difference between single and multiple case study

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Research Guides

Multiple Case Studies

Nadia Alqahtani and Pengtong Qu

Description

The case study approach is popular across disciplines in education, anthropology, sociology, psychology, medicine, law, and political science (Creswell, 2013). It is both a research method and a strategy (Creswell, 2013; Yin, 2017). In this type of research design, a case can be an individual, an event, or an entity, as determined by the research questions. There are two variants of the case study: the single-case study and the multiple-case study. The former design can be used to study and understand an unusual case, a critical case, a longitudinal case, or a revelatory case. On the other hand, a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena (Lewis-Beck, Bryman & Liao, 2003; Yin, 2017). …a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena

The difference between the single- and multiple-case study is the research design; however, they are within the same methodological framework (Yin, 2017). Multiple cases are selected so that “individual case studies either (a) predict similar results (a literal replication) or (b) predict contrasting results but for anticipatable reasons (a theoretical replication)” (p. 55). When the purpose of the study is to compare and replicate the findings, the multiple-case study produces more compelling evidence so that the study is considered more robust than the single-case study (Yin, 2017).

To write a multiple-case study, a summary of individual cases should be reported, and researchers need to draw cross-case conclusions and form a cross-case report (Yin, 2017). With evidence from multiple cases, researchers may have generalizable findings and develop theories (Lewis-Beck, Bryman & Liao, 2003).

Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Los Angeles, CA: Sage.

Lewis-Beck, M., Bryman, A. E., & Liao, T. F. (2003). The Sage encyclopedia of social science research methods . Los Angeles, CA: Sage.

Yin, R. K. (2017). Case study research and applications: Design and methods . Los Angeles, CA: Sage.

Key Research Books and Articles on Multiple Case Study Methodology

Yin discusses how to decide if a case study should be used in research. Novice researchers can learn about research design, data collection, and data analysis of different types of case studies, as well as writing a case study report.

Chapter 2 introduces four major types of research design in case studies: holistic single-case design, embedded single-case design, holistic multiple-case design, and embedded multiple-case design. Novice researchers will learn about the definitions and characteristics of different designs. This chapter also teaches researchers how to examine and discuss the reliability and validity of the designs.

Creswell, J. W., & Poth, C. N. (2017). Qualitative inquiry and research design: Choosing among five approaches . Los Angeles, CA: Sage.

This book compares five different qualitative research designs: narrative research, phenomenology, grounded theory, ethnography, and case study. It compares the characteristics, data collection, data analysis and representation, validity, and writing-up procedures among five inquiry approaches using texts with tables. For each approach, the author introduced the definition, features, types, and procedures and contextualized these components in a study, which was conducted through the same method. Each chapter ends with a list of relevant readings of each inquiry approach.

This book invites readers to compare these five qualitative methods and see the value of each approach. Readers can consider which approach would serve for their research contexts and questions, as well as how to design their research and conduct the data analysis based on their choice of research method.

Günes, E., & Bahçivan, E. (2016). A multiple case study of preservice science teachers’ TPACK: Embedded in a comprehensive belief system. International Journal of Environmental and Science Education, 11 (15), 8040-8054.

In this article, the researchers showed the importance of using technological opportunities in improving the education process and how they enhanced the students’ learning in science education. The study examined the connection between “Technological Pedagogical Content Knowledge” (TPACK) and belief system in a science teaching context. The researchers used the multiple-case study to explore the effect of TPACK on the preservice science teachers’ (PST) beliefs on their TPACK level. The participants were three teachers with the low, medium, and high level of TPACK confidence. Content analysis was utilized to analyze the data, which were collected by individual semi-structured interviews with the participants about their lesson plans. The study first discussed each case, then compared features and relations across cases. The researchers found that there was a positive relationship between PST’s TPACK confidence and TPACK level; when PST had higher TPACK confidence, the participant had a higher competent TPACK level and vice versa.

Recent Dissertations Using Multiple Case Study Methodology

Milholland, E. S. (2015). A multiple case study of instructors utilizing Classroom Response Systems (CRS) to achieve pedagogical goals . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3706380)

The researcher of this study critiques the use of Classroom Responses Systems by five instructors who employed this program five years ago in their classrooms. The researcher conducted the multiple-case study methodology and categorized themes. He interviewed each instructor with questions about their initial pedagogical goals, the changes in pedagogy during teaching, and the teaching techniques individuals used while practicing the CRS. The researcher used the multiple-case study with five instructors. He found that all instructors changed their goals during employing CRS; they decided to reduce the time of lecturing and to spend more time engaging students in interactive activities. This study also demonstrated that CRS was useful for the instructors to achieve multiple learning goals; all the instructors provided examples of the positive aspect of implementing CRS in their classrooms.

Li, C. L. (2010). The emergence of fairy tale literacy: A multiple case study on promoting critical literacy of children through a juxtaposed reading of classic fairy tales and their contemporary disruptive variants . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3572104)

To explore how children’s development of critical literacy can be impacted by their reactions to fairy tales, the author conducted a multiple-case study with 4 cases, in which each child was a unit of analysis. Two Chinese immigrant children (a boy and a girl) and two American children (a boy and a girl) at the second or third grade were recruited in the study. The data were collected through interviews, discussions on fairy tales, and drawing pictures. The analysis was conducted within both individual cases and cross cases. Across four cases, the researcher found that the young children’s’ knowledge of traditional fairy tales was built upon mass-media based adaptations. The children believed that the representations on mass-media were the original stories, even though fairy tales are included in the elementary school curriculum. The author also found that introducing classic versions of fairy tales increased children’s knowledge in the genre’s origin, which would benefit their understanding of the genre. She argued that introducing fairy tales can be the first step to promote children’s development of critical literacy.

Asher, K. C. (2014). Mediating occupational socialization and occupational individuation in teacher education: A multiple case study of five elementary pre-service student teachers . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3671989)

This study portrayed five pre-service teachers’ teaching experience in their student teaching phase and explored how pre-service teachers mediate their occupational socialization with occupational individuation. The study used the multiple-case study design and recruited five pre-service teachers from a Midwestern university as five cases. Qualitative data were collected through interviews, classroom observations, and field notes. The author implemented the case study analysis and found five strategies that the participants used to mediate occupational socialization with occupational individuation. These strategies were: 1) hindering from practicing their beliefs, 2) mimicking the styles of supervising teachers, 3) teaching in the ways in alignment with school’s existing practice, 4) enacting their own ideas, and 5) integrating and balancing occupational socialization and occupational individuation. The study also provided recommendations and implications to policymakers and educators in teacher education so that pre-service teachers can be better supported.

Multiple Case Studies Copyright © 2019 by Nadia Alqahtani and Pengtong Qu is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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SINGLE CASE STUDIES VS. MULTIPLE CASE STUDIES: A COMPARATIVE STUDY - DIVA PORTAL

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Single Case Versus Multiple Case Studies

One of Yin's dimensions for classifying case studies involves single-case versus multiple-case studies. In some instances, only a single-case study is necessary or at times even possible; this is true when a unique case comes along that presents a valuable source of information. For example, a social scientist wanting to explore the emotional impact of a national tragedy on elementary-school children might choose to study the Challenger space shuttle disaster or the World Trade Center attacks, as a single-case study.

Eminent Russian psychologist Aleksandr Luria, in his book The Mind of a Mnemonist: A Little Book About a Vast Memory (1968), has, in a most engaging style, described a single-case (holistic) study. The case involved a man by the name of Shereshevskii (identified in the book as subject "S") who possessed an extraordinary memory. Luria began to observe "S" systematically in the 1920's, after "S" had asked him to test his memory. Luria was so astounded by the man's ability to study information for brief periods of time and then repeat it back to him without an error that he continued to observe and test "S" over the following thirty years. Luria was convinced that this man possessed one of the best memories ever studied.

Because of the nature of the phenomenon—an unusually vast memory— and the fact that this man was capable of performing memory feats never before witnessed, a single-case (holistic) study was begun. When studying rare phenomena, as in this instance, it is not possible to find the number of subjects typically required for an experiment; thus, the case-study approach presents the best alternative. Over the ensuing thirty years, Luria carefully documented the results of literally hundreds of memory feats. In some instances, Luria presented "S" with a list of words to memorize and asked him to recall them immediately. At other times, without any forewarning, Luria asked "S" to recall words from lists given more than fifteen years before. In most of these instances, "S" recalled the list with only a few errors. Luria commented on much more than the results of these memory tests; he also carefully studied the personality of "S." Luria wanted to understand him as a whole person, not only as a person with a great memory. Closely involved with his subject, Luria personally gave the instructions and collected the data. Whereas the data from the memory tasks provided some degree of objectivity to the study, most of the information came from the subjective observations and judgments made by Luria himself. The study was reported in a book-length narrative.

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Readers' Questions

What is the differences between single case and multiple case study designs?

A single case study design is an intensive investigation of one person, group, or event. It has the aim of creating an in-depth, holistic understanding of the case. Single case study designs often involve observations, interviews, and document reviews to explore the case study in detail. A multiple case study design is a type of research methodology which seeks to study several cases in the same context. These studies involve multiple cases that are studied over a period of time, and they are often used to compare cases to one another. Multiple case study designs allow researchers to explore similarities and differences between the cases, and to evaluate the effects of context on different outcomes. They also provide an opportunity to study the impact of data collection methods, as multiple cases are more likely to yield robust results due to sample size.

