Market Returns to Digital Innovations: A Group Based Trajectory Approach

In this paper, we examine how stock market valuation and market expectations of future growth versus current period performance determine incumbent investments in technological innovation. To this end, we examine how incumbent firms respond to the pervasive shift towards digitally biased innovations. Given that expectation of performance might also condition adoption, we use group- based trajectory (GBT) models to empirically identify heterogeneous incumbent types that are unobserved and difficult to theoretically predict ex ante and descriptively derive the underlying strategic position that conditions their response to technological change. Finally, we use the GBT models in conjunction with propensity score matching to identify returns to technological innovation, contingent on the prior performance of the firms. Our analyses, therefore, address the endogenous relationship between technological innovation and performance that makes it hard to discern the impact of technology adoption. Using data at the intersection of COMPUSTAT, CRSP and the Google patent assignment database spanning the years 1981-2010, we find that firms with greater market expectations of future growth versus current period profitability are more likely to adopt digital innovation and obtain higher ex post market valuations. We discuss the scholarly and managerial implications of these results.