MIS Quarterly · 2012 · 278 citations · 70 references
HumanitiesInformation SystemsPhilosophyCritical TheoryInformation Systems ManagementPhilosophy Of TechnologyCase Study ResearchPositivismCritical Case StudyInterpretive ParadigmsMethodological RigorRealist Methodology
Critical realism is an emerging philosophical paradigm for social science research, positioned as an alternative to positivism and interpretivism, yet few studies provide clear guidance on its application, and it defines causal explanation by linking structural entities and contextual conditions to observed events. The authors propose a set of methodological principles for conducting and evaluating critical realist explanatory case studies in information systems. These principles are derived from critical realism’s ontological and epistemological assumptions and illustrated through examples from existing critical realist case studies. The article concludes by outlining the implications of critical realist research for information systems research and practice.
Critical realism is emerging as a viable philosophical paradigm for conducting social science research, and has been proposed as an alternative to the more prevalent paradigms of positivism and interpretivism. Few papers, however, have offered clear guidance for applying this philosophy to actual research methodologies. Under critical realism, a causal explanation for a given phenomenon is inferred by explicitly identifying the means by which structural entities and contextual conditions interact to generate a given set of events. Consistent with this view of causality, we propose a set of methodological principles for conducting and evaluating critical realism-based explanatory case study research within the information systems field. The principles are derived directly from the ontological and epistemological assumptions of critical realism. We demonstrate the utility of each of the principles through examples drawn from existing critical realist case studies. The article concludes by discussing the implications of critical realism based research for IS research and practice.
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