Investigating Consumer Adoption of Related Technology Products

Abstract

We present a framework for modeling consumer adoption of multiple categories of technology products that may be related as complements (or substitutes). The context of technology products as well as the relationship between categories poses some unique challenges. First, the declining prices (and the corresponding increase in quality levels) over time imply that consumers anticipate these changes and make a trade-off between adopting the product early on and consuming the product for a longer time versus adopting later at lower prices. Second, the durable nature of technology products implies that even if two categories are related as complements, consumers may stagger their purchases over several periods; unlike in the case of packaged goods, one cannot infer complementary relationships between these categories based on joint purchases. Third, the adoption decision for some categories (such as printers) may be contingent upon adoption of another related category (such as a personal computer). We illustrate how our proposed modeling framework is flexible enough to address these issues in the context of two related categories and discuss how it can be extended to multiple categories. We apply our modeling framework to a unique dataset that contains information on consumer adoption of three related categories of technology products - personal computers, digital cameras, and printers. The results reveal a strong complementary relationship between these categories. As a result, the probability that a consumer would adopt a given category increases significantly if she has already adopted one or more of the related categories. Policy simulations based on a temporary price decrease in any one category provide interesting insights into how consumers would modify their adoption behavior over time as well as across categories as a consequence of the price decrease.

Keywords: Technology products, product adoption, multiple categories, complementarity, forward-looking consumers

JEL Classification: C13, D91, M30, O39