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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.

The purpose is to replicate and extend Ambulkar et al.’s (2015) work testing resource reconfiguration as a mediator of the supply chain disruption/firm resilience relationship and testing risk management infrastructure as a moderator. This study extends the work of Ambulkar in that it uses analysis of survey data gathered from manufacturing firms during an actual disruption event (COVID-19). The previous work is also in extended in that the authors include a pandemic disruption impact variable and supply chain performance is an expanded model.

Partial least squares structural equation modeling techniques were used to analyze data gathered from 184 US manufacturing managers during the height (Summer 2021) of the COVID-19 pandemic.

Two of four of Ambulkars et al.’s (2015) hypotheses were confirmed as relevant to firm resilience during the pandemic while two were not confirmed. Results also show that supply chain disruption orientation, risk management infrastructure and resource reconfiguration combine to improve firm resilience, which in turn improves supply chain performance while mitigating the disruption impact of COVID-19.

Previous work is replicated and extended, using data from an actual disruption event (COVID-19). This study presents a more comprehensive model using a newly developed and validated scale to measure pandemic impact and including supply chain performance.

The purpose of this conceptual paper is to explore the role of strategic leadership under conditions of uncertainty and unpredictability. The authors argue that highly improbable, but high-impact events require the upper echelons of management, traditionally the custodians of strategy formulation to offer a new kind of strategic leadership focused on new mindsets, organizational capabilities, more in tune with high uncertainty and unpredictability.

Drawing on strategic leadership, and complexity leadership theory, the authors review the literature and present a conceptual framework for exploring the nature of strategic leadership under uncertainty. The authors conceptualize organizations as complex adaptive systems and discuss the imperatives for developing new mental models for emergent leadership.

Strategic leaders have a key role to play in preparing their organizations for episodic disruptions. These include developing their adaptive capabilities and building resilient organizations to ensure their organizations cannot only bounce back after a disruption but have the capacity for transformation to new fitness levels when necessary. Strategic leaders must engage with complexity leadership by seeing their organizations as complex adaptive systems, reconfigure their leadership approaches and organizations to build strategic adaptive capability.

This is a conceptual paper and the authors cannot make any claims of causality.

Organizational leaders need to reconfigure their mental models and leadership approaches to reflect the new normal of uncertainty and unpredictability. Developing the strategic adaptive capability of organizations should prepare them for dealing with high impact events. To assure business continuity in the face of disruptions requires building flexible, adaptable business models.

The paper focuses on how managers can offer strategic leadership for a new normal that challenges some of our most cherished leadership and strategic management paradigms. The authors explore the new mental models and leadership models in an era of great uncertainty.

Global supply chains are increasingly becoming more prone to high-impact disruptions, which has been fairly evident with the coronavirus disease 2019 (COVID-19) pandemic. The capacity to address disruptions is essential for the survival of any organization. Coping with increasing complexity and uncertainties requires a systemic view of supply chains. Furthermore, a comprehensive understanding of the governance structure and timely decision-making are critical in times of disruptions. Although several aspects of supply chain resilience (SCRES) are broadly studied in the literature, the relationship between supply chain orientation (SCO), decentralization in decision-making and SCRES is an understudied area.

This study takes a longitudinal approach to address this research gap with a comprehensive meta-analytic review to explore the relationships between the constructs of interest through the lenses of contingency and dynamic capability theories. Furthermore, 2 surveys with sample sizes of 250 and 200 were conducted with supply chain professionals to test the research framework before and after the pandemic to compare the findings.

Structural Equation Modeling (SEM) analysis indicates a positive relationship between SCO and decentralization and between decentralization and SCRES. The post-COVID-19 analysis further validates the influence of agility, collaboration and situational awareness related to decentralization and resilience. More importantly, capabilities have a higher impact on resilience during the pandemic than before.

The results entreat organizations to attain decentralized decision-making vis-à-vis dedicated functional teams charged with reacting timely to disruptions. The teams should be empowered to leverage their knowledge and experiences regardless of their position in the hierarchy.

Although SCRES is an active research stream, the structural aspects of SCRES and its relationship with SCO are understudied. Therefore, this research puts forth a research framework and empirically tests hypotheses that frame the relationship between SCO, decentralization and resilience outcomes in pre- and post-COVID environments.

Rare but high impact (R-HI) disruptions, which are caused by legal changes, socio-technical accidents, or natural disasters, are becoming more frequent and have strong short-term and long-term impacts on performance. Meanwhile, the short-term perspective of managers leads to adoption of mitigation strategies with lower investments and immediate performance improvement. The purpose of this paper is to provide insights on supply chain collaboration (SCC) to establish so-called twin-objective strategy to help both risk mitigation (through moderation effects) and performance improvement (through a direct positive impact). Moreover, power position will be considered as the control variable.

A cross-sectional approach was adopted with primary data collected through a survey in China. Data were analyzed using structural equation modeling with partial least squares estimations. A sub-group model analysis was applied to test the effect of the control variable.

The findings verify that SCC has both a direct positive impact on performance and moderation effects on the relationships between sources of R-HI disruptions and performance. The results of sub-group model analysis illustrate that both powerful and weak focal firms benefit from SCC, but in different ways.

