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.

The conventional wisdom amongst information systems (IS) researchers is that information systems is an applied discipline drawing upon other, more fundamental, reference disciplines. These reference disciplines are seen as having foundational value for IS. We believe that it is time to question the conventional wisdom. We agree that many disciplines are relevant for IS researchers, but we suggest a re-think of the idea of “reference disciplines” for IS. In a sense, IS has come of age. Perhaps the time has come for IS to become a reference discipline for others.