Working Paper: NBER ID: w29654
Authors: Ashish Arora; Andrea Fosfuri; Thomas Roende
Abstract: Startups in IT and life sciences appear to be flourishing. However, startups in other sectors, such as new materials, automation, and eco-innovations, which are often called "deep tech", seem to struggle. We argue that innovations with both technical and commercial challenges, typical of deep tech innovations, are especially disadvantaged in a startup-based innovation system. We develop an analytical model where startups are more efficient at solving technical challenges and incumbents are more efficient at solving commercial challenges. We find that the startup-based system works better for "specialized" innovations, where only one type of challenges is significant. Startups which face both technical and commercial challenges are disadvantaged because they capture a smaller fraction of the value they create. We discuss the implications for various public policies that have been proposed to encourage deep-tech.
Keywords: Startup Innovation; Deep Tech; Venture Capital; Technical Challenges; Commercial Challenges
JEL Codes: L26; O31; Q55
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| startups (M13) | technical challenges solved (O30) |
| incumbents (G18) | commercial challenges solved (L14) |
| technical + commercial challenges (O36) | decreased attractiveness to investors (G24) |
| technical + commercial challenges (O36) | lower bargaining power (D43) |
| division of labor (L23) | inefficiency for deep tech (O39) |