Multiple Case-Based Grounded Theory
Also known as: multi-case grounded theory, MCGT, comparative case grounded theory, cross-case grounded theory
Multiple case-based grounded theory is a qualitative research design that embeds grounded theory's inductive coding logic inside a structured multiple-case framework. Rather than generating theory from a single site or interview pool, researchers iteratively collect and analyze data across two or more purposefully selected cases, using constant comparison both within and across cases until theoretical saturation is reached. The result is a substantive theory grounded in rich, cross-site empirical evidence.
Key highlights
- Produces theory grounded in multiple empirical contexts, making theoretical propositions more transferable than single-case findings.
- Combines the contextual depth of case study with grounded theory's systematic inductive coding, yielding both richness and analytic rigor.
- Replication logic across cases strengthens confidence that identified patterns are not idiosyncratic to one site.
- Theoretical sampling ensures data collection remains purposeful and tied to the developing theory rather than arbitrary.
- Well-suited to novel or under-theorized phenomena where existing frameworks are absent or inadequate.
Intuition
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How it works
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When to use it
Use multiple case-based grounded theory when you want to build a new theory or substantially extend an existing one, and when a single case or a non-comparative approach would leave the theory underspecified or context-bound. It is particularly suited to organizational, management, education, and social science research where phenomena vary meaningfully across sites. The method requires rich qualitative data (interviews, documents, observations) from at least two — preferably four to six — distinct cases. Do not use it when theory already exists and you seek to test or confirm it (use deductive methods instead), when only one case is accessible, or when time and resources are insufficient to conduct deep within-case analysis across multiple sites.
Strengths & limitations
- Produces theory grounded in multiple empirical contexts, making theoretical propositions more transferable than single-case findings.
- Combines the contextual depth of case study with grounded theory's systematic inductive coding, yielding both richness and analytic rigor.
- Replication logic across cases strengthens confidence that identified patterns are not idiosyncratic to one site.
- Theoretical sampling ensures data collection remains purposeful and tied to the developing theory rather than arbitrary.
- Well-suited to novel or under-theorized phenomena where existing frameworks are absent or inadequate.
- Highly resource-intensive: multiple sites require sustained access, extensive data collection, and long analysis cycles.
- Managing and integrating large volumes of cross-case data demands advanced organizational and analytic skills.
- Determining when theoretical saturation is genuinely reached across multiple cases is a judgment call that requires experience.
- Findings are analytically rather than statistically generalizable; the method does not support population-level inference.
Common pitfalls
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Applications
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Frequently asked
How is this different from a standard multiple-case study?
A standard multiple-case study typically tests or illustrates an existing theoretical framework through replication logic, presenting thick descriptions of each case. Multiple case-based grounded theory aims to generate new theory. Data collection and case selection are guided by the emerging theory (theoretical sampling), and the analysis follows grounded theory's constant comparison procedure rather than predefined themes or propositions.
How many cases do I need?
There is no fixed rule, but Eisenhardt suggests four to ten cases as a workable range. Too few cases limit cross-case variation; too many become unmanageable. The guiding principle is theoretical saturation — you add cases until new sites no longer introduce new categories or modify existing ones. In practice, four to six cases with deep data are more valuable than ten cases with shallow data.
Can I use this method in a PhD thesis?
Yes, and it is increasingly common in management, education, and information systems dissertations. The design is demanding but well-suited to doctoral work because it combines theoretical contribution (required for a PhD) with empirical grounding across multiple contexts. Plan for at least 18–24 months of fieldwork and analysis if you are conducting four or more in-depth cases.
Is theoretical sampling the same as purposive sampling?
They overlap but are not identical. Purposive sampling selects cases or participants based on predetermined criteria before data collection begins. Theoretical sampling is dynamic — the emerging theory itself dictates where to sample next. You may start with purposive selection, but as categories develop you seek data specifically to test, extend, or disconfirm them. This iterative interplay between data and theory is what distinguishes grounded theory from other qualitative approaches.
What software can I use for analysis?
NVivo, ATLAS.ti, and MAXQDA all support the coding and memo-writing practices central to grounded theory. For cross-case comparison, Miles and Huberman-style matrices built in spreadsheets or word processors can supplement qualitative software. The software manages data; the analytic logic of constant comparison, theoretical sampling, and category development must be driven by the researcher.
Sources
- 1.Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550.
- 2.Glaser, B. G., & Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine.ISBN 978-0202302607
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Cite this page
ScholarGate. (2026, June 3). Multiple Case-Based Grounded Theory. ScholarGate. https://scholargate.app/qualitative/multiple-case-based-grounded-theory