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We predict and find that regulated firms’ mandatory disclosures crowd out unregulated firms’ voluntary disclosures. Consistent with information spillovers from regulated to unregulated firms, we document that unregulated firms reduce their own disclosures in the presence of regulated firms’ disclosures. We further find that unregulated firms reduce their disclosures more the greater the strength of the regulatory information spillovers. Our findings suggest that a substitutive relationship between regulated and unregulated firms’ disclosures attenuates the effect of disclosure regulation on the market-wide information environment.

With permission of Elsevier

© 2025 The Author(s). Journal of Occupational and Organizational Psychology published by John Wiley & Sons Ltd on behalf of The British Psychological Society.

Emerging crowdsourcing and crowdfunding mechanisms enable citizens to decide which research projects should be funded. By transferring control from professional scientists, these mechanisms reflect a broader shift towards more open “Mode 2” knowledge production that allows non-academic stakeholders to shape the direction of science. Although this may lead to a greater emphasis on the social impact of research, there is no systematic evidence on how crowd evaluators weigh social impact relative to other criteria such as scientific merit or team qualifications. There are also concerns that the personal financial costs associated with crowdfunding prevent certain socio-economic groups from participating, reducing the representativeness of opinions. Similarly, it is not clear what role citizens’ personal interest in particular topics plays in shaping their evaluations. We provide empirical evidence using data from over 2,300 crowd evaluators who assessed four research proposals in different fields and could express their support using a crowdsourcing mechanism (i.e., recommendation) and a crowdfunding mechanism (i.e., donation of own money). We confirm that crowd evaluators give significant weight to perceived social impact, although this weight is not larger than that of scientific merit. Compared to crowdsourcing, crowdfunding gives greater voice to citizens with higher income and education. Personal interest in a topic tends to be associated with greater project support, which may partly reflect an inflated assessment of social impact. Despite these general patterns, we also observe differences across projects – illustrating context-specificity and variability that make open Mode 2 processes difficult to predict and control.

with permission of Elsevier

How can the selection of innovation projects be designed to reduce false positives and false negatives? Prior research has provided theoretical insights into organizing to reduce errors, yet we know little about how organizations adapt selection over time and the effects of this on selection outcomes. Drawing from qualitative data from 126 interviews conducted over several years, we explore how an accelerator evolved through three selection regimes for high-stakes funding decisions, focusing on the organizational changes and their underlying reasons. We then analyze quantitative data from all 3,580 submissions they received, assessing false positives and false negatives across these regimes. Our findings reveal a persistent occurrence of both types of errors, with relatively small differences across the regimes despite deliberate efforts to enhance the process. In the final regime, which increased submission quality by emphasizing applicant track record and adding additional layers of screening, evaluators surprisingly became more prone to making selection errors. This finding stands net of accounting for (1) differences in the pool of submissions, (2) differences in treatment effects through training and resources provided, (3) learning, and (4) market evolution. By combining qualitative and quantitative data, we explain this through two mechanisms: (1) mean reversion in combination with increased emphasis on applicant track record and (2) within-type adverse selection enabled by a more stringent selection process. The study reveals that evolving an organization’s selection regime may require adjustments across multiple aspects, resulting in unintended consequences.

© 2025, INFORMS