Improving Supply Chain Resilience Research Articles

Resilience enhancers and barriers analysis for Industry 4.0 in supply chains using grey influence analysis (GINA)

This study investigates the impact of Industry 4.0 (I4.0) enabling technologies in enhancing the resilience of supply chain systems and the barriers to adopting Industry 4.0 in the supply chains. We use the novel grey influence analysis (GINA) to examine the influence relations among supply chain resilience enhancers and barriers. The study has identified seven enhancers and nine barriers to adopting I4.0 that can improve supply chain resilience. While analyzing the enhancers, the research findings indicate that visibility and coordination in the supply chain are the major enhancers. For barriers, based on the overall influence score, financial constraints, lack of skills and expertise, and inaccessibility of new technology have ranked first, second, and third, respectively. The identified barriers to adopting I4.0 indicate that reducing financial constraints could facilitate the implementation of Industry 4.0 technologies. This study is among the initial investigations to analyze the supply chain resilience enhancers and barriers together for adoption of Industry 4.0. The findings of this study can assist decision-makers and practitioners in overcoming the identified barriers, thereby focusing on the important enhancers of resilience for facilitating the effective adoption of Industry 4.0 in supply chains.

Optimizing Supply Chain Efficiency Using Cross-Efficiency Analysis and Inverse DEA Models

Our study employs cross-efficiency analysis (CEA) and machine learning techniques to optimize supply chain performance. By integrating inverse DEA models with directional distance functions, we measure operational efficiency across various decision-making units (DMUs), accounting for undesirable outputs such as excess costs and emissions. Our results indicate a 20% improvement in market recognition efficiency and a 15% increase in earnings persistence efficiency after model application. Additionally, machine learning classifiers, including Random Forest and Support Vector Machines, further enhanced predictive accuracy, with Random Forest achieving the lowest mean absolute error of 0.07. These findings underscore the effectiveness of advanced analytical models in improving supply chain resilience and decision-making accuracy, contributing to sustainable operational performance.

The Impact of Supply Chain ESG Management on Supply Chain Resilience With Emerging IT Technologies

Supply chain resilience is an important topic, defined as the ability of a fractured supply chain to rebuild itself, maintain stability in response to changes in the external environment. This study explores the impact of supply chain ESG management on supply chain resilience. In this paper, a total of 371 questionnaires were collected from Chinese firms, and a PLS-based structural equation model was constructed for empirical testing. This study reveals the positive impact of supply chain ESG management on supply chain resilience. Information network capability mediates the relationship between supply chain ESG management and supply chain resilience. The application of emerging IT technologies positively moderates the impact of supply chain ESG governance on supply chain network capability. This study provides a novel perspective that contributes to the understanding of the importance of supply chain ESG governance in improving supply chain resilience, offers empirical evidence for the role of information network capabilities and emerging IT technologies.

De-risking Global Supply Chains: Looking Beyond Material Flows

executive summary: This essay examines supply chain de-risking driven by two forces: (1) the renewed concerns of the U.S. and its allies about supply chain resilience and (2) China's long-standing strategy to redefine the global order. main argument A defining feature of global supply chains is they are powered by material, information, financial, and human flows. By examining these multiple flows in the evolution of global supply chains, our analysis goes beyond the singular focus on material flows that is common in recent economic and foreign policy discourse. Another defining feature of global supply chains is the strategic interaction between different actors. Following this line of thinking, we argue that de-risking is not a unilateral option for the West and its developed economy partners but rather an interactive and fluid development taking place around the globe. This can be seen in the U.S.'s growing emphasis on improving supply chain resilience through reshoring, nearshoring, and friendshoring, as well as in China's diversification into markets such as Russia and the global South, with broader implications for major economies. Looking beyond material flows to information, financial, and human flows is important to monitor these indicators of the ongoing transitions in global supply chains. policy implications • Policymakers must recognize that de-risking is not a unilateral process but involves strategic interactions among multiple global actors. • It is imperative to consider the implications of information, financial, and human flows, in addition to material flows, to develop effective de-risking strategies. • Ensuring political stability and policy continuity is essential to effective de-risking, particularly in the context of changing administrations and economic policies. • In implementing de-risking, efforts should ensure coordination across the four types of flows while addressing the challenges of increased complexity and potential lack of visibility into operations. • The role of emerging economies in de-risking is critical, as they stand to benefit significantly but also play a key role in achieving diversified and resilient supply chains.

