Supply chain resilience: an adaptive cycle approach

PurposeThe COVID-19 crisis has caused major supply chain disruptions, and these can be traced back to basic supply chain risks that have previously been well identified in literature. The purpose of this paper is to suggest a pathway for closing the gap between supply chain resilience research and efforts in industry to develop a more resilient supply chain.Design/methodology/approachBased upon virtual roundtables with supply chain executives, supplemented with interviews and publicly available datapoints about COVID-19 impact on the supply chain, we explore challenges in industry and suggest opportunity areas where research can support efforts in industry to improve supply chain resilience.FindingsDuring the COVID-19 crisis, participating supply chain executives are experiencing textbook supply, demand and control risks in the supply chain. They also observe a lack of preparedness, shortcomings of current response plans and the need for greater supply chain resilience. Focus areas in improving resilience mirror generic recommendations from literature and provide a rich opportunity to reduce the gap between research findings and efforts in industry.Research limitations/implicationsMore empirical, event-based and less conceptual research into supply chain resilience has been called for several times during the last two decades. COVID-19 provides a very rich opportunity for researchers to conduct the type of research that has been called for. This research may contribute to the structurally de-risking of supply chains. Areas of research opportunity include decision models for supply chain design that avoid overfocusing on costs only, and that consider the value of flexibility, short response times and multiple sources as well as methods for enriching supplier segmentation and evaluation models to reduce a focus on savings and payment terms only.Practical implicationsKey levers for de-risking the supply chain include the need to balance global sourcing with nearshore and local sourcing, the adoption of multiple sources and a greater utilization of information technology to drive more complete and immediate information availability. Perhaps most importantly, talent management in supply chain management needs to promote a focus not just on costs, but also on resilience as well as on learning from current events to improve decision-making.Social implicationsThere is a great opportunity for supply chain managers to grow their contribution to society beyond risk response into the proactive reduction of risks for the future. Researchers can serve society by informing this progress with impactful research.Originality/valueThis article offers initial empirical exploration of supply chain risks experienced in the context of COVID-19 and approaches considered in industry to improve supply chain resilience. Opportunities for empirical, event-based and less conceptual research that has been called for years, are identified. This research can help close the gap between supply chain resilience research and efforts in industry to improve supply chain resilience. Hopefully the research opportunities identified can inspire the flurry of research that can be expected in response to the multiple special issues planned by journals in our field.

Purpose This study aims to explore the interplay between supply chain collaboration and disruption and their joint impact on supply chain resilience. It also aims to identify the configurational conditions under which supply chain resilience is achieved, providing a holistic framework for enhancing supply chain management practices amidst disruptions. Design/methodology/approach This study uses a fuzzy-set qualitative comparative analysis (fsQCA) to investigate the complex causal mechanisms linking supply chain collaboration and disruption with supply chain resilience. The research integrates three dimensions of collaboration with three dimensions of disruption, offering a comprehensive understanding of supply chain resilience factors. Findings This study reveals that supply chain resilience is not solely dependent on individual elements but is shaped by unique configurations of collaboration and disruption factors. Information sharing emerges as a core factor in high resilience, while the absence of supply and facility disruptions significantly influences resilience outcomes. The research highlights the importance of multiple paths leading to supply chain resilience and the asymmetrical impact of collaboration and disruption. Research limitations/implications The study acknowledges limitations due to data sourced exclusively from China and the use of static data, suggesting the need for cross-temporal and international samples to enhance broader applicability. Future research should consider dynamic temporal changes and diverse theoretical perspectives to comprehensively examine the factors influencing supply chain resilience. Practical implications The research underscores the critical role of information sharing in bolstering supply chain resilience and advises firms to prioritize it in their strategies. It also highlights the importance of mitigating supply and facility disruptions through supplier diversification and robust contingency planning, offering actionable insights for enhancing operational efficiency and risk management in supply chain management. Social implications This research has significant social implications, particularly in the context of global supply chain disruptions. By identifying key factors that enhance supply chain resilience, it can help businesses better prepare for and respond to crises, thereby reducing economic instability and social disruption. Improved resilience can lead to more stable employment, maintain the flow of essential goods and services and contribute to overall societal well-being during times of supply chain stress. Originality/value This study offers original insights by applying fsQCA to explore the multifaceted relationship between supply chain collaboration, disruption and resilience. Its value lies in revealing the complex causal configurations that lead to high or low levels of supply chain resilience, challenging traditional linear perspectives and providing a nuanced understanding that can guide both academic research and practical supply chain management strategies.