The study shows that the allocation of gains from collaborative advantage should be added to the theory-building of relational view. Meanwhile, the research extends the focal firm’s context to its supply chain’s context so that classic contingency theory can be extended to adequately explain supply chain management phenomena.

The enormous impact of the COVID-19 pandemic showcases the key role of supply chain risk management (SCRM) in achieving and maintaining business performance, competitiveness and survival in the “new normal”. The purpose of this paper is to explore what impact the COVID-19 pandemic has had and may yet have on supply chains (SCs), which SCRM approaches have proved successful and how logistics service providers (LSPs) have applied the knowledge they have gained to improve their SCRM practices and resilience so as to prepare better for the next major disruption.

This paper combines an extensive literature review with a multiple-case study of 10 internationally operating LSPs and how they have handled the impact of the COVID-19 pandemic so far. To bridge the research-practice gap, this study draws on the dynamic-capabilities view and provide insights that are valuable to both academia and practice.

This study provides empirical evidence on the severe impact of the COVID-19 pandemic on SCs, which has posed several challenges to LSPs. The study identifies eight factors that are critical to the adaptive capabilities of LSPs and, therefore, to their resilience in extreme conditions. The findings of this study show that these factors determine whether an SCRM system is robust and agile enough to allow an LSP to anticipate potential disruption and to respond fast enough when disruption occurs. Specifically, this study finds that robustness and agility demonstrably strengthen business performance, while learning from experience proves key to reconfiguring an SCRM design in response to acute disruption.

This paper is among the first to provide rich, empirical and practically applicable insights into the impact of the COVID-19 pandemic on business in relation to SCRM. These novel insights offer inspiring opportunities for further research.

The objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.

The research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.

The synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.

The two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single region

New Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.

The use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.

In the context of the COVID-19 pandemic, this study investigates a variety of approaches to supply disruption risk management for achieving effective responses for resilience at the supply management subunit level (e.g. category of items). Drawing on the attention-based view of the firm, the authors model the attentional antecedents of supply resilience as (1) attentional perspectives and (2) attentional selection. Attentional perspectives focus on either supply risk sources or supply network recoverability, and both are hypothesised to have a direct positive association with supply resilience. Attentional selection is top down or bottom up when it comes to disruption detection, and these are hypothesised to moderate the association between disruption risk management perspectives and resilience.

Conducted at the early phases of the COVID-19 pandemic, this study employs a hierarchical regression analysis on a multicountry survey of 190 procurement professionals, each responding from the perspective of their own subunit area of supply responsibility.

Both attentional disruption risk management perspectives are needed to achieve supply resilience, and neither is superior in terms of achieving supply resilience. Both the efficiency of the top down and exposure to the unexpected with the bottom up are needed – to a balanced degree – for improved supply resilience.

The results encourage firms to purposefully develop their supply risk management practices, first, to include both perspectives and, second, to avoid biases in attentional selection for disruption detection. Ensuring a more balanced approach may allow firms to improve their supply resilience.

The results contribute to the understanding of the microfoundations that underpin firms' operational capabilities for supply risk and disruption management and possible attentional biases.

This paper aims to describe a high-level model portraying the relationships between operational, investment, commercial and regulatory pressures, and reports the early findings from testing alternative strategies, both over the long- and short-term. Concern about the vulnerability of utility networks (electricity, gas and water) and other infrastructures, including transport and telecommunications, to environmental, terrorist and other threats has increased in recent years. This has been motivated both by a perceived increase in such threats and by recognition that the commercial pressures and regulation of companies operating these infrastructures could unintentionally have increased that risk. Powerful simulation tools already help utility operators develop asset investment polices to improve both the performance and resilience of their networks, while others have helped increase their capability to respond efficiently when disruptive events occur. However, these tools need to be further developed to increase understanding of how the interdependencies between operational, investment, commercial and regulatory pressures influence and eventually define the strategic policies available to these organisations and what the long-run consequences will be for the resilience of these systems and hence for service continuity.

Use of system dynamics methods and tools to develop a new approach to strategy and policy development for risk management for organisations operating the critical national infrastructure.

System dynamics is a valid approach to address the problem of understanding risk and developing risk mitigation and management strategies for organisations operating the critical national infrastructure. To develop policies that will effectively manage and mitigate risk in the critical national infrastructure, it is essential to identify and model the interactions and interdependencies between the organisational, investment, commercial and regulatory factors.

The research has developed a proof-of-concept model and set of simulation tools which produce good results using test data from one type of organisation operating in the critical national infrastructure. The model has not been tested using data from other types of organisations. Similarly, the software written in the model has not been tested in operational conditions and further testing will be required.

The model at the moment can only be applied to single organisation. The interactions between organisations are not in scope.

Although some work in the field using simulation tools and methods has been done in the USA, the use of system dynamics and its application to the specific situation on the UK and Europe is new. The model uses earlier work which applied system dynamics to the subject of asset investment planning, but is a major step forward from this work. Risk and resilience is one of the major challenges facing operators of the critical national structure. This work will be of potential value to all these organisations.