Online Retailing in Spatially Dispersed Offline Markets

Loading...
Thumbnail Image
Degree type
Doctor of Philosophy (PhD)
Graduate group
Marketing
Discipline
Subject
E-Commerce
Spatio-Temporal Model
Long Tail
Social Influence
Preference Minorities
Marketing
Funder
Grant number
License
Copyright date
Distributor
Related resources
Contributor
Abstract

This dissertation comprises three essays that study online demand coming from local offline markets. In the first essay, I study two social influence effects reflected in physical proximity and in demographic similarity, respectively, on online demand evolution. As these effects can be time-varying, I specify their dynamics using a polynomial smoother embedded within the Bayesian framework. Using new buyers at Netgrocer.com in Pennsylvania, I find that the proximity effect is especially strong in the early phases of demand evolution, whereas the similarity effect becomes more important with time. In the second essay, I study social influence effects emanating from two types of buyers in the installed base—search buyers, those acquired by online search, and WOM buyers, those acquired by offline word-of-mouth (WOM)—on online demand evolution. Since Internet retailers acquire buyers from multiple locations over time, I allow time-varying parameters to also vary across counties. Using data on new buyers at Childcorp.com, I find that WOM buyers are on average of “better quality”, however, substantial variation in the temporal parameter paths over counties suggests that a third of the markets are better able to breed social influence from search buyers. In the third essay, I examine how online demand in a location is affected by the relative size of the target population holding the absolute size constant. I hypothesize that in regions where this target group is in the minority online category sales will be higher (H1) and will be relatively price-insensitive (H2). I further conjecture that online sales of niche brands, relative to popular brands, will be even more responsive to preference minority status (H3). Finally, I show that niche brands in the tail of the Long Tail sales distribution (Anderson 2006) will draw a greater proportion of their total sales from high preference minority regions (H4). Sales data from Childcorp.com supports all four hypotheses. This dissertation concludes with a short chapter, briefly discussing the key findings and describing areas for future research.

Advisor
David R. Bell
Date of degree
2010-05-17
Date Range for Data Collection (Start Date)
Date Range for Data Collection (End Date)
Digital Object Identifier
Series name and number
Volume number
Issue number
Publisher
Publisher DOI
Journal Issue
Comments
Recommended citation