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The purpose of this paper is to examine the role of digital supply chain (DSC) technologies in automotive supply chain resilience (SCR) practices to improve the supply chain performance (SC-Perf.) objectives of companies operating in the automotive industry. This study also compares the results of the associated SC-Perf objectives before and after the COVID-19 pandemic outbreak lockdown situation.

The authors undertook in-depth empirical research using a questionnaire survey to explore the performance of automotive supply chains. The sample for this study consisted of practitioners from supply chain entities such as automotive original equipment manufacturers, Tier-1 component manufacturers and lead logistics providers in Asia-Pacific (AP) emerging markets. Research questions, framework and hypotheses were developed using the literature review.

The research outcome from analysis of the data the authors collected from an emerging market context, specifically the automotive sector, emphasizes the role of DSC technologies and encourages the firm’s SCR practices which, in turn, supports the SC-Perf objectives. The DSC technologies competency moderates the SCR and SC-Perf objectives relation, and the moderation effect is higher for post-COVID-19 pandemic outbreak lockdown situation than at prior state.

The scope of the study is restricted to the automotive firms in the AP region. The data were collected from a representative sample of the population through a questionnaire survey. The small size of the sample incurs a certain level of subjectivity.

This research provides practical insights for practitioners and academicians on DSC technologies’ influence in SCR practices to improve the firm’s SC-Perf. This research shares the literature insights on use of DSC technologies across the sector to allow the automotive firm to reassess the existing operational practices.

The paper adds insights on introducing or implementing DSC technologies across AP automotive firms to increase the operations’ performance by improving SCR practices and sustainability.

The adverse interactions between disruptions can increase the supply chain's vulnerability. Accordingly, establishing supply chain resilience to deal with disruptions and employing business continuity planning to preserve risk management achievements is of considerable importance. The aforementioned idea is discussed in this study.

This study proposes a multi-objective optimization model for employing business continuity management and organizational resilience in a supply chain for responding to multiple interrelated disruptions. The improved augmented e-constraint and the scenario-based robust optimization methods are adopted for multi-objective programming and dealing with uncertainty, respectively. A case study of the automotive battery manufacturing industry is also considered to ensure real-world conformity of the model.

The results indicate that interactions between disruptions remarkably increase the supply chain's vulnerability. Choosing a higher fortification level for the supply chain and foreign suppliers reduces disruption impacts on resources and improves the supply chain's resilience and business continuity. Facilities dispersion, fortification of facilities, lateral transshipment, order deferral policy, dynamic capacity planning and direct transportation of products to markets are the most efficient resilience strategies in the under-study industry.

Applying resource allocation planning and portfolio selection to adopt preventive and reactive resilience strategies simultaneously to manage multiple interrelated disruptions in a real-world automotive battery manufacturing industry, maintaining the long-term achievements of supply chain resilience using business continuity management and dynamic capacity planning are the main contributions of the presented paper.

Critical infrastructures (CIs) for essential services such as water supply and electricity delivery are notoriously vulnerable to disruptions. While extant literature offers important insights into the resilience of CIs following large-scale disasters, our understanding of CI resilience to the more typical disruptions that affect CIs on a day-to-day basis remains limited. The present study investigates how the interorganizational (supply) network that uses and manages the CI can mitigate the adverse consequences of day-to-day disruptions.

Longitudinal archival data on 277 day-to-day disruptions within the Dutch national railway CI were collected and analyzed using generalized estimating equations.

The empirical results largely support the study’s predictions that day-to-day disruptions have greater adverse effects if they co-occur or are relatively unprecedented. The findings further show that the involved interorganizational network can enhance CI resilience to these disruptions, in particular, by increasing the overall level of cross-boundary information exchange between organizations inside the network.

This study helps managers to make well-informed choices regarding the target and intensity of their cross-boundary information-exchange efforts when dealing with day-to-day disruptions affecting their CI. The findings illustrate the importance of targeting cross-boundary information exchange at the complete interorganizational network responsible for the CI and to increase the intensity of such efforts when CI disruptions co-occur and/or are unprecedented.

