1. Readings Seminar September 21, 2009

2. Sutton, R. I. & Staw, B. M. (1995).What theory is not. Administrative Science Quarterly, 40, 371-384. strong versus weak theory.

3. 1.References Are Not Theory Mark Twain defined a classic as "A book which people praise but don't read." 2.Data Are Not Theory Data describe which empirical patterns Were observed and theory explains why empirical patterns were observed or are expected to be observed.

4. 3.Lists of Variables or Constructs Are Not Theory 4.Diagrams Are Not Theory Diagrams and figures should be considered as stage props rather than the performance itself 5.Hypotheses (or Predictions) Are Not Theory

5. Hypotheses can be an important part of a well- crafted conceptual argument. They serve as crucial bridges between theory and data, making explicit how the variables and relationships that follow from a logical argument will be operationalized Hypotheses do not (and should not) contain logical arguments about why empirical relationships are expected to occur. Hypotheses are concise statements about what is expected to occur, not why it is expected to occur.

6. What is strong theory? Strong theory delves into underlying processes so as to understand the systematic reasons for a particular occurrence or nonoccurrence It may have implications that run counter to our common sense

7. Mitchell & James Mitchell, T. R. & James, L. R. (2001). Building better theory: Time and the specification of when things happen. Academy of Management Review, 26, 530-548. Does X cause Y?

8. Mitchell & James When examining whether an X causes a Y, we need to know when X occurs and when Y occurs. Do we have the timing right? X should precede Y to cause it – correct?

9. Mitchell & James First, we need to know the time lag between X and Y. How long after X occurs does Y occur? Second, X and Y have durations. Not all variables occur instantaneously. Third, X and Y may change over time. We need to know the rate of change. Fourth, in some cases we have dynamic relationships in which X and Y both change. The rate of change for both variables should be known, as well as how the X,Y relationship changes. Fifth, in some cases we have reciprocal causation: X causes Y and Y causes X

10. Mitchell & James

11. Configuration 1: X causes Y. Configuration 2: X causes Y, and the relationship is stable over time. Configuration 3: X causes Y, and Y changes over time. X precedes Y, and the time lag is important between X and all three occasions when Y occurs.

12. Mitchell & James Configuration 4: X causes Y, but over repeated exposure to X, Y changes. Configuration 5: X causes Y, and then a changed X causes a changed Y. Configuration 6: X causes Y, which causes a changed X, which causes a changed Y.

13. Mitchell & James Configuration 7: X causes Y, which causes a different variable Z, which may, in turn, cause a different variable Q. Configuration 8: X causes Z, but the strength of the relationship varies as a function of the level of Y.

14. Mitchell & James Findings Time and context crucial to theory development

15. Research Reviews Format –Topic –Citation –Theory –Hypothesis –Data –Results –Conclusions of researchers –Implications for management science