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The ability of companies to develop organizational resilience before, during and after crises is crucial for their development and growth. The future forecasts increasingly more crises, thus this paper aims at identifying key topics around organizational resilience in COVID-19 times, differentiating them of pre-crisis literature and synthesizing them into a research framework.

Based on Web of Science and Scopus, the authors analysed the content of the only twenty-seven VHB-ranked primary studies discussing organizational resilience during COVID-19, providing a complete survey of this research area.

Following a content analysis, the authors identified main topics of interest for researchers at the moment of COVID-19, how it differed from before this adversity and provide an outlook on future research. The results presented include in the COVID-19 context: an adapted definition of organizational resilience, key theoretical framework, insights for future research. Some topics have been found to be increasingly more important during COVID-19 (i.e. digitalization, partnerships and learning) while others have been less explored although present in pre-COVID-19 research on organizational resilience (i.e. dynamic capabilities, anticipation and preparedness).

Understanding key issues in global disruptions could help practitioners in fostering resilience as much as researchers in identifying new ways to advance and maintain resilience. This paper differs from other reviews by providing a full text analysis, based on qualitative content analysis, of all ranked published papers in the considered period.

As part of a national plan to govern professional and organizational development in Norwegian specialist healthcare, the country’s hospital clinics are tasked with constructing development plans. Using the development plan as a case, the paper analyzes how managers navigate and legitimize the planning process among central actors and deals with the contingency of decisions in such strategy work.

This study applies a qualitative research design using a case study method. The material consists of public documents, observations and single interviews, covering the process of constructing a development plan at the clinical level.

The findings suggest that the development plan was shaped through a multilevel translation process consisting of different contending rationalities. At the clinical level, the management had difficulties in legitimizing the process. The underlying tension between top-down and bottom-up steering challenged involvement and made it difficult to manage the contingency of decisions.

The findings are relevant to public sector managers working on strategy documents and policymakers identifying challenges that might hinder the fulfillment of political intentions.

This paper draws on a case from Norway; however, the findings are of general interest. The study contributes to the academic discussion on how to consider both the health authorities’ perspective and the organizational perspective to understand the manager’s role in handling the contingency of decisions and managing paradoxes in the decision-making process.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.