Signal bundling and follow-on investment performance: how age, R&D and export activity shape investment speed and amount in publicly supported deep-tech startups

Purpose This study examines how deep-tech startups transition from public support to private capital. Drawing on signaling theory and the resource-based view, we investigate how firm age, R&D intensity and export activity – individually and as a signal bundle – shape the timing and magnitude of follow-on investment after participation in Korea's Tech Incubator Program for Startups (TIPS). Design/methodology/approach We integrate government TIPS records with CB Insights data, yielding 319 deep-tech startups and 2,834 firm-year observations. Weibull hazards models analyze investment timing; Heckman two-step models examine amounts while correcting for selection bias. The three focal signals are modeled as independent and interacting predictors. Findings Firm age exhibits a U-shaped relationship with both investment speed and amount. R&D intensity enlarges follow-on funding and accelerates timing when complementary signals are present, functioning as a cornerstone signal within the bundle. Export activity operates as an attention signal accelerating investor engagement. A significant three-way interaction shows that the bundled configuration of age, R&D and export yields faster and larger investments, with signal complementarity strengthening as firms mature. Practical implications Young startups should bundle R&D with early export engagement; mid-aged firms should refresh their signal portfolio to avoid signal ambiguity. Policymakers can enhance program effectiveness by coupling grants with export facilitation and investor-readiness services. Originality/value This study advances a contingent signal bundling framework, empirically testing a three-way signal configuration in government-supported deep-tech ventures – extending beyond the two-way designs examined in prior research. By jointly modeling timing and amount, we reveal that signal bundles operate through complementary mechanisms. The U-shaped age pattern challenges linear assumptions about the liability of newness.