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The goal of the paper is twofold. First, it aims to empirically conceptualize whether a wide array of fragmented demand planning activities, performed in supply chains, can be logically categorized into actionable sets of practices, which then form a broader conceptualization of the demand planning process. Second, regarding certain contextual factors, our research seeks to investigate the contribution of demand planning, as a higher-order construct, to mitigating disruptions induced by operational risks in supply chains.

In this study, PLS-SEM was used to estimate the reflective-formative nature of the model. The results of PLS-SEM were additionally complemented by the assessment of the predictive power of our model. Finally, to reveal possible contingency effects, the multigroup analysis (MGA) was conducted.

The study suggests that demand planning process (DPP) is a second-order construct that is composed of four sets of practices, including goal setting, data gathering, demand forecasting, communicating the demand predictions and synchronizing supply with demand. The study also reveals that the demand planning practices, only when considered together, as a higher-order factor, significantly contribute to mitigating disruptions driven by operational risks. Finally, the research shows that the strength of the impact of demand planning on disruptions is contextually dependent.

While the study makes some important contributions, the obtained findings ought to be considered within the context of limitations. First, the study only investigates disruptions driven by operational risks, ignoring the negative consequences of environmental risks (terrorist attacks, natural disasters, etc.), which may have a far more negative impact on supply chains. Second, the sample is mostly composed of medium and large companies, not necessarily representative of demand planning performed by the entire spectrum of companies operating in the market.

The study shows that to effectively mitigate disruptions induced by operational risks, the demand planning practices should be integrated into a higher-order construct. Likewise, our research demonstrates that the intensity of demand planning process is contingent upon a number of contextual factors, including firm size, demand variability and demand volume.

The study indicates that to mitigate disruptions of operational risk, demand planning as a higher-order dynamic capability can be referred to the concept of organizational learning, which contributes to forming a critical common ground, ensuring the balance between formal and informal dynamic routines.

The paper depicts that to fully deal with disruptions, the demand planning practices need to be integrated and categorized into the dedicated higher-order. This may lead to forming demand planning as a higher-order dynamic capability that provides a more rapid and efficient rebuttal to any disruptions triggered by operational risks.

The purpose of this paper is to explore the effects of demand planning practices on the disruptions induced by operational risk. The study reveals whether the negative consequences of operational risk factors (covering demand, supply, control and process risks) can be absorbed or amplified through the application of specific demand planning practices in supply chains.

The study involves the partial least squares path model procedure. Likewise, the items of the constructs in the outer model were subjected to a purification process by principal component analysis with the orthogonal (varimax) and oblique (Promax) methods of rotation.

The findings suggest that although one may not observe uniformity and standardization in the role of demand planning in alleviating the negative effects of operational risks, still some regularities can be obtained. Having said that some demand planning practices tend to mitigate or reinforce disruptions driven by operational risk, whereas the other practices simultaneously absorb and amplify disruptions driven by operational risk.

The study shows that different managerial instruments, which are not inherently dedicated to risk management, when appropriately applied, may have an indirect impact on the mitigation of supply chain risk. In particular, the concept of demand planning might be very helpful for managers when dealing with demand and control risks.

The study simultaneously examines a more detailed bundle of practices forming the demand planning process. The research attempts to investigate the link between the demand planning process and operational risk consequences, derived from all sources (supply, demand, process and control). The paper shows that risk management is not a sole tool to mitigate disruptions. Among the concepts, which contribute to decrease risks is the demand planning process. The study demonstrates that the demand planning process when applied as a component of supply chain management, may contribute to mitigate certain operational risks.

This study investigates the possible curvilinear relationship between operational interdependency and supply chain performance as well as the contingency effect of supply chain disruptions, in terms of disruption orientation and disruption impact.

Path analysis was employed to test the hypotheses using the data collected from Chinese manufacturers.

The results confirm an inverted U-shape effect of operational interdependency. As level of buyer-supplier operational dependency increase, the supply chain performance is enhanced. However, the benefits of operational interdependency diminish beyond a certain point. Additionally, the findings of this study show the disruption orientations positively moderate the relationship between interdependency and performance, whereas the effect of disruption impact is not significant.

