Enhance Supply Chain Resilience Research Articles

Demand Forecasting in Supply Chain Using Uni-Regression Deep Approximate Forecasting Model

This research presents a uni-regression deep approximate forecasting model for predicting future demand in supply chains, tackling issues like complex patterns, external factors, and nonlinear relationships. It diverges from traditional models by employing a deep learning strategy through recurrent bidirectional long short-term memory (BiLSTM) and nonlinear autoregressive with exogenous inputs (NARX), focusing on regression-based approaches. The model can capture intricate dependencies and patterns that elude conventional approaches. The integration of BiLSTM and NARX provides a robust foundation for accurate demand forecasting. The novel uni-regression technique significantly improves the model’s capability to detect intricate patterns and dependencies in supply chain data, offering a new angle for demand forecasting. This approach not only broadens the scope of modeling techniques but also underlines the value of deep learning for enhanced accuracy in the fluctuating supply chain sector. The uni-regression model notably outperforms existing models in accuracy, achieving the lowest errors: mean average error (MAE) at 1.73, mean square error (MSE) at 4.14, root mean square error (RMSE) at 2.03, root mean squared scaled error (RMSSE) at 0.020, and R-squared at 0.94. This underscores its effectiveness in forecasting demand within dynamic supply chains. Practitioners and decision-makers can leverage the uni-regression model to make informed decisions, optimize inventory management, and enhance supply chain resilience. Furthermore, the findings contribute to the ongoing evolution of supply chain demand forecasting methodologies.

Unleashing supply chain agility: Leveraging data network effects for digital transformation

The global manufacturing supply chain is undergoing a digital transformation (DT) powered by various digital technologies. In both stable and turbulent environments, DT helps safeguard supply chain performance by enhancing supply chain agility. While research on the use of digital technologies and their impacts on supply chains is growing, there is a lack of an overarching theoretical lens to synthesize their diverse functionalities, effects, and benefits. To address this gap, we adapt the concept of the data network effect to the supply chain context and propose that DT improves supply chain performance by enhancing supply chain resilience (SCRes) and robustness (SCRob) capabilities. To validate our hypotheses, we conducted a large-scale survey for data collection and performed Partial Least Squares Structural Equation Modelling (PLS-SEM) for data analysis. The results confirm the positive effect of DT on supply chain performance and the mediating roles of SCRob and SCRes. Our study contributes to the ongoing discussion on DT in the context of supply chains by introducing a novel theoretical perspective on the supply chain data network effect.

The Impact of Digital Transformation on ESG Performance: The Role of Supply Chain Resilience

With the development of digital technologies, the impact of digital transformation on corporate performance in environmental, social responsibility, and governance areas warrants further research. This study aims to delve into how digital transformation may impact a company’s ESG performance from the perspective of supply chain resilience. We collect non-financial listed companies in China’s A-shares from 2009 to 2022 as research samples. The results show that digital transformation can significantly improve the ESG performance. Digital transformation can enhance supply chain resilience, namely by reducing supplier and customer concentration to improve a company’s ESG performance. We also reveal that non-heavy polluting companies, high-tech companies, and companies in the eastern regions are more sensitive to digital transformation in terms of ESG performance. This paper contributes to examining the relationship between digital transformation and corporate ESG performance, providing both a theoretical foundation and practical recommendations for guiding companies in achieving digital transformation and improving their ESG performance.

Enhancing supply chain resilience under disruption: analysis of the farmed data by Monte Carlo simulation

Motivated by the critical need for supply chains to withstand disruptions, this paper investigates the application of three core resilience strategies and their combinations at the network design level. We propose an investigation framework that utilises Monte Carlo simulation to generate disruption rates of varying severity. This allows for the mathematical optimisation of eight different models, each representing a combination of the three core resilience strategies, based on the simulated disruptions. The framework also incorporates farmed structured data analysis to examine the performance and features of each model. Considering disruptions that can affect both suppliers and factories, a detailed comparison is performed between the strategies. Numerical comparisons reveal that the model incorporating all resilience strategies (Multiple Allocation Network with Backup Suppliers and Factories, or MANBSF) outperforms others, potentially achieving zero shortages even under significant disruptions. This comprehensive model allows for multiple allocations of facilities and incorporates backup suppliers and factories. The analysis further suggests that network resilience increases with size, density, and the number of complete paths.

