Social Networks

Prof. Christophe Van den Bulte, Ph.D.

Associate Professor of Marketing at Wharton, University of Pennsylvania.

Ph.D. Seminar

scheduled end of August 2011
Location: tba

Course Description:
The objective of this PhD mini-course is to provide a selective primer on social network theory and methods relevant to research in business, especially marketing and management. Social network research is somewhat unique in that it asks questions not only about characteristics of people or organizations, or even about characteristics of relations among people or organizations, but about the pattern or structure of these relations. That requires both different theories and different research methods. So, the course covers both theory/concepts and methods/techniques.

For the theoretical concepts and mechanisms, we will draw mostly on literature in sociology and organization research since this is where much of the theory and best research has originated. For the methods, we will focus on basic quantitative tools and use the Ucinet software package for simple data analysis problems. The course will focus on deterministic tools. It will briefly touch upon more advanced statistical tools applied in recent research, but merely to raise awareness of them. Knowledge of linear regression is the only statistical prerequisite.

From a substantive point of view, we will focus on framing and analyzing issues of interest to business researchers from the perspective of “how does network structure influence …”:

• The flow of information (relevant for word-of-mouth about new products and for R&D-marketing interaction in new product development);
• Power (relevant for the ability to charge higher prices, obtain scarce resources, and mobilize colleagues and other departments, etc.);
• Trust (relevant for cooperation among and within organizations);
• Prestige and status, which in turn affect power, trust, and competitive structure.

From a theory and research technique point of view, we will focus on:

• Collecting and handling network data
• Density and closure
• Small worlds, information brokerage, and weak ties
• Centrality
• Closure, brokerage and tie strength: Further arguments and contingencies
• Identifying groups: Relational and positional approaches
• Social contagion and diffusion
• Network visualization and statistical analysis

Required Readings:
To be communicated.

Syllabus