Building supply chain risk resilience: Role of big data analytics in supply chain disruption mitigation

Unlocking sustainable supply chain performance through dynamic data analytics: a multiple mediation model of sustainable innovation and supply chain resilience

This article provides a theoretical framework for comprehending the connections between dynamic data analytics capability (DDAC), innovation capabilities (IC), supply chain resilience (RES), and sustainable supply chain performance (SSCP). Since this is the first empirical investigation of the sequential mediation effect between DDAC and SSCP through IC and RES, it fills a critical need in the supply chain literature. A quantitative methodology was used, involving a survey questionnaire distributed to 259 large Pakistani manufacturing firms. We used PLS-SEM to test for the expected associations. Findings show that using DDAC has a beneficial effect on both innovative and resilient capabilities, which in turn leads to better SSCP. The research illuminates the sequential mediating roles of product, process, and resilience, underlining the need of combining data-driven innovation with resilience in order to achieve sustainable supply chain performance. These results provide useful guidance for businesses that want to boost their sustainability results by taking a more all-encompassing approach to data-driven innovation and resilience.

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

The outbreak of COVID-19 has accelerated the building of resilient supply chains, and supply chain digitalization is gradually being recognized as an enabling means to this end. Nevertheless, scholars generally agree that more empirical studies will need to be conducted on how digitalization can facilitate supply chain resilience at various stages and enhance supply chain performance in a highly uncertain environment. To echo the call, this study develops a theoretical influence mechanism of "supply chain digitalization → supply chain resilience → supply chain performance" based on dynamic capability theory. The proposed relationships are validated using survey data collected from 210 Chinese manufacturing companies. The results help identify the paths digitalization and supply chain resilience can take to improve supply chain performance in a turbulent environment. The different roles of three supply chain resilience capabilities, namely absorptive capability (before the disruption), response capability (during the disruption), and recovery capability (after the disruption), which impact on supply chain performance differently, are highlighted. In addition, it is found that digitalization can bring a differential impact on these three supply chain resilience capabilities through different aspects of resource and structural adjustment measures. The findings also confirm the mediating role of absorptive capability, response capability, and recovery capability between digitalization and supply chain performance. During crisis, supply chain digitalization can increase cost-effectiveness, enhance information and communication efficiency, and promote supply chain resilience to achieve better performance. For theoretical contribution, this study enriches the research on supply chain digitalization and resilience by underpinning the relationships between the two with dynamic capability theory. For practical contribution, the research findings provide insights for enterprises to leverage digitalization to strengthen resilience in supply chain.

What Can Managers Learn From Professional Poker Players About Decision-Making?

This paper aims to investigate how past decision-making experiences can improve future decision-making. Nine semi-structured interviews were conducted with profitable professional Poker players. The results point out that it is the knowledge background of the decision-maker that makes him make sense of the situations he experiences. The research findings allowed the identification of three mechanisms that facilitate and make future decisions faster and more appropriate based on past experiences: (1) memory, (2) reflection, and (3) tools and analytical approach. The research contributes by showing evidence that, when supported by analytical tools, decision-makers can improve the quality and speed of the decision-making process. For organizations and supply chains, the paper highlights the importance of recognizing patterns based on the past to make sense of the future. For operations management, in events like COVID-19, companies can take advantage of memory to enact over unprecedented scenarios, prevent disruptions, and recover.

Prescriptive analytics applications in sustainable operations research: conceptual framework and future research challenges

In the broad sphere of Analytics, prescriptive analytics is one of the emerging areas of interest for both academicians and practitioners. As prescriptive analytics has transitioned from its inception to an emerging topic, there is a need to review existing literature in order to ascertain development in this area. There are a very few reviews in the related field but not specifically on the applications of prescriptive analytics in sustainable operations research using content analysis. To address this gap, we performed a review of 147 articles published in peer-reviewed academic journals from 2010 to August 2021. Using content analysis, we have identified the five emerging research themes. Through this study, we aim to contribute to the literature on prescriptive analytics by identifying and proposing emerging research themes and future research directions. Based on our literature review, we propose a conceptual framework for studying the impacts of the adoption of prescriptive analytics and its impact on sustainable supply chain resilience, sustainable supply chain performance and competitive advantage. Finally, the paper acknowledges the managerial implications, theoretical contribution and the limitations of this study.

