges, and the critical role they play in the evolution of supply chain management in today's dynamic business environment. Keyword: Supply Chain, Advance Logistics, Courier Management, Supply Solution, Automation, Demant Management

Construction of supply chain management information system based on networked web service composition technology

Web service composition is crucial for creating valuable services by integrating pre-existing ones. With their service-oriented architecture (SOA), which can be used for any system design, web services can increase flexibility. Fusing Web services architecture with Semantic Web services can better assist supply chain coordination in a distributive, autonomous, and ever-changing corporate environment than current information technology. Decisions must be made quickly and with enough information many systems fail to provide real-time supply chain insight. Forecasting, inventory management, and decision-making may all be impacted by poor data quality. Modifying preexisting systems according to unique organizational needs may be challenging and expensive. Hence, this paper proposes a semantic web service-based supply chain management framework (SWS-SCMF) to analyze the web services in supply chains and examine how they interact using Web Ontology Language (OWL)-S, including automated discovery, construction, and invocation. The suggested method for improving supply chain data integration uses an ontology-based multiple-agent decision support system. Different accessibility tools, data formats, management information systems, semantic web, and databases are integrated across the five interconnected levels of the system. Businesses may find the proposed approach useful for data and information sharing when dealing with complex supply chain management. The suggested SWS-SCMF is an adaptable, accurate, and effective method for bidirectional chaining composition that uses mediators to enable the automated composition of Semantic Web services. The numerical results show that our proposed method enhances the overall performance ratio by 94%, accuracy ratio by 98%, and supply chain management ratio by 91% compared to other methods.

Advanced Queueing and Location-Allocation Strategies for Sustainable Food Supply Chain

Background: This study presents an integrated multi-product, multi-period queuing location-allocation model for a sustainable, three-level food supply chain involving farmlands, facilities, and markets. The model employs M/M/C/K queuing systems to optimize the transportation of goods, enhancing efficiency and sustainability. A mixed-integer nonlinear programming (MINLP) approach is used to identify optimal facility locations while maximizing profitability, minimizing driver waiting times, and reducing environmental impact. Methods: The grasshopper optimization algorithm (GOA), a meta-heuristic algorithm inspired by the behavior of grasshopper swarms, is utilized to solve the model on a large scale. Numerical experiments demonstrate the effectiveness of the proposed model, particularly in solving large-scale problems where traditional methods like GAMS fall short. Results: The results indicate that the proposed model, utilizing the grasshopper optimization algorithm (GOA), effectively addresses complex and large-scale food supply chain problems. Compared to GAMS, GOA achieved similar outcomes with minimal differences in key metrics such as profitability (with a gap ranging from 0.097% to 1.11%), environmental impact (0.172% to 1.83%), and waiting time (less than 0.027%). In large-scale scenarios, GOA significantly reduced processing times, ranging from 20.45 to 64.78 s. The optimization of processing facility locations within the supply chain, based on this model, led to improved balance between cost (up to $74.2 million), environmental impact (122,112 hazardous units), and waiting time (down to 11.75 h). Sensitivity analysis further demonstrated that increases in truck arrival rates and product value had a significant impact on improving supply chain performance.

Exploring the psychological antecedents of suppliers' sustainability practices: A qualitative investigation in the Indian textile industry

AbstractThe uncertainties associated with modern businesses complicate decision‐making, especially in complex supply chains, such as those of the textile industry, which has its hub in emerging South Asian countries. Using the Indian textile industry as the research setting, this paper explores from a psychological lens how suppliers process uncertainties while adopting sustainability practices. The study uncovers certification agencies, interpersonal trust between suppliers and buyers, and suppliers' size, as key constructs that influence how suppliers perceive and process risks and ambiguities, and in turn how that influences their adoption of sustainability practices. Combining these empirical insights with the stakeholder and relational view theories, we develop a comprehensive framework to model suppliers' sustainability decision‐making in the face of uncertainty. This study uncovers nuances of uncertainty aversion, which provide valuable insights for practitioners while also breaking fertile ground for future academic research to quantify the emergent propositions.