A critical review of machine learning applications in supply chain risk management

This article examines the transformative role of Machine Learning (ML) in Supply Chain Risk Management (SCRM), emphasizing its ability to enhance risk prediction and mitigation through real-time, data-driven insights. It demonstrates how ML applications like demand forecasting, inventory optimization, supplier risk assessment, and fraud detection improve supply chain resilience by analyzing large datasets to identify patterns, predict risks, and recommend proactive actions. However, the article also highlights key challenges, including data quality, availability, and privacy issues, which limit the effectiveness of ML models. Integrating ML with legacy systems poses additional technical and financial difficulties, particularly for smaller businesses. High implementation costs and scalability constraints further hinder widespread adoption. Ethical concerns, such as data bias and privacy, still need to be explored, raising questions about responsible ML use in supply chains. Future research should address these gaps by improving data governance frameworks for accuracy and privacy, developing scalable ML models suited to various supply chain environments, and exploring synergies with technologies like blockchain and the Internet of Things (IoT). These advancements will help realize ML’s full potential, fostering more agile, transparent, and resilient supply chains capable of navigating complex global risks. By tackling these challenges, ML can shift SCRM from reactive to proactive, ensuring long-term operational continuity and a competitive edge in the evolving global market.

A Systematic Literature Review on Flexible Strategies and Performance Indicators for Supply Chain Resilience

AbstractSupply chain resilience is a widely useful concept for managing risk and disruption. Designing strategies for preparedness, response, and recovery can help businesses to mitigate risks and disruptions. Among them, flexible strategies can effectively improve supply chain resilience. In the literature, several studies have considered different types of flexible strategies and investigated their impacts on supply chain resilience. However, a systematic literature review (SLR) paper on this topic can further help to understand the scientific progress, research gaps, and avenues for future research. Hence, this study aims to explore how the literature has contributed to the area of flexible strategies and the impact on supply chain resilience performance. To achieve our objective, we apply an SLR methodology to identify themes such as research areas and key findings, contexts and industry sectors, methodologies, and key strategies and performance indicators in the connection between flexible strategies and supply chain resilience. The findings show that many studies connect flexible strategies to supply chain resilience. However, research gaps exist in analysing relationships between flexible strategies and performance, conducting comparative studies, developing dynamic resilience plans, applying flexible strategies, conducting theoretically grounded empirical studies, and applying multiple analytical tools to develop decision-making models for supply chain resilience. Finally, this study suggests several future research opportunities to advance the research on the topic. The findings can be a benchmark for researchers who are interested in conducting research in the area of flexible strategies and supply chain 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.

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.

Does service-oriented manufacturing improve customer stability?

Stabilizing customer relationships plays an important role in improving supply chain resilience. Based on a sample of A-share listed companies in the manufacturing industry from 2009 to 2022, this work investigates the impact of SOM(service-oriented manufacturing) on supply chain resilience from the perspective of customer stability. The results showed that SOM has a positive impact on customer relationship stability, indicating that manufacturing enterprises carrying out SOM can improve customer relationship stability, and this stable relationship is long lasting. Analysis of service-oriented manufacturing structure reveals that service that supports the supplier's product (e.g., after-sale services) is less effective in promoting customer relationship stability than service that supports the customer (e.g., training service). This study theoretically expands the research on the allocation of enterprise resources among supply chains, promotes the deep integration of modern service industry and advanced manufacturing industry, and provides experience for implementation of relevant decision-making and deployment of supply chain security and stability in practice.

COVID-19 Lessons for the Tourism Sector: Role of Top Management Support, Communication, and Organisational Culture in Supply Chain Resilience

