Economic and empirical analysis of consumer purchase intentions in electronic and traditional retail channels, Internet retailer pricing strategies, and price dispersion on the Internet

Date of Completion

January 2002


Business Administration, Management|Economics, Commerce-Business|Information Science




This dissertation, consisting of four independent but complementary research papers, examines buying behavior of consumers in retail channels, efficiency characteristics of the Internet market, and pricing strategies of Internet retailers. This investigation involves both theoretical and empirical work. ^ Theoretically, we develop a multi-attribute economic model to analyze consumer behavior for traditional and electronic channels based on consumers' risk profiles—low risk tolerance vs. high risk tolerance. Current literature focuses on only one dimension of measurement as opposed to multi-attribute models. We then conduct comparative analyses of consumer purchase decisions to derive strategies for different channels. Theoretical propositions are developed concerning consumer channel switching behavior, incentives to consumers, and pricing strategies for different channels. We use simulations to gain insights for cases where analytical model becomes intractable. ^ Empirically, we analyze efficiency characteristics of the Internet for two product sets: (1) 14 product categories encompassing 3 product classes (commodity, quasi-commodity, and differentiated products) and (2) 3 top-selling products on the Internet (books, CDs, and flight tickets). Focusing on consumer information search and evaluation behavior, we propose the pricing model and log-linear price dispersion model to identify factors that influence Internet retailers' pricing strategies and price dispersion on the Internet. One of our findings shows that the CD market is the most price-competitive among the 3 top-selling product markets, whereas the quasi-commodity market experiences relatively stronger price competition than the other two product classes. A second finding shows that retailers' heterogeneity in inducing consumer search and evaluation efforts is highly related to price dispersion in e-markets. ^ Additionally, we develop surveys to empirically investigate the relationship between operating characteristics of consumer purchasing decision process and consumer purchase intentions. Online and offline models in this relationship are compared and tested. Findings provide evidence that, the overall channel switching percentage from offline to online is approximately 47%. The analysis show that overall, differences in channel risk perceptions, price search intentions, evaluation effort, and waiting time between online and offline channels appear to have significant impact on respondents' switching from offline to online shopping environment. Other interesting findings and managerial implications are discussed. ^