This is the authors' abstract. We don't add key points for this paper.
Everything about theory is contested in our field today.First, there's the role of theory in IS research.Is it necessary for research publications to make a theoretical contribution?What is a theoretical contribution?Should we devote more effort to building theory or to testing theory?Can you test theory with qualitative data?Is theory even relevant if one is doing research with analytic or machine learning methods?Second, there's the issue of how to build theory.Can you build theory with quantitative data?Do you need empirical data to build theory?How important is the literature review (and what type of review) in theory building papers (Leidner 2018)?What is the role of "disciplined imagination" (Weick 1989) in IS theorizing?Is "armchair theorizing" permissible, and, if so, when?Third, there's the issue of what theory looks like.Is a good theory a boxes-and-arrows diagram followed by themore-X-the-more-Y type propositions?Or are there other persuasive ways to present theories?One possibility might be events, conditions and mechanisms.Another might be narratives of how things happen.And, perhaps most important of all, how do we as a field cope with multiple, overlapping, possibly inconsistent, theories of the same phenomenon?
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Hassan et al. (2023) studied this question.
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