Seminar: Allen Lee, "Generalizing Generalizability in Information Systems Research" (4/9/2009)

Generalizability is a major concern to those who do, and use, research. Statistical, sampling-based generalizability is well known, but methodologists have long been aware of conceptions of generalizability beyond the statistical. The purpose of this essay is to clarify the concept of generalizability by critically examining its nature, illustrating its use and misuse, and presenting a framework for classifying its different forms. The framework organizes the different forms into four types, which are defined by the distinction between empirical and theoretical kinds of statements. On the one hand, the framework affirms the bounds within which statistical, sampling-based generalizability is legitimate. On the other hand, the framework indicates ways in which researchers in information systems and other fields may properly lay claim to generalizability, and thereby broader relevance, even when their inquiry falls outside the bounds of sampling-based research.

Wikipedia Biography of Allen Lee (accessed 4/7/2008):

Allen S. Lee is an eminent scholar of Information Systems research best known for his work on integrating positivist and interpretative research methods. Additionally, Allen S. Lee served prominently on the MIS Quarterly editorial board for 15 years, holding the positions of associate editor, senior editor, and editor-in-chief. As an advocate for integrated research approaches, Allen S. Lee has championed equality for interpretative, qualitative and case-study methods in Information Systems research. Recently, Allen S. Lee has also championed design science research as a means of addressing and possibly resolving the rigor vs. relevance connundrum in Information Systems research. As of 2008, Allen S. Lee continues a research agenda which relates and combines qualitative, positivist and interpretive research methods.