A fundamental premise of the information processing approach in entrepreneurship theory is that the distribution and processing of information is key to opportunity identification. We propose that collectivist-individualist cultural values influence the efficacy of information processing leading to different levels of entrepreneurial orientation (EO). Specifically, we submit that collectivism enhances shared information processing and goal setting in a dynamic environment, while individualism facilitates creativity and divergent thinking that can help EO if sufficient informational input is available. To empirically verify our theory, we study the relationships using survey and archival data from a sample of 487 firms in six industries in Brazil and Belgium, two countries that contrast in collectivism-individualism. Consistent with our predictions, we find higher EO in the collectivist culture of Brazil under high environmental dynamism and low information availability, and this difference is increased by strategic planning.

In July 2022, we released a preprint of Chapter 38 of The Cambridge Handbook of Experimental Jurisprudence. In the months that followed, there were a variety of judicial reactions, ranging from levity and philosophical reflection, to irritation and ad hominem criticism. The most detailed response consisted in a paper, 'Academia', co-authored by a High Court judge, that was published online in May 2023. In this rejoinder, we show that the concerns expressed in that paper are ill-founded.

When job tasks are automated, does this augment or diminish the value of labor in the tasks that remain? We argue the answer depends on whether removing tasks raises or reduces the expertise required for remaining non-automated tasks. Since the same task may be relatively expert in one occupation and inexpert in another, automation can simultaneously replace experts in some occupations while augmenting expertise in others. We propose a conceptual model of occupational task bundling that predicts that changing occupational expertise requirements have countervailing wage and employment effects: automation that decreases expertise requirements reduces wages but permits the entry of less expert workers; automation that raises requirements raises wages but reduces the set of qualified workers. We develop a novel, content-agnostic method for measuring job task expertise, and we use it to quantify changes in occupational expertise demands over four decades attributable to job task removal and addition. We document that automation has raised wages and reduced employment in occupations where it eliminated inexpert tasks, but lowered wages and increased employment in occupations where it eliminated expert tasks. These effects are distinct from—and in the case of employment, opposite to—the effects of changing task quantities. The expertise framework resolves the puzzle of why routine task automation has lowered employment but often raised wages in routine task-intensive occupations. It provides a general tool for analyzing how task automation and new task creation reshape the scarcity value of human expertise within and across occupations.