Abstract
This chapter focuses on collective case study: (1) what it is, (2) what separates it from other case study formats (case study and multiple case study), and (3) how to effectively use collective case study design for research. This chapter walks researchers through the overarching components necessary in conducting research using collective case study design, providing helpful strategies and examples the authors have found useful in their own research. While highly useful in qualitative research, this chapter also notes possible challenges to using collective case study design. This chapter concludes with a list of additional resources for more in-depth explorations of the procedural elements addressed.
TopBackground
To begin, the researcher must first understand case study design. Case study is defined as an examination of a confined or bounded system or unit, in context, involving both an in-depth examination and analysis in order to examine, reveal, or better understand a phenomenon, or a social or cultural issue (Creswell, 2013; Merriam & Tisdell, 2016; Putney, 2010; Stake, 1995; Yin, 2006). A case typically consists of an examination of one individual, organization, process, event, role, (sub)culture, encounter, period of time, or program (Miles, et al., 2020; Yin, 2006). Case studies can be either instrumental or intrinsic, and determining which type the researcher intends to use is an important step early on in the study design process. Instrumental cases are referred to when the case being examined is considered instrumental to comprehending not only that specific case, but something larger than itself (Putney, 2010; Stake, 1995). Intrinsic cases, in comparison, are used when there is an intrinsic interest in a particular case, not to learn about something that allows for generalization, but rather because of what the particular case has to offer in and of itself (Putney, 2010; Stake, 1995). Regardless of whether the case study is instrumental or intrinsic, the examination of a single case, bound in time and context, is the focus for this particular study design. There are significantly more elements to consider, in terms of design, when considering case study. For more information about case study design, the researcher may consult both Putney (2010) and Yin (2018).
Key Terms in this Chapter
Multiple Case Study: Explores a multiple bounded system involving multiple sources of information or relies on several instrumental, bounded cases to provide more extensive descriptions and explanations of a phenomenon or issue using varied data collection strategies to understand case similarities and differences to generalize conclusions over several units of analyses.
Case: A single bounded system or unit that is the investigational focus for a case study.
Data Management: The systematic organization of data into sets to assist meaning-making and prepare for analysis.
Data Collection: The process of gathering information in a systematic, organized, unbiased way.
Collective Case Study: Explores individual cases to provide detail and explanation regarding a situation, phenomenon, or experience where individual studies provides information into the “why” or “how,” and provides elaborative data through comparing cases cross-wise that allows for a more expansive understanding of the issue.
Case Study: An examination of a confined or bounded system or unit, in context, involving both an in-depth examination and analysis to examine, reveal, or better understand a phenomenon, or a social or cultural issue.
Results: The researcher’s systematic interpretation of the data in relation to the research question(s), making sense of the findings and providing contextual answers to the posited questions.
Findings: The identification of patterns and systematic recording of what the data sets display, prior to the researcher interpreting to determine results.
Data Analysis: The process of breaking down units into individual pieces for comparative and contrasting analysis, seeking intersection between pieces to identify patterns, and examining outliers to best understand how the pieces work in aggregate to explain the whole.