Synthesis of strategies in post-COVID-19 public sector supply chains under an intuitionistic fuzzy environment

Entities in public sector supply chains (SCs) often operate independently despite having interdependent objectives. Such a fragmented operational design poses several problems magnified by the presence of necessary public health measures fueled by COVID-19. This work contributes to the domain literature by introducing an overarching framework for synthesizing strategies in public sector SCs. The underlying component is the translation of information from the upstream to the downstream entities of the SCs, which is carried out by a Kano-enhanced quality function deployment. The proposed framework introduces intuitionistic fuzzy (IF) decision maps with the aid of the full consistency method to incorporate inherent interrelationships among strategies in the translation agenda. Under an IF environment that better captures judgment uncertainties, an actual case study of a multi-level public sector SC motivated by a government-funded project under the COVID-19 pandemic is demonstrated in this work. Findings of the case suggest that the government prioritizes meeting all project objectives. This requirement is reflected in the downstream SC. The project planning entity focuses on creating an overarching plan of operations, material request entity on complying with government procurement protocols, and maintaining public health and safety in operations for the procurement entity. Results show the effective synthesis of strategies across the SC, ensuring SC integration and collaboration. The case study demonstrates that maintaining public health and safety is a significant component of post-COVID-19 public sector SCs. Several practical insights on the synthesis of public sector SC strategies are also provided in this work.

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience.

Predicting supply chain risks through big data analytics: role of risk alert tool in mitigating business disruption

Purpose

As organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how to effectively manage the increasing risks to their supply chain. Therefore, the purpose of this paper is to bring these two issues on a single platform to understand how firms can effectively predict supply chain risk by developing and using BDA capabilities, through an automated risk alert tool.

Design/methodology/approach

The authors used a questionnaire-based survey methodology supported by secondary data to collect information related to managerial perceptions on how firms can develop a risk alert tool by improving BDA capabilities. A database of 213 senior and middle-level managers was developed and used to test the proposed hypothesis. Using econometric techniques, the authors identify the conditions necessary for such an automated risk management tool to be effective.

Findings

The results suggest that if organizations focus on developing an effective IT infrastructure supported by a strong BDA capability, they will be able to leverage these capabilities to develop an effective risk management tool. Moderating influences of Upstream and Downstream Supply Chain IT Infrastructure capabilities were also observed on different types of BDA capabilities within a firm. In conclusion, it was argued that the effectiveness of a risk alert tool is dependent on how well firms harness big data analytics capability.

Originality/value

The value of the research stems from the fact that it uses managerial surveys to identify specific BDA capabilities that can enable firms to develop risk resilience capabilities. In addition, the article is one of the few empirical studies that aims to identify how firms can use BDA capabilities within a supply chain context to develop an automated risk alert tool. The article, therefore, contributes to the literature that identifies the value of BDA capabilities within the context of supply chain risk management.

Digital Innovation, Data Analytics, and Supply Chain Resiliency: A Bibliometric-based Systematic Literature Review

In recent times, the literature has seen considerable growth in research at the intersection of digital innovation, data analytics, and supply chain resilience. While the number of studies on the topic has been burgeoning, due to the absence of a comprehensive literature review, it remains unclear what aspects of the subject have already been investigated and what are the avenues for impactful future research. Integrating bibliometric analysis with a systematic review approach, this paper offers the review of 262 articles at the nexus of innovative technologies, data analytics, and supply chain resiliency. The analysis uncovers the critical research clusters, the evolution of research over time, knowledge trajectories and methodological development in the area. Our thorough analysis enriches contemporary knowledge on the subject by consolidating the dispersed literature on the significance of innovative technologies, data analytics and supply chain resilience thereby recognizing major research clusters or domains and fruitful paths for future research. The review also helps improve practitioners' awareness of the recent research on the topic by recapping key findings of a large amount of literature in one place.

The interplay between relationships, technologies and organizational structures in enhancing supply chain resilience: empirical evidence from a Delphi study

Purpose

COVID-19 has highlighted the need to reflect on how firms should improve their supply chains (SCs) to enhance agility and robustness. Recent studies focus more on the short-term rather than on the long-term developments and lack insights regarding the enhancement of supply chain resilience (SCRES) based on the interplay between multiple levers. Therefore, using a long-term perspective, this research evaluates the interaction between three SCRES levers – relationships, technologies and organizational structures – to improve SCRES.

Design/methodology/approach

Based on an extensive literature review, multiple interviews and workshops, 13 future projections were developed. These projections were assessed using a two-round Delphi study that included 83 international experts from industry, academia and politics/associations to determine the probability of occurrence by 2035, their impact on SCRES and their desirability.

