Strategies for theorizing from process data

Abstract

In this article I describe and compare a number of alternative generic strategies for the analysis of process data, looking at the consequences of these strategies for emerging theories. I evaluate the strengths and weaknesses of the strategies in terms of their capacity to generate theory that is accurate, parsimonious, general, and useful and suggest that method and theory are inextricably intertwined, that multiple strategies are often advisable, and that no analysis strategy will produce theory without an uncodifiable creative leap, however small. Finally, I argue that there is room in the organizational research literature for more openness within the academic community toward a variety of forms of coupling between theory and data.