Author List: Tsang, Eric W.K.; Williams, John N.;
MIS Quarterly, 2012, Volume 36, Issue 3, Page 729-748.
In "Generalizing Generalizability in Information Systems Research," Lee and Baskerville (2003) try to clarify generalization and classify it into four types. Unfortunately, their account is problematic. We propose repairs. Central among these is our balance-of-evidence argument that we should adopt the view that Hume's problem of induction has a solution, even if we do not know what it is. We build upon this by proposing an alternative classification of induction. There are five types of generalization: (1) theoretical, (2) within-population, (3) cross-population, (4) contextual, and (5) temporal, with theoretical generalization being across the empirical and theoretical levels and the rest within the empirical level. Our classification also includes two kinds of inductive reasoning that do not belong to the domain of generalization. We then discuss the implications of our classification for information systems research.
Keywords: deduction; generalizability; generalization; Hume's problem of induction; induction; inductive analogy; Research methodology; statistical generalization; statistical syllogism
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#175 0.646 taxonomy systems different concept isd alternative generalization mechanistic distinction types generalizability theoretical speech richer induction original form inductive empirical organic
#21 0.161 research information systems science field discipline researchers principles practice core methods area reference relevance conclude set focus propose perspective inquiry
#31 0.080 problem problems solution solving problem-solving solutions reasoning heuristic theorizing rules solve general generating complex example formulation heuristics effective given finding