Analysis of the COVID-19 pandemic’s impacts on manufacturing: a systematic literature review and future research agenda

Supply chain digitalization and performance: A moderated mediation of supply chain visibility and supply chain survivability

The COVID-19 crisis has notably impacted global supply chains as it has disrupted manufacturing operations. To recover from the aforementioned disruptions, supply chain digitalization [SCD] is increasingly being acknowledged to help the recovery process. Based on this, scholars have called for additional research on how SCD can enhance supply chain visibility [SCV] and boost supply chain performance [SCP] in turbulent environments. Based on 399 valid responses collected through cross-sectional method from Turkish manufacturing firms and using a non-probabilistic sampling method [i.e., purposive sampling], this research explores the effect of SCD on SCP. The mediating role of SCV and the moderating role of supply chain survivability [SCS] on the SCD-SCP relationship were also explored. The findings showed that SCD has a positive effect on SCP. SCD has a positive effect on SCV. SCV has a positive effect on SCP. The link between SCD and SCP is mediated by SCP. The results also revealed that SCS moderated the SCD-SCV link such that SCD has a stronger, positive relationship with SCV when SCS is high than when it's low. SCS moderates the SCD-SCP link, such that at low levels of SCS, the positive effect of SCD on SCP is weakened. The indirect positive effect of SCD on SCP via SCV is strongest when supply chain survivability is high. The findings suggest that SCD can improve cost-effectiveness, promote communication and information efficiency, and enhance supply chain resilience to improve performance after disruptions. This study provides insightful new implications for both supply chain literature and practitioners.

How did COVID-19 affect logistics and supply chain processes? Immediate, short and medium-term evidence from some industrial fields of Italy

This paper provides empirical evidence on the impact of the Covid-19 pandemic on logistics and supply chain processes of five industrial sectors of Italy, namely food & beverage, machine manufacturing, metal mechanical industry, logistics & transport, and textile & fashion. A questionnaire survey, with 82 useful responses, was conducted to investigate various effects of Covid-19 on these businesses, such as the volumes handled and the service performance in the immediate-, short- and medium-term, the countermeasures implemented by companies and the future decision-making strategies. The period of analysis spans from January 2020 to June 2021. Results show that the impact of Covid-19 on volumes and service performance varied across the sectors: the food & beverage and logistics & transport were poorly affected by the pandemic and experienced a general increase in the demand and volumes, while mechanical or textile & fashion industries were mostly affected by a decrease in demand. The positive/negative impacts were particularly evident at the beginning of the pandemics, but, depending on the sector, the effects could cease quite quickly or last in the short-term. The countermeasures adopted against the Covid-19 emergency differ again across sectors; in general, industry fields that were particularly impacted by the pandemic emergency have applied more countermeasures. Typical strategies for risk management (e.g., the diversification in transport modes or the stock increase) turned out to be applied as immediate countermeasures or in plan for the future in few industries only. Differences across sectors were also observed about the sourcing strategies already in use, implemented to counteract the pandemics or expected to be maintained in time. Empirical outcomes offered are expected to help researchers gain a deep understanding of Covid-19 related phenomena, thus inspiring further research activities.

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.

Intelligent Process Automation and Business Continuity: Areas for Future Research

Robotic process automation and intelligent process automation have gained a foothold in the automation of business processes, using blocks of software (bots). These agents interact with systems through interfaces, replacing human intervention with the aim of improving efficiency, reducing costs and mitigating risks by ensuring and enforcing compliance measures. However, there are aspects of the incorporation of this new reality within the business continuity lifecycle that are still unclear, and which need to be evaluated. This study provides a multivocal literature review of robotic process automation and intelligent process automation correlated with business continuity, to identify the level of awareness of these two emerging forms of automation within the business continuity management lifecycle. Based on the reviewed literature, the study develops a discussion of the main research areas for investigation, identifying what is attracting the attention of practitioners and researchers and which areas they highlight as promising for future research. Numerous sources from relevant backgrounds reveal an interest in these interrelated topics but there as yet is little or no information available on the direct connection between them.

The mediating role of knowledge management processes in the effective use of artificial intelligence in manufacturing firms

Purpose

This paper aims to provide and empirically test a conceptual model in which artificial intelligence (AI), knowledge management processes (KMPs) and supply chain resilience (SCR) are simultaneously considered in terms of their reciprocal relationships and impact on manufacturing firm performance (MFP).