Findings

This study provides empirical evidence that the long-term enhancement of SCRES is achieved through the interplay of multiple levers rather than unilateral optimization. The study suggests that, by 2035, collaboration between SC partners will be a key factor for SCRES enhancement. Additionally, SC stakeholders should be aware that failing to invest in digital technologies will negatively impact the agility and robustness of future SCs. Furthermore, humans are expected to continue to play a major role, given that relationship-oriented tasks are perceived to remain important.

Originality/value

This paper adds to current literature, describing how SCRES can be improved in the long term through the interplay of multiple levers and the combination of robust and agile elements. Considering the importance of ensuring resilient SCs, this paper provides valuable insights for academics and practitioners.

Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework

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.

Building SMEs’ resilience in times of uncertainty: the role of big data analytics capability and co-innovation

Purpose

This paper aims to enhance the small and medium enterprises’ (SMEs) ability to develop resilience in the face of any turbulences, addressing the question on how these organizations can maintain business continuity when faced with a critical event.

Design/methodology/approach

A mediated regression analysis is conducted to investigate the relationships among big data analytics (BDA) capabilities, coinnovation (CI) and organizational resilience (OR) with reference to 192 big data SMEs in Europe.

Findings

Research reveals that the BDA capability and CI are positively associated with OR. Moreover, this study discovers the mediating impact of CI on the relationship between BDA capability and OR.

Originality/value

This paper provides important implications for considering CI as a viable strategy especially in a time of crisis and shows how SMEs are more able to recognize business opportunities. The microfoundations of the resilience building capacity of SMEs are also identified. These microfoundations become recommendations for practitioners to enhance SMEs’ responsiveness in light of coronavirus-related crises.

Big data analytics capability and supply chain performance: the mediating roles of supply chain resilience and innovation

Purpose

Big data analytics (BDA) capabilities can affect supply chain performance in several ways. The main purpose of this study was to understand how BDA capabilities could affect supply chain performance through supply chain resilience and supply chain innovation.

Design/methodology/approach

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. Accordingly, 187 responses were collected and analyzed using partial least squares (PLS) in the SmartPLS3.

Findings

The results showed that BDA capabilities improve supply chain performance through resilience and innovation of the supply chain.

Originality/value

The present study also contributed to the existing literature by demonstrating the mediating role of supply chain resilience and supply chain innovation between BDA capabilities and supply chain performance. In this context, some theoretical and managerial implications were proposed and discussed.

Contributions of Healthcare 4.0 digital applications to the resilience of healthcare organizations during the COVID-19 outbreak

In this paper, we examine the contributions of digital applications to the resilience of healthcare organizations during the COVID-19 outbreak. The studied applications are framed as Healthcare 4.0 (H4.0), comprising bundles of information and communication technologies used to improve operations in the health value chain. Data collection was carried out through semi-structured interviews with 10 senior managers from clinician and non-clinician departments of two large-sized Brazilian hospitals treating patients infected with SARS-CoV-2. Interviews were analyzed through content analysis, using data analysis categories related to the application focus (i.e., supply chain, patient diagnosis, patient treatment, and patient follow-up) and targeted resilience ability (i.e., monitor, anticipate, respond, and learn). Results indicate that applications oriented to supply chain and patient diagnosis contribute to all resilience abilities. Furthermore, depending on the resilience ability to be improved, different applications may be prioritized. Four research propositions for theory-testing in future studies are also presented.

Procurement process risk and performance: empirical evidence from manufacturing firms

Purpose

This paper employs the positivism paradigm, quantitative approach and explanatory research design. It analyses primary data obtained from manufacturing firms via structured questionnaires and uses the partial least square-structural equation modelling technique to establish the effect of individual procurement process risk on procurement performance.

Design/methodology/approach

Procurement risks are inevitable in manufacturing procurement process; a situation that could undermine the performance of manufacturing firms if not properly managed. Yet, with procurement accounting of about 14–19% of developing countries gross domestic product, the effects of procurement process risk on performance remain scarce in manufacturing firms in developing countries. Therefore, the paper aims to investigate the effect of procurement process risk on procurement performance of manufacturing firms.

Findings

In this paper, five out of the six procurement process risks studied were found to be undermining procurement performance of manufacturing firms significantly. However, the risk threshold effect on the performance differs.

Research limitations/implications

Although this research is geographically/sector bias, several insightful managerial implications can be drawn to manage procurement process risk in manufacturing settings irrespective of the area of operation. The results of this research imply that manufacturing firms' procurement process is risk prone and the effect of risk surrounding each procurement process on procurement performance differs. Hence, the need to identify and analyse the risks surrounding each procurement process before making managerial decision to spend firms limited resources in response to the individual risk to improve procurement performance in the manufacturing sector.

