This study explores how firms sought to effectively match their internal competence with external resources from the supply chain network to improve operational resilience (OR) during the COVID‐19 pandemic. Drawing upon matching theory, this study provides an internal–external matching perspective based on flexibility–stability features of OR to explain the operational mechanisms underlying the different matchings between internal flexibility (i.e., product diversity)/stability (i.e., operational efficiency) and external flexibility (i.e., structural holes)/stability (i.e., network centrality). We find that more heterogeneous matchings between internal (external) flexibility and external (internal) stability have a complementary effect that enhances OR, whereas more homogeneous matchings between internal flexibility (or stability) and external flexibility (or stability) have a substitutive effect that reduces OR. This study provides valuable contributions to research focusing on the supply chain, organizational resilience, and operations management.

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This paper applies upper echelons theory to investigate whether chief information officers (CIOs) and boards of directors affect the development of AI orientation, which represents firms’ overall strategic direction and goals regarding the introduction and application of artificial intelligence (AI)technology. We tested our model using a dataset drawn from 1,454 publicly listed firms in China. Our findings show that the presence of a CIO positively influences AI orientation and that board educational diversity, R&D experience, and AI experience positively moderate the CIO’s effect on AI orientation. Our post hoc analysis further demonstrates that these board characteristics represent contingencies that impact AI orientation but not conventional IT orientation. This paper contributes to the upper echelons literature and IT management research by offering contextualized arguments that explain new business and IT strategies such as AI orientation. Further, our findings suggest important implications about how to build top management teams and boards capable of effectively developing AI orientations

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The Chinese construction industry is characterised by the frequent job changes of lower-level workers, which has been identified as one of the principal causes of poor performance, quality and safety accidents, and high technology loss in the construction industry. Assuming that each party has incomplete market information about the other, we can thus define a dynamic game relationship between employers' incentives to retain workers and workers' mobility behaviour. By using evolutionary game theory, in this study we analyse various conditional evolutionary stable strategies and explore how employer behaviour influences the mobility of the workers in this industry in China. The results show that under the prevailing employment model, construction workers are bound to change jobs regardless of whether their employers adopt incentives to retain them or not. This finding suggests that the government, as the market regulator, should reform its employment model to ensure that construction workers switch jobs in an orderly and rational manner.