Development and validation of a domain-specific scale of founder characteristics associated with startup success

Early differentiation of startup founders with high success potential remains a central challenge for entrepreneurship research, innovation policy, and capital allocation in high-uncertainty environments. Existing approaches rely largely on broad personality models or intention-based instruments developed primarily to explain entry into entrepreneurship rather than differentiation of founders associated with realized venture success. In this study, we introduce a domain-specific model of founder success characteristics and develop a 31-item Startup Founder Success Scale (SFSS) to differentiate realized success from entrepreneurial intent. The sample (N = 10,007) included startup founders recruited from predefined pools meeting objective funding, revenue, or acquisition benchmarks, as well as corporate managers and aspiring entrepreneurs. Exploratory and confirmatory factor analyses supported six distinct dimensions-Relentless Resilience, Value-Creating Opportunism, Intrinsic Curiosity, Courageous Decision-Making, Strategic Innovativeness, and Transformational Leadership-which together accounted for 71% of the common variance in founder-specific latent trait measures within the scale, indicating strong internal coherence. Group comparisons showed that these dimensions reliably distinguished Successful Startup Founders from Corporate Managers and Aspiring Entrepreneurs, with large effect-size separations (Cohen's d = 0.83-1.77) exceeding the small-to-moderate effects (d ≈ 0.2-0.5) typically reported for broad personality traits in entrepreneurship research. Conceptually, these findings are consistent with a multi-level framework in which founder-specific characteristics are closely aligned with decision-making under uncertainty and resource orchestration during early venture execution, helping explain why intent-based and general personality models, while valuable for understanding entrepreneurial entry, may be less closely aligned with realized startup success. Practically, the SFSS provides a validated psychometric tool that may support more structured evaluation of founder-related characteristics, targeted training, and resource allocation across venture capital, angel investing, public investment bodies, accelerators, and entrepreneurial education programs. Prospective longitudinal research is required to establish predictive validity for real-world outcomes.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-06-26
DOI
https://doi.org/10.1371/journal.pone.0351970
Primary Topic
Entrepreneurship Studies and Influences
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and validation of a domain-specific scale of founder characteristics associated with startup success

Nick E. Barraclough, Irena C. Danilovska, Catherine Preston, Manousos Klados
PLoS ONE
Entrepreneurship Studies and Influences
article

Development and validation of a domain-specific scale of founder characteristics associated with startup success

Nick E. Barraclough, Irena C. Danilovska, Catherine Preston, Manousos Klados
article en

Abstract

Early differentiation of startup founders with high success potential remains a central challenge for entrepreneurship research, innovation policy, and capital allocation in high-uncertainty environments. Existing approaches rely largely on broad personality models or intention-based instruments developed primarily to explain entry into entrepreneurship rather than differentiation of founders associated with realized venture success. In this study, we introduce a domain-specific model of founder success characteristics and develop a 31-item Startup Founder Success Scale (SFSS) to differentiate realized success from entrepreneurial intent. The sample (N = 10,007) included startup founders recruited from predefined pools meeting objective funding, revenue, or acquisition benchmarks, as well as corporate managers and aspiring entrepreneurs. Exploratory and confirmatory factor analyses supported six distinct dimensions-Relentless Resilience, Value-Creating Opportunism, Intrinsic Curiosity, Courageous Decision-Making, Strategic Innovativeness, and Transformational Leadership-which together accounted for 71% of the common variance in founder-specific latent trait measures within the scale, indicating strong internal coherence. Group comparisons showed that these dimensions reliably distinguished Successful Startup Founders from Corporate Managers and Aspiring Entrepreneurs, with large effect-size separations (Cohen's d = 0.83-1.77) exceeding the small-to-moderate effects (d ≈ 0.2-0.5) typically reported for broad personality traits in entrepreneurship research. Conceptually, these findings are consistent with a multi-level framework in which founder-specific characteristics are closely aligned with decision-making under uncertainty and resource orchestration during early venture execution, helping explain why intent-based and general personality models, while valuable for understanding entrepreneurial entry, may be less closely aligned with realized startup success. Practically, the SFSS provides a validated psychometric tool that may support more structured evaluation of founder-related characteristics, targeted training, and resource allocation across venture capital, angel investing, public investment bodies, accelerators, and entrepreneurial education programs. Prospective longitudinal research is required to establish predictive validity for real-world outcomes.

PLoS ONEVol. 21(6)
University of York (GB)
Decent work and economic growth
Openalex Percentile: Top 4%
Entrepreneurship Studies and Influences
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.