Reflections on Theme 3: Research and theory

During this week we read the articles “The Nature of Theory in Information Systems” (Gregor, 2006) and “What Theory is Not” (Sutton and Staw, 1995). I found Gregor’s taxonomy of theory types really interesting because it included types which were not traditionally seen as theory. According to Gregor, the five theory types in Information Systems Research are: Analysis, Explanation, Prediction, Explanation and Prediction and Design and Action.  

In the first seminar we discussed the journals and the papers that we found interesting. Each group chose to discuss one of the articles, its results, the theory used, the limitations etc. My group discussed the “Channeling Science Information Seekers' Attention? A Content Analysis of Top-Ranked vs. Lower-Ranked Sites in Google” (Li et al., 2013). I found the discussion on the implications of Google as a dominant search engine on the diversity of online science content to be really interesting.

I was troubled by the fact that most-if not all- of the discussed articles had limitations in their methodologies; that results could not be generalized or that they were not clear conclusions. But what I got from this seminar is that even when a theory is considered to have limitations, it can still contribute to the advancement of knowledge. Researchers can learn from this mistake and avoid it in future theories and methodologies .

At the second seminar we discussed different theories and explained which theory type were used in some articles. My group discussed the Theory of Social Capital, according to which individuals can benefit from their networks. According to the results of the paper “The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites” (Ellison et al., 2007), there is a strong association between Facebook usage and the three dimensions of social capital: bridging of social capital, as well as bonding and maintained social capital. We argued that the major theory used in this paper is analysis because the theory provided an analysis of something that was poorly examined beforehand, a description of this phenomenon. We noted that it might also be an explanation theory because this theory explained how and why individuals can benefit by using Facebook, e.g. Facebook connections could pay off in terms of opportunities, such as jobs, internships etc. After the discussions in the second seminar, I could argue that the theory types used in this paper are analysis-mainly- and prediction, because the theory also provided patterns, but it did not have well developed justificatory causal explanations (Gregor, Ibid: 620). As we discussed during the seminars, it is not always easy to categorize a theory.

We also discussed the definition of theory in the course’s Wiki. Theory is a proposition describing and explaining why and how phenomena occur, connections between them. It can also try to explain the causal logic between cause and effect. The focus of the discussion was the theory’s justification and generalization through scientific repetition. My group did not agree with the opinion that when a theory is accepted by a majority of people, it can be regarded as a true belief. We disagreed with the term true belief and that it can be shaped trough the majority of people. We also noted that what is considered to be a true belief today may not be considered as such in 50 years. After all, theories can evolve, be revised.

To conclude, a theory should be scientifically justifiable. It is also important to be accepted by the gatekeepers. Being published in journals with high Impact Factor means that the theory has been through a quality process. 

REFERENCES

Ellison, N. B., Steinfield, C. and Lampe, C. (2007), The Benefits of Facebook “Friends:” Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication, 12: 1143–1168. doi: 10.1111/j.1083-6101.2007.00367.x

Gregor, S. (2006). The Nature of Theory in Information Systems. MIS Quarterly, 30(3), 611-642.

Li, N., Anderson, A., Brossard, D. and Scheufele, D. (2013). Channeling Science Information Seekers' Attention? A Content Analysis of Top-Ranked vs. Lower-Ranked Sites in Google. Journal of Computer-Mediated Communication. doi: 10.1111/jcc4.12043.

Sutton, R. I. & Staw, B. M. (1995). What Theory is Not. Administrative Science Quarterly, 40(3), 371-384.