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Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

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With the increasing frequency and impact of disruptions (i.e., in the wake of COVID 19, Suez Canal blockage), researchers and practitioners are faced with an ongoing challenge to enable supply chain resilience. Drawing on the theory of paradox and ambidexterity, this study highlights paradoxes in enabling supply chain resilience and proposes that firms manage such paradoxes by developing an ambidexterity capability. We build a research model hypothesizing the role of social capital that enables organizational ambidexterity to realise supply chain resilience. The model is tested using structural equation modelling comprising survey data of 204 Pakistani manufacturing firms. Based on the results of this study our overall model finds support with the exception that cognitive capital is not related to ambidexterity. This research contributes to the further conceptualization f paradoxes in supply chain resilience and advances the theory for a more comprehensive understanding of the impact of organizational social capital on ambidexterity. Management relevance statementMost firms are directly or indirectly affected by supply chain disruptions due to Covid-19 lockdowns or its aftermath. This even forces businesses in several cases into bankruptcy. Therefore, across industries across attention is on building resilience in their supply chain functions. Supply chain resilience allows firms to prepare and avoid disruptions and act accordingly in the face of disruptions. In this study, we help managers to understand that based on social capital firms can create supply chain resilience by making use of organizational ambidexterity. Lessons learned through the joint pursuit of alignment and adaptability (ambidexterity) also generate positive outcomes for supply chain resilience. Thus, balancing alignment and adaptability is a better strategy to generate supply chain resilience instead of solely focusing on alignment or adaptability. This provides counterintuitive advice as managers might be otherwise tempted to focus solely on adaptability versus alignment.

Energy communities will play a central role in the sustainable energy transition by helping inform and engage end users to become more responsible consumers of energy. However, the true potential of energy communities can only be unlocked at scale. This scalability requires data-driven solutions that model not just the behaviour of building occupants but also of energy flexible resources in buildings, distributed generation and grid conditions in general. This understanding can then be utilized to improve the design and operation of energy communities in a variety of real-world settings. However, in practice, collecting and analysing the data necessary to realize these objectives forms a large part of such projects, and is often seen as a prohibitive stumbling block. Furthermore, without a proper understanding of the local context, these projects are often at risk of failure due to misplaced expectations. However, this process can be considerably accelerated by utilizing open source datasets and models from related projects, which have been carried out in the past. Likewise, a number of open source, general-purpose tools exist that can help practitioners design and operate LECs in a near-optimal manner. These resources are important because they not only help ground expectations, they also provide LECs and other relevant stakeholders, including utilities and distribution system operators, with much-needed visibility on future energy and cash flows. This review provides a detailed overview of these open-source datasets, models and tools, and the many ways they can be utilized in optimally designing and operating real-world energy communities. It also highlights some of the most important limitations in currently available open source resources, and points to future research directions. Highlights:1. The importance of open-source datasets and tools for local energy communities 2. Common use cases for open-source datasets, models and tools for energy communities 3. A thorough review of electricity demand and meteorological datasets and models 4. Most important shortcomings with currently available datasets, models and tools