This study examines whether AHP-derived risk-prioritization frames observed within a publicly supported entrepreneurship programme are associated with objective early-stage venture outcomes, distinguishing intermediate diagnostic outcomes from ultimate venture-performance outcomes.
Survey data from 114 respondent-level observations collected from 50 early-stage firms and pre-start-up teams in South Korea are analyzed using AHP-derived pairwise priority weighting, k-means clustering, ordered logit regression and count models. The empirical survey was conducted from 11 November to 10 December 2024. The analysis is exploratory and cross-sectional; it does not estimate causal programme impact.
Three founder profiles are identified: distribution-oriented, expert-network-oriented and manufacturing-oriented. These profiles are not significantly associated with revenue category or employment size. Sectoral context is more strongly associated with objective performance.
The study is based on a programme-related sample, same-wave measurement and no counterfactual group. Findings should therefore be interpreted as associational evidence. Future research should use longitudinal and counterfactual designs.
Risk-prioritization tools can be used as diagnostic intake instruments, but should be followed by sector-sensitive support and longer-term outcome tracking.
This study contributes to entrepreneurship and public policy research by distinguishing cognitive diagnostic outputs from objective venture-performance outcomes. It links AHP-derived founder risk-prioritization frames to revenue and employment indicators and shows that coherent risk-ordering structures do not necessarily translate into measurable venture scaling. The study therefore clarifies why public entrepreneurship support should not treat mentoring, risk awareness or diagnostic profiling as substitutes for performance evidence.