Originality/value

This paper is the first to provide existing and future procuring practitioners/firms with in-depth empirical evidence of the effect of the procurement process risks on procurement performance in manufacturing firms operating in developing economies.

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions.

Enhancing Value Co-Creation Through the Lens of DART Model, Innovation, and Digital Technology: An Integrative Supply Chain Resilient Model

The global supply chain process has been badly affected by the COVID-19 pandemic. Consequently, firms search for factors that influence supply chain resilience and improve firm operational performance. The current research develops an integrated resilient supply chain model that combines factors underpinned DART model, innovation, digital technology, and value co-creation to investigate supply chain resilience during the COVID-19 pandemic. The research framework was empirically tested with a data set of 329 responses from employees working in logistics firms. the study find that supply chain resilience is determined by value co-creation, the DART model, innovation, and digital technology. The factors underpinning the DART model, including dialogue, access, risk assessment, and transparency, have positively impacted value co-creation. The structural model shows that dialogue has a positive impact on developing value co-creation between manufacturing firms and stakeholders, Empirical investigation revealed that value co-creation in supply chain operations is estimated by dialogue, access, risk assessment, transparency, innovation, and digital technology and revealed substantial variance R^2 71.9% in measuring value co-creation. This research is significant as it develops a resilient supply chain model with the combination of the DART model, innovation, digital technology, and value co-creation and investigates supply chain resilience during the COVID-19 pandemic. Although current research contributes to theory, practice, and method, disclosing research limitations opens numerous avenues for future researchers. This study does not claim to include all factors that impact the value co-creation process in supply chain operations. For instance, other factors, such as IT infrastructure, commitment, and integrative quality, may positively influence value co-creation. Second, supply chain resilience is determined by value co-creation and network capability. Therefore, the research encourages academicians and policymakers to investigate the supply chain resilience phenomenon with other market-oriented facts. future researchers are suggested to investigate the current research model in longitudinal method

A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy

While embracing digitalization that is further accentuated by the Covid-19 pandemic, the real business outcome is achieved through a robust and well-crafted ‘Data Science Strategy’ (DSS), as significant constituent of Enterprise Digital Strategy. Extant literature has studied the challenges in adoption of components of ‘Data Science’ in discrete for various industry sectors and domains. There is dearth of studies on comprehensive ‘Data Science’ adoption as an umbrella constituting all of its components. The study conducts a “Systematic Literature Review (SLR)” on enablers and barriers affecting the implementation and success of DSS in enterprises. The SLR comprised of 113 published articles during the period 1998 and 2021. In this SLR, we address the gap by synthesizing and proposing a novel framework of ‘Enablers and Barriers’ influencing the success of DSS in enterprises. The proposed framework of ‘Data Science Strategy’ can help organizations taking the right steps towards successful implementation of ‘Data Science’ projects.

Insights from systematic literature review of supply chain resilience and disruption

Purpose

The study of supply chain disruption (SCD) and supply chain resilience (SCR) remains to be studied deeply in the field of business management. The purpose of this paper is to showcase a framework of SCR strategies to reduce the adverse effects of SCD using systematic literature review and data visualization.

Design/methodology/approach

Using a systematic literature review approach, the paper explores the concepts of supply chain disruption and supply chain resilience. Through rigorous systematic screening, authors studied papers on both the concepts and have proposed a framework for the same. The authors also have used data visualization and network diagram approaches for better understanding of the topic.

Findings

The systematic literature review of both the concepts brings out some exciting results which give a new direction to supply chain field. The outcome of this research also outlines numerous future research direction, which will be useful for the research community.

Practical implications

The numerous strategies of SCR should be implemented by manufacturing as well as a service organization. The framework reported in this research help academician and practitioners to understand SCR and to easily overcome any level of disruption. Supply chain managers must also formulate strategies accordingly and make plans to continually expand the system.

Originality/value

This research is the first such attempt to showcase a formal systematic framework and co-occurrence networks as well as overlay networks of SCR and SCD.

The role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries

Purpose

Big data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.

Design/methodology/approach

A two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.

Findings

Statistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.

Research limitations/implications

This study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.

Originality/value

For the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.

Supply chain resilience during the COVID-19: empirical evidence from an emerging economy

Purpose

Although the advances in the supply chain resilience (SCR) literature, there is a critical gap concerning this understanding in a high disruption context, such as in the case of the COVID-19. This paper aims to investigate some dimensions (agility, robustness, disruption orientation and resource reconfiguration) of the SCR during this unprecedented disruption in the Brazilian supply chain context.

