Journal of Business and Psychology, 2026

Understanding Risk Takers at Work

A meta-analytic investigation on the construct validity of risk propensity at work: insights from decision science and large language models

NSF Funded Open Access
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Subjects
Background

Theoretical Foundation & Aims

Theoretical Background

Risk propensity (RP) is a central construct in personality, economic, and decision sciences. We define it as a stable individual difference reflecting a person's psychological tendency to approach or avoid decision situations characterized by uncertainty and potential variance in outcomes.

While economists often view risk strictly as variance, our psychological perspective broadens this to include sensitivity to potential gains (rewards) and losses (harm).

Research Aims

  • Clarify the Construct: Address conceptual ambiguity by defining RP as a trait stemming from decision research.
  • Establish Validity: Test RP's predictive utility across nine work behaviors and demonstrate its incremental validity over the Big Five.
  • Methodological Innovation: Introduce a novel approach integrating Large Language Models (LLMs) to quantify decision attributes.
Process

Literature Search (PRISMA)

Systematic review process from initial search to final inclusion.

Step 1 of 7

Initial Database Search

We conducted a comprehensive search across seven major electronic databases covering psychology, business, and social sciences to identify all relevant studies on risk-taking in workplace settings.

Records identified: n = 7,368

Supplementary Search

To ensure comprehensive coverage, we supplemented our database search with forward citation searches, reference list scanning, and direct contact with researchers to identify unpublished work.

Additional records: n = 3,037

Duplicate Removal

After consolidating records from all sources, we systematically removed duplicates to create a unique set of articles for screening.

Unique records for screening: n = 7,091

Inclusion Criteria

Studies were included if they met the following requirements:

  • Employee samples (not student or general population)
  • Measured both workplace outcomes and individual risk-taking
  • Empirical studies with sufficient data to compute effect sizes
  • Excluded laboratory experiments to focus on real-world contexts

Abstract Screening

Each abstract was evaluated against our inclusion criteria. The vast majority were excluded at this stage, primarily because they lacked measures of workplace outcomes or risk-taking constructs.

Abstracts screened: n = 7,091

Abstracts excluded: n = 6,446 (91%)

Full-Text Evaluation

We obtained and carefully reviewed full-text articles, excluding those that failed to meet our criteria upon closer inspection.

Full texts evaluated: n = 627

Full texts excluded: n = 547

Full texts unobtainable: n = 18

Final Sample

Our final meta-analysis includes studies that met all inclusion criteria and provided sufficient data for quantitative synthesis.

Articles included: n = 80

Independent samples: 87

Effect sizes analyzed: 207

Total participants: N = 55,846

Results

Key Findings

Correlations with Risk Propensity

Corrected ρ with 95% CI. Bars show effect magnitude.

Outcome-Specific Findings

Meta-Regression: Subgroup Analyses

Select an outcome to view subgroup analyses across methodological and substantive moderators.

Incremental Validity Over the Big Five

Stacked bars: Big Five R² (gray) + incremental RP ΔR² (color). RP adds substantial variance beyond the Big Five, especially for CWB and Creative Performance.

Highlights

  • CWB: RP adds ΔR² = .19 (76% increase), ~50% of total explained variance.
  • Creative Performance: RP adds ΔR² = .08 (35% increase), rivaling Openness.
  • Task Performance & Safety: Meaningful incremental variance (ΔR² = .02–.02).
  • RP demonstrates distinct predictive utility beyond the Big Five.

Interpretation

Colored segments = additional variance from Risk Propensity after controlling for Big Five. Green ΔR² > .05; Blue .01–.05; Gray smaller but significant.

Nomological Network: RP and Related Traits

Meta-analytic ρ between risk propensity and personality/work-related traits (95% CI).

Summary

Strong positive: Proactivity (ρ = .36), Creativity (ρ = .35), Locus of Control (ρ = .28).

Moderate/weak: Dark Traits (ρ = .13), Self-Esteem (ρ = .11), Trust (ρ = .13); Self-Control (ρ = −.27).

Practice

Practical Implications

Safety Management

Impact: In a facility with 1,000 employees, selecting for lower risk propensity could prevent ~11 safety incidents/year, saving ~$440,000.

Action: Use valid assessments for safety-critical roles. Implement strict non-negotiable consequences for violations.

Innovation Management

Impact: Risk propensity drives creativity. Risk-averse teams may struggle to innovate.

Action: Place risk-prone talent in R&D. Create "safe-to-fail" environments where experimentation is encouraged.

Assessment Guide

1. Use Validated Measures: Ad-hoc scales perform poorly. Use the DOSPERT or GRiPS.

2. Demographic Fairness: Men and younger adults tend to score higher. Monitor for adverse impact.

For Team Leaders

Risk propensity is a "double-edged sword." It enables innovation but invites risk.

Strategy: Balance your teams. A team of only risk-takers may be chaotic; a team of only risk-avoiders may be stagnant.

Explore the Full Research

Access the complete meta-analysis, interactive visualizations, downloadable datasets, and supplementary materials.

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