Explanation in information systems

Explanation of observed phenomena is a major objective of both those who conduct and those who apply research in information systems (IS). Whereas explanation based on the statistical relationship between independent and dependent variables is a common outcome of explanatory IS research, philosophers of science disagree about whether statistical relationships are the sole basis for the explanation of phenomena. The purpose of this paper is to introduce an expanded concept of explanation into the realm of IS research. We present a framework based on the four principle explanation types defined in modern philosophy: covering-law explanation, statistical-relevance explanation, contrast-class explanation and functional explanation. A well-established research stream, media richness, is used to illustrate how the different explanation types complement each other in increasing comprehension of the phenomenon. This framework underlies our argument that explanatory pluralism can be used to broaden research perspectives and increase scientific comprehension of IS phenomena above and beyond the methodological and ontological pluralism currently in use in IS research.