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This study explored the relationship between employees' cognitive capabilities and firm performance by exploring the moderating role of decision-making style and the mediating effect of knowledge creation. Understanding the role of cognitive capabilities in value creation is crucial for human resource management to achieve the anticipated organizational performance.

Structural equation modeling, cognitive skills theory, cognitive skills acquisition theory and a knowledge creation framework were applied.

The first finding suggests that only A-shaped skills predict higher knowledge creation, while T-shaped skills do not. Second, knowledge creation predicts higher financial performance and a lower level of financial uncertainty. Third, T-shaped skills have no indirect effect on financial performance or financial uncertainty. Fourth, A-shaped skills exerted significant indirect effects on financial performance and uncertainty. Fifth, the rational decision-making style did not moderate the link between knowledge creation and financial performance, as opposed to the intuitive decision-making style.

A review of existing research indicates a lack of studies examining the effect of cognitive skills on organizational outcomes and contingencies under which cognitive skills lead to superior outcomes. This study advances research on T-shaped and A-shaped skills and knowledge creation by empirically exploring their interrelationships with financial performance. Managerial implications and suggestions for future research are also highlighted.

In the wake of severe socio-economic damage, many firms have made creative and technological progress in their responses to the COVID-19 crisis. This paper examines internal and external environmental complexity elements as antecedents of business responses and builds a framework for tourism firms to respond to the pandemic crisis.

This study obtained survey data from 395 respondents in the Vietnamese tourism and hospitality industry. A partial least squares structural equation modeling–artificial neural network approach was used to examine various combinations of internal and external environmental complexity elements that have different impacts on business responses and firms' performance.

The knowledge and practice created by the firm's employees (individual creativity), obtained from traditional contexts (traditionality) were identified as internal environmental complexity factors while practice learned from other firms (mimetic pressure), information processing (status certainty) and digital transformation (digital technology speed) were treated as external environmental complexity factors. Internal and external environmental complexity factors influence business responses and firms' performance positively but differently.

This study demonstrates that firms should integrate their internal environment of creativity and traditionality with external environmental factors of mimetic pressure, status certainty and digital technology speed to create better business responses, and thus firm performance in the COVID-19 era.

This investigation contributes to environmental research and narrows the existing research gap relating to the association between types of environmental complexity and firms' responsive action, which then influence firms' performance in terms of sustainable competitiveness.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.