What are the difference between single case and multple case study designs?

Single case study designs focus on a single individual, group, or site, while multiple case studies involve the study of two or more individuals, groups, or sites. In single case studies, the researcher is attempting to understand a particular phenomenon in-depth, often by collecting qualitative data. In multiple case studies, the researcher may be attempting to compare different cases and assess whether variables relating to them differ. Multiple case studies involve analyzing and comparing data from multiple studies to provide a more comprehensive understanding of the phenomenon under investigation.

What is (are) the difference(s) between single case and multiple case study designs?

Scope: Single case study designs focus on a single unit of analysis, while multiple case study designs involve multiple units of analysis. Nature: Single case studies usually involve an in-depth investigation of an individual case or a limited number of cases, while multiple case studies involve investigating a wider range of cases. Data Collection: Single case studies involve gathering data on a single unit of analysis, while multiple case studies involve collecting data from multiple sources or locations. Generalizability: Single case studies are not very generalizable, while multiple case studies can provide more generalizable results. Study Length: Single case studies are usually shorter than multiple case studies. Purpose: Single case studies typically have a descriptive purpose, while multiple case studies can have a more explanatory purpose.

What is the difference between single case and multiple case study designs?

Single case study designs involve an in-depth examination of one or a few people, places, events, or phenomena. This type of research often focuses on understanding a particular situation or event in-depth. It is useful when an overview of a phenomenon is needed or when the researcher cannot study a larger number of cases because of time constraints or limited resources. Multiple case study designs involve looking at several people, places, events, or phenomena simultaneously. This type of research provides a broader perspective and can reveal patterns or relationships among different cases that may not be seen in a single case. It is useful when there is a need to understand the broader context in which certain phenomena occur. Multiple case studies also allow for comparison and contrast of different cases, which can provide more insight into a particular situation or event.

What is the difference between single case study design and multiple Case research design?

Single case study design is an in-depth exploration of a single entity or phenomenon. This type of research design allows researchers to gain an understanding of a phenomenon through an extended, detailed analysis of a single case. Multiple case research design is a research design in which multiple cases are studied and analyzed in order to draw more general conclusions. It is a method used to explore complex phenomena when single case studies are not enough to provide an understanding of the phenomenon. Multiple cases give researchers the ability to examine broader dimensions and to consider more contextual factors that might be influencing the phenomenon.

What are the differences between single case and multiple case study design?

Single case study design: A single case study design focuses on a single individual, group, or event. It involves collecting data from a single source, such as an interview or observation, over a limited period of time. This type of study is used when the researcher has a specific research question or hypothesis in mind. Multiple case study design: A multiple case study design involves collecting data from multiple sources, such as interviews or observations, over a longer period of time. It can involve collecting data from different individuals, groups, or events and comparing them to each other. This type of study is used when the researcher has a broader research question or hypothesis and wants to better understand the complexity of the issue.

The theory contribution of case study research designs

• Original Research
• Open access
• Published: 16 February 2017
• Volume 10 , pages 281–305, ( 2017 )

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• Hans-Gerd Ridder 1  

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The objective of this paper is to highlight similarities and differences across various case study designs and to analyze their respective contributions to theory. Although different designs reveal some common underlying characteristics, a comparison of such case study research designs demonstrates that case study research incorporates different scientific goals and collection and analysis of data. This paper relates this comparison to a more general debate of how different research designs contribute to a theory continuum. The fine-grained analysis demonstrates that case study designs fit differently to the pathway of the theory continuum. The resulting contribution is a portfolio of case study research designs. This portfolio demonstrates the heterogeneous contributions of case study designs. Based on this portfolio, theoretical contributions of case study designs can be better evaluated in terms of understanding, theory-building, theory development, and theory testing.

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1 Introduction

Case study research scientifically investigates into a real-life phenomenon in-depth and within its environmental context. Such a case can be an individual, a group, an organization, an event, a problem, or an anomaly (Burawoy 2009 ; Stake 2005 ; Yin 2014 ). Unlike in experiments, the contextual conditions are not delineated and/or controlled, but part of the investigation. Typical for case study research is non-random sampling; there is no sample that represents a larger population. Contrary to quantitative logic, the case is chosen, because the case is of interest (Stake 2005 ), or it is chosen for theoretical reasons (Eisenhardt and Graebner 2007 ). For within-case and across-case analyses, the emphasis in data collection is on interviews, archives, and (participant) observation (Flick 2009 : 257; Mason 2002 : 84). Case study researchers usually triangulate data as part of their data collection strategy, resulting in a detailed case description (Burns 2000 ; Dooley 2002 ; Eisenhardt 1989 ; Ridder 2016 ; Stake 2005 : 454). Potential advantages of a single case study are seen in the detailed description and analysis to gain a better understanding of “how” and “why” things happen. In single case study research, the opportunity to open a black box arises by looking at deeper causes of the phenomenon (Fiss 2009 ). The case data can lead to the identification of patterns and relationships, creating, extending, or testing a theory (Gomm et al. 2000 ). Potential advantages of multiple case study research are seen in cross-case analysis. A systematic comparison in cross-case analysis reveals similarities and differences and how they affect findings. Each case is analyzed as a single case on its own to compare the mechanisms identified, leading to theoretical conclusions (Vaughan 1992 : 178). As a result, case study research has different objectives in terms of contributing to theory. On the one hand, case study research has its strength in creating theory by expanding constructs and relationships within distinct settings (e.g., in single case studies). On the other hand, case study research is a means of advancing theories by comparing similarities and differences among cases (e.g., in multiple case studies).

Unfortunately, such diverging objectives are often neglected in case study research. Burns ( 2000 : 459) emphasizes: “The case study has unfortunately been used as a ‘catch –all’ category for anything that does not fit into experimental, survey, or historical methods.”

Therefore, this paper compares case study research designs. Such comparisons have been conducted previously regarding their philosophical assumptions and orientations, key elements of case study research, their range of application, and the lacks of methodological procedures in publications. (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). This paper aims to compare case study research designs regarding their contributions to theory.

Case study research designs will be analyzed regarding their various strengths on a theory continuum. Edmondson and McManus ( 2007 ) initiated a debate on whether the stage of theory fits to research questions, style of data collection, and analyses. Similarly, Colquitt and Zapata-Phelan ( 2007 ) created a taxonomy capturing facets of empirical article’s theoretical contributions by distinguishing between theory-building and theory testing. Corley and Gioia ( 2011 ) extended this debate by focusing on the practicality of theory and the importance of prescience. While these papers consider the whole range of methodological approaches on a higher level, they treat case studies as relatively homogeneous. This paper aims to delve into a deeper level of analysis by solely focusing on case study research designs and their respective fit on this theory continuum. This approach offers a more fine-grained understanding that sheds light on the diversity of case study research designs in terms of their differential theory contributions. Such a deep level of analysis on case study research designs enables more rigor in theory contribution. To analyze alternative case study research designs regarding their contributions to theory, I engage into the following steps:

First, differences between case study research designs are depicted. I outline and compare the case study research designs with regard to the key elements, esp. differences in research questions, frameworks, sampling, data collection, and data analysis. These differences result in a portfolio of various case study research designs.

Second, I outline and substantiate a theory continuum that varies between theory-building, theory development, and testing theory. Based on this continuum, I analyze and discuss each of the case study research designs with regard to their location on the theory continuum. This analysis is based on a detailed differentiation of the phenomenon (inside or outside the theory), the status of the theory, research strategy, and methods.

As a result, the contribution to the literature is a portfolio of case study research designs explicating their unique contributions to theory. The contribution of this paper lies in a fine-grained analysis of the interplay of methods and theory (van Maanen et al. 2007 ) and the methodological fit (Edmondson and McManus 2007 ) of case study designs and the continuum of theory. It demonstrates that different designs have various strengths and that there is a fit between case study designs and different points on a theory continuum. If there is no clarity as to whether a case study design aims at creating, elaborating, extending, or testing theory, the contribution to theory is difficult to identify for authors, reviewers, and readers. Consequently, this paper aims to clarify at which point of the continuum of theory case study research designs can provide distinct contributions that can be identified beyond their traditionally claimed exploratory character.

2 Differences across case study design: a portfolio approach

Only few papers have compared case study research designs so far. In all of these comparisons, the number of designs differs as well as the issues under consideration. In an early debate between Dyer and Wilkins ( 1991 ) and Eisenhardt ( 1991 ), Dyer and Wilkins compared the case study research design by Eisenhardt ( 1989 ) with “classical” case studies. The core of the debate concerns a difference between in-depth single case studies (classical case study) to a focus on the comparison of multiple cases. Dyer and Wilkins ( 1991 : 614) claim that the essence of a case study lies in the careful study of a single case to identify new relationships and, as a result, question the Eisenhardt approach which puts a lot of emphasis on comparison of multiple cases. Eisenhardt, on the contrary, claims that multiple cases allow replication between cases and is, therefore, seen as a means of corroboration of propositions (Eisenhardt 1991 ). Classical case studies prefer deep descriptions of a single case, considering the context to reveal insights into the single case and by that elaborate new theories. The comparison of multiple cases, therefore, tends—in the opinion of Dyer and Wilkens—to surface descriptions. This weakens the possibility of context-related, rich descriptions. While, in classic case study, good stories are the aim, the development of good constructs and their relationships is aimed in Eisenhardt’s approach. Eisenhardt ( 1991 : 627) makes a strong plea on more methodological rigor in case study research, while Dyer and Wilkins ( 1991 : 613) criticize that the new approach “… includes many of the attributes of hypothesis-testing research (e.g., sampling and controls).”

