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 latters common marketing mix into unique resources that enhance the resellers 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 resellers access to the manufacturers valuable resources. Furthermore, we find that over embeddedness affects the resellers profit in a non-linear manner. That is, a resellers effort to develop a relationship with a particular manufacturer may generate information that lacks freshness, objectivity or usefulness, thereby diminishing the resellers profitability.
Theory of social contagion states that individuals 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 entitys 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 entitys 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. / Marketing
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/1027 |
| Date | 06 1900 |
| Creators | Li, Shenyu |
| Contributors | Peter T.L. Popkowski Leszczyc (Department of Marketing, Business Economics and Law), Siva K. Balasubramanian (Stuart School of Business, Illinois Institute of Technology), Paul R. Messinger (Department of Marketing, Business Economics and Law), Adam Finn (Department of Marketing, Business Economics and Law), Haifang Huang (Department of Economics), Christophe Van Den Bulte (The Wharton School of Business, University of Pennsylvania) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | 1249707 bytes, application/pdf |
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