Enhancing Supply Chain Resilience: the Impact of Blockchain & Emerging Technologies on Traceability

Supply chain traceability is an invaluable tool for companies to gain a competitive advantage today. The ever-changing global business environment, unpredictable market conditions, and changing consumer preferences call for agile supply chain systems. The pandemic helped reveal the vulnerabilities within the supply chain networks that need addressing. Various challenges, such as data reliability and integration, affect the current supply chain traceability and must be addressed. Such factors lead to inefficiencies within the system, which affect the process and lead to inconsistencies. The paper uses a systematic literature review to identify recent challenges and solutions to supply chain traceability. An analysis of blockchain technology's role in promoting transparency and security in supply chain systems was conducted. Lastly, an in-depth analysis of how improving traceability can help the supply chain networks build resilience.

The convergence of edge computing and supply chain resilience in retail marketing

In the fast-paced world of retail, having a strong and flexible supply chain is essential for success as businesses face increasing customer expectations and market uncertainties. Edge computing is emerging as a key technology that can enhance supply chain resilience by processing data in real-time, reducing delays, and improving responsiveness. This article explores how edge computing and supply chain resilience intersect within retail marketing and how they can optimize marketing strategies and customer experiences. Edge computing works by handling data close to where it is generated, which speeds up processing and reduces delays compared to traditional cloud systems. This real-time data processing is crucial for retailers who need to manage inventory, track shipments, and adjust to market changes quickly. With edge computing, retailers can get immediate insights into their supply chains, enabling faster and more accurate decision-making. The article reviews current research and case studies to illustrate the benefits of edge computing in retail. These benefits include better inventory management through real-time updates, more personalized and engaging marketing campaigns, and increased efficiency in logistics by automating processes. Edge computing also enhances the in-store experience with technologies like augmented reality, which can boost customer interaction and satisfaction. However, adopting edge computing also comes with challenges, such as high implementation costs, the complexity of integrating new systems, and concerns about data security. The article addresses these challenges and provides strategies for overcoming them, offering practical advice for effectively using edge computing. In summary, the article argues that edge computing will be a vital factor in retail’s future success and innovation. By making supply chains more agile, responsive, and efficient, edge computing helps retailers meet market demands and stay ahead of the competition. As technology continues to evolve, the role of edge computing in improving supply chain resilience and transforming retail marketing will become even more significant.

Effective Supply Chain Strategies in Addressing Demand and Supply Uncertainty: A Case Study of Ethiopian Pharmaceutical Supply Services

Background: Ensuring the consistent availability of essential medicines is crucial for effective healthcare systems. However, Ethiopian public health facilities have faced frequent stockouts of crucial medications, highlighting systemic challenges such as inadequate forecasting, prolonged procurement processes, a disjointed distribution system, suboptimal data quality, and a shortage of trained professionals. This study focuses on the Ethiopian Pharmaceutical Supply Services (EPSS), known for its highly unstable and volatile supply chain, aiming to identify risks and mitigation strategies. Methods: Using a mixed-method approach involving surveys and interviews, the research investigates successful and less successful strategies, key success factors, and barriers related to pharmaceutical shortages. Results: Proactive measures such as communication, stock assessment, supervision, and streamlined procurement are emphasized as vital in mitigating disruptions, while reactive strategies like safety stock may lack long-term efficacy. The study highlights the importance of aligning supply chain strategies with product uncertainties, fostering collaboration, and employing flexible designs for resilience. Managerial implications stress the need for responsive structures that integrate data quality, technology, and visibility. Conclusions: This study contributes by exploring proactive and reactive strategies, elucidating key success factors for overcoming shortages in countries with unstable supply chains, and offering actionable steps for enhancing supply chain resilience. Embracing uncertainty and implementing proactive measures can help navigate volatile environments, thereby enhancing competitiveness and sustainability.

When does entrepreneurial leadership enhance supply chain resilience? A three-way interaction analysis

PurposeThe research on entrepreneurial leadership (EL) and supply chain resilience (SCR) relationship is still in its exploration stage. Previous research indicates that EL is important for enhancing supply chain performance, including its resilience. However, the conditions through which EL affects SCR remain unclear. The purpose of this study is to examine the effect of EL on SCR in the context of SMEs, in addition to explore the combined moderating effects of big data analytics capability (BDAC) and environmental dynamism (ED) in the EL–SCR relationship.Design/methodology/approachHierarchical regression analysis via PROCESS Macro was used to analyze the data collected from manufacturing SMEs in India.FindingsThe findings reveal that EL positively and significantly affects SCR. Importantly, BDAC actually positively moderates the EL–SCR relationship regardless of the level of dynamism of the business environment.Originality/valueThis research expands the existing body of knowledge on EL and SCR within the context of developing countries. The findings offer useful insights for SME managers and decision-makers, who are anticipated to consider the adoption of BDAC in their firms. This has implications that with BDAC adoption, it is anticipated that SMEs will be able to take advantage of the full potential of EL to enhance their SCR regardless of the level of dynamism of the business environment.