Design/methodology/approach

In the study, six hypotheses have been developed and tested through an empirical survey administered to 120 senior executives of Italian manufacturing firms. The data analysis has been carried out via the partial least squares structural equation modelling approach, using the Advanced Analysis for Composites 2.0 variance-based software program.

Findings

Using a conceptual model validated using an empirical survey, the study sheds light on the relationships between AI, KMPs and SCR, as well as their impacts on MFP. In particular, the authors show the positive effects of the adoption of AI on KMPs, as well as the influence of KMPs on SCR and MFP. Finally, the authors demonstrate that KMPs act as a mediator through which AI affects SCR and MFP.

Practical implications

This study highlights the critical role of KMPs for manufacturing firms that can deploy AI to stimulate KMPs and through attaining a high level of the latter might succeed in enhancing both their SCR and MFP.

Originality/value

This study demonstrates that manufacturing firms interested in properly applying AI to ameliorate their performance and resilience must carefully consider KMPs as a mediator mechanism.

Bi-objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID-19 pandemic

This paper develops an approach to optimize a vaccine distribution network design through a mixed-integer nonlinear programming model with two objectives: minimizing the total expected number of deaths among the population and minimizing the total distribution cost of the vaccination campaign. Additionally, we assume that a set of input parameters (e.g., death rate, social contacts, vaccine supply, etc.) is uncertain, and the distribution network is exposed to disruptions. We then investigate the resilience of the distribution network through a scenario-based robust-stochastic optimization approach. The proposed model is linearized and finally validated through a real case study of the COVID-19 vaccination campaign in France. We show that the current vaccination strategies are not optimal, and vaccination prioritization among the population and the equity of vaccine distribution depend on other factors than those conceived by health policymakers. Furthermore, we demonstrate that a vaccination strategy mixing the population prioritization and the quarantine restrictions leads to an 8.5% decrease in the total number of deaths.

Government Supports, Digital Capability, and Organizational Resilience Capacity during COVID-19: The Moderation Role of Organizational Unlearning

This paper provides an investigation into how different types of government supports can be used to enhance organizational resilience capacity during the COVID-19 pandemic. Based on resource orchestration theory, this study examines the effects of direct government support and indirect government support on organizational resilience capacity, the mediation role of digital capability, and the moderation effects of organizational unlearning. The empirical results from 205 Chinese firms show that direct government support and indirect government support have positive effects on organizational resilience capacity, which were mediated by digital capability. In addition, organizational unlearning positively and negatively moderates the positive relationship between direct government support, indirect government support and digital capability. Our theoretical discussion and empirical results contribute to the literature related to organizational resilience, digital capability, government support, and organizational unlearning.

Blackout and supply chains: Cross-structural ripple effect, performance, resilience and viability impact analysis

Increased electricity consumption along with the transformations of the energy systems and interruptions in energy supply can lead to a blackout, i.e., the total loss of power in an area (or a set of areas) of a longer duration. This disruption can be fatal for production, logistics, and retail operations. Depending on the scope of the affected areas and the blackout duration, supply chains (SC) can be impacted to different extent. In this study, we perform a simulation analysis using anyLogistix digital SC twin to identify potential impacts of blackouts on SCs for scenarios of different severity. Distinctively, we triangulate the design and evaluation of experiments with consideration of SC performance, resilience, and viability. The results allow for some generalizations. First, we conceptualize blackout as a special case of SC risks which is distinctively characterized by a simultaneous shutdown of several SC processes, disruption propagations (i.e., the ripple effect), and a danger of viability losses for entire ecosystems. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of blackouts, mitigation and recovery strategies. The major observation from the simulation experiments is that the dynamics of the power loss propagation across different regions, the blackout duration, simultaneous unavailability of supply and logistics along with the unpredictable customer behavior might become major factors that determine the blackout impact and influence selection of an appropriate recovery strategy. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of blackouts on the SCs and viability and develop mitigation and recovery strategies. The paper is concluded by summarizing the most important insights and outlining future research agenda toward SC viability, reconfigurable SC, multi-structural SC dynamics, intertwined supply networks, and cross-structural ripple effects.