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Although scholars in strategic management have identified innovating and exit as firms’ two sequential strategic responses to long-run crisis, the potential interdependency has yet remained implicit. Specifically, in the context of Chinese Privately Owned Enterprises (POEs), this study investigates the interrelationship of these two strategic responses during long-run crisis. Building on resource redeployment perspective, the authors propose that firms tend to simultaneously leverage innovating and exit responses.

The authors use the data from the 2010 Chinese POEs survey to verify how firms in the long-term crisis made strategic responses after the 2008 financial crisis. Besides, the authors utilize Probit regressions as the basic analysis and further employ bivariate Probit regressions to conduct robustness tests.

This study provides empirical evidence confirming that firms in the long-run period of the crisis tend to adopt both exit and innovating strategies at the same time, that is, the strategy of resource redeployment. Moreover, this study further finds that government subsidies, the degree of marketization and firm’s organizational capability could all accentuate the decision-making of firms’ resource redeployment.

The authors thus contribute to the study of strategic responses to crisis in strategic management by dynamically find out the interdependency of two responses and enrich the research on resource redeployment perspective by identifying three influential positive antecedents, adding to the ongoing investigation on positive drivers of resource redeployment.

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.