Optimizing Supply Chain Efficiency using Innovative Goal Programming and Advanced Metaheuristic Techniques

This paper presents an optimization approach for supply chain management that incorporates goal programming (GP), dependent chance constraints (DCC), and the hunger games search algorithm (HGSA). The model acknowledges uncertainty by embedding uncertain parameters that promote resilience and efficiency. It focuses on minimizing costs while maximizing on-time deliveries and optimizing key decision variables such as production setups, quantities, inventory levels, and backorders. Extensive simulations and numerical results confirm the model’s effectiveness in providing robust solutions to dynamically changing supply chain problems when compared to conventional models. However, the integrated model introduces substantial computational complexity, which may pose challenges in large-scale real-world applications. Additionally, the model’s reliance on precise probabilistic and fuzzy parameters may limit its applicability in environments with insufficient or imprecise data. Despite these limitations, the proposed approach has the potential to significantly enhance supply chain resilience and efficiency, offering valuable insights for both academia and industry.

Adapting to disruption: the impact of agility, absorptive capacity and ambidexterity on supply chain resilience

PurposeThis study aims to explore the key drivers contributing to supply chain resilience, with specific attention on agility, absorptive capacity and ambidexterity. It focuses on the roles of supply chain absorptive capacity (SCAC), supply chain ambidexterity (SCAB), supply chain agility (SCAG) and supply chain flexibility (SCF) in enhancing supply chain resilience (SCR).Design/methodology/approachA survey based on a questionnaire with established scales for SCAC, SCAB, SCAG, SCF and SCR was conducted among professionals in various industries within India, receiving 356 responses. Structural equation modeling is used to test the hypothesis.FindingsThe study reveals significant relationships between SCAC, SCAB, SCAG and SCR. SCAC and SCAB are positively correlated with SCAG, which in turn positively influences SCR. Further, SCF directly influences SCR and moderates the relationships between SCAC/SCAB and SCAG, enhancing the agility and resilience of the supply chain. These findings underline the importance of integrating knowledge management, adaptability and flexibility in supply chain strategies to cope with the dynamic business environment.Originality/valueThe uniqueness of this study lies in its integrated investigation of absorptive capacity, ambidexterity, agility and supply chain flexibility, with a specific focus on the moderating role of flexibility. This research is unique in demonstrating how these dynamic capabilities transform disruptions into innovative and growth opportunities for supply chain management.

Optimisation of recovery policies in the era of supply chain disruptions: a system dynamics and reinforcement learning approach

Incidents like the COVID-19 pandemic or military conflicts disrupted global supply chains, causing long-lasting shortages in multiple sectors. This so-called ripple effect denotes the propagation of disruptions to further elements of the supply chain. Due to the severity of the impact that the ripple effect has on revenues, service levels, and reputation among supply chain entities, it is essential to understand the related implications. Given the unpredictable nature of disrupting events, this study emphasises the value of a reactive development of effective recovery policies on an operational level. In this article, a system dynamics model for a supply chain is used as framework to investigate the ripple effect. Based on this model, recovery policies are generated using reinforcement learning (RL), which represents a novel approach in this context. As main findings, the experimental results demonstrate the applicability of the proposed approach in mitigating the ripple effect based on secondary data from a major aerospace and defence supply chain and furthermore, the results indicate a broad applicability of the approach without the need for complete information about the disruption characteristics and supply chain entities. With further refinement and real-world implementation, the presented approach provides the potential to enhance supply chain resilience in practice.

Integrating Perishables into Closed-Loop Supply Chains: A Comprehensive Review

In an era where sustainability and efficient resource utilization are paramount, the closed-loop supply chain (CLSC) emerges as a critical approach, particularly in the context of perishable goods. The perishability of products adds a layer of complexity to supply chain management, necessitating innovative strategies for maximizing product life and minimizing waste. This comprehensive review article delves into the integration of perishable products within the framework of CLSC. The study thoroughly examines existing research to identify gaps and outline future research directions. It emphasizes the unique challenges and complexities of managing perishable goods, a crucial but often overlooked component in sustainable supply chain practices. The review highlights the balance between efficiency and sustainability, underscoring the importance of reverse logistics and circular economy principles in enhancing supply chain resilience. By synthesizing various methodologies and findings, the article presents a holistic view of the current state of perishable product management in CLSCs, offering valuable insights for academia and industry practitioners. The study not only contributes to the theoretical understanding of CLSCs, but also proposes practical approaches for their optimization, aligning with broader sustainability goals.

