Signaling for success in university research funding applications

Signaling theory explains how organizations convey credible information under conditions of information asymmetry. Yet, while recent work highlights that signals often interact—reinforcing or substituting—most studies have treated signals as independent and additive, and empirical evidence of configurational interaction patterns remains limited. This study addresses this limitation by examining how multiple institutional signals jointly shape evaluators’ judgments in peer-reviewed university research funding. Using fuzzy-set qualitative comparative analysis (fsQCA), we identify distinct configurations of capability, reputation, and status signals that lead to both high and low funding success. The findings reveal that no single signal ensures success; rather, outcomes emerge from specific portfolios of signals whose effects depend on their combinations. We extend signaling theory by demonstrating that signals can also suppress or neutralize one another, and by introducing a configurational perspective that captures synergy, substitution, and suppression within signal portfolios.

Authors

Institutions

Publication Details

Journal
Journal of Business Research
Published
2026-09-04
DOI
https://doi.org/10.1016/j.jbusres.2026.116519
Primary Topic
Research, Science, and Academia
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Signaling for success in university research funding applications

David Bruce Audretsch, Evan J. Douglas, Per Davidsson, Forough Zarea Fazlelahi et al.
Journal of Business Research
Research, Science, and Academia
article

Signaling for success in university research funding applications

David Bruce Audretsch, Evan J. Douglas, Per Davidsson, Forough Zarea Fazlelahi, Dietmar W. Hutmacher
article en

Abstract

Signaling theory explains how organizations convey credible information under conditions of information asymmetry. Yet, while recent work highlights that signals often interact—reinforcing or substituting—most studies have treated signals as independent and additive, and empirical evidence of configurational interaction patterns remains limited. This study addresses this limitation by examining how multiple institutional signals jointly shape evaluators’ judgments in peer-reviewed university research funding. Using fuzzy-set qualitative comparative analysis (fsQCA), we identify distinct configurations of capability, reputation, and status signals that lead to both high and low funding success. The findings reveal that no single signal ensures success; rather, outcomes emerge from specific portfolios of signals whose effects depend on their combinations. We extend signaling theory by demonstrating that signals can also suppress or neutralize one another, and by introducing a configurational perspective that captures synergy, substitution, and suppression within signal portfolios.

Journal of Business ResearchVol. 218
Queensland University of Technology (AU), Indiana University Bloomington (US), Jönköping University (SE)
Australian Research Council
Openalex Percentile: Top 4%
Research, Science, and Academia
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.