스타트업 인수 가능성에 영향을 미치는 신호 요인 분석: 자원기반관점과 신호이론의 통합적 접근

This study empirically examines the key signaling factors that predict startup acquisition likelihood in the highly information-asymmetric market environment. As the global startup exit landscape has rapidly shifted from funding-driven growth toward acquisition-centered outcomes, the interpretation of publicly observable signals has become a critical determinant in investors’ and acquirers’ decision-making. However, prior studies have primarily applied signaling theory to the contexts of fundraising or IPOs, leaving the signaling effects at the M&A stage empirically underexplored. To address this research gap, this study proposes an integrated analytical framework combining Signaling Theory, the Resource-Based View, and the Liability of Newness, to investigate how startups’ minimal observable signals influence their likelihood of acquisition. Using the publicly available Kaggle dataset (n=923), the dependent variable was defined as the startup’s status (acquired=1, closed=0). The explanatory variables included total funding amount (log_funding_total_usd), time to first external funding (age_first_funding_year), and Series A round entry (has_roundA). The analysis employed binary logistic regression complemented by Average Marginal Effects (AME) and Partial Dependence Plot (PDP) visualization to capture both the direction and nonlinearity of the signaling effects. The results reveal that higher cumulative funding significantly increases acquisition likelihood, indicating that financial capacity functions as a credible quality signal. Conversely, a longer time to first investment reduces acquisition likelihood, implying that early funding acts as a positive signal of market legitimacy and learning efficiency. The effect of Series A entry was positive but marginally significant at the 10% level. The PDP analysis further identified a concave (saturating) pattern for total funding and a monotonic decline for delayed funding, empirically supporting the diminishing marginal utility of financial slack and the legitimacy-signaling mechanism of early investment. These findings demonstrate that early, rapid, and sufficient funding serves not merely as a financial outcome but as a central signal of market credibility and organizational capability. Theoretically, this study extends the application of signaling theory from the fundraising to the acquisition stage, thereby deepening the theoretical understanding of startup exits through the integration of RBV and new venture perspectives. Practically, it offers an interpretable quantitative framework for predicting acquisition likelihood using minimal public signals, providing valuable insights for acquirers and investors to enhance decision-making efficiency in information-asymmetric markets.