RESILIENCE OF GREEN BUILDING SUPPLY CHAIN: CAPABILITIES, RISKS AND INFLUENCE MECHANISM

ABSTRACT Green buildings are more effective in saving energy and reducing carbon dioxide emissions than conventional buildings. However, the long-term development of green buildings depends heavily on the resilience of their supply chain. This study examines how capability factors (readiness, response, and recovery) and risk factors (technological, organizational, and environmental) interact to influence the resilience of the green building supply chain, using a third-order partial least squares structural equation model. The results indicate that response capability and technological risk significantly impact resilience, while readiness capability mitigates organizational and environmental risks. The study suggests three strategies to enhance supply chain resilience: strengthening readiness capabilities and increasing resistance to organizational or environmental risks. The findings provide green building project managers with practical insights and tools to make informed decisions that improve supply chain resilience.

Technology as a solution to the supply chain problems in the United States: What more can be done?

The study examined the critical role of technology in addressing supply chain challenges in the United States, with a focus on identifying gaps and exploring opportunities for improvement. Through a comprehensive analysis of existing literature and empirical studies, the research uncovered key supply chain challenges faced by firms in the U.S., including issues related to counterfeit goods, logistics inefficiencies, environmental concerns, inaccurate demand forecasting, and cyber-security threats. Also, the study examined the role of emerging technologies such as blockchain, artificial intelligence, Internet of Things, big data analytics, and machine learning in enhancing supply chain resilience and agility. This study highlighted the contributions of these technologies in promoting transparency, traceability, sustainability, and efficiency across various aspects of supply chain management. By synthesizing insights from diverse sources and datasets, the study provided valuable recommendations and strategies for leveraging technology to address supply chain challenges effectively. These recommendations covers areas such as investment in advanced technologies, collaborative data sharing platforms, integration of sustainability metrics, predictive analytics for risk management, and supply chain resilience planning.

Leveraging advanced technologies in Supply Chain Risk Management (SCRM) to mitigate healthcare disruptions: A comprehensive review

The Healthcare sector is undeniably one of the most critical sectors in any given economy and disruptions in this industry have dire consequences that affect patient care, the efficiency of healthcare systems and by far public health. This publication seeks to analyze and discuss the vital role of supply chain risk management in addressing disruptions, becoming resilient and ensuring that healthcare services function effectively. The pandemic (COVID-19) brought to fore just how critical it is to have a robust and agile system for supply chain risk management in healthcare, the sudden and unprecedented surge in demand for essential medical equipment like personal protective equipment (PPE) left millions of people at risk thereby jeopardizing their safety and health. This crisis echoed the urgent need for efficient and effective supply chain risk management strategies to mitigate such risks and ensure the availability of vital medical supplies. This review paper will be sharing different strategies and actionable tips to develop contingency plans, identify, reduce potential disruptions and recommended practices for risk management in the healthcare supply chain. This will highlight key areas such as inventory management and stockpiling, which focuses on maintaining safety stock levels to buffer against sudden disruptions, using advanced analytics to forecast demand and manage inventory levels. It will also examine risk assessment and identification by pinpointing potential attacks, threats, and vulnerabilities within the healthcare supply chain through thorough risk assessments. Additionally, it will cover supplier base diversification, emphasizing the importance of engaging multiple suppliers to reduce dependency on a single source and enhance supply chain resilience by balancing global and local suppliers to mitigate geographic disruption risks. Furthermore, it will explore the integration of technology, leveraging innovative solutions like blockchain for enhanced transparency, security, and traceability of supply chain transactions.

Analyzing resilience influencing factors in the prefabricated building supply chain based on SEM-SD methodology

The supply chain for prefabricated buildings (PB) currently grapples with pressing challenges. In order to ensure the safe and stable development of the prefabricated building supply chains (PBSC), this study aims to identify the key factors and internal mechanisms affecting the PBSC, and propose a supply chain resilience enhancement mechanism, so as to promote the sustainable development of the PB industry. The study combined a literature review and survey data to identify key resilience factors in PBSC. A Structural Equation Model (SEM) was used to explore the relationships between these factors. System dynamics were applied to create a simulation model, assessing the resilience impact level and conducting sensitivity analysis. The results show that the transportation and procurement processes are the most significant factors influencing supply chain resilience. The external environmental factors wielded a more pronounced impact on the overall evaluation of supply chain resilience than the delivery and use processes, but delivery and use processes are more sensitive. The study uses the Pressure-State-Response (PSR) model to suggest strategies for enhancing supply chain resilience. This study contributes to more sustainable and efficient construction practices by offering an innovative theoretical framework to analyze the factors influencing PBSC resilience and proposing enhancement strategies.

