Economic models of information technology in retail banking

This study is structured as a set of three essays which focus on the economics of information technology in the retail banking industry. Employing a game-theoretic analysis, the first paper explains the economic reasoning behind the trend in retail banks in the U.S. to develop most of their application software in-house. It also establishes thresholds for the time to develop, and quality of product taking into account technical competencies, investment decisions, and market shares. The second paper studies pricing decisions for online banking given the existence of network externalities. Most literature has examined the effect of network externalities on pricing decisions for durable goods. In the case of online banking, however, the customer\u27s decision does not end with adoption of a mode of online banking since the customer is free in later periods to change an adopted mode. We develop an economic model that incorporates the customer\u27s ability to switch in a later period. Three significant findings of this paper are as follows: (i) In the presence of positive network externalities, the bank can commit itself to increasing future fees for online banking services, (ii) The bank can afford to offer discounts, incentives, and one-time monetary payouts to ensure initial signup for online banking service, and (iii) Service quality can become a proxy for switching costs and, thus, be used to regulate the stickiness of the market. The final paper employs a stochastic dynamic programming model to examine the effects of word-of-mouth and expert opinions on dynamic pricing strategies for online banking. Departing from previous literature, we model network effects as stochastic, in particular following a jump-diffusion process. The word-of-mouth contributes to the Wiener portion of the mixed-diffusion process, while expert opinion reviews contribute to the Poisson component. We derive the optimal dynamic pricing policy under this situation, and analyze the impact of uncertainty on both expected profits and pricing policy