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Essays on the Influence of Social Networks on the Marketing Distribution Channel and New Product Diffusion Open Access


Other title
Social Networks
Marketing Distribution
New Product Diffusion
Type of item
Degree grantor
University of Alberta
Author or creator
Li, Shenyu
Supervisor and department
Peter T.L. Popkowski Leszczyc (Department of Marketing, Business Economics and Law)
Siva K. Balasubramanian (Stuart School of Business, Illinois Institute of Technology)
Examining committee member and department
Haifang Huang (Department of Economics)
Christophe Van Den Bulte (The Wharton School of Business, University of Pennsylvania)
Paul R. Messinger (Department of Marketing, Business Economics and Law)
Adam Finn (Department of Marketing, Business Economics and Law)
School of Business

Date accepted
Graduation date
Doctor of Philosophy
Degree level
The first essay studies the channel relationship between the reseller and the manufacturer based on a social network theory framework. We propose a conceptual model that approaches this topic from a relational embeddedness perspective. Our analysis shows how the reseller can strategically develop relational ties with a manufacturer that transform the latter’s common marketing mix into unique resources that enhance the reseller’s own profit. Results from a large scale survey of beer resellers in a local Chinese market suggest that in a channel setting, social norms (e.g. communication effectiveness and conflict resolution) and social relations influence the reseller’s access to the manufacturer’s valuable resources. Furthermore, we find that over embeddedness affects the reseller’s profit in a non-linear manner. That is, a reseller’s effort to develop a relationship with a particular manufacturer may generate information that lacks freshness, objectivity or usefulness, thereby diminishing the reseller’s profitability. Theory of social contagion states that individual’s adoption of new product depends on the adoption of his immediate neighbors in a social network in addition to the influence from other sources. This research models the dynamic diffusion process of new drug in a social network of physicians. We simulated the information transmission process in a social network, where each network entity repetitively influences the probability of connected entity’s new product adoption. The simulation approach integrates two seemingly contradictive concepts of cohesion and structural equivalence into a single modeling framework. Besides, it incorporates a coefficient that describes an individual entity’s efficiency of information transmission. On the one extreme it assumes that information transmits to only one of the network neighbors and on the other extreme it assumes that information transmits to all of the network neighbors. We revisited Medical Innovation data and empirically find an optimum point for each of the four cities in this data set, using a discrete time hazard model. The four cities demonstrate different patterns of information transmission. Managerially, we suggest different ways of pinpointing initial adopters in different types of social networks.
License granted by Shenyu Li ( on 2010-03-04 (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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