Tourism is a worldwide industry that is associated with global risks. Tourists from various countries are susceptible to diseases that are transmitted as a result of ecological, genetic, and human-related causes. Presently, the escalating spread of viruses, epidemics, and pandemics exemplify the adverse repercussions of globalisation, resulting in fatalities and substantial economic downturns due to their detrimental effects on the tourism sector. During the COVID-19 pandemic, unique and long-lasting risks made many tourism-related companies very difficult to run; they even risked survival. Because of this, we need a better understanding of the factors that affect or improve supply chain resilience. Addressing the public health sector of tourists is a pressing concern in such a scenario. This study seeks to examine the management of tourism, specifically focusing on the role of top management support, communication, and organisational culture in supply chain resilience. A particular focus is made on the impact of top management support, communication, and organisational culture on supply chain resilience, as well as the impact of supply chain resilience on supply chain performance. A total of 128 pieces of information were collected from various tourism sector organisations to analyse the potential relationship between the variables. Among respondents, there were 35 females and 93 males. SPSS 23 and SmartPLS, both based on structural equation modelling, are used to perform tests on the obtained data. The investigation findings indicate that the support of top management, communication, and organisational culture substantially improves supply chain resilience in the tourism sector. Furthermore, research has demonstrated that a higher level of supply chain resilience positively impacts the overall performance of firms engaged in providing tourism services. Enhancing the efficiency of the supply chain can decrease the health hazards faced by tourists, leading to an overall improvement in public health within the tourism and leisure business.

Prediction-based decomposition optimisation for multi-portfolio supply chain resilience strategies under disruption risks

ABSTRACT This paper focuses on the design of supply chain (SC) risk mitigation and recovery strategies during long-term disruptions caused by the COVID-19 outbreak, which affect both suppliers and plants. Consequently, concurrent disruptions in supply and production are observed, which vary in duration and result in time-varying reductions in supply and production capacity. To cope with long-term disruptions, a modified multi-portfolio approach that integrates simulation and predictions is proposed to develop efficient mitigation and recovery plans. This approach involves selecting primary and recovery supply and production portfolios concurrently. To achieve this objective, time-dependent mixed integer programming (MIP) models that incorporate preparedness and recovery measures are developed to optimise SC operations. A prediction-based decomposition optimisation method is proposed to solve MIP problems and coordinate supply and production portfolios under disruptions and uncertainties. Furthermore, a heuristic approach is established to provide a comprehensive solution process. Finally, computational experiments and comparative analysis are conducted on a real-life case study. The results demonstrate that the proposed modelling and optimisation methods can effectively address disruptions and improve SC resilience. In addition, the developed models and approaches have the potential to serve as decision-making tools in SC management during disruptions.

Impact of innovation, entrepreneurial orientation and entrepreneurial leadership on supply chain resilience in handicraft industry: moderating role of supply chain orientation

PurposeThe study aims to explore dynamic capabilities such as innovation, entrepreneurial leadership, absorptive capability, and the dimension of entrepreneurial orientation in the handicraft sector to enhance supply chain resilience and innovation during unprecedented times. This study also used innovation as a mediating construct and supply chain orientation as a moderating construct.Design/methodology/approachWe gathered data from the handicraft sector in the Uttar Pradesh (UP) in India using a pretested questionnaire. We used variance-based partial least squares structural equation modelling (PLS-SEM) to test our research hypotheses.FindingsOur study indicates that to enhance innovation and improve supply chain resilience, firms should focus on developing dynamic capabilities such as entrepreneurial leadership, absorptive capacity, artificial intelligence (AI), innovativeness, risk-taking ability, and protectiveness. The study highlights the significant role of dynamic capabilities in the handicraft sector during times of crisis, enabling innovation and resilience to risk.Practical implicationsThe study highlights the significant role of dynamic capabilities in the handicraft sector during times of crisis, enabling innovation and resilience to risk.Originality/valueThis study provides significant insights into the current understanding of dynamic capability theory and supply chain orientation and expands upon the existing literature in this field. It comprehensively analyses the latest research and advances knowledge in this area.

Adaptive Supply Chain Risk Management Using AI Mitigating Disruptions and Enhancing Resilience in the Post-Pandemic Era.

The COVID-19 pandemic has starkly revealed the vulnerabilities within global supply chains, prompting the urgent need for enhanced risk management strategies. This paper explores the application of Artificial Intelligence (AI) in adaptive supply chain risk management to mitigate disruptions and enhance resilience in the post-pandemic era. By leveraging AI technologies such as machine learning, predictive analytics, and optimization algorithms, organizations can proactively identify, assess, and respond to risks in real-time, thereby fortifying their supply chains against unforeseen disruptions. [1] This paper reviews existing literature on supply chain risk management, AI applications in supply chain management, and post-pandemic supply chain challenges. Furthermore, it presents examples illustrating how AI-driven adaptive risk management approaches have been implemented successfully to navigate disruptions and improve supply chain resilience. Through this analysis, the paper aims to provide insights into the transformative potential of AI-enabled adaptive risk management strategies in building agile and robust supply chains for the future. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6294

