Selection regimes and selection errors
File(s)
Author(s)
Sharapov, Dmitry
Dahlander, Linus
Type
Journal Article
Abstract
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.
Date Issued
2025-11-01
Date Acceptance
2025-03-26
Citation
Organization Science, 2025, 36 (6), pp.2324-2348
ISSN
1047-7039
Publisher
Institute for Operations Research and Management Sciences
Start Page
2324
End Page
2348
Journal / Book Title
Organization Science
Volume
36
Issue
6
Copyright Statement
© 2025 The Author(s). https://doi.org/10.1287/orsc.2023.17482, used under a Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/.” his work is licensed under a Creative Commons Attribution 4.0 InternationalLicense. You are free to copy, distribute, transmit and adapt this work, but you must attribute thiswork as “Organization Science.
Identifier
10.1287/orsc.2023.17482
Publication Status
Published
Date Publish Online
2025-05-14