Beyond feasibility filters: How expertise heterogeneity enables innovation recognition

Abstract Research Summary Organizations often struggle to identify promising innovations that balance novelty and feasibility in multidisciplinary domains, yet how does evaluator expertise heterogeneity shape these assessments? This study examines how evaluator expertise influences innovation evaluation through a field experiment with National Aeronautics and Space Administration's (NASA) Astrobee Robotic Arm Challenge, involving 354 evaluators assessing 101 solutions. Domain‐spanning evaluators assign higher novelty ratings while maintaining similar feasibility ratings compared to domain‐specific evaluators. Domain‐adjacent evaluators show higher ratings on both dimensions. Human‐LLM analysis of 3007 evaluator comments reveals a two‐stage process: feasibility filtering (evaluating minimum viability) followed by integrative assessment (evaluating enhancement potential). Different expertise types serve complementary functions: domain‐spanning evaluators recognize enhancement potential while maintaining rigorous standards; domain‐adjacent evaluators show openness to novel approaches; domain‐specific evaluators ensure technical rigor. These findings suggest effective innovation evaluation depends on strategically combining complementary expertise types rather than identifying optimal individual evaluators. Managerial Summary Organizations often struggle to identify innovations that are both novel and feasible, risking missed breakthroughs or wasted resources. We study how evaluator expertise shapes innovation assessments in a field experiment with NASA, in which 354 evaluators reviewed 101 robotic arm designs. Evaluators with expertise spanning multiple domains recognize more novel yet feasible ideas. Those with single‐domain expertise provide essential technical gatekeeping but overlook cross‐domain improvements, while adjacent‐field experts are more open but less rigorous. Organizations can strengthen innovation selection by strategically combining these complementary expertise types—using domain‐specific experts for initial feasibility screening and domain‐spanning experts to identify integrative opportunities—rather than seeking one “ideal” evaluator.

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Publication Details

Journal
Strategic Management Journal
Published
2026-01-13
DOI
https://doi.org/10.1002/smj.70060
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
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article

Beyond feasibility filters: How expertise heterogeneity enables innovation recognition

Zoe Szajnfarber, Michael Menietti, Jacqueline N. Lane, Jason Crusan
Strategic Management Journal
Innovation and Knowledge Management
article

Beyond feasibility filters: How expertise heterogeneity enables innovation recognition

Zoe Szajnfarber, Michael Menietti, Jacqueline N. Lane, Jason Crusan
article en

Abstract

Abstract Research Summary Organizations often struggle to identify promising innovations that balance novelty and feasibility in multidisciplinary domains, yet how does evaluator expertise heterogeneity shape these assessments? This study examines how evaluator expertise influences innovation evaluation through a field experiment with National Aeronautics and Space Administration's (NASA) Astrobee Robotic Arm Challenge, involving 354 evaluators assessing 101 solutions. Domain‐spanning evaluators assign higher novelty ratings while maintaining similar feasibility ratings compared to domain‐specific evaluators. Domain‐adjacent evaluators show higher ratings on both dimensions. Human‐LLM analysis of 3007 evaluator comments reveals a two‐stage process: feasibility filtering (evaluating minimum viability) followed by integrative assessment (evaluating enhancement potential). Different expertise types serve complementary functions: domain‐spanning evaluators recognize enhancement potential while maintaining rigorous standards; domain‐adjacent evaluators show openness to novel approaches; domain‐specific evaluators ensure technical rigor. These findings suggest effective innovation evaluation depends on strategically combining complementary expertise types rather than identifying optimal individual evaluators. Managerial Summary Organizations often struggle to identify innovations that are both novel and feasible, risking missed breakthroughs or wasted resources. We study how evaluator expertise shapes innovation assessments in a field experiment with NASA, in which 354 evaluators reviewed 101 robotic arm designs. Evaluators with expertise spanning multiple domains recognize more novel yet feasible ideas. Those with single‐domain expertise provide essential technical gatekeeping but overlook cross‐domain improvements, while adjacent‐field experts are more open but less rigorous. Organizations can strengthen innovation selection by strategically combining these complementary expertise types—using domain‐specific experts for initial feasibility screening and domain‐spanning experts to identify integrative opportunities—rather than seeking one “ideal” evaluator.

Strategic Management Journal
George Washington University (US), Department of the Premier and Cabinet (AU), Baim Institute for Clinical Research (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 90%
Innovation and Knowledge Management
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