Deploying Industry 5.0 drivers to enhance sustainable supply chain risk resilience

ABSTRACT With global supply chains facing increasing complexity and uncertainty, mitigating sustainable supply chain risks (SSCRs) has become an important research topic. Industry 5.0 (I5.0) is a supplement to, and re-development of, Industry 4.0, but no research on improving supply chain resilience (SCRE) through I5.0 drivers to mitigate SSCRs currently exists. Therefore, we developed a QFD approach to investigate the relationship between SSCRs, SCRE, and I5.0 drivers. This study utilises the FDM-FDISM-ANP-TOPSIS method, considers China’s largest private logistics enterprises as the object of empirical analysis, and establishes a sustainable supply chain identification system and SCRE evaluation index system for logistics enterprises through two-stage House of Quality. The findings reveal that 20 key I5.0 significantly bolster 17 SCRE, thereby mitigating 13 SSCRs by QFD-MCDM framework. These I5.0 drivers play a pivotal role in enhancing SCRE of logistics enterprises. This study contributes to the field of supply chain risk resilience in sustainable engineering by integrating the perspectives of SSCRs, SCRE and I5.0. It underscores the necessity for managers in logistics enterprises to develop SCRE solutions that incorporate both SSCRs and I5.0 considerations. Furthermore, our findings offer valuable insights for other industries aiming to bolster their supply chain competitive advantages in an increasingly complex global landscape.

Optimal resilience strategy for manufacturers to deal with supply disruptions: Investment in supply stability versus dual sourcing

Enhancing supply chain resilience is fundamental to the stable development of manufacturing enterprises. By comparing three resilience strategies (investment in fixed supplier for stable supply, dual sourcing by adding backup suppliers, and hybrid strategy), we investigate their effects on improving supply chain resilience under supply disruption and selecting resilience strategies for manufacturing enterprises in a complex supply chain environment. We then propose a corresponding management approach for manufacturers. This study reveals the following: (1) Compared with the non-resilience strategy, the investment strategy for supply stability and hybrid strategy may adversely impact the manufacturer’s profits while concurrently enhancing expected sales when the manufacturer’s investment cost is high, whereas the dual sourcing strategy is an effective strategy to increase the manufacturer’s expected profit. (2) Compared with investment and dual sourcing strategies, the hybrid strategy has a lower wholesale price but not always a lower sale price. (3) Manufacturers who prefer supply stability always adopt a hybrid strategy to ensure maximum expected sales volume; manufacturers who prefer profit adopt a hybrid strategy only when the investment cost is within a certain range; otherwise, they adopt a dual sourcing strategy to obtain higher profits. (4) Under an asymmetric sourcing strategy, when suppliers’ costs of production differ significantly, manufacturers adopting dual sourcing and hybrid strategies do not always increase sales, and adopting an investment strategy for supply stability is a more sales-resilient strategy. (5) The results of manufacturer resilience strategy selection under a multi-product supply chain are similar to those for a single product.

A Market Convergence Prediction Framework Based on a Supply Chain Knowledge Graph

Market convergence challenges socially sustainable supply chain management (SSSCM) due to the increasing competition. Identifying market convergence trends allows companies to respond quickly to market changes and improve supply chain resilience (SCR). Conventional approaches are one-sided and biased and cannot predict market convergence trends comprehensively and accurately. To address this issue, we propose a framework based on info2vec that solves the problem of matching multidimensional data by using the technology layer as the focal layer and the supply chain as the supporting layer. The framework enriches the supply chain dimension with the technology dimension. A knowledge graph is constructed to facilitate cross-domain information connectivity by integrating different data sources. The nodes in the knowledge graph were characterized using a representation learning algorithm, which enhanced feature mining during supply chain and market convergence. Changes in market demand were predicted based on link prediction experiments. Market convergence has an impact on firm cooperation and, thus, on SCR. The framework recommends potential technological and innovative cooperation opportunities for firms. In this way, it has been demonstrated to improve SSSCM through network resilience experiments. This method predicts market convergence efficiently based on the supply chain knowledge graph, which provides decision support for enterprise development.