Dooley ( 2002 : 346) briefly takes the case study research designs by Yin (1994) and Eisenhardt ( 1989 ) as exemplars of how the processes of case study research can be applied. The approach by Eisenhardt is seen as an exemplar that advances conceptualization and operationalization in the phases of theory-building, while the approach by Yin is seen as exemplar that advances minimally conceptualized and operationalized existing theory.

Baxter and Jack ( 2008 ) describe the designs by Yin (2003) and Stake ( 1995 ) to demonstrate key elements of qualitative case study. The authors outline and carefully compare the approaches by Yin and Stake in conducting the research process, neglecting philosophical differences and theoretical goals.

Piekkari et al. ( 2009 ) outline the methodological richness of case study research using the approaches of Yin et al. (1998), and Stake. They specifically exhibit the role of philosophical assumptions, establishing differences in conventionally accepted practices of case study research in published papers. The authors analyze 135 published case studies in four international business journals. The analysis reveals that, in contrast to the richness of case study approaches, the majority of published case studies draw on positivistic foundations and are narrowly declared as explorative with a lack of clarity of the theoretical purpose of the case study. Case studies are often designed as multiple case studies with cross-sectional designs based on interviews. In addition to the narrow use of case study research, the authors find out that “… most commonly cited methodological literature is not consistently followed” (Piekkari et al. 2009 : 567).

Welch et al. ( 2011 ) develop a typology of theorizing modes in case study methods. Based on the two dimensions “contextualization” and “causal explanation”, they differentiate in their typology between inductive theory-building (Eisenhardt), interpretive sensemaking (Stake), natural experiment (Yin), and contextualised explanation (Ragin/Bhaskar). The typology is used to analyze 199 case studies from three highly ranked journals over a 10-year period for whether the theorizing modes are exercised in the practice of publishing case studies. As a result, the authors identify a strong emphasis on the exploratory function of case studies, neglecting the richness of case study methods to challenge, refine, verify, and test theories (Welch et al. 2011 : 755). In addition, case study methods are not consistently related to theory contribution: “By scrutinising the linguistic elements of texts, we found that case researchers were not always clear and consistent in the way that they wrote up their theorising purpose and process” (Welch et al. 2011 : 756).

As a result, the comparisons reveal a range of case study designs which are rarely discussed. In contrast, published case studies are mainly introduced as exploratory design. Explanatory, interpretivist, and critical/reflexive designs are widely neglected, narrowing the possible applications of case study research. In addition, comparisons containing an analysis of published case studies reveal a low degree in accuracy when applying case study methods.

What is missing is a comparison of case study research designs with regard to differences in the contribution to theory. Case study designs have different purposes in theory contribution. Confusing these potential contributions by inconsistently utilizing the appropriate methods weakens the contribution of case studies to scientific progress and, by that, damages the reputation of case studies.

To conduct such a comparison, I consider the four case study research approaches of Yin, Eisenhardt, Burawoy, and Stake for the following reasons.

These approaches are the main representatives of case study research design outlined in the comparisons elaborated above (Baxter and Jack 2008 ; Dooley 2002 ; Dyer and Wilkins 1991 ; Piekkari et al. 2009 ; Welch et al. 2011 ). I follow especially the argument by Piekkari et al. ( 2009 ) that these approaches contain a broad spectrum of methodological foundations of exploratory, explanatory, interpretivist, and critical/reflexive designs. The chosen approaches have an explicit and detailed methodology which can be reconstructed and compared with regard to their theory contribution. Although there are variations in the application of the designs, to the best of my knowledge, the designs represent the spectrum of case study methodologies. A comparison of these methodologies revealed main distinguishable differences. To highlight these main differences, I summarized these differences into labels of “no theory first”; “gaps and holes”; “social construction of reality”; and “anomalies”.

I did not consider descriptions of case study research in text books which focus more or less on general descriptions of the common characteristics of case studies, but do not emphasize differences in methodologies and theory contribution. In addition, I did not consider so-called “home grown” designs (Eisenhardt 1989 : 534) which lack a systematic and explicit demonstration of the methodology and where “… the hermeneutic process of inference—how all these interviews, archival records, and notes were assembled into a coherent whole, what was counted and what was discounted—remains usually hidden from the reader” (Fiss 2009 : 425).

Finally, although often cited in the methodological section of case studies, books are not considered which concentrate on data analysis in qualitative research per se (Miles et al. 2014 ; Corbin and Strauss 2015 ). Therefore, to analyze the contribution of case study research to the scientific development, it needs to compare explicit methodology. This comparison will be outlined in the following sections with regard to main methodological steps: the role of the case, the collection of data, and the analysis of data.

2.1 Case study research design 1: no theory first

A popular template for building theory from case studies is a paper by Eisenhardt ( 1989 ). It follows a dramaturgy with a precise order of single steps for constructing a case study and is one of the most cited papers in methods sections (Ravenswood 2011 ). This is impressive for two reasons. On the one hand, Eisenhardt herself has provided a broader spectrum of case study research designs in her own empirical papers, for example, by combining theory-building and theory elaboration (Bingham and Eisenhardt 2011 ). On the other hand, she “updated” her design in a paper with Graebner (Eisenhardt and Graebner 2007 ), particularly by extending the range of inductive theory-building. These developments do not seem to be seriously considered by most authors, as differences and elaborations of this spectrum are rarely found in publications. Therefore, in the following, I focus on the standards provided by Eisenhardt ( 1989 ) and Eisenhardt and Graebner ( 2007 ) as exemplary guidelines.

Eisenhardt follows the ideal of ‘no theory first’ to capture the richness of observations without being limited by a theory. The research question may stem from a research gap meaning that the research question is of relevance. Tentative a priori constructs or variables guide the investigation, but no relationships between such constructs or variables are assumed so far: “Thus, investigators should formulate a research problem and possibly specify some potentially important variables, with some reference to extant literature. However, they should avoid thinking about specific relationships between variables and theories as much as possible, especially at the outset of the process” (Eisenhardt 1989 : 536).

Cases are chosen for theoretical reasons: for the likelihood that the cases offer insights into the phenomenon of interest. Theoretical sampling is deemed appropriate for illuminating and extending constructs and identifying relationships for the phenomenon under investigation (Eisenhardt and Graebner 2007 ). Cases are sampled if they provide an unusual phenomenon, replicate findings from other cases, use contrary replication, and eliminate alternative explanations.

With respect to data collection, qualitative data are the primary choice. Data collection is based on triangulation, where interviews, documents, and observations are often combined. A combination of qualitative data and quantitative data is possible as well (Eisenhardt 1989 : 538). Data analysis is conducted via the search for within-case patterns and cross-case patterns. Systematic procedures are conducted to compare the emerging constructs and relationships with the data, eventually leading to new theory.

A good exemplar for this design is the investigation of technology collaborations (Davis and Eisenhardt 2011 ). The purpose of this paper is to understand processes by which technology collaborations support innovations. Eight technology collaborations among ten firms were sampled for theoretical reasons. Qualitative and quantitative data were used from semi-structured interviews, public and private data, materials provided by informants, corporate intranets, and business publications. The data was measured, coded, and triangulated. Writing case histories was a basis for within-case and cross-case analysis. Iteration between cases and emerging theory and considering the relevant literature provided the basis for the development of a theoretical framework.

Another example is the investigation of what is learned in organizational processes (Bingham and Eisenhardt 2011 ). This paper demonstrates that the case study design is not only used for theory-building, but can also be combined with theory elaboration. Based on the lenses of the organizational knowledge literature, organizational routines literature, and heuristics literature, six technology-based ventures were chosen for theoretical reasons. Several data sources were used, especially quantitative and qualitative data from semi-structured interviews, archival data, observations, e-mails, phone calls, and follow-up interviews. Within-case analysis revealed what each firm has learned from process experience. Cross-case analysis revealed emerging patterns from which tentative constructs and propositions were formed. In replication logic constructs and propositions were refined across the cases. When mirroring the findings with the literature, both the emergences of the constructs were compared and unexpected types were considered. The iteration of theory and data as well as the consideration of related research sharpened the theoretical arguments, eventually leading to a theoretical framework. “Thus, we combined theory elaboration (Lee 1999 ) and theory generation (Eisenhardt 1989 )” (Bingham and Eisenhardt 2011 : 1448).

2.2 Case study research design 2: gaps and holes

Contrary to “No Theory First”, case study research design can also aim at specifying gaps or holes in existing theory with the ultimate goal of advancing theoretical explanations (Ridder 2016 ). A well-known template for this case study research design is the book by Yin ( 2014 ). It is a method-orientated handbook of how to design single and multiple case studies with regard to this purpose. Such a case study research design includes: “A ‘how’ and ‘why’ question” (Yin 2014 : 14). Research questions can be identified and shaped using literature to narrow the interest in a specific topic, looking for key studies and identifying questions in these studies. According to Yin’s design, existing theory is the starting point of case study research. In addition, propositions or frameworks provide direction, reflect the theoretical perspective, and guide the search for relevant evidence.

