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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.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

This study aims to investigate how organizations from different sectors interpret the meaning of business continuity management (BCM) in the light of the COVID-19 pandemic.

A survey was conducted to capture the views of organizations across five different sectors. The sample consisted of ten senior managers; two from the banking sector; two from the supply chain sector (agricultural and food supply chains); two from the tourism sector; two from the services sector; and two from the higher education sector. An interviewer-administered questionnaire was used to collect the data. One manager from each sector represented a local business/enterprise and the other represented an international business/enterprise.

It was found that different organizations/businesses understood BCM differently. Therefore, a variety of interpretations have been obtained.

This study sheds light on how different organizations understand BCM in times of crisis, such as the COVID-19 pandemic. By understanding the different interpretations, it becomes clearer whether or not these organizations have applicable business continuity plans in place.

This is the first study to investigate the different interpretations of the meaning of BCM across different business sectors. The majority of the existing studies on BCM discuss the process from the perspective of a single business or sector. The study was conducted during the COVID-19 pandemic, a period that witnessed prolonged and critical disruptions facing almost all businesses and organizations and which threatened the survival of some of them.

Resilience as a novel concept has attracted the most attention in the management of engineering systems. The main goal of engineering systems is production assurance and increasing customer satisfaction which depends on the suitable performance of mechanical equipment. “A resilient system is defined as a system that is resistant to disruption and failures and can recover itself and returns to the state before failure as soon as possible in the case of failure.” Estimate the value of the system’s resilience to increase its resilience by covering the weakness in the resilience indexes of the system.

In this article, a suitable approach to estimating resilience in complex engineering systems management in the field of mining has been presented. Accordingly, indexes of reliability, maintainability, supportability, efficiency index of prognostics and health management of the system, and ultimately the organization resilience index, have been used to evaluate the system resilience.

The results of applying this approach indicate the value of 80% resilience if the risk factor is considered and 98% if the mentioned factors are ignored. Also, the value of 58% resilience of this organization’s management group indicates the weakness of situational awareness and weakness in the vulnerable points of the organization.

To evaluate the resilience in this article, five indicators of reliability, maintainability, and supportability are used as performance indicators. Also, organization resilience and the prognostic and health management of the system (PHM) are used as management indicators. To achieve more favorable results, the environmental and operational variables governing the system have been used in performance indicators, and expert experts' opinions have been used in management indicators.

Building supply chain (SC) resilience has become a priority for many organizations, following a global increase in disruptive events. While management accounting and control (MAC) systems play a supportive role in supply chain management (SCM) decisions, little is known about the contributions offered to resilience decisions in service organizations. The purpose of this study is to examine the performance implications of MCS's impact on proactive and reactive resilience of healthcare supply chains.

This study conducted a survey of 127 public health managers via structural equation modeling. The partial least squares version 3.3.3 was used.

The results show a statistically positive impact of MAC dimensions on proactive and reactive resilience, which in turn impacts the quality, delivery speed and cost effectiveness of the health SC. However, the integration dimension had an insignificant effect on reactive resilience but a positive effect on proactive resilience.

This study examined the performance implications of MAC system dimensions and proactive and reactive resilience on operational performance in health SCs, using empirical data from only one country. Thus, generalizing the findings to include other jurisdictions may be impossible.

Healthcare managers in public health facilities should embrace the four MAC dimensions (except the integrated dimension in reactive resilience) to support information generation in SC resilience decisions.

Perhaps, the first to provide preliminary empirical evidence on the interactive effect of proactive and reactive resilience and MAC dimensions in terms of broad scope, timeliness, integration and aggregation on health SC operational performance under disruption, in the context of an emerging economy.

This paper aims to investigate business-to-business sales executives’ navigation of challenges and changes in planning during two separate periods (prevaccine and postvaccine) of time, which were impacted by a disruptive event (the COVID-19 pandemic).

This study uses a two-phase qualitative data collection approach. Thirteen executives, primarily from the Business-to-Business (B2B) manufacturing industry, were interviewed in phase one (2–3 months before the first COVID-19 vaccine). The second period of data collection was collected 4–5 months after vaccines became available.

The prevaccine business environment focused on short-term challenges, while the vaccine created exponential changes to long-term sales practices, suggesting the need to focus on critical inflection points that occur after the initial disruptive event.

This exploratory study is a step toward developing a deeper understanding of managing disruptive events within a business-to-business sales environment by stressing the importance of both the actual disruptive event and the inflection points that follow the event.

New business models are constantly developing and evolving. However, this study suggests the biggest changes could occur after an inflection point from the disruption. Thus, firms need to consider different planning strategies before and after certain inflection points following a disruptive event. First, firms should adapt from their predisruption strategy to focus on short-term challenges during the initial phases of a disruption, likely halting most of the long-term planning. Second, inflection points create the need to move beyond short-term challenges and changes to focus on long-term changes. Third, long-term strategies and planning postinflection point will be different, and likely more complex, than long-term strategies and planning predisruption.

Most studies look at a disruptive event through a single data collection period. This longitudinal study compares prevaccine and postvaccine thought processes to explore the impact of an inflection point.

