A Rational Expectations Theory of Technology Adoption: Evidence from the Electronic Billing Industry

In this paper, we draw on concepts from the rational expectations hypothesis (REH) and adaptive learning theory to introduce a new rational expectations theory of technology adoption. Although the REH and adaptive learning theory have been applied in many non-technology contexts, this research is among the first that applies rational expectations and adaptive learning theory to issues related to technology adoption. The proposed theory allows us to examine technology adoption settings where multiple parties seek to align their expectations of future value prior to making a decision to adopt. It also takes into account the learning and information sharing that generally occurs in the marketplace between multiple parties that can further influence clustered adoption and the overall adoption rate. In our effort to test our new theory, we construct several hypotheses that allow us to examine issues associated with information technology adoption that involves multiple parties (multi-partite technology adoption) and strong network externalities. We test for the existence of clustered adoption and the effects of information transmission in the electronic bill presentment and payment (EBPP) industry. We hypothesize that clustered adoption by firms will be influenced by their geographical collocation, the reach of their consumer bases, their industry sector associations, and their consensus choices of the technology vendor. Our results show preliminary evidence to support the proposed theory.