There are different rationales for choosing a single case design (Yin 2014 : 51). Purposeful sampling is conducted if an extreme case or an unusual case is chosen and if rarely observable phenomena can be investigated with regard to unknown matters and their relationships. Common cases allow conclusions for a broader class of cases. Revelatory cases provide the opportunity to investigate into a previously inaccessible inquiry, and the longitudinal study enables one to investigate a single case at several points in time. A rationale for multiple case designs has its strength in replication logic (Yin 2014 : 56). In the case of literal replication, cases are selected to predict similar results. In the case of theoretical replication, cases are selected to predict contrasting results but for theoretical reasons. Yin provides several tactics to increase the reliability (protocol; data base) of the study.

Yin ( 2014 : 103) emphasizes that interviews are one of the most important sources of data collection but considers other sources of qualitative data as well. Data triangulation is designed to narrow problems of construct validity, as multiple sources of data provide multiple measures of the same phenomenon. Yin ( 2014 : 133) offers a number of data analysis strategies (e.g., case description; examining rival explanations) and analytic techniques which are apt to compare the proposed relationships with empirical patterns. Pattern-matching logic compares empirically based patterns with predicted patterns, enabling further data analysis techniques (explanation building, time series analysis, logic models, and cross-case synthesis). In analytical generalization, the theory is compared with the empirical results, leading to the modification or extension of the theory.

An appropriate model for this case study design can be identified in a paper by Ellonen et al. ( 2009 ). The paper is based on the emerging dynamic capability theory. The four cases were chosen for theoretical reasons to deliver an empirical contribution to the dynamic capability theory by investigating the relationship of dynamic capabilities and innovation outcomes. The authors followed a literal replication strategy and identified patterns between dynamic capabilities of the firms and their innovation outcomes.

Shane ( 2000 ) is an author who developed specific propositions from a framework and examined the propositions in eight entrepreneurial cases. Using several sources of interviews and archival data, the author compared the data with the propositions using the pattern-matching logic, which concluded in developing entrepreneurship theory.

2.3 Case study research design 3: social construction of reality

So far, the outlined case study research designs are based on positivist roots, but there is richness and variety in case study research stemming from different philosophical realms. The case study research design by Stake ( 1995 , 2000 , 2005 ), for example, is based on constructivist assumptions and aims to investigate the social construction of reality and meaning (Schwandt 1994 : 125).

According to this philosophical assumption, there is no unique “real world” that preexists independently of human mental activity and symbolic language. The world is a product of socially and historically related interchanges amongst people (social construction). The access to reality is given through social constructions, such as language and shared meanings: “The meaning-making activities themselves are of central interest to social constructionists/constructivists, simply because it is the meaning-making/sense making attributional activities that shape action or (inaction)” (Guba and Lincoln 2005 : 197). Therefore, the researcher is not looking for objective “facts”, nor does he aim at identifying and measuring patterns which can be generalized. Contrarily, the constructivist is researching into specific actions, in specific places, at specific times. The scientist tries to understand the construction and the sharing of meaning (Schwandt 1994 ).

According to Stake ( 2005 ), the direction of the case study is shaped by the interest in the case. In an intrinsic case study, the case itself is of interest. The purpose is not theory-building but curiosity in the case itself. In an instrumental case study, the case itself is of secondary interest. It plays a supportive role, as it facilitates the understanding of a research issue. The case can be typical of other cases. Multiple or collective case study research designs extend the instrumental case study. It is assumed that a number of cases will increase the understanding and support theorizing by comparison of the cases.

The differentiation by Stake ( 1995 , 2005 ) into intrinsic and instrumental cases guides the purposive sampling strategy. In intrinsic case studies, the case is, by definition, already selected. The researcher looks for specific characteristics, aiming for thick descriptions with the opportunity to learn. Representativeness or generalization is not considered. In instrumental case study design, purposive sampling leads to the phenomenon under investigation. In multiple case study designs, the ability to compare cases enhances the opportunity to theorize.

A case study requires an integrated, holistic comprehension of the case complexity. According to Stake ( 2005 ), the case study is constructed by qualitative data, such as observations, interviews, and documents. Triangulation first serves as clarification of meaning. Second, the researcher is interested in the diversity of perceptions.

Two methods of data analysis are considered in such qualitative case study design: direct interpretation and categorical aggregation (Stake 1995 : 74). The primary task of an intrinsic case study is to understand the case. This interpretation is offered to the reader, but the researcher has to provide the material in a sufficient way (thick descriptions), so that the reader can learn from the case as well as draw his or her own conclusions. Readers can thus make some generalizations based on personal and vicarious experiences (“naturalistic generalization”). In instrumental case studies, the understanding of phenomena and relationships leads to categorical aggregation, and the focus is on how the phenomenon exists across several cases.

Greenwood and Suddaby ( 2006 ), for example, used the instrumental case study design by Stake, combining network location theory and dialectical theory. They identified new dynamics creating a process model of elite institutional entrepreneurship.

Ituma et al. ( 2011 ) highlighted the social construction of reality in their study of career success. The majority of career studies have been conducted in Western countries and findings have been acknowledged as universally applicable. The authors demonstrated that realities of managers in other areas are constructed differently. As a result of their study, they provided a contextually sensitive frame for the analysis of career outcomes.

2.4 Case study research design 4: anomalies

Identifying anomalies as a basis for further research is common in management and organization research (Gilbert and Christensen 2005 ). In case study research, the extended case study method is used for this case study research design (Ridder 2016 ). Following Burawoy ( 1991 , 1998 , 2009 ), the research question derives from curiosity. Researchers normally look at what is “interesting” and what is “surprising” in a social situation that existing theory cannot explain. Initially, it is not important whether the expectations develop from some popular belief, stereotype, or from an academic theory. The extended case study research design is guided by anomalies that the previous theory was not able to explain through internal contradictions of theory, theoretical gaps, or silences. An anomaly does not reject theory, but rather demonstrates that the theory is incomplete. Theory is aimed to be improved by “… turning anomalies into exemplars” (Burawoy 1991 : 10).

The theoretical sampling strategy in this case study research design stems from the theoretical failure in confrontation with the site. According to the reflexive design, such cases do not favour individuals or isolated phenomena, but social situations in which a comparative strategy allows the tracing of differences across the cases to external forces.

In the extended case study, the researcher deals with qualitative data, but also considers the broader complex social situation. The researcher engages into a dialogue with the respondents (Burawoy ( 1991 , 1998 , 2009 ). An interview is an intervention into the life of a respondent. By means of mutual interaction it is possible to discover the social order under investigation. The observer has to unpack those situational experiences by means of participant observation and mutual interpretation. This situational comprehension aims at understanding divergent “voices”, reflecting the variety of respondents’ understandings of the social situation.

As in other sciences, these voices have to be aggregated. This aggregation of multiple readings of a single case is conducted by turning the aggregation into social processes: “The move from situation to process is accomplished differently in different reflexive methods, but it is always reliant on existing theory” (Burawoy 2009 : 41). Social processes are now traced to the external field as the conditions of the social processes. Consequently, this leads to the question concerning “… how those micro situations are shaped by wider structures” (Burawoy 1991 : 282). “Reflexive science insists, therefore, on studying the everyday world from the standpoint of its structuration, that is, by regarding it as simultaneously shaped by and shaping an external field of forces” (Burawoy 2009 : 42). Such social fields cannot be held constant, which undermines the idea of replication. The external field is in continuous flux. Accordingly, social forces that influence the social processes are identified, shaping the phenomenon under investigation. Extension of theory does not target representativeness as a relationship of sample and population. Generality in reflexive science is to reconstruct an existing theory: “We begin with our favorite theory but seek not confirmations but refutations that inspire us to deepen that theory. Instead of discovering grounded theory, we elaborate existing theory. We do not worry about the uniqueness of our case, since we are not as interested in its representativeness as its contribution to reconstructing theory. Our theoretical point of departure can range from the folk theory of participants to any abstract law. We consider only that the scientist consider it worth developing” (Burawoy 2009 : 43). Such elaboration stems from the identification of anomalies and offers new predictions with regard to the theory.

It is somewhat surprising that the extended case study design has been neglected in the management literature so far, and it appears that critical reflexive principles have to be resurrected as they have been in other disciplines (see the overview at Wadham and Warren 2014 ). Examples in the management and organization literature are rare. Danneels ( 2011 ) used the extended case study design to extend the dynamic capabilities theory. In his famous Smith Corona case, Danneels shows how a company tried to change its resource base. Based on detailed data, the Smith Corona case provides insights into the resource alteration processes and how dynamic capabilities operate. As a result, the paper fills a process gap in dynamic capability theory. Iterating between data collection and analysis, Danneels revealed resource cognition as an element not considered so far in dynamic capability theory. The use of the extended case study method is limited to the iteration of data and theory. First, there is “running exchange” (Burawoy 1991 : 10) between field notes and analysis. Second, there is iteration between analysis and existing theory. Unlike Burawoy, who aims to reconstruct existing theory on the basis of “emergent anomalies” (Burawoy 1991 : 11) considering social processes and external forces, Danneels confronts the dynamic capabilities literature with the Smith Corona case to extend the theory of dynamic capabilities.