This study contributes to our academic understanding of how network-level processes (i.e. cross-boundary information exchange) can be managed to ensure interorganizational (supply) networks’ resilience to day-to-day disruptions in a CI context. Subsequent research may draw from the conceptual framework advanced in the present study for examining additional supply network-level processes that can influence the effectiveness of entire supply networks. As such, the present research may assist scholars to move beyond a simple dyadic context and toward examining complete supply networks

Existing supply chain literature provides examples of countermeasures that firms can adopt to mitigate abnormal or catastrophic supply chain disruptions. However, none address reducing interactive complexity prior to adopting countermeasures to mitigate everyday or normal supply chain disruptions. Most mitigation strategies focus on adding capabilities or resources to protect an organization. Here, the authors aim to consider an alternative strategy of examining current processes to determine whether processes can be simplified by using the normal accident theory and its constructs of interactive complexity and coupling as a theoretical basis.

The authors develop a model based on the normal accident theory and use logistic regression to test their propositions in the context of a steel processing plant and its customers.

The findings show the importance of reducing interactive complexity to mitigate supply chain disruptions. However, high inventory is not considered a significant countermeasure, and high inventory levels may increase the likelihood of causing a disruption downstream. These findings support the lean management approach of operating under low inventory levels while eliminating complexity to make problems more visible, causing fewer disruptions.

While others have examined the impact of mitigation strategies conceptually, no study has captured information from actual supply chain disruptions to assess how interactive complexity and inventory levels affect disruption potential at downstream customers' facilities. Capturing information from supply chain disruptions enables managers to assess the situation as the disruption is occurring. The authors suggest a strategy in which countermeasures that increase slack in the system should be considered only after the system is sufficiently simplified to mitigate disruptions.

This study proposes an integrated model to explore the relationships between dynamic capability and supply chain resilience (SCRE) and the relationships' impacts on firms' financial performance with supply chains (FPwSC) during the coronavirus disease 2019 (COVID-19) pandemic.

Based on resource-based theory and knowledge-based theory, the dynamic capability is classified into resource-based dynamic capability (RBDC) and knowledge-based dynamic capability (KBDC). The study collects 158 useable survey samples from manufacturers in Taiwan and analyzes the samples with the structural equation model.

The results show that knowledge is power; KBDC is crucial for FPwSC, SCRE and RBDC. In addition, SCRE mediates the relationship between KBDC and FPwSC. Finally, RBDC significantly suppresses FPwSC.

Future researchers could replicate this study in other industries and expand this to other countries to generalize the results.

A firm with KBDC can adopt and implement strategies that exploit its internal strengths to respond to environmental opportunities, overcome internal weaknesses and mitigate external threats. Furthermore, a firm should fully utilize SCRE with proactive and reactive strategies. Exercising a firm's KBDC could facilitate SC collective intelligence to handle the risk of SC disruption and vice versa.

The study is the first to combine KBDC, RBDC and SCRE into an integrated model for FPwSC. Moreover, this study reveals that resilience relies on knowledge, not resources, as evidenced by SCRE being affected significantly by KBDC but not RBDC.

The purpose of this paper is to examine (1) how the recovery speed using promotional investment and (2) distributed production using additive manufacturing (AM) improve the resilience of the supply chain to manage any disruptions in the diffusion of green products.

The environmental performance, service level performance and economic performance are the measures of interest. These measures are studied through the integration of inventory and production planning (I&PP) of the reverse logistics system and consumer behavior using Bass (1969) model of diffusion of innovation under the paradigm of Industry 4.0 architecture. The Taguchi experimental design framework was used for the simulation analysis.

The adoption patterns based on the Bass model in conjunction with recovery speed and production on AM during the disruption period suggest that there exist tradeoff decisions between various combinations of information-sharing and I&PP policies.

The extensive sensitivity analyses provide real-time support for managerial decisions. Besides the potentials of Industry 4.0 capabilities, the present research suggests paying close attention to the recovery speed in conjunction with the inventory management system.

The integration of consumers' behavior (Bass model) to digital technologies is an additional contribution of the present research toward sustainability issues from the social perspective.

