Designing interviews to generate rich data for information systems research

Information Systems (IS) publications that use interviews for data generation tend to provide very little insight into the research process and very few rely on a carefully chosen and well-articulated interviewing method. Given the wide variety of interviewing approaches available to qualitative researchers, it seems that the IS discipline is lagging behind and can easily enhance its methodological sophistication. In this paper, we address this opportunity by (i) highlighting the potential of interviewing as a means of generating data that provides insight into people's experiential life; (ii) discussing the various epistemological stances that can be taken to interviewing; (iii) introducing and illustrating three interviewing methods (i.e., appreciative, laddering and photo-diary interviewing); and (iv) juxtaposing these methods to identify the conditions under which they are most effective.