2.5 A comparison of case study research processes

Commonalities and differences emerged from the comparison of the designs. Table  1 provides a brief summary of these main differences and the resulting portfolio of case study research designs which will be discussed in more detail.

There is an extensive range between the different designs regarding the research processes. In “no theory first”, there is a broad and tentative research question with some preliminary variables at the outset. The research question may be modified during the study as well as the variables. This design avoids any propositions regarding relationships.

On the contrary, the research question in “gaps and holes” is strongly related to existing theory, focusing on “how and why” questions. The existing theory contains research gaps which, once identified within the existing theory, lead accordingly to assumed relationships which are the basis for framework and propositions to be matched by empirical data. This broad difference is even more elaborated by a design that aims the “social construction of reality”. There is no research question at the outset, but a curiosity in the case or the case is a facilitator to understand a research issue. This is far away from curiosity in the “anomaly approach”. Here, the research question is inspired by questioning why an anomaly cannot be explained by the existing theory. What kind of gaps, silences, or internal contradictions demonstrates the insufficiency of the existing theory?

Various sampling strategies are used across these case study research designs, including theoretical sampling and purposeful sampling, which serve different objectives. Theoretical sampling in “no theory first” aims at selecting a case or cases that are appropriate to highlight new or extend preliminary constructs and reveal new relationships. There is a distinct difference from theoretical sampling in the “anomalies” approach. Such a sampling strategy aims to choose a case that is a demonstration of the failure of the theory. In “gaps and holes” sampling is highly focused on the purpose of the case study. Extreme and unusual cases have other purposes compared to common cases or revelatory cases. A single case may be chosen to investigate deeply into new phenomena. A multiple case study may serve a replication logic by which the findings have relevance beyond the cases under investigation. In “social construction of reality”, the sampling is purposeful as well, but for different reasons. Either the case is of interest per se or the case represents a good opportunity to understand a theoretical issue.

Although qualitative data are preferred in all of the designs, quantitative data are seen as a possible opportunity to strengthen cases by such data. Nevertheless, in “social construction of reality”, there is a strong emphasis on thick descriptions and a holistic understanding of the case. This is in contrast to a more construct- and variable- oriented collection of data in “no theory first” and “gaps and holes”. In addition, in contrast to that, the “anomaly” approach is the only design that receives data from dialogue between observer and participants and participant observation.

Finally, data analysis lies within a wide range. In “no theory first”, the research process is finalized by inspecting the emerging constructs within the case or across cases. Based on a priory constructs, systematic comparisons reveal patterns and relationships resulting in a tentative theory. On the contrary, in “gaps and holes”, a tentative theory exists. The final analysis concentrates on the matching of the framework or propositions with patterns from the data. While both of these approaches condense data, the approach of “social construction of reality” ends the research process with thick descriptions of the case to learn from the case or with categorical comparisons. In the “anomaly” approach, the data analysis is aggregation of data, but these aggregated data are related to its external field and their pressures and influences by structuration to reconstruct the theory.

As a result, it is unlikely that the specified case study designs contribute to theory in a homogeneous manner. This result will be discussed in light of the question regarding how these case study designs can inform theory at several points of a continuum of theory. This analysis will be outlined in the following sections. In a first step, I review the main elements of a theory continuum. In a second step, I discuss the respective contribution of the previously identified case study research designs to the theory continuum.

3 Elements of a theory continuum

What a theory is and what a theory is not is a classic debate (Sutton and Staw 1995 ; Weick 1995 ). Often, theories are described in terms of understanding relationships between phenomena which have not been or were not well understood before (Chiles 2003 ; Edmondson and McManus 2007 ; Shah and Corley 2006 ), but there is no overall acceptance as to what constitutes a theory. Theory can be seen as a final product or as a continuum, and there is an ongoing effort to define different stages of this continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). In the following section, basic elements of the theory and the construction of the theory continuum are outlined.

3.1 Basic elements of a theory

Most of the debate concerning what a theory is comprises three basic elements (Alvesson and Kärreman 2007 ; Bacharach 1989 ; Dubin 1978 ; Kaplan 1998 ; Suddaby 2010 ; Weick 1989 , 1995 ; Whetten 1989 ). A theory comprises components (concepts and constructs), used to identify the necessary elements of the phenomenon under investigation. The second is relationships between components (concepts and constructs), explaining the how and whys underlying the relationship. Third, temporal and contextual boundaries limit the generalizability of the theory. As a result, definitions of theory emphasize these components, relationships, and boundaries:

“It is a collection of assertions, both verbal and symbolic, that identifies what variables are important for what reasons, specifies how they are interrelated and why, and identifies the conditions under which they should be related or not related” (Campbell 1990 : 65).

“… a system of constructs and variables in which the constructs are related to each other by propositions and the variables are related to each other by hypotheses” (Bacharach 1989 : 498).

“Theory is about the connections among phenomena, a story about why acts, events, structure, and thoughts occur. Theory emphasizes the nature of causal relationships, identifying what comes first as well as the timing of such events” (Sutton and Staw 1995 : 378).

“… theory is a statement of concepts and their interrelationships that shows how and/or why a phenomenon occurs” (Corley and Gioia 2011 : 12).

The terms “constructs” and “concepts” are either used interchangeably or with different meanings. Positivists use “constructs” as a lens for the observation of a phenomenon (Suddaby 2010 ). Such constructs have to be operationalized and measured. Non-positivists often use the term “concept” as a more value neutral term in place of the term construct (Gioia et al. 2013 ; Suddaby 2010 : 354). Non-positivists aim at developing concepts on the basis of data that contain richness and complexity of the observed phenomenon instead of narrow definitions and operationalizations of constructs. Gioia et al. ( 2013 : 16) clarify the demarcation line between constructs and concepts as follows: “By ‘concept,’ we mean a more general, less well-specified notion capturing qualities that describe or explain a phenomenon of theoretical interest. Put simply, in our way of thinking, concepts are precursors to constructs in making sense of organizational worlds—whether as practitioners living in those worlds, researchers trying to investigate them, or theorists working to model them”.

In sum, theories are a systematic combination of components and their relationships within boundaries. The use of the terms constructs and concepts is related to different philosophical assumptions reflected in different types of case study designs.

3.2 Theory continuum

Weick ( 1995 ) makes an important point that theory is more a continuum than a product. In his view, theorizing is a process containing assumptions, accepted principles, and rules of procedures to explain or predict the behavior of a specified set of phenomena. In similar vein, Gilbert and Christensen ( 2005 ) demonstrate the process character of theory. In their view, a first step of theory building is a careful description of the phenomena. Having already observed and described the phenomena, researchers then classify the phenomena into similar categories. In this phase a framework defines categories and relationships amongst phenomena. In the third phase, researchers build theories to understand (causal) relationships, and in this phase, a model or theory asserts what factors drive the phenomena and under what circumstances. The categorization scheme enables the researchers to predict what they will observe. The “test” offers a confirmation under which circumstances the theory is useful. The early drafts of a theory may be vague in terms of the number and adequateness of factors and their relationships. At the end of the continuum, there may be more precise variables and predicted relationships. These theories have to be extended by boundaries considering time and space.

Across that continuum, different research strategies have various strengths. Several classifications in the literature intend to match research strategies to the different phases of a theory continuum (Andersen and Kragh 2010 ; Colquitt and Zapata-Phelan 2007 ; Edmondson and McManus 2007 ; Snow 2004 ; Swedberg 2012 ). These classifications, although there are differences in terms, comprise three phases with distinguishable characteristics.

3.2.1 Building theory

Here, the careful description of the phenomena is the starting point of theorizing. For example, Snow ( 2004 ) puts this phase as theory discovery, where analytic understandings are generated by means of detailed examination of data. Edmondson and McManus ( 2007 ) state the starting phase of a theory as nascent theory providing answers to new questions revealing new connections among phenomena. Therefore, research questions are open and researchers avoid hypotheses predicting relationships between variables. Swedberg ( 2012 ) highlights the necessity of observation and extensive involvement with the phenomenon at the early stage of theory-building. It is an attempt to understand something of interest by observing and interpreting social facts. Creativity and inspiration are necessary conditions to put observations into concepts and outline a tentative theory.

3.2.2 Developing theory

This tentative theory exists in the second phase of the continuum and has to be developed. Several possibilities exist. In theory extension, the preexisting constructs are extended to other groups or other contexts. In theoretical refinement, a modification of existing theoretical perspectives is conducted (Edmondson and McManus ( 2007 ). New antecedents, moderators, mediators, and outcomes are investigated, enhancing the explanation power of the tentative theory.

3.2.3 Test of theories

Constructs and relationships are well developed to a mature state; measures are precise and operationalized. Such theories are empirically tested with elaborate methods, and research questions are more precise. In the quantitative realm, testing of hypotheses is conducted and statistical analysis is the usual methodological foundation. Recently, researchers criticize that testing theories has become the major focus of scientists today (Delbridge and Fiss 2013 ); testing theories does not only happen to mature theory but to intermediate theory as well. The boundary between theory development and theory testing is not always so clear. While theory development is adding new components to a theory and elaborating the measures, testing a theory implies precise measures, variables, and predicted relationships considering time and space (Gilbert and Christensen ( 2005 ). It will be of interest whether case studies are eligible to test theories as well.

