Conservatism Gets Funded? A Field Experiment on the Role of Negative Information in Novel Project Evaluation

Jacqueline N. Lane (), Misha Teplitskiy (), Gary Gray (), Hardeep Ranu (), Michael Menietti (), Eva C. Guinan () and Karim R. Lakhani ()
Additional contact information
Jacqueline N. Lane: Harvard Business School, Boston, Massachusetts 02163
Misha Teplitskiy: Laboratory for Innovation Science at Harvard, Boston, Massachusetts 02134; University of Michigan School of Information, Ann Arbor, Michigan 48109
Gary Gray: Harvard Medical School, Boston, Massachusetts 02115
Hardeep Ranu: Harvard Medical School, Boston, Massachusetts 02115
Michael Menietti: Harvard Business School, Boston, Massachusetts 02163; Laboratory for Innovation Science at Harvard, Boston, Massachusetts 02134
Eva C. Guinan: Laboratory for Innovation Science at Harvard, Boston, Massachusetts 02134; Harvard Medical School, Boston, Massachusetts 02115; Dana-Farber Cancer Institute, Boston, Massachusetts 02215
Karim R. Lakhani: Harvard Business School, Boston, Massachusetts 02163; Laboratory for Innovation Science at Harvard, Boston, Massachusetts 02134

Management Science, 2022, vol. 68, issue 6, 4478-4495

Abstract: The evaluation and selection of novel projects lies at the heart of scientific and technological innovation, and yet there are persistent concerns about bias, such as conservatism. This paper investigates the role that the format of evaluation, specifically information sharing among expert evaluators, plays in generating conservative decisions. We executed two field experiments in two separate grant-funding opportunities at a leading research university, mobilizing 369 evaluators from seven universities to evaluate 97 projects, resulting in 761 proposal-evaluation pairs and more than $250,000 in awards. We exogenously varied the relative valence (positive and negative) of others’ scores and measured how exposures to higher and lower scores affect the focal evaluator’s propensity to change their initial score. We found causal evidence of a negativity bias, where evaluators lower their scores by more points after seeing scores more critical than their own rather than raise them after seeing more favorable scores. Qualitative coding of the evaluators’ justifications for score changes reveals that exposures to lower scores were associated with greater attention to uncovering weaknesses, whereas exposures to neutral or higher scores were associated with increased emphasis on nonevaluation criteria, such as confidence in one’s judgment. The greater power of negative information suggests that information sharing among expert evaluators can lead to more conservative allocation decisions that favor protecting against failure rather than maximizing success.

Keywords: project evaluation; innovation; knowledge frontier; information sharing; negativity bias (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:6:p:4478-4495

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