Summary & Review of Article - "What Theory is Not" by R. I. Sutton & B. M. Shaw

The content of this blog post is based primarily on the following article:

Sutton, R. I., & Staw, B. M. (1995). What theory is not. Administrative Science Quarterly, Vol. 40, No. 3, pp. 371-384.

In the article "What theory is not" by Sutton and Staw (1995), it is noted that many researchers mistake references, data, variables/constructs, diagrams, and hypotheses for theory. The authors also urged journals and editors to be more receptive to papers that investigate a part of rather than an entire theory, and utilise illustrative (qualitative) rather than definitive (quantitative) data. 

Sutton and Staw (1995) explained that:

• References are not theory, because researchers need to explain which concepts and arguments are adopted from sources and how they are linked to the theory.  
• Data are not theory, because data merely describes which empirical patterns were observed and theory explains why empirical patterns were observed. It does not constitute a theory. Researchers who use qualitative data must develop causal arguments (theory) to explain why findings are observed. 
• Variables/constructs are not theory. The key issue is why certain variables are more important and thus chosen, not what variables/construct are in the theoretical model. 
•  Diagrams are not theory, because they don't explain why. However, the authors acknowledged that a good theory is often representational and verbal.
•  Hypothesis (or predictions) are not theory, because hypotheses are statements about what is expected to occur, not why it is expected to occur.

A strong theory answers why and delves into the underlying processes. According to the authors, strong theories are missing in many quantitative research papers, as they seem to be overly concerned with methodology. There is a need to rebalance the selection process between theory and method. However, the authors also noted that theory is often over-emphasized in qualitative research. In light of these findings, the authors argued that the best papers are those that strike a fine balance between theory and method.