To summarize: there is a conversation as to where on a continuum of theory development, various methods are required to target different contributions to theory (methodological fit). In this discussion, case study research designs have been discussed as a homogeneous set that mostly contributes to theory-building in an exploratory manner. Hence, what is missing is a more differentiated analysis of how case study methodology fits into this conversation, particularly how case study research methodologically fits theory development and theory testing beyond its widely assumed explorative role. In the following section, the above types of case study research designs will be discussed with regard to their positions across the theory continuum.

This distinction adds to existing literature by demonstrating that case study research does not only contribute to theory-building, but also to the development of tentative theories and to the testing of theories. This distinction leads to the next question: is there any interplay between case study research designs and their contributions to the theory continuum? This paper aims at reconciling this interplay with regard to case study design by mirroring phases of a theory continuum with specific types of case study research designs as outlined above. The importance of the interplay between theory and method lies in the capacity to generate and shape theory, while theory can generate and shape method. “In this long march, theory and method surely matter, for they are the tools with which we build both our representations and understandings of organizational life and our reputations” (van Maanen et al. 2007 : 1145). Theory is not the same as methods, but a relationship of this interplay can broaden or restrict both parts of the equation (Swedberg 2012 : 7).

In the following, I discuss how the above-delineated case study research designs unfold their capacities and contribute differently to the theory continuum to build, develop, and test theory.

4 Discussion of the contribution of case study research to a theory continuum

Case study research is diverse with distinct contributions to the continuum of theory. The following table provides the main differences in terms of contributions to theory and specifically locates the case study research designs on the theory continuum (Table  2 ).

In the following, I outline how these specific contributions of case study designs provide better opportunities to enhance the rigor of building theory, developing theory, testing, and reconstructing theory.

4.1 Building theory

In building theory, the phenomenon is new or not understood so far. There is no theory which explains the phenomenon. At the very beginning of the theory continuum, there is curiosity in the phenomenon itself. I focus on the intrinsic case study design which is located in the social construction of reality approach on the very early phase of the theory continuum, as intrinsic case study research design is not theory-building per se but curiosity in the case itself. It is not the purpose of the intrinsic case study to identify abstract concepts and relationships; the specific research strategy lies in the observation and description of a case and the primary method is observation, enabling understanding from personal and vicarious experience. This meets long lasting complaints concerning the lack of (new) theory in management and organization research and signals that the gap between research and management practice is growing. It is argued that the complexity of the reality is not adequately captured (Suddaby et al. 2011 ). It is claimed that management and organization research systematically neglect the dialogue with practice and, as a result, miss new trends or recognize important trends with delay (Corley and Gioia 2011 ).

The specific case study research design’s contribution to theory is in building concrete, context-dependent knowledge with regard to the identification of new phenomena and trends. Openness with regard to the new phenomena, avoiding theoretical preconceptions but building insights out of data, enables the elaboration of meanings and the construction of realities in intrinsic case studies. Intrinsic case studies will enhance the understanding by researcher and reader concerning new phenomena.

The “No Theory First” case study research design is a classic and often cited candidate for building theory. As the phenomenon is new and in the absence of a theory, qualitative data are inspected for aggregation and interpretation. In instrumental case study design, a number of cases will increase the understanding and support building theories by description, aggregation, and interpretation (Stake 2000 ). New themes and concepts are revealed by case descriptions, interviews, documents, and observations, and the analysis of the data enables the specific contribution of the case study design through a constructivist perspective in theory-building.

Although the design by Eisenhardt ( 1989 ) stems from other philosophical assumptions and there are variations and developments in this design, there is still an overwhelming tendency to quote and to stick to her research strategy which aims developing new constructs and new relationships out of real-life cases. Data are collected mainly by interviews, documents, and observations. From within-site analysis and cross-case analysis, themes, concepts, and relationships emerge. Shaping hypotheses comprises: “… refining the definition of the construct and (…) building evidence which measures the construct in each case” (Eisenhardt 1989 : 541). Having identified the emerged constructs, the emergent relationships between constructs are verified in each case. The underlying logic is validation by replication. Cases are treated as experiments in which the hypotheses are replicated case by case. In replication logic cases that confirm the emergent relationships enhance confidence in the validity of the relationships. Disconfirmation of the relationships leads to refinement of the theory. This is similar to Yin’s replication logic, but targets the precision and measurement of constructs and the emerging relationships with regard to the emerging theory. The building of a theory concludes in an understanding of the dynamics underlying the relationship; the primary theoretical reasons for why the relationships exist (Huy 2012 ). Finally, a visual theory with “boxes and arrows” (Eisenhardt and Graebner 2007 ) may visually demonstrate the emerged theory. The theory-building process is finalized by iterating case data, emerging theory, and extant literature.

The “No Theory First” and “Social Construction of Reality” case study research designs, although they represent different philosophical assumptions, adequately fit the theory-building phase concerning new phenomena. The main contribution of case study designs in this phase of the theory continuum lies in the generation of tentative theories.

Case studies at this point of the theory continuum, therefore, have to demonstrate: why the phenomenon is new or of interest; that no previous theory that explains the phenomenon exists; how and why detailed descriptions enhance the understanding of the phenomenon; and how and why new concepts (constructs) and new relationships will enhance our understanding of the phenomenon.

As a result, it has to be demonstrated that the research strategy is in sync with an investigation of a new phenomenon, building a tentative theory.

4.2 Developing theory

In the “Gaps and Holes” case study research design, the phenomenon is partially understood. There is a tentative theory and the research strategy is theory driven. Compared to the theory-building phase, the existence and not the development of propositions differentiate this design along the continuum. The prediction comes first, out of an existing theory. The research strategy and the data have to be confronted by pattern-matching. Pattern-matching is a means to compare the theoretically based predictions with the data in the site: “For case study analysis, one of the most preferred techniques is to use a pattern-matching logic. Such a logic (…) compares an empirically based pattern–that is, one based on the findings from your case study–with a predicted one made before you collected your data (….)” (Yin 2014 : 143). The comparison of propositions and the rich case material is the ground for new elements or relationships within the tentative theory.

Such findings aim to enhance the scientific usefulness of the theory (Corley and Gioia 2011 ). To enhance the validity of the new elements or relationships of the tentative theory, literal replication is a means to confirm the new findings. By that, the theory is developed by new antecedents, moderators, mediators, or outcomes. This modification or extension of the theory contributes to the analytical generalization of the theory.

If new cases provide similar results, the search for regularities is based on more solid ground. Therefore, the strength of case study research in “Gaps and Holes” lies in search for mechanisms in their specific context which can reveal causes and effects more precisely.

The “Gaps and Holes” case study research design is an adequate candidate for this phase of the theory continuum. Case studies at this point of the theory continuum, therefore, have to outline the tentative theory; to demonstrate the lacks and gaps of the tentative theory; to specify how and why the tentative theory is aimed to be extended and/or modified; to develop theoretically based propositions which guide the investigation; and to evaluate new elements, relationships, and mechanisms related to the previous theory (analytical generalization).

As a result and compared to theory-building, a different research strategy exists. While in theory building the research strategy is based on the eliciting of concepts (constructs) and relationships out of data, in theory development, it has to be demonstrated that the research strategy aims to identify new elements and relationships within a tentative theory, identifying mechanisms which explain the phenomenon more precisely.

4.3 Test of theory

In “Gaps and Holes” and “Anomalies”, an extended theory exists. The phenomenon is understood. There is no search for additional components or relationships. Mechanisms seem to explain the functioning or processes of the phenomenon. The research strategy is focused on testing whether the theory holds under different circumstances or under different conditions. Such a test of theories is mainly the domain of experimental and quantitative studies. It is based on previously developed constructs and variables which are the foundation for stating specific testable hypotheses and testing the relations on the basis of quantitative data sets. As a result, highly sophisticated statistical tools enable falsification of the theory. Therefore, testing theory in “Gaps and Holes” is restricted on specific events.

Single case can serve as a test. There is a debate in case study research whether the test of theories is related to the falsification logic of Karl Popper (Flyvbjerg 2006 ; Tsang 2013 ). Another stream of the debate is related to theoretical generalizability (Hillebrand et al. 2001 ; Welch et al. 2011 ). More specifically, test in” Gaps and Holes” is analogous to a single experiment if a single case represents a critical case. If the theory has specified a clear set of propositions and defines the exact conditions within which the theory might explain the phenomena under investigation, a single case study, testing the theory, can confirm or challenge the theory. In sum Yin states: “Overall, the single-case design is eminently justifiable under certain conditions—where the case represents (a) a critical test of existing theory, …” (Yin 2014 : 56). In their survey in the field of International Business, Welch et al. conclude: “In addition, the widespread assumption that the role of the case study lies only in the exploratory, theory-building phase of research downplays its potential to propose causal mechanisms and linkages, and test existing theories” (Welch et al. 2011 : 755).