Research on the Manufacturer’s Strategies under Different Supply Interruption Risk Based on Supply Chain Resilience

In order to study the selection of coping strategies for the manufacturer facing different supply interruption risks, this paper constructs a supply chain consisting of one manufacturer and one supplier and uses no-taking coping strategies as the benchmark model to analyze the resilience of supply chain formed by the manufacturer’s adoption of penalty mechanism, emergency supplier mechanism, and strategic investment mechanism. The research shows that in the face of various levels of supply interruption risk, the manufacturer adopting a strategic investment mechanism will achieve high resilience, enabling the manufacturer and supplier to achieve mutual benefit and win-win results. In some cases of high interruption risk, the manufacturer adopting an emergency supplier mechanism can achieve higher chain resilience compared with not taking emergency measures, but its ability to improve supply chain resilience is weaker than that of a strategic investment mechanism. The penalty mechanism is applicable to situations where some interruption risk is characterized by low risk, and in such cases, both the penalty mechanism and the strategic investment mechanism can enhance the resilience of the supply chain.

What Does Not Kill You Makes You Stronger: Supply Chain Resilience and Corporate Sustainability Through Emerging IT Capability

Global epidemics and international conflicts disrupt supply chain operations. Many enterprises employ emerging information technology (IT) to reduce supply chain vulnerability and enhance supply chain resilience. Technologies like artificial intelligence and blockchain facilitate more robust supply chain operations, such as remanufacturing, just-in-time production, and automated workflow, leading to corporate sustainability along economic, environmental, and social dimensions. From a dynamic capability perspective, this article conceptualizes emerging IT capability and investigates its role in helping enterprises survive supply chain disruptions and prosper in the long run. A research model depicts the relationships among environmental uncertainty, supply chain vulnerability vigilance, emerging IT capability, supply chain resilience, and corporate sustainability. A partial least square analysis on survey observations collected from more than 200 enterprises in China that are highly susceptible to supply chain disruptions provides supporting evidence to most research hypotheses. The results show that high vigilance to potential supply chain disruptions will motivate enterprises to develop emerging IT capability, which will enhance supply chain resilience as well as economic, environmental, and social performances. The mediating role of emerging IT capability suggests a viable path for enterprises to adapt to the increasingly turbulent environment and improve supply chain resilience and corporate sustainability.

IMPACT OF SUPPLY CHAIN DISRUPTIONS ON ENERGY SECURITY IN ZAMBIA: CHALLENGES AND MITIGATION STRATEGIES

This study examines the impact of supply chain interruptions on Zambia's energy security, highlighting the nation's significant reliance on hydroelectric power, which generates about 83% of its total electricity production (Jürisoo et al., 2019). According to the study, Zambia's energy sector is significantly impacted by global supply chain risks, such as geopolitical conflicts and environmental issues (Mwanza et al., 2023). The analysis explores how these problems exacerbate problems related to energy security, particularly during load-shedding incidents (Jürisoo et al., 2019; Alzoubi, 2024). Furthermore, the study looks at the obstacles to establishing circular supply chains in Zambia's energy sector and emphasizes how cutting-edge technologies like artificial intelligence and blockchain might improve supply chain resilience (Mwanza et al., 2023; Alzoubi, 2024). The conclusions stress how urgently legislative changes and focused investments are needed to support Zambia's energy infrastructure and keep it safe from future shocks.

Uncovering the Hidden Factors of Resilience: Supply Chain Ecocentricity, Exploitation, and Exploration

This article sheds light on often overlooked organizational antecedents that build supply chain resilience by drawing on knowledge management theory and the resource-based view because of their focus on exploitation and exploration as capabilities related to organizational learning. It was examined whether the relationships between supply chain ecocentricity and supply chain exploitation and exploration practices enable supply chain resilience. It was also determined whether environmental uncertainty would affect the relationship between these enablers and resilience. Manufacturing companies operating in France were surveyed and variance-based structural equation modeling was used to analyze primary data from 405 completed questionnaires. Ecocentricity, driven mainly by secondary stakeholders, was found to influence supply chain resilience as well as the exploitation and exploration of resources and capabilities, confirming that they are enablers of supply chain resilience. Firms should be aware that secondary stakeholders cannot be neglected in the supply chain network, because they contribute to knowledge management and a better understanding of market contingencies and in turn improve supply chain resilience. The original contributions of this article are to demonstrate the relevance of the ecocentricity perspective and its role in helping achieve resilience in supply chains.