Circular Economy Implementation in an Organization: A Case Study of the Taiwan Sugar Corporation

The implementation of circular economy principles is increasingly seen as a viable way to promote sustainable development and reduce environmental impact. This case study examines the implementation of circular economy principles at the Taiwan Sugar Company (TSC), a leading sugar manufacturer in Taiwan. This study analyzes the company’s efforts to redesign its production processes, develop closed-loop systems, and promote resource efficiency. It also explores the challenges and opportunities associated with implementing circular economy principles in the sugar industry, such as the complexity of supply chains, the need for stakeholder engagement, and the availability of sustainable technologies. This study follows the principles of British standard 8001:2017 to implement the concept of a circular economy into the organization. This study finds that the Taiwan Sugar Company has made significant progress in implementing circular economy principles, including adopting renewable energy sources, using byproducts as raw materials, developing sustainable packaging solutions, and using the output products of the company to make another useful product for industrial or agricultural use. These initiatives will result in the reduction of waste, an increase in resource efficiency, and enhanced environmental performance. However, this study also identifies several challenges that the company faces in implementing circular economy principles, such as the lack of standardized regulations and guidelines, the need for investment in sustainable technologies, and the need for stakeholder collaboration. Overall, this case study provides valuable insights into the implementation of circular economic principles in the sugar industry and offers practical recommendations for other organizations seeking to adopt circular economy principles. This study highlights the importance of stakeholder engagement, technological innovation, and regulatory support in promoting a transition toward a more sustainable and circular economy.

Under the context of competition between platform sales and live streaming sales, who has the pricing power of products?

The rapid rise of live-streaming selling and the increasing diversity of e-commerce channels have sparked ongoing debates regarding product pricing power. This price competition behaviour of online dual channels triggered by the supply-side pricing dilemma is a topic of significant research interest and forms the focal point of this paper. Therefore, we leverage the principles of game theory to construct a three-party evolutionary game model consisting of a brand, a steamer, and a traditional e-commerce platform. Within this framework, the brand holds the primary pricing authority. Our analysis examines the equilibrium strategies adopted by the various players under diverse scenarios and explores how the evolving behaviours of these parties impact the overall game system. Additionally, we employ the “people-goods-scene” perspective to deconstruct the intricate dynamics within this complex supply chain ecosystem. Our findings reveal two distinct evolutionary stable strategies: one in which brands maintain a stance against low-price negotiation, streamers avoid bargaining, and platforms avoid providing subsidies; the other in which brands are open to negotiating low prices, streamers engage in bargaining, and platforms provide subsidies. Notably, in most cases, brands tend to avoid explicitly stating their opposition to low-price negotiation. However, if a brand’s strategy shifts towards rejecting such negotiation, the negative implications of price wars across channels become a critical consideration. Conversely, when a brand opts for a more concessive pricing strategy, we need to consider the potential positive impacts of low-price competition.

The Role of Green Supply Chain Management in Enhancing Corporate Sustainability Performance

To improve the sustainability performance of corporations in light of growing environmental concerns and stakeholder demands, Green Supply Chain Management (GSCM) has become an essential tactic. the function of GSCM in advancing sustainability through the incorporation of ecological concerns into all stages of the supply chain, beginning with product conception and sourcing and continuing through production, delivery, and disposal. Sustainable sourcing, environmentally friendly packaging, waste minimisation, and energy efficiency are some of the important practices that lead to better economic and environmental results, as can be seen from case studies and empirical research across different industries. In addition to lowering their environmental effect, organisations who adopt GSCM methods save money, boost their reputation, and encourage innovation. Nevertheless, difficulties in implementing GSCM effectively include supply chain complexity, a lack of standardised measurements, and opposition to change. companies to conquer these obstacles and make the most of GSCM to generate sustainable growth and a competitive edge in the long run.