Multiple Case-Based Autoethnography
Multiple Case-Based Autoethnographic Research · Also known as: collective autoethnography, multi-case autoethnography, collaborative autoethnography, multi-site autoethnography
Multiple case-based autoethnography is a qualitative design that extends autoethnographic inquiry across two or more researcher-participants or cases, enabling systematic comparison of personal lived experiences within a shared cultural or social phenomenon. By generating rich first-person narratives from each case and then conducting a structured cross-case analysis, the approach combines the depth and reflexivity of autoethnography with the comparative analytical power of multiple case design.
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When to use it
Use multiple case-based autoethnography when the research question concerns a shared cultural phenomenon, professional experience, or social process as lived by two or more insiders, and when systematic comparison of those insider accounts is needed to build robust understanding. It is particularly valuable in studies of professional identity, organizational culture, marginalized communities, or cross-cultural experience where the researchers themselves are legitimate members of the culture being studied. Avoid this design when participant anonymity is paramount and self-disclosure poses ethical risk; when the phenomenon requires an external observer stance rather than an insider-reflexive one; when only one researcher-participant is available (standard autoethnography suffices); or when quantitative generalizability is the goal.
Strengths & limitations
- Combines the thick, reflexive depth of autoethnography with the comparative analytical rigor of multiple case design.
- Surfaces shared cultural patterns while preserving the distinctiveness of individual experience.
- Reduces the risk of idiosyncratic findings endemic to single-participant autoethnography.
- Enables researchers from different positionalities to interrogate the same phenomenon collaboratively.
- Particularly powerful for studying under-researched communities where the researchers are themselves cultural insiders.
- Requires substantial investment from all researcher-participants in sustained, vulnerable self-disclosure.
- Coordinating data generation and analysis across multiple cases adds logistical and relational complexity.
- Findings remain context-specific; statistical generalizability is not a goal or outcome of this design.
- Cross-case comparison can inadvertently homogenize experience if not carefully balanced with within-case depth.
- Ethical tensions around representing co-researchers' stories require ongoing negotiation and member-checking.
Frequently asked
How is this different from collaborative autoethnography?
The terms overlap substantially. Collaborative autoethnography (Chang et al., 2013) emphasizes the co-writing and dialogic process among researcher-participants. Multiple case-based autoethnography foregrounds the case-comparison structure — each researcher-participant constitutes a bounded case, and the analytic logic follows the cross-case comparison procedures associated with multiple case study design. In practice, many studies combine both features.
How many cases are needed?
Two cases is the minimum for genuine comparison, but two cases carry a high risk of producing a simple contrast rather than transferable insight. Three to six cases are more typical; this range allows meaningful pattern identification without making coordination impractical. The selection criterion is purposive rather than numeric: cases should share the focal phenomenon while offering theoretically relevant variation.
Are the researchers also participants?
In most implementations, yes — the researcher-participants write from their own lived experience. However, the design can also be applied when researchers collect first-person accounts from cultural insiders who are not the researchers themselves, provided those accounts are treated with the reflexive, evocative standards of autoethnographic writing rather than conventional interview data.
What ethical issues are specific to this design?
Key issues include negotiating authorship and ownership of shared narratives, managing vulnerability and self-disclosure among co-researchers, ensuring genuine informed consent when researcher-participants' accounts may identify them or others, and handling disagreements about interpretation between collaborators. These issues should be addressed in a written collaboration agreement before data generation begins.
Can I use NVivo or Atlas.ti for the cross-case analysis?
Yes, qualitative data software can assist with organizing each case's corpus and managing cross-case coding matrices. However, the reflexive, interpretive work — especially the synthesis of personal meaning across cases — requires the researcher's sustained engagement with the texts and cannot be delegated to software.
Sources
- Chang, H., Ngunjiri, F. W., & Hernandez, K. A. C. (2013). Collaborative Autoethnography. Left Coast Press. ISBN: 978-1611321104
- Ellis, C. (2004). The Ethnographic I: A Methodological Novel about Autoethnography. AltaMira Press. ISBN: 978-0759103726
How to cite this page
ScholarGate. (2026, June 3). Multiple Case-Based Autoethnographic Research. ScholarGate. https://scholargate.app/en/qualitative/multiple-case-based-autoethnography
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- AutoethnographyQualitative↔ compare
- Comparative autoethnographyQualitative↔ compare
- Multiple-Case StudyQualitative↔ compare
- Narrative InquiryQualitative Research↔ compare