Building theories from case study research
Построение теорий на основе кейс-исследований
2009-02-01
SCID: 54.1/xktfgua2
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case study researchinductive theory buildingreplication logicwithin-case analysis
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Abstract (AI)
- This paper describes the process of inducting theory using case studies from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process described here is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas. The resultant theory is often novel, testable, and empirically valid. Finally, framebreaking insights, the tests of good theory (e.g., parsimony, logical coherence), and convincing grounding in the evidence are the key criteria for evaluating this type of research.
Key Findings
1
Case-study induction is particularly suitable for research in new topic areas.
2
Good case-study theory is evaluated by frame-breaking insights, parsimony, logical coherence, and strong grounding in evidence.
3
Some process elements (problem definition, construct validation) resemble hypothesis-testing research, while others (within-case analysis, replication logic) are unique to case-oriented induction.
4
The inductive, case-oriented process is highly iterative and closely tied to empirical data.
5
The paper outlines a detailed, iterative process for inducting theory from case studies, from research question specification to closure.
6
Theories generated from case studies tend to be novel, testable, and empirically valid.
Research Object
Inductive theory-building process using case study research
Research Subject
Procedures and criteria for developing and validating theory from case studies, including problem definition, within-case analysis, replication logic, construct validation, iteration tied to data, and evaluation criteria (parsimony, coherence, empirical grounding)
Publication Details
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2009-02-01
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