Gauttier, Stéphanie (2017, August 10-12). Increasing transparency in interpretive research: Q-method to objectivize the researcher’s subjectivity. In Diane Strong & Janis Gogan (Chairs), 23rd Americas Conference on Information Systems (AMCIS 2017): A Tradition of Innovation (Proceedings, Boston, Vol. 4, pp. 2849-2858). Atlanta: Association for Information Systems. (Access: https://aisel.aisnet.org/amcis2017/Openness/Presentations/3/ )
Abstract: While research needs to be transparent, traceable and reproducible – data generation and interpretation often appear as a black box in qualitative research. Literature recommends reflective activities so the researcher is aware of his/her own subjectivity and thus decrease interpretation bias but their effect is limited. We suggest that Q-method offers a more transparent and direct way to capture the researcher’s subjectivity. The Researcher set up a longitudinal study, interviewing 3 participants over 10 weeks about Augmented Reality. Then the Researcher created a Q-study on the basis of the interview transcripts. All 3 participants proceeded to the study, as well as the Researcher who expressed what she thought was the opinion of each participants. All Q-sorts were analysed together, allowing to capture shared representations. The results are interpreted regarding the ability of Q to capture the Researcher’s subjectivity in a transparent way and increase the quality of interview data interpretation.
Stéphanie Gauttier <email@example.com> is in the Department of Management & Technology, Université de Nantes, Nantes; and the Grenoble Ecole de Management, Grenoble, France.