Design/methodology/approach

Supported by the resource-based view, dynamic capabilities and the SCR literature, we developed a model, which in turn was analyzed and validated by partial least squares structural equation modelling.

Findings

The results revealed that while resource reconfiguration and supply chain disruption orientation positively affect SCR, we found a non-significant effect of supply chain robustness and agility.

Practical implications

The findings suggest that in a considerable disruption scenario, managers with their supply chain operations in emerging economies should prioritize the development of resources to support the disruption orientation and manage the scarce resources adequately by reconfiguring them.

Originality/value

Our study is one of the first that reported the dynamics of the SCR dimensions in an emerging economy during the COVID-19.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

Purpose

Big data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.

Design/methodology/approach

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.

Findings

The results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.

Originality/value

The present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

Contributions of Industry 4.0 to supply chain resilience

Purpose

This study aims at identifying the contribution of Industry 4.0 (I4.0) integration into supply chains (SCs) to the enhancement of SC resilience.

Design/methodology/approach

A scoping review was conducted so that the relevant literature on SC resilience, and I4.0 integrated into SC management was examined.

Findings

The authors summarize the main findings from existing research and propose three research directions: (1) empirical validation of the contribution of I4.0 ICTs to SC resilience; (2) explore the role of processing-actuation technologies in enhancing restorative capacity; and (3) integration between I4.0 ICTs and omni-channel strategy as a means to resilience development at consumer and retail levels. The literature on the design of resilient smart SCs is far outnumbered by works reporting applications of I4.0 ICTs at different SC tier levels. However, the authors’ scoping review organizes the information available on these themes, setting the ground for the development of new theoretical propositions.

Originality/value

The integration of digital technologies from I4.0 can fundamentally change the SC management, acting as enablers of a more effective response to disruptions. However, the digital transformation of SCs is still incipient, and literature is particularly sparse when considering the contribution of I4.0 to the resilience of SCs.

Improving supply chain resilience through industry 4.0: A systematic literature review under the impressions of the COVID-19 pandemic

The COVID-19 pandemic is one of the most severe supply chain disruptions in history and has challenged practitioners and scholars to improve the resilience of supply chains. Recent technological progress, especially industry 4.0, indicates promising possibilities to mitigate supply chain risks such as the COVID-19 pandemic. However, the literature lacks a comprehensive analysis of the link between industry 4.0 and supply chain resilience. To close this research gap, we present evidence from a systematic literature review, including 62 papers from high-quality journals. Based on a categorization of industry 4.0 enabler technologies and supply chain resilience antecedents, we introduce a holistic framework depicting the relationship between both areas while exploring the current state-of-the-art. To verify industry 4.0's resilience opportunities in a severe supply chain disruption, we apply our framework to a use case, the COVID-19-affected automotive industry. Overall, our results reveal that big data analytics is particularly suitable for improving supply chain resilience, while other industry 4.0 enabler technologies, including additive manufacturing and cyber-physical systems, still lack proof of effectiveness. Moreover, we demonstrate that visibility and velocity are the resilience antecedents that benefit most from industry 4.0 implementation. We also establish that industry 4.0 holistically supports pre-disruption resilience measures, enabling more effective proactive risk management. Both research and practice can benefit from this study. While scholars may analyze resilience potentials of under-explored enabler technologies, practitioners can use our findings to guide industry 4.0 investment decisions.

Managing the adverse effect of supply chain risk on corporate reputation: The mediating role of corporate social responsibility practices

Within the last decade, research has focussed on corporate social responsibility (CSR) practices as a strategic tool that enables firms to improve stakeholder perception, brand image and corporate reputation. However, one area that remains understudied is the role played by CSR practices in managing corporate reputation under conditions of supply chain risk. To answer this research question, we conduct a literature review and develop the corresponding hypothesis. We test our hypothesis using quantitative analysis of both primary and secondary data collected from organizations dispersed globally. The results highlight that under conditions of supply chain network disruption risk, CSR practices play an important role in enabling firms to manage the negative impact of such risk drivers on corporate reputation. The study further suggests that CSR practices positively impact supply chain risk management (SCRM) practices and are a necessary condition for SCRM practices to be effective in improving corporate reputation of organizations.

