Theses and Dissertations from UMD >
UMD Theses and Dissertations >
Please use this identifier to cite or link to this item:
|Title: ||ESSAYS ON MARKETING MODEL APPLICATIONS FOR ONLINE AND OFFLINE COMMUNITIES|
|Authors: ||Gao, Jing|
|Advisors: ||Kannan, P.K.|
|Department/Program: ||Business and Management: Marketing|
|Sponsors: ||Digital Repository at the University of Maryland|
University of Maryland (College Park, Md.)
content analysis, online word-of-mouth, promotion strategy, social influence
|Issue Date: ||2011|
|Abstract: ||Social interactions in a community influence perceptions and values of members of the community. Recently Web 2.0 technologies have stimulated rapid growth of online communities, where communications between participants are made much easier. It is important to study how participants' behaviors and preferences are affected by their communities. In my dissertation, I develop quantitative marketing models to empirically study perceptions and attitudes of participants in online and offline communities.
Essay 1 examines an offline community, distributor community in multi-level marketing organizations. We propose a spatial model to understand the determinants of distributor satisfaction and simultaneously account for biases in measures in the context of cross-country marketing operations. We define an attribute-space using measures such as sales momentum and effort expended on business by distributors. The relationship between distributor satisfaction and its drivers varies within this attribute-space and across markets. Based on survey data from a large multi-national multilevel marketing firm, we empirically illustrate how marketing control variables
impact distributor satisfaction scores across countries after controlling for biases. We also discuss the resource allocation implications based on the study.
Essay 2 studies an online community, online bargain hunting forum. We investigate whether and how online discussions posted by active participants affect the interest and preference of the silent majority. We collect data from a major bargain hunting forum. Our analysis of the online discussions goes beyond measures of volume and valence, and delves into the specific contents of discussions posted in the forum. We classify the contents into a range of specific categories, and develop a Bayesian Poisson-Binomial model to examine how silent viewers' interest in and preference for a featured deal are influenced by the discussions, while controlling for many other factors. Our results show that the content of discussions posted by active participants indeed affects the silent viewers' interest in and preference for a featured deal, and that the effects are different across the specific categories of content. Our findings demonstrate that marketers can benefit from monitoring activities in online bargaining hunting forums, and suggest ways for them to participating in these forums.|
|Appears in Collections:||Marketing Theses and Dissertations|
UMD Theses and Dissertations
All items in DRUM are protected by copyright, with all rights reserved.