Purpose– Supply chains (SCs) have become increasingly vulnerable to catastrophic events/disruptions that may be natural or man-made. Hurricanes, tsunamis and floods are natural disasters, whereas man-made disasters may be strikes, terrorist attacks, etc. Failure at any point in the SC network has the potential to cause the entire network to fail. SCs must therefore be properly designed to survive well in the disruption scenario. The capability of successful survival (of the firm’s SC) against those adverse events/happenings is termed as resilience; and, the SC designed under resilience consideration is called a resilient SC. Effective supplier selection is considered as a key strategic consideration in SC management. It is felt that apart from considering traditional suppliers selection criterions, suppliers’ resiliency strategy must be incorporated while selecting a potential supplier which can provide best support to the firm even in the disaster/disruption scenario. The purpose of this paper is to focus aspects of evaluation and selection of resilience supplier by considering general as well as resiliency strategy, simultaneously.Design/methodology/approach– In this work, subjectivity associated with ill-defined (vague) evaluation information has been tackled through logical exploration of fuzzy numbers set theory. Application of VIKOR embedded with fuzzy mathematics has been utilized here. Sensitivity analysis has been performed to reflect the effect of decision-makers’ (DM) risk bearing attitude in selecting the best potential supplier in a resilient SC. A case empirical example has also been presented.Findings– The work attempts to focus on a decision-making procedural hierarchy towards effective supplier selection in a resilient SC. The work exhibits application potential of VIKOR method integrated with fuzzy set theory to select potential supplier based on general strategy as well as resiliency strategy. The final supplier selection score (obtained by considering general strategy) and that of obtained by analyzing resiliency strategy have been combined to get a final compromise solution. The decision-support framework thus reported here also considers DMs’ risk bearing attitude.Practical implications– The study bears significant impact to the industry managers who are trying to adapt resiliency strategy in their SC followed by potential supplier selection in the context of resilient SC.Originality/value– Exploration of VIKOR embedded with fuzzy set theory towards suppliers’ evaluation and selection by considering general and resiliency criteria both. The decision-support module(s) adapted in this paper considers DMs’ risk bearing attitude to arrive the best compromise solution.

PurposeOrganisations must build resilience to be able to deal with disruptions or non-routine events in their supply chains. While learning is implicit in definitions of supply chain resilience (SCRes), there is little understanding of how exactly organisations can adapt their routines to build resilience. The purpose of this study is to address this gap.Design/methodology/approachThis paper is an in-depth qualitative case study based on 28 interviews across five companies, exploring learning to build SCRes.FindingsThis study uncovers six learning mechanisms and their antecedents that foster SCRes. The learning mechanisms identified suggest that through knowledge creation within an organisation and knowledge transfer across the supply chain and broader network of stakeholders, operating routines are built and/or adapted both intentionally and unintentionally during three stages of a supply chain disruption: preparation, response and recovery.Practical implicationsThis study shows how the impact of a supply chain disruption may be reduced by intentional and unintentional learning in all three disruption phases. By being aware of the antecedents of unintentional learning, organisations can more consciously adapt routines. Furthermore, findings highlight the potential value of additional attention to knowledge transfer, particularly in relation to collaborative and vicarious learning across the supply chain and broader network of stakeholders not only in preparation for, but also in response to and recovery from disruptions.Originality/valueThis study contributes novel insights about how learning leads both directly and indirectly to the evolution of operating routines that help an organisation and its supply chains to deal with disruptions. Results detail six specific learning mechanisms for knowledge creation and knowledge transfer and their antecedents for building SCRes. In doing so, this study provides new fine-grained theoretical insights about how SCRes can be improved through all three phases of a disruption. Propositions are developed for theory development.

Supply chain resilience and structure: An evaluation framework

Enhancing the supply chain resilience of the information and communications manufacturing industry is closely related to the competitiveness of enterprises and the security of the national economy, and has attracted widespread attention from all sectors of society. This study develops a multidimensional synergistic resilience framework based on the Technology-Organization-Environment theory. Using panel data from 29 Chinese provinces over the 2011–2022 period, it empirically examines the impact of artificial intelligence technology on supply chain resilience in the information and communication technology manufacturing industry and investigates its underlying mechanisms. Research findings: Artificial intelligence significantly enhances supply chain resilience, and this conclusion holds after a series of endogeneity and robustness tests. Mechanism analysis reveals that artificial intelligence promotes the low-carbon transition by optimizing energy intensity and synergistically enhances resilience effects through technological innovation. Heterogeneity analysis shows that the impact of artificial intelligence on supply chain resilience is stronger in eastern China, significantly outperforming western China, but its effect in central China is not significant. Supply chain disruptions weaken the positive effects generated by artificial intelligence when they occur. The research provides a theoretical foundation and practical basis for improving the resilience of information and communications manufacturing supply chain networks, thereby contributing to the development of intelligent, resilient and sustainable supply chain networks.

Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model

This study investigates supply chain (SC) disruptions in order to present a conceptual framework in line with evaluating and improving resiliency in SC networks. The SCs resiliency may be affected by various different factors and certainly simultaneously improving all factors is impossible. So practitioners need to find out the most important factors to improve those factors. This study segmenting complex influencing resilience factors into groups to improve them in a stepwise way. For this purpose, based on the literature reviews, key resilience factors were recognised and redefined for SC networks. Then, decision making trial and evaluation laboratory (DEMATEL) method is used to identify critical success resilience factors in SCs. To this end, a questionnaire is constructed and answered by experts to obtain the degree of the direct affect between each pair of capabilities. To deal with uncertainties associated with expert's judgments, fuzzy theory is employed. With this method, practitioners can identify the factors that have greatest impact on SCs resiliency and the casual relations among the factors are constructed through a cause-effect relationship diagram. The proposed policy is to help managers to identify the most appropriate strategy for surviving SCs from disruptions.

In the face of global competition, competitive enterprises should pursue sustainable development, and strengthen their supply chain resilience to cope with risks at any time. In addition, big data analysis has been successfully applied in a variety of fields. However, the method has not been applied to improve supply chain resilience in order to reduce sustainable supply chain risks. An approach for enhancing the capabilities of big data analytics must be developed to enhance supply chain resilience, and mitigate sustainable supply chain risks. In this study, a decision framework that integrates two-stage House of Quality and multicriteria decision-making was constructed. By applying this framework, enterprise decision-makers can identify big data analytics that improve supply chain resilience, and resilience indicators that reduce sustainable supply chain risks. A case study of one of China’s largest relay manufacturers is presented to demonstrate the practicability of the framework. The results showed that the key sustainable supply chain risks are risks regarding the IT infrastructure and information system efficiency, customer supply disruptions, transport disruptions, natural disasters, and government instability. To reduce risk in sustainable supply chains, enterprises must improve the key resilience indicators ‘financial capability’, ‘flexibility’, ‘corporate culture’, ‘information sharing’, and ‘robustness’. Moreover, to increase supply chain resilience, the following most important big data analysis enablers should be considered: ‘capital investment’, ‘building big data sharing mechanism and visualisation’, and ‘strengthening big data infrastructures to support platforms and systems’. This decision framework helps companies prioritise big data analysis enablers to mitigate sustainable supply chain risks in manufacturing organisations by strengthening supply chain resilience. The identified priorities will benefit companies that are using big data strategies and pursuing supply chain resilience initiatives. In addition, the results of this study show the direction of creating a fruitful combination of big data technologies and supply chain resilience to effectively mitigate sustainable risks. Despite the limited enterprise resources, management decision-makers can determine where big data analysis enablers can be most cost-effectively improved to promote risk resilience of sustainable supply chains; this ensures the efficient implementation of effective big data strategies.

PurposeHealthcare organizations are placing greater emphasis on enhancing supply chain performance to cut costs and boost operational efficiency. Despite the growth of literature on the relevance of contemporary supply chain technologies in enhancing supply chain performance, it is still unclear how healthcare organizations could leverage supply chain analytics through supply chain strategies to improve healthcare supply chain performance (HSCP). This paper attempts to bridge this gap by examining how enhanced HSCP could be achieved through supply chain analytics (SCA) as well as building responsive, resilient, and reconfiguration (3Rs) SCs. The paper further assessed the moderating role of desorptive capacity between SCA and HSCP.Design/methodology/approachThe practice-based view motivated the study. The model underwent validation using primary data collected from 374 managers of healthcare facilities in Ghana. Data analysis was conducted using a structural equation model.FindingsThe findings revealed that SCA significantly drives HSCP, supply chain resilience, responsiveness, and reconfiguration. The findings further showed that the three supply chain strategies (supply chain resilience, responsiveness, and reconfiguration) aid in channeling the effect of SCA to drive enhanced HSCP. Finally, we also observed high levels of desorptive capacity amplifying SCA’s impact on HSCP.Practical implicationsThis paper makes important contributions to both literature and practice by empirically demonstrating how the effect of SCA can be channeled through supply chain strategies (supply chain resilience, responsiveness, and reconfiguration) to enhance SCP at varying levels of desorptive capacity. Practically, our study has demonstrated that SCA is not a “silver bullet” and that it must be integrated with supply chain strategies to reap the full benefits.Originality/valueTo the best of our knowledge, this paper is among the few attempts to empirically validate the relevance of supply chain analytics from the healthcare perspective. Moreover, the novelty of this paper demonstrates the coverage of the newfound mechanism, where supply chain resilience, responsiveness, and reconfiguration mediate and desorptive capacity moderate SCA and HSCP relationship. Finally, the paper questions the use of traditional organizational theories (RBV and DCT) and validates the applicability of a practice-based view as an alternative theoretical lens that could offer more nuanced insights into the unique characteristics and challenges of healthcare supply chains.