The Performance of Resilient Supply Chain Sustainability in Covid-19 by Sourcing Technological Integration

The present study describes technological integration as source of the sustainable supply chain resilience. The implementation of sustainable supply chain resilience has recently played a vital role, owing to its substantial factors which influence the business continuity. The influence of sustainable supply chain resilience is greatly varying, to embrace companies’ efficiency during a crisis such as COVID-19. In the present study, systematic model-based integration of sustainable supply chain resilience is developed, which can benefit the companies’ profile of work normalcy during the pandemic situation by managing the associated risks. Different variable factors are considered, to assess their impact on the sustainable supply chain. These factors are environmental regulatory system, customer response monitoring system, environmental uncertainty, interoperability and operational integration. Data were collected by questionnaire and analyzed with statistical tools of interpretation. This research is concluded with the assessment that there is a significant correlation between technological integration and the resilient supply chain’s sustainability. The business organizations need to understand the current COVID-19 situation, the supply chain issues, and their impact on the other factors. Business organizations need to implement international quality standards through the use of technology. This study highlights the critical components of technological advancement, which can uplift the existing standards. Overall, the study portrays the recent sustainable supply chain resilience-based orientation to cope with the current pandemic situation.

Enabling Blockchain Based SCM Systems with a Real Time Event Monitoring Function for Preemptive Risk Management

The risk of supply chain disruption is usually related to daily disturbances in supply chain operations (e.g., demand fluctuations) and some emergency risks, such as earthquakes and epidemic outbreaks. During a crisis, companies need agility to quickly find new suppliers and open auxiliary sales channels to meet customer needs and remain competitive. However, identifying “event” is one of the most difficult challenges of current decision support systems. If the system encounters an emergency, it is usually unable to promptly notify users of the warning to avoid risks. A sensible solution is to incorporate the real-time event-monitoring system into SCM (i.e., supply chain management) in order to share emergency information in the early stage for preemptive management in the supply chain. On the other hand, in order to process confidential supply chain data with other members, the SCM infrastructure requires secure data sharing. The blockchain-based SCM system can improve the transparency of traceability to ensure that the supply chain system provides high-quality products and protects data privacy and security. The view is taken; therefore, in this work, we combined a method of real-time event detection using collected Twitter data and blockchain technology for event monitoring to improve the visibility of the supply chain system and take preemptive measures for risk avoidance. The experiments show some interesting results and potentials for future work in the field of the agile supply chain.

Procurement 4.0 to the rescue: catalysing its adoption by modelling the challenges

Purpose

The pandemic crisis has resulted in global chaos that had caused massive disruption to the supply chain. The pharmaceutical industry, in particular, has been working tirelessly to ensure that they can cater to the people who need them. With restrictions being imposed to prevent the spread of the COVID-19 virus, the movement of raw materials required has been affected, thus creating the need for the procurement function to be innovative. This study proposes the application of Industry 4.0 concepts into the procurement activities of an organization to make it more resilient and efficient.

Design/methodology/approach

To study the intensity of the challenges, Total Interpretive Structural Modelling is used alongside the “Matrice des Impacts Croises Multiplication Appliquee a un Classement” (MICMAC) technique.

Findings

Resilience can be achieved through the collaboration between the organization and its network of suppliers. This is however easier said than done. High and unclear investments have been identified as the challenge that is taking a toll on all technological investments in the pandemic era. The study also shows that organizational inertia which is present in established and structured firms are a deterrent as well.

Originality/value

This study is based on the application of procurement 4.0 to ensure that pharmaceutical supply chains stay least affected since they are essentials. This study using a multi-criteria decision-making approach to prioritize the challenges. This will help practitioners make decisions faster.

Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts' evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation.

Effect of inter-organizational systems appropriation in agility and resilience development: an empirical investigation

Purpose

This study explored the role of inter-organizational systems (IOS) appropriation in the form of five key IOS usage-based capabilities, namely, IOS use for communication, intelligence, integration, collaboration and coordination in the development of tourism SC agility and resilience. Furthermore, the inter-relationship among these IOS usage-based capabilities were explored.

Design/methodology/approach

The study collected perceptual measures from hotel managers and tour managers having sufficient experience in the tourism sector. With 209 completed responses, the data were analyzed using partial least squares.

Findings

The study found IOS use of communication and intelligence as prominent enablers of IOS use for integration, collaboration and coordination. Furthermore, IOS use for integration, collaboration and coordination was found to have a prominent influence in the development of tourism SC agility and resilience. However, the influence of IOS use for communication on collaboration was not supported. Also, the impact of IOS use for collaboration in tourism resilience development was not supported.

Originality/value

The study is the foremost to explore the role of IOS appropriation in the development of dynamic capabilities like agility and resilience in tourism. Furthermore, the study also contributed to extant literature on IOS appropriation through suggesting two additional factors, namely, IOS use for collaboration and coordination to the existing IOS usage-based capabilities.