In multiple case studies, a theoretical replication is a test of theory by comparing the findings with new cases. If a series of cases have revealed pattern-matching between propositions and the data, theoretical replication can be revealed by new waves of cases with contrasting propositions. If the contrasting propositions reveal contrasting results, the findings of the first wave are confirmed. Several possibilities exist to test the initial findings of multiple case studies using different lenses from inside and outside the management realm (Corley and Gioia 2011 ; LePine and Wilcox-King 2010 ; Okhuysen and Bonardi 2011 ; Zahra and Newey 2009 ), but have not become a standard in case study research.

In rival explanations, rival theoretical propositions are developed as a test of the previous theory. This can be distinguished from theoretical replication where contrasting propositions aim to confirm the initial findings. This can, as well, be distinguished from developing theory where rival explanations might develop theory by the elimination of possible influences (interventions, implementations). The rich data enable one to identify internal and external interventions that might be responsible for the findings. Alternative explanations in a new series of cases enable to test, whether a theory “different from the original theory explains the results better (…)” (Yin 2014 : 141).

As a result, it astonishes that theoretical replication and rival explanations, being one of the strengths of case study research, are rarely used. Although the general debate about “lenses” has informed the discussion about theory contributions, this paper demonstrates that there is a wide range of possible integration of vertical or horizontal lenses in case study research design. Case study research designs aiming to test theories have to outline modes of replication and the elimination of rival explanations.

The “anomaly approach” is placed in the final phase of the theory testing, as well. In this approach, a theory exists, but the theory fails to explain anomalies. Burawoy goes a step further. While Yin ( 2014 ) sees a critical case as a test that challenges or contradicts a well formulated theory, in Burawoy’s approach, in contrast to falsification logic (Popper 2002 ), the theory is not rejected but reconstructed. Burawoy relates extended case study design to society and history. Existing theory is challenged by intervention into the social field. Identifying processes of historical roots and social circumstances and considering external forces by structuration lead to the reconstruction of the theory.

It is surprising that this design has been neglected so far in management research. Is there no need to reflect social tensions and distortions in management research? While case study research has, per definition, to investigate phenomena in its natural environment, it is hard to understand why this design has widely been ignored in management and organization research. As a result, testing theory in case study research has to demonstrate that an extended theory exists; a critical case or an anomaly can challenge the theory; theoretical replication and rival explanations will be means to contradict or confirm the theory; and societal circumstances and external forces explain the anomaly.

Compared to theory-building (new concepts/constructs and relationships out of data) and theory development (new elements and relationships within a tentative theory), testing theory challenges extended theory by empirical investigations into failures and anomalies that the current theory cannot explain.

5 Conclusion

Case studies provide a better understanding of phenomena regarding concrete context-dependent knowledge (Andersen and Kragh 2010 ; Flyvbjerg 2006 : 224), but as literature reviews indicate, there is still confusion regarding the adequate utilization of case study methodology (Welch et al. 2011 ). This can be interpreted in a way that authors and even reviewers are not always aware of the methodological fit in case study research. Case study research is mainly narrowed to its “explorative” function, neglecting the scope of possibilities that case study research provides. The claim for more homogeneity of specified rules in case study research misses the important aspect that a method is not a means in itself, but aims at providing improved theories (van Maanen et al. 2007 ). This paper contributes to the fit of case study research designs and the theory continuum regarding the following issues.

5.1 Heterogeneity of case study designs

Although case study research, overall, has similar characteristics, it incorporates various case study research designs that have heterogeneous theoretical goals and use various elements to reach these goals. The analysis revealed that the classical understanding, whereby case study research is adequate for the “exploration” of a theory and quantitative research is adequate for “testing” theory, is oversimplified. Therefore, the theoretical goals of case study research have to be outlined precisely. This study demonstrates that there is variety of case study research designs that have thus far been largely neglected. Case study researchers can utilize the entire spectrum, but have to consider how the phenomenon is related to the theory continuum.

Case study researchers have to demonstrate how they describe new or surprising phenomena, develop new constructs and relationships, add constructs (variables), antecedents, outcomes, moderators, or mediators to a tentative theory, challenge a theory by a critical case, theoretical replication or discarding rival explanations, and reconstruct a theory by tracking failures and anomalies to external circumstances.

5.2 Methodological fit

The rigor of the case study can be enhanced by considering the specific contribution of various case study research designs in each phase of the theory continuum. This paper provides a portfolio of case study research designs that enables researchers and reviewers to evaluate whether the case study arsenal has been adequately located:

At an early phase of the theory continuum, case studies have their strengths in rich descriptions and investigations into new or surprising empirical phenomena and trends. Researchers and readers can benefit from such rich descriptions in understanding and analyzing these phenomena.

Next, on the theory continuum, there is the well-known contribution of case study research in building tentative theory by eliciting constructs or concepts and their relationships out of data.

Third, development of theories is strongly related to literal replication. Strict comparisons, on the one hand, and controlled theoretical advancement, on the other hand, enable the identification of mechanisms, strengthen the notions of causality, and provide generalizable statements.

Fourth, there are specific circumstances under which case study approaches enable one to test theories. This is to confront the theory with a critical case, to test findings of pattern-matching by theoretical replication and discarding rival explanations. Therefore, “Gaps and Holes” provide the opportunity for developing and testing theories through case study design on the theory continuum.

Finally, testing and contradicting theory are not the final rejection of a theory, but is the basis for reconstructing theory by means of case study design. Anomalies can be traced to historical sources, social processes, and external forces.

This paper demonstrates that the precise interplay of case study research designs and theory contributions on the theory continuum is a prerequisite for the contribution of case study research to better theories. If case study research design is differentiated from qualitative research, the intended contribution to theory is stated and designs that fit the aimed contribution to theory are outlined and substantiated; this will critically enhance the rigor of case study research.

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Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice.  Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences. 

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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Case Study vs. Single-Case Experimental Designs

What's the difference.

Case study and single-case experimental designs are both research methods used in psychology and other social sciences to investigate individual cases or subjects. However, they differ in their approach and purpose. Case studies involve in-depth examination of a single case, such as an individual, group, or organization, to gain a comprehensive understanding of the phenomenon being studied. On the other hand, single-case experimental designs focus on studying the effects of an intervention or treatment on a single subject over time. These designs use repeated measures and control conditions to establish cause-and-effect relationships. While case studies provide rich qualitative data, single-case experimental designs offer more rigorous experimental control and allow for the evaluation of treatment effectiveness.

Further Detail

Introduction.

When conducting research in various fields, it is essential to choose the appropriate study design to answer research questions effectively. Two commonly used designs are case study and single-case experimental designs. While both approaches aim to provide valuable insights into specific phenomena, they differ in several key attributes. This article will compare and contrast the attributes of case study and single-case experimental designs, highlighting their strengths and limitations.

Definition and Purpose

A case study is an in-depth investigation of a particular individual, group, or event. It involves collecting and analyzing qualitative or quantitative data to gain a comprehensive understanding of the subject under study. Case studies are often used to explore complex phenomena, generate hypotheses, or provide detailed descriptions of unique cases.

On the other hand, single-case experimental designs are a type of research design that focuses on studying a single individual or a small group over time. These designs involve manipulating an independent variable and measuring its effects on a dependent variable. Single-case experimental designs are particularly useful for examining cause-and-effect relationships and evaluating the effectiveness of interventions or treatments.

Data Collection and Analysis

In terms of data collection, case studies rely on various sources such as interviews, observations, documents, and artifacts. Researchers often employ multiple methods to gather rich and diverse data, allowing for a comprehensive analysis of the case. The data collected in case studies are typically qualitative in nature, although quantitative data may also be included.

In contrast, single-case experimental designs primarily rely on quantitative data collection methods. Researchers use standardized measures and instruments to collect data on the dependent variable before, during, and after the manipulation of the independent variable. This allows for a systematic analysis of the effects of the intervention or treatment on the individual or group being studied.

Generalizability

One of the key differences between case studies and single-case experimental designs is their generalizability. Case studies are often conducted on unique or rare cases, making it challenging to generalize the findings to a larger population. The focus of case studies is on providing detailed insights into specific cases rather than making broad generalizations.

On the other hand, single-case experimental designs aim to establish causal relationships and can provide evidence for generalizability. By systematically manipulating the independent variable and measuring its effects on the dependent variable, researchers can draw conclusions about the effectiveness of interventions or treatments that may be applicable to similar cases or populations.

Internal Validity

Internal validity refers to the extent to which a study accurately measures the cause-and-effect relationship between variables. In case studies, establishing internal validity can be challenging due to the lack of control over extraneous variables. The presence of multiple data sources and the potential for subjective interpretation may also introduce bias.

In contrast, single-case experimental designs prioritize internal validity by employing rigorous control over extraneous variables. Researchers carefully design the intervention or treatment, implement it consistently, and measure the dependent variable under controlled conditions. This allows for a more confident determination of the causal relationship between the independent and dependent variables.

Time and Resources

Case studies often require significant time and resources due to their in-depth nature. Researchers need to spend considerable time collecting and analyzing data from various sources, conducting interviews, and immersing themselves in the case. Additionally, case studies may involve multiple researchers or a research team, further increasing the required resources.

On the other hand, single-case experimental designs can be more time and resource-efficient. Since they focus on a single individual or a small group, data collection and analysis can be more streamlined. Researchers can also implement interventions or treatments in a controlled manner, reducing the time and resources needed for data collection.

