The innovation ecosystem in America increasingly consists of a division of innovative labor between startups (which develop new inventions, often based on university discoveries) and incumbents, which acquire the inventions and commercialize them (Arora, Belenzon, Patacconi, and Suh, 2020). This system seems to work well for IT innovations, such as software and social media applications, and innovations in life sciences. However, many observers (Lerner and Nanda, Nanda, BCG report) have pointed out that the startup-based system works less well in other sectors, such as new materials, automation, and eco-innovations, which are often called “deep tech”. If indeed the current startup-based system is biased against deeptech, understanding the reasons is important, not only to design appropriate policy responses, but also to help entrepreneurs and investors.
Several explanations have been offered. For instance, it is suggested that the startup based system is biased against innovations that require large investments, have long time-horizons, or are too risky. Other explanations tend to be sector-specific e.g., eco innovations require regulatory or policy changes to make them commercially viable, or require large complementary investments in infrastructure (e.g., charging stations for electric vehicles, or changes to road infrastructure for autonomous vehicles). Others have suggested that the structure of venture financing may be at fault: VC financing is concentrated in two main sectors, namely IT, particular software and consumer technologies, and Life Sciences.
In this paper we offer a complementary explanation. To succeed in the marketplace, inventors must overcome a variety of technical challenges, as well as commercial challenges.Broadly speaking, technical challenges are more important than commercialization challenges in innovations in life sciences, as compared to IT innovations, where commercialization challenges are relatively more important. Deeptech innovations tend to be more balanced in terms of the relative importance of technical and commercial challenges.
We develop an analytical model where startups are more efficient at solving technical challenges and incumbents are more efficient at solving commercial challenges. A market for technology (or equivalently, a market for startups) can accomplish the efficient commercialization of innovations. Innovations differ in the relative importance of technical and commercial challenges, but are otherwise identical — all have the same total cost, as well as the same gross value. However, the value the startup can appropriate depends on the outcome of the bargaining process when the startup negotiates with the incumbent to commercialize the innovation (cf. Scotchmer and Green).
The key insight from our model is that the market for startups does not work well when both commercial and technical challenges are important, because the startup has the weakest bargaining position. Put differently, the startup-based system works better for “specialized” innovations, where only one type of challenge is significant. The implication is that all else equal, deeptech startups are disadvantaged because they are less able to capture the value they create.
In extensions, we discuss the implications of bargaining power, complementary commercialization infrastructure, and various public policies, including public subsidies for venture capital
This is a joint seminar with the Entrepreneurial Management Seminar.
Email us at firstname.lastname@example.org for information on attending this seminar.