Assessment of risks associated with third-party logistics in restaurant supply chain

Purpose

The restaurant network is reforming rapidly due to the advancements encountered so far in the restaurant–third party logistics (3PL) collaborations. These collaborations resulting from a strategical partnership between the restaurant and the 3PLs play a significant role in getting a good handle on the web, logistics activities, online business and many more services. Despite the collaborations, 3PL in the restaurant supply chain is associated with many risks that may hamper the supply chain's profitability. In this study, several risks related to 3PL are investigated and analysed.

Design/methodology/approach

Deciding the relative importance of different risks is an intricate errand. The predominance of one risk over the others changes from individual to individual and ?rm to ?rm. Therefore, to catch the changeability in choice, the fuzzy analytical hierarchy process (AHP) is an extremely valuable tool used in this research. In addition to this, fuzzy AHP is incorporated with fuzzy TOPSIS for preference ranking of 3PL risks in the restaurant supply chain and obtain risk index value, which provides an excellent approach to rank the risks. Furthermore, we performed a sensitivity analysis to analyse the stability of the results obtained in this study.

Findings

Results indicate that “macro-level risks” (i.e. the risks associated with 3PL in the restaurant supply chain due to political agitation in the district, cataclysmic events, ailments like COVID-19, bird influenza, etc.) is the most relevant first-level risk with high-risk index as well as high relative weight. As per the analysis of second-level risks, the occurrence of cataclysmic events holds the most elevated risk index value.

Practical implications

This research provides the restaurant industry and the 3PL with a generalized framework with set parameters that can be used to attain a successful 3PL in the restaurant supply chain of any developing nation.

Originality/value

This research proposes an evaluation framework for the risk assessment of third-party logistics in the restaurant supply chain. This paper explores risks for efficient implementation of 3PL in the restaurant supply chain. From a managerial perspective, the rank table is also provided with the goal that mitigation of the risks can be done quickly.

The impact of information technology usage on supply chain resilience and performance: An ambidexterous view

Scholars and practitioners have recognized the importance of supply chain (SC) resilience. However, it remains unclear how to build SC resilience and whether SC resilience can enhance firm performance and bring values to customers. By analyzing data collected from 206 manufacturers in China, this study empirically examines how firms implement different information technology (IT) patterns (exploitative versus explorative) with SC partners to achieve supplier and customer resilience from information processing theory, and examines the performance implications of these two dimensions of SC resilience. In addition, this study also investigates how IT ambidexterity reconciles the paradox between IT exploitation and IT exploration in enhancing SC resilience. The results show that both supplier and customer resilience could improve SC performance. To achieve the two aspects of SC resilience, only explorative use of IT with suppliers and customers have significant effects. The results also show that the ambidextrous use of IT on the customer side takes effect. The exploitative and explorative use of IT complement each other to improve customer resilience. The findings of this study contribute to IT and SC resilience literature.

Exploring potential implications of Belt and Road Initiative for supply chain resilience: a comparative study of five South Asian countries

Purpose

This paper explores the potential opportunities and challenges that Belt and Road Initiative (BRI) may bring for resilient supply chains.

Design/methodology/approach

This study employs multiple case study methodology by considering five south Asian countries. Overall, 36 semi-structured interviews with supply chain managers from three supplying firms, two transportation centers and four buying firms are undertaken. Three supplying firms were based in Pakistan, providing cement and steel products. Simultaneously, two transportation centers were located in Sri Lanka and Bangladesh, mainly engaged in cargo and freight handling. Finally, the buying firms were located in Mainland China and India, mainly constructing road and rail networks.

Findings

Our findings reveal both challenges and opportunities for supply chain resilience within the context of BRI. In particular, findings suggest that BRI can improve quality infrastructure, greater connectivity for logistics firms and enhance consumer markets. Conversely, BRI also poses challenges to supply chain resilience in managing large-scale logistics infrastructure and the potential conflicts between countries participating in BRI.

Research limitations/implications

As this study attempts to build a theory, its result should not be generalized to a broader population. Second, this study only explores BRI's implications for resilient supply chains within five South Asian countries.

Practical implications

Firms can use our study results to understand BRI’s implications for resilient supply chains. Particularly, it presents firms with the potential opportunities and challenges that BRI brings for resilient supply chains.

Originality/value

BRI has been the subject of much research in domains like political science, economics and law but its application to the supply chain resilience is rather scant. Our study, therefore, contributes to the emergent literature on supply chain resilience within the context of BRI by exploring its potential opportunities and challenges.

