The effects of quality and price on adoption dynamics of competing technologies

We study the dynamics and patterns of adoption of two competing technologies as well as the effectiveness and optimality of viral pricing strategies by a technology seller. Our model considers two incompatible technologies of differing quality and a market in which user valuations are heterogeneous and subject to network effects. Taking the perspective of a seller of the higher quality technology with imperfect information about user preferences, we investigate the problem of predicting market equilibrium outcomes. We provide partial characterization results about the structure and robustness of equilibria and give conditions under which the higher quality technology purveyor can make significant in-roads into the competitor's market share. We then show that myopic best-response dynamics in our setting are monotonic and convergent, and propose two pricing mechanisms that use this insight to help the entrant technology seller tip the market in its favor. Comparable implementations of both mechanisms reveals that the non-discriminatory strategy, based on a calculated public price subsidy, is less costly and just as effective as a discriminatory policy. Additionally, we study discriminatory and non-discriminatory price mechanisms in the context of profit maximization and show that problem is NP-Hard under uncertainty for both regimes. Finally, we use simulations to analyze a game in which the pricing decisions of both competing sellers are endogenous and now show, in contrast to our analytical results with exogenous prices, that a higher quality technology consistently holds a competitive advantage over the lower quality competitor, irrespective of its market share.