Navigating uncertainties: impact of supply chain resilience on organizational performance, mediated and moderated model: Pakistan manufacturing sector case

PurposeThis study aimed to investigate the relationship between supply chain resilience and organizational performance with innovation as a mediator and information sharing as a moderator.Design/methodology/approachThe study thoroughly explored how supply chain resilience, organizational performance, innovation and information sharing are connected. It used an exploratory approach and quantitative methods. Data were collected from large manufacturing firms through online questionnaire surveys using Google Forms, emails and WhatsApp.FindingsThe findings demonstrated that supply chain resilience positively impacts sustainability efforts. Furthermore, leveraging innovation and effective information sharing mediated and moderated the relationship, playing pivotal roles in enhancing sustainability within the supply chain.Research limitations/implicationsThe study provided actionable insights for businesses to strengthen their sustainability efforts. Managers could utilize these findings to implement strategies that enhance supply chain resilience, drive innovation and promote effective information sharing, ultimately leading to a more sustainable supply chain.Originality/valueThis study contributed to the existing body of knowledge by examining the complex relationships between supply chain resilience, organizational performance, innovation and information sharing in the context of achieving sustainability. The exploration of these components in a holistic manner added originality to the research and shed light on effective strategies for sustainable supply chain management.

Product Quality Improvement through Effective Operational Management

Purpose: This study explores the impact of advanced technologies and strategies on supply chain optimization within operational management, aiming to understand how AI, ML, IoT, blockchain, effective inventory management, supplier relationship management, risk management strategies, and sustainability practices enhance supply chain performance. Research Design and Methodology: The study uses a qualitative research design, including semi-structured interviews with supply chain experts from various industries and document analysis. The thematic analysis identifies patterns and themes, offering a detailed understanding of factors contributing to supply chain optimization. Findings and Discussion: The study reveals advanced technologies significantly improve demand forecasting accuracy, real-time decision-making, and supply chain transparency. Strategies such as JIT, Lean Inventory, EOQ, and VMI optimize inventory levels and reduce costs. Strong supplier relationships and robust risk management strategies enhance supply chain resilience and agility, while sustainability practices lead to cost savings, improved brand reputation, and regulatory compliance. The findings support the hypothesis that technological integration and strategic management enhance supply chain performance, aligning with the resource-based view and dynamic capabilities theories. Implications: This research provides insights for businesses seeking to optimize their supply chains. It highlighting the need for a holistic approach integrating technological solutions with human and organizational factors. The findings offer practical guidance for implementing advanced technologies and strategies, contributing to scientific understanding and practical applications in supply chain management.

Resilience optimization in disruption-prone sustainable reverse supply chains for lead-acid battery waste management in Brazil: A stochastic model for public and private policy formulation

This study explores the relationship between disruptive events in supply chains and investments from public and private policies aimed at recovery. It focuses on the improper disposal of lead-acid battery waste in Brazil, which poses environmental and health risks, and suggests strategies for managing this waste through Brazilian reverse supply chains. A stochastic model was developed to optimize investments in resilient capabilities like absorption, adaptation, and recovery before and after disruptions. The results show that proactive investments should prioritize creating redundancies and collaboration to ensure timely restoration of waste supply, especially during low-severity events. The study provides a model that guides the allocation of resources for sustainable waste management in Brazilian lead-acid battery operations and highlights the importance of public and private policy formulation in enhancing supply chain resilience.

Post-hazard supply chain disruption: Predicting firm-level sales using graph neural network

Evaluating the damage caused by supply chain disruptions triggered by natural hazards has an important role in supply chain risk management. This study proposes a novel approach to predict annual sales change rates for firms post-hazard. The approach employs graph neural networks, a machine learning technique that considers both internal factors such as sales and number of employees and external factors such as inter-firm relations and damages incurred from hazards. The model was trained on firm and flood data from previous floods in Japan and was found to outperform baseline models that did not consider inter-firm relations. To address the model's explainability problem, we employed Explainable Artificial Intelligence techniques to identify the factors influencing sales post-disruption and analysed the importance of firms and trades in the supply chain from a spatial perspective. The findings highlight the crucial role of business partners in a firm's supply chain and the impact of distance between suppliers on a firm's sales. The study contributes to improved supply chain risk management practices in industry as well as government, ultimately enhancing supply chain resilience.