A systematic literature review on supply chain risk management: is healthcare management a forsaken research field?

Purpose

This paper aims to present a systematic literature review (SLR) to investigate how supply chain risk management (SCRM) is applied to the healthcare supply chains and which improvement opportunities are being missed in this segment.

Design/methodology/approach

This SLR used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to answer three research questions: (1) Which are the main gaps concerning healthcare supply chain risk management (HCSCRM)? (2) What is the definition of HCSCRM? and (3) What are the risk management techniques and approaches used in healthcare supply chains?

Findings

The authors present a complete summary of the HCSCRM body of research, investigating research strings like clinical engineering and high reliability organizations (HROs) and its relations with HCSCRM; (1) This research revealed the five pillars of HCSCRM; (2) The authors proposed a formal definition for HCSCRM considering all the literature blocks explored and (3) The authors generated a list of risks present in healthcare supply chains resulting from extensive article research.

Research limitations/implications

The authors only reviewed international journal articles (published in the English language), excluding conference papers, dissertations and theses, textbooks, book chapters, unpublished articles and notes. In addition, the study did not thoroughly investigate specific countries' particularities concerning how the healthcare providers are organized.

Originality/value

The contribution of this article is threefold: (1) To the best of authors knowledge, there is no other SLR about HCSCRM published in the scientific literature by the time of realization of authors’ work, suggesting that is the first effort to fulfill this research gap; (2) Following the previous contribution, in this work the authors propose a first formal definition for HCSCRM and (3) The authors analyzed concepts such as clinical engineering and HROs to establish the building blocks of HCSCRM.

Understanding the impact of supply-side decisions and practices on supply risk management

Purpose

In the era of market turbulence, sourcing specialists consistently face challenges to keep the availability of the material efficiently and effectively without any disruption. Sourcing strategies and planning have a huge impact on procurement performance. The purpose of this paper is to examine the relationships among different sourcing strategies and supply risk management and performance and additionally, the role of procurement practices in different strategic settings.

Design/methodology/approach

This is empirical research that collected data gathered from 223 procurement specialists working in various manufacturing firms through a structured questionnaire. Valid data is then analyzed through the structure equation modeling technique for hypotheses testing.

Findings

The findings of this study reveal that supplier development is a partial complementary mediator between multiple supplier strategy and supply-side risk management. While in a volatile business environment, strategic supplier strategy has a significant negative impact on supply-side risk management, and in this case supplier development acts as a competing partial mediator between the two. Contract management has resulted in an important mechanism to be deployed in a strategic sourcing strategy. It is also shown that supplier risk management is also associated with improved supply management performance.

Practical implications

This paper establishes an explanation of theoretical and practical understanding of sourcing strategies and empirically shows that supplier development is the appropriate mechanism to deal with supply-side risk management, which in turn positively impacts on supplier management performance.

Originality/value

This study contributes to supply chain risk management literature, especially in the context of strategic risk management and explains how a strategic decision can impact supply risk management. This provides a piece of empirical evidence regarding the use of well-established procurement practices to improve supply performance.

A collaborative scenario-based decision model for a disrupted dual-channel supply chain

Purpose

Distribution systems usually utilize both traditional retailing channels in conjunction with e-channels. The purpose of this paper is to investigate a dual-channel supply chain, comprising a traditional retailing channel and an e-channel under disruption. By benchmarking against the centralized decision structure, the authors intend to propose a collaboration model to achieve channel coordination as well as more reliable decisions.

Design/methodology/approach

Four different channel disruption scenarios, with customers’ reaction toward disruptions, are examined, and then, optimal pricing decisions for both centralized and decentralized decision-making structures are extracted. Next, a collaboration mechanism based on the dominancy power of channel members is developed to entice all channel members to participate in channel coordination. By benchmarking the proposed collaboration model against both the decentralized/centralized structures a win–win solution is guaranteed for all channel members. In addition, the proposed model ensures more reliable decisions than the centralized structure, as it guarantees less fluctuated income levels.

Findings

This study shows, as the disruption probability grows, the channel profit decreases while the channel-retailing price increases. Furthermore, the exact alignment of the centralized decision-making approach and the proposed collaboration model is not achievable due to the problem infeasibility. Numerical experiments and sensitivity analyses benchmark the performance of the proposed collaboration mechanism against the centralized structure for the full alignment with centralized decision-making approach.

Originality/value

This study contributes to the channel conflict literature as jointly considers pricing decisions, disruptions and coordination. Further, consumers’ reaction toward disruption is analyzed through a transshipment agreement.