Disruptions at ports may destroy the planned ship schedules profoundly, which is an imperative operation problem that shipping companies need to overcome. This paper attempts to help shipping companies cope with port disruptions through recovery scheduling.

This paper studies the ship coping strategies for the port disruptions caused by severe weather. A novel mixed-integer nonlinear programming model is proposed to solve the ship schedule recovery problem (SSRP). A distributionally robust mean conditional value-at-risk (CVaR) optimization model was constructed to handle the SSRP with port disruption uncertainties, for which we derive tractable counterparts under the polyhedral ambiguity sets.

The results show that the size of ambiguity set, confidence level and risk-aversion parameter can significantly affect the optimal values, decision-makers should choose a reasonable parameter combination. Besides, sailing speed adjustment and handling rate adjustment are effective strategies in SSRP but may not be sufficient to recover the schedule; therefore, port skipping and swapping are necessary when multiple or longer disruptions occur at ports.

Since the port disruption is difficult to forecast, we attempt to take the uncertainties into account to achieve more meaningful results. To the best of our knowledge, there is barely a research study focusing on the uncertain port disruptions in the SSRP. Moreover, this is the first paper that applies distributionally robust optimization (DRO) to deal with uncertain port disruptions through the equivalent counterpart of DRO with polyhedral ambiguity set, in which a robust mean-CVaR optimization formulation is adopted as the objective function for a trade-off between the expected total costs and the risk.

The agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.

The authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.

Downstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.

This study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

While, supply chain resilience (SCRES) continues to be a dominant topic in both academic and business literature and has gained more attention recently, there is limited knowledge on SCRES capabilities specific to business functions. The purpose of this paper is to identify and investigate capabilities shared between supply, operations and logistics that are most important for SCRES.

To address this gap, the authors followed a multi-method research approach. First, the authors used the grounded theory method to generate a theoretical framework based on interviews with 51 managers from five companies in automotive SCs. Next, the authors empirically validated the framework using a survey of 340 SC professionals from the manufacturing industry.

Five significant capabilities emerged from the qualitative study; all were significant in empirical validation. This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES.

This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES. In addition, the findings of this research help managers better allocate resources among significant capabilities.

This study analyzes antecedents explaining the lack of resilience in family-owned firms. Our model suggests that family-owned firms’ strategic behaviors and heterogeneity explain a particular crisis outcome: a lack of recovery.

Our evidence is based on a sample of 842 European family-owned firms. We complement regression analysis results with fuzzy-set qualitative comparative analysis (fsQCA).

Our results show that lack of resilience is relevant. In fact, in our sample, 60% of family firms (FFs) failed to recover their sales. This evidence supports the role played by exploitation and exploration behavior as well as family heterogeneity in explaining the lack of recovery.

Our results may offer guidance to practitioners and policymakers on the pathways that explain the lack of resilience.

Although it is unlikely that an external crisis such as COVID-19 will occur again to the same extent, other threatening events may occur and impact FFs. Understanding how FFs can avoid non-recovery is crucial: it can inform managers on how to deal with stressful events and provide guidance to economic authorities on how to help FFs around the world avoid non-recovery, which affects the economy.

First, the study contributes to FF research by offering a theoretical explanation for the different effects of FF attributes on non-recovery in the context of a global crisis. Second, it contributes to the literature on organizational resilience by examining explorative and exploitative behaviors as antecedents of FF non-recovery. Third, we show the usefulness of combining fsQCA and regression analysis to understand complex phenomena.

本研究擬分析家族企業缺乏復原力的原因。我們的模型暗示了家族企業的策略性行為和異質性是可闡明一個特殊的危機後果：企業未能成功恢復。

我們的證據是建基於一個涵蓋842間歐洲家族公司的樣本。我們以模糊集質性比較分析，去補充迴歸分析的結果。

研究結果顯示，缺乏復原力是有相關性的。事實上，在我們的樣本裡，有百分之六十的家族企業未能恢復其銷售量。研究結果提供了證據，確認了若要闡明缺乏復原力的原因，我們必須瞭解開發和探索行為、以及家族異質性所扮演的角色。

我們的研究結果，或許可為從業人員和政策制訂者提供引導，幫助他們找出缺乏復原力的原因。

雖然像2019冠狀病毒病的外部危機以同樣的程度發生的機會是很微的，但其它有威脅性的事件或會發生，並會影響家族企業; 因此，瞭解家族企業如何能避免缺乏復原力的弊端是非常重要的。這可讓經理瞭解如何處理令人憂慮的事件，亦可為經濟事務當局的高層人員提供引導，幫助他們瞭解如何協助世界各地的家族企業，去避免影響經濟的復原乏力。

首先，本研究在家族企業的探討上作出了貢獻。研究人員在一個全球危機的背景下提出了理論解釋，讓人們明白家族企業的屬性，如何會對復原乏力產生各種影響。其次，本研究在探討組織彈性的文獻方面作出了貢獻，因研究人員對作為引發家族企業復原乏力因素的探索和開發行為、進行了探討和研究。最後，研究人員展示了若要瞭解複雜的事物或現象，把模糊集質性比較分析和迴歸分析結合起來運用是有效的。