The findings of this study provide an explanation to the theoretical gap about the equivocal results of the effect of dependency, which provide new insights into the literature regarding buyer-supplier relationships. Furthermore, this paper identifies the moderating role of supply chain disruption in the relationship between operational interdependency and supply chain performance, which provide further explanation about the mixed results of the effect of dependency. The results confirmed that supply chain disruption orientation positively moderate the relationship between operational interdependency and supply chain performance.

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.

Does internal integration extend to business continuity and to managing supply chain disruptions (SCDs)? Despite the voluminous literature on supply chain integration, evidence on its effectiveness on risk management and disruption response is scant. The purpose of this paper is to assess the effectiveness of business continuity management (BCM) and of supply chain involvement in BCM (SCiBCM) on reputational and operational damage containment in the face of SCDs.

This study draws on Simons’ Levers of Control framework to explain how the involvement of supply chain in BCM affects firm capabilities in containing damages caused by major SCDs. The authors develop and test hypotheses by analyzing large-scale questionnaire responses from 448 European companies.

Results of the data analysis suggest that BCM improves reputational damage containment, whereas SCiBCM improves operational damage containment. The findings also show that the significant effects of BCM and SCiBCM on reputational and operational damage containment, respectively, were amplified for the firms facing higher supply chain vulnerability. Post-hoc analysis further reveals the complementarity effect between BCM and SCiBCM for the companies exposed to high supply chain vulnerability.

Evidence on the effects of BCM and its internal integration on performance is limited. This study offers empirical evidence on the topic. Also, while supply chain integration can improve information sharing and coordination, some may not fully recognize its potential benefits in addressing SCDs. This study theoretically and empirically demonstrates the role played by internal integration, in the form of SCiBCM, in improving organizational damage containment efforts.

The purpose of this article is to discuss how the mastery of resilience in operations and supply chains plays a significant role in the transition to a more sustainable future. Furthermore, it is supposed to propose avenues for future research on operational and supply chain resilience, interacting with the sustainability literature in our field.

A conceptual review of resilience and sustainability themes within operations and supply chain management research is conducted. Reflections on the topic are informed by relevant literature published over the last decade.

The major conceptual contributions are threefold: (1) This article elaborates on the understanding of operational resilience and supply chain resilience concepts and reviews their respective primary research streams. (2) It proposes resilience as the missing element in the pursuit of excellence in organizations that want to contribute to a more sustainable future. (3) The article offers a research framework that provides a future research agenda at the intersection of resilience and sustainability in operations and supply chain management research.

The article highlights gaps in current research and illustrates further areas of research that need to be addressed to maximize the contribution of operations and supply chain management research in supporting practitioners to achieve a more sustainable future.

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.

To study how supply chain decision makers gather, process and use the available internal and external information when facing supply chain disruptions.

The paper reviews relevant supply chain literature to build an information management model for disruption management. Afterwards, three case studies in the vehicle assembly sector, namely cars, trucks and aircraft wings, bring the empirical insights to the information management model.

This research characterises the phases of disruption management and identifies the information companies use to recover from a variety of disruptive events. It presents an information management model to enhance supply chain visibility and support disruption management at the operational level. Moreover, it arrives at two design propositions to help companies in the redesign of their disruption discovery and recovery processes.

This research studies how companies manage operational disruptions. The proposed information management model allows to provide visibility to support the disruption management process. Also, based on the analysis of the disruptions occurring at the operational level we propose a conceptual model to support decision makers in the recovery from daily disruptive events.

The purpose of this paper is to investigate the knowledge existing in the literature on supply chain resilience for identifying the supply chain practices adopted for securing resilience in given uncertain event.

A systematic literature review is conducted to identify 84 conceptual and empirical studies. The research findings are synthesized in categories of uncertain events, supply chain practices and outcomes.

A set of propositions linking the uncertain events, mechanisms and supply chain resilience improvement is developed. It was found that the sufficient conditions for resilience under unexpected disasters are substantially different from those required for resilience against disruptions caused by internal practices or complexity.

Practitioners can benefit from the knowledge of interventions and mechanisms to improve their supply chain resilience in the face of different unpredictable situations. The contribution of this paper is twofold: first, it develops an actionable theory of supply chain resilience by developing testable propositions in the context of supply chains exposed to uncertainties resulting from unexpected disruptions, complexity of supply chains and adoption of certain internal practice; second, the paper highlights the key shortcomings of existing literature and provides opportunities for further research and improvement.

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.