This study investigates supply chain (SC) disruptions in order to present a conceptual framework in line with evaluating and improving resiliency in SC networks. The SCs resiliency may be affected by various different factors and certainly simultaneously improving all factors is impossible. So practitioners need to find out the most important factors to improve those factors. This study segmenting complex influencing resilience factors into groups to improve them in a stepwise way. For this purpose, based on the literature reviews, key resilience factors were recognised and redefined for SC networks. Then, decision making trial and evaluation laboratory (DEMATEL) method is used to identify critical success resilience factors in SCs. To this end, a questionnaire is constructed and answered by experts to obtain the degree of the direct affect between each pair of capabilities. To deal with uncertainties associated with expert's judgments, fuzzy theory is employed. With this method, practitioners can identify the factors that have greatest impact on SCs resiliency and the casual relations among the factors are constructed through a cause-effect relationship diagram. The proposed policy is to help managers to identify the most appropriate strategy for surviving SCs from disruptions.

The Importance of Supply Chain Resilience: An Empirical Investigation

The aim of this study is to investigate the effect of supply chain risk management on supply chain resilience in the presence of Internet-of-Things as an intermediate variable. In other words, the study seeks to identify whether supply chain risk management completely affects supply chain resilience. Collecting data by a questionnaire from a sample composed of managers of Jordanian industrial firms, the results show that supply chain risk management has a direct and indirect effect on supply chain resilience through Internet-of-Things. These results do not support the hypothesis that supply chain risk management completely affects supply chain resilience and accepted the hypothesis that Internet-of-Things intervenes the effect of supply chain risk management on supply chain resilience. The study contributes to the literature through filling a research gap regarding the mediating role of Internet-of-Things in the relationship between supply chain risk management and supply chain resilience and contributes to the industry through instructing managers to adopt technologies such as Internet-of-Things to help their firms cope with supply chain risks.

Pig sector in China is faced with high risks, such as price fluctuation and food safety, and environmental regulation uncertainty. The recent African swine fever has caused public panic and drop down of pork consumption in a short term. The “wu-shui-gong-zhi” policy is a newly recognized environmental policy risk, and its key content is to shut down directly the pig farms close to water resources. Lots of small- and medium-sized farms have been affected, especially in coastal provinces. Supply chain integration received wide attention in supply chain management. Literature has shown that a well-coordinated food supply chain will bring positive outcomes for chain stakeholders. However, the relationship between food supply chain integration and resilience is not empirically captured. This research aims to explore the relationship between supply chain integration and supply chain resilience, and the mechanism of how supply chain integration works on supply chain resilience. To achieve the research purpose, an in-depth ethnographical case study is performed. Four cases in China’s pig sector were selected, with different types of supply chain integration between cooperative and companies. They differ in supply chain resilience levels. We found that supply chain integration has a positive effect on supply chain resilience through agility and robustness. Supply chain agility also has positive relationship with supply chain robustness. It implies that supply chain stakeholders should efficiently exchange information, enhance circulation rate, and jointly make plans to be more resilient to risks. The government needs to make policies to encourage and facilitate supply chain integration among supply chain members to enhance supply chain resilience.

PurposeThe coronavirus disease 2019 (COVID-19) pandemic unveiled resilience deficits in supply chains. Scholars and practitioners aim to identify supply chain resilience (SCRES) measures suitable for this unique disruption; however, empirical evidence on a pandemic's specific characteristics, resulting challenges, and suitable countermeasures is scarce.Design/methodology/approachA single-case study on an automotive supply chain network (ASCN), including eight nodes, was conducted. Based on current research and interviews with 35 experts, characteristic pandemic challenges for the ASCN were identified. Moreover, promising SCRES measures were determined along the most prominent SCRES levers. The findings lead to five central propositions and advance organizational information processing theory in the context of SCRES.FindingsThis study’s results confirm unique pandemic characteristics along the supply chain disruption's duration, severity, propagation, and volatility. The resulting unprecedented challenges made the ASCN apply novel SCRES measures, particularly regarding collaboration and risk management culture. However, well-known visibility and flexibility strategies were also suitable. Overall, agility and collaboration measures showed the highest capacity to address characteristic pandemic challenges. A lack of preparedness impeded some measures' application, calling for enhanced proactive risk management following the pandemic.Originality/valueThis paper addresses several research calls by providing in-depth empirical evidence on hitherto conceptually researched pandemic characteristics, challenges, and suitable SCRES measures from a network perspective. The study uncovers the different perceptions of individual tiers, emphasizing the need to analyze supply chain disruptions from multiple angles.