Is Grounded Theory an Option with Big Data?

This week’s readings really harp on the importance of theory and the scientific method. While I agree with the authors for the most part, I’m wondering if theory is always necessary. Perhaps there are some phenomena that are new and/or don’t fit nicely into an established theory. In these cases, a grounded theory approach may be useful. According to the Grounded Theory Institute (,

“Grounded Theory is an inductive methodology.  Although many call Grounded Theory a qualitative method, it is not.  It is a general method. It is the systematic generation of theory from systematic research.  It is a set of rigorous research procedures leading to the emergence of conceptual categories.  These concepts/categories are related to each other as a theoretical explanation of the action(s) that continually resolves the main concern of the participants in a substantive area.  Grounded Theory can be used with either qualitative or quantitative data.”

Grounded Theory is a research methodology which directs the researcher on issues concerning data collection and describes procedures for data analysis. With Grounded Theory, the researcher doesn’t have any a-priori hypotheses about the phenomenon. Rather, the researcher develops a theory from the ground up via extensive data analysis.

I think Grounded theory is useful for new phenomena or in situations in which using an existing theory would be like putting a square peg into a round hole. I remember reading an article that used Grounded Theory during the dissertation phase of my Ph.D.  This article investigated the political and rational roles of a systems development methodology. I found the article relevant and interesting and actually cited it in my own work.

Overall, while I strongly believe in using theory, I also think the importance of theory needs to be balanced. There are some phenomena that are new or don’t neatly fit into established theory; for these phenomena, a Grounded Theory approach may be useful.

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