Previous research studies have discussed resilience to manage the ripple effect. However, none of them have addressed the changing scope of resilience to manage the ripple effect caused by the disruption in the diffusion of green products in a reverse logistics setup.

The SARS-CoV-2 pandemic has had severe effects on economies worldwide and, in particular, on public institutions that must keep their operations running while supply chains are interrupted. The purpose of this study is to examine how public institutions act during a pandemic to ensure the security of supply.

The distinct focus is if, why and how public institutions have adopted additive manufacturing (AM) – a production technology colloquially known as three-dimensional printing in which a product is created by joining raw material layer by layer based on a digital model (computer-aided design [CAD] file) of the product – in reaction to supply disruptions caused by the SARS-CoV-2 pandemic. For this purpose, four cases within the context of the pandemic supply disruption are used as the units of analysis.

The findings are twofold: public institutions reacted, on the one hand, with a behavioral solution approach, trying to solve the supply disruption with new or changed forms of cooperation and collaboration. On the other hand, public institutions used a technical solution approach (TSA) as a supply disruption response and intensified their use of AM.

This research derives an implications model that focuses on the TSA. Considering the ex ante and ex post phases of the disruption, several effects of AM on resilience are identified. The most relevant is the long-term learning effect (i.e. AM data created during this disruption might also help in a new disruption).

Practitioners who act under extreme pressure and uncertainty are informed by cases that have managed to close bottleneck situations with either a behavioral or TSA. Specific strategies are given for how public buyers could use AM within a pandemic situation to mitigate supply bottlenecks, such as increasing their robustness by localizing sourcing and increasing agility by combining traditional and additive supply sources. Additionally, insights are provided into how public organizations can increase their level of preparedness by including disruption paragraphs, establishing CAD databases, in contract clauses and keeping reserve contracts with AM service providers.

This research contrasts behavioral and technical solution concepts for a pandemic in the public sector. Thus, it provides insights into the relative benefits of AM and causes and effect with regard to how AM affects supply robustness and agility.

Past research has shown that culture has significant effects on people's evaluation of and responses to risk. Despite this important role, the supply chain risk literature has been silent on this matter. The purpose of this paper is to examine the impact of cultural value orientations on managerial perception of and responses to a supply disruption risk.

The authors conduct a scenario-based experiment to investigate the effect of cultural value orientations – i.e. individualism-collectivism and uncertainty avoidance – on individuals' perception of risk and supplier switching intention in the face of a supply disruption.

The findings highlight the negative effect of individualism-collectivism on disruption risk perception and switching intention in high uncertain circumstances. However, these relationships are non-significant in relatively less uncertain situations. Moreover, the findings show that the impact of uncertainty avoidance on risk perception and supplier switching is positive and significant in both low and high uncertain circumstances.

Extant research has traditionally assumed that when confronted with disruption risks, managers make decisions using an economic utility model, to best serve the long-term objectives of the firm. This paper draws from advances of behavioural research to show that cultural value orientations influence such decisions through a mediating mechanism of subjective risk perception.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

The lean and global character of supply networks today opens supply chains to potential disruptions, especially in volatile environments. Most disruptions are of relatively low potential impact; however, firms also occasionally face high-impact disruptions that may even threaten survival. This study applies and extends absorptive capacity concepts to organize resilience capabilities identified in the literature and to examine whether capabilities that provide low-impact resilience are different from those that provide high-impact resilience. A second and related objective is to evaluate whether low-impact resilience supports high-impact resilience through “learning by experience.”

Survey and industry data are used to understand capabilities involved with achieving both low-impact resilience and high-impact resilience.

The results of our analysis of survey and industry data uncover significant complex interactions in the effects of capabilities and volatility on resilience; suggesting that different absorptive capacity capabilities are related to low-impact resilience and high-impact resilience, respectively, and these effects depend on industry context. Moderating influences of exploitation capability and environmental volatility are consistent with a “learning by experience” explanation of the association of low-impact resilience to high-impact resilience.

This study thus provides a unifying framework with which to consider resiliency capabilities. Further, it answers a question raised in prior research, and it extends our understanding of important relationships between capabilities for different levels of resilience.