Ethical Considerations

Both case studies and single-case experimental designs require researchers to consider ethical implications. In case studies, researchers must ensure the privacy and confidentiality of the individuals or groups being studied. Informed consent and ethical guidelines for data collection and analysis should be followed to protect the rights and well-being of the participants.

Similarly, in single-case experimental designs, researchers must consider ethical considerations when implementing interventions or treatments. The well-being and safety of the individual or group being studied should be prioritized, and informed consent should be obtained. Additionally, researchers should carefully monitor and evaluate the potential risks and benefits associated with the intervention or treatment.

Case studies and single-case experimental designs are valuable research approaches that offer unique insights into specific phenomena. While case studies provide in-depth descriptions and exploratory analyses of individual cases, single-case experimental designs focus on establishing causal relationships and evaluating interventions or treatments. Researchers should carefully consider the attributes and goals of their study when choosing between these two designs, ensuring that the selected approach aligns with their research questions and objectives.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

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Single case studies vs. multiple case studies: A comparative study

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Single case studies vs. multiple case studies: A comparative study

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... Further, single-case design has been considered beneficial as it allows deeper understanding of the phenomenon under study (Gustafsson 2017) and is particularly useful when examining a complex and content-specific topic (Halinen and Törnroos 2005). ...

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"Single case studies vs. multiple ca..." refers background or methods in this paper

... A difference between a single case study and a multiple case study is that in the last mentioned, the researcher are studying multiple cases to understand the differences and the similarities between the cases (Baxter & Jack, 2008; Stake, 1995). ...

... Merriam (2009), Mayer (2001) and Stake (1995) mean that the case study research is seen as a flexible method. ...

... A vision for the researcher is that the readers can understand the findings so well that they can implement the study in their own situation (Stake, 1995). ...

... Further, qualitative case study research is a flexible method (Merriam, 2009; Mayer, 2001, Stake, 1995) and presented qualitative case study methodologies are formed by study design, epitome and selection of methods. ...

... Merriam (2009), Mayer (2001) and Stake (1995) mean that the case study research is seen as a flexible method. Further, to write a good case study, Wells (2004) mean that the paper should have a chronicle composition that leads from one finding to another and therefore cannot be randomly. ...

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... Case studies often look different in the published literature but the composition should be identified during the design of the case study according to Yin (2009). Table 1 represent ten single cases and Table 2 represent ten multiple cases. ...

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Complex PTSD symptom clusters and executive function in UK Armed Forces veterans: a cross-sectional study

• Natasha Biscoe   ORCID: orcid.org/0000-0003-3471-6472 1 ,
• Emma New 2 &
• Dominic Murphy   ORCID: orcid.org/0000-0002-9530-2743 1 , 3  

BMC Psychology volume  12 , Article number:  209 ( 2024 ) Cite this article

Metrics details

Less is known about complex posttraumatic stress disorder (CPTSD) than postrraumatic stress disorder (PTSD) in military veterans, yet this population may be at greater risk of the former diagnosis. Executive function impairment has been linked to PTSD treatment outcomes. The current study therefore aimed to explore possible associations between each CPTSD symptom cluster and executive function to understand if similar treatment trajectories might be observed with the disorder.

A total of 428 veterans from a national charity responded to a self-report questionnaire which measured CPTSD symptom clusters using the International Trauma Questionnaire, and executive function using the Adult Executive Function Inventory. Single and multiple linear regression models were used to analyse the relationship between CPTSD symptom clusters and executive function, including working memory and inhibition.

Each CPTSD symptom cluster was significantly associated with higher executive function impairment, even after controlling for possible mental health confounding variables. Emotion dysregulation was the CPTSD symptom cluster most strongly associated with executive function impairment.

Conclusions

This is the first study to explore the relationship between executive function and CPTSD symptom clusters. The study builds on previous findings and suggests that executive function could be relevant to CPTSD treatment trajectories, as is the case with PTSD alone. Future research should further explore such clinical implications.

Peer Review reports

Military veterans face a greater risk of experiencing PTSD than the general UK population [ 1 ] and are more likely to meet criteria for Complex PTSD (CPTSD) than PTSD [ 2 ]. PTSD encompasses a set of symptoms which may be experienced following a traumatic event, including hyperarousal, re-experiencing (nightmares, intrusions), cognitive and behavioural avoidance and negative alterations in mood (DSM-V; [ 3 ]). CPTSD was added to the International Classification of Diseases in 2011 [ 4 ] as a distinct disorder. A diagnosis of CPTSD includes experiencing clusters of symptoms that encompass PTSD, as well as symptom clusters referred to as Disturbances in Self-Organisation (DSO), which are: emotion dysregulation, interpersonal difficulties, and negative self-concept, as well as functional impairment connected to both PTSD and DSO symptoms.

CPTSD has been linked with sustained and multiple traumas [ 5 ] as well as interpersonal trauma [ 6 ]. Military veterans appear to be at greater risk of CPTSD than PTSD [ 7 ]. Indeed, CPTSD appears to be more prevalent in UK treatment-seeking veterans than PTSD (with 80% meeting criteria for CPTSD compared to 20% for PTSD; [ 2 , 8 ]. Additionally, proportionally higher treatment dropout rates are reported for veterans with CPTSD [ 9 ]. It is therefore clinically important to understand factors which may be relevant to both PTSD and CPTSD, as interventions may need to be tailored to each disorder respectively.

PTSD and executive function

An association between impairments in executive function (EF), and posttraumatic stress disorder (PTSD) is well-established in the literature (for review see: [ 10 , 11 , 12 ]). EFs are a collection of abilities grouped together for their relevance to planning and executing complex, goal-directed behaviour [ 13 , 14 , 15 ]. There is significant variation in both definitions of the concept and how the construct is operationalised, although the current study follows Miyake and colleagues [ 16 ] as this conceptualisation aligns well with the self-report measure of executive function used in this study. These authors identify cognitive flexibility, working memory and inhibition as core EFs, deficits in all of which may be relevant to PTSD [ 17 , 18 , 19 , 20 , 21 ]. Furthermore, one study has reported that greater inhibitory control is associated with a better improvement in PTSD symptoms following psychological treatment, indicating the possible relevance of EF in PTSD recovery trajectories [ 22 ]. Less is known about whether similar trajectories would be observed in those with CPTSD. However, insight may be drawn from neurocognitive explanations of the observed associations between EF and PTSD.

Neurocognitive models of PTSD and EF

Several meta-analyses of lesion and neuroimaging studies implicate the prefrontal cortex (PFC) as key in supporting EF [ 23 , 24 , 25 ]. The PFC has been theorised as a control centre, mediating between sensory inputs and behavioural outputs via regulation of brain systems central to emotion processing such as the amygdala [ 26 ]. The PFC is also structurally associated with PTSD, as well as the amygdala, hippocampus, and cingulate cortex [ 27 ], with this system key to attaching emotional valence to memories relevant to the fear-based experiences that lead to PTSD [ 19 ].

The shared relevance of these brain systems to both EF and PTSD suggests a neurocognitive explanation for the overlap observed between the two constructs. For example, one neurocognitive model of PTSD posits that PFC (and associated deficits in EF) may be ineffectively regulating hyperarousal of the amygdala in individuals with PTSD when a perceive threat is observed in a safe environment [ 28 , 29 , 30 ]. Furthermore, elevated arousal – a symptom of PTSD – may deplete cognitive resources leading to deficits in EF as attention is focused instead on regulating hyperarousal [ 20 , 31 , 32 , 33 ].

EFs and CPTSD

Neuroimaging studies reinforce this theory and suggest functional connectivity between the PFC and brain regions relevant to emotion regulation are key to supporting EF [ 34 , 35 ]. Emotion dysregulation therefore may be pertinent to the observed overlap between PTSD and EF. Given emotion dysregulation is a DSO symptom of CPTSD, exploring associations between CPTSD and EFs could inform understanding of the disorder and how existing PTSD interventions could be tailored to improve treatment response in veterans seeking treatment for CPTSD. In a study using an adolescent sample, deficits in EFs were associated with greater CPTSD severity [ 36 ]. However, less is known about the relationship between CPTSD and EFs in veteran populations.

The current study

Given the potential relevance of EF to PTSD treatment outcomes in veterans, and the need to further understand CPTSD in this population, the current study explores the relationship between both PTSD and CPTSD and a self-report measure of EF (inhibition and working memory) in a clinical sample of UK veterans. Associations between each PTSD symptom cluster and EFs are separately investigated, including the DSO clusters that encompass CPTSD. In line with previous studies [ 36 ], it is hypothesised that lower executive functioning scores (both working memory and inhibition) will be associated with greater severity of CPTSD symptoms.

This study was approved by [blinded for review].

Participants

Of the veterans seeking treatment UK charity, a 20% random sample was selected to assess whether they met study inclusion criteria: (1) having a valid email address; (2) having provided consent to contact from the research team about studies; (3) had attended one or more appointments (classed as treatment-seeking). In total 989 veterans were emailed with the study link, to which 428/989 responded (43.3% response rate; M age =50.4, SD age =10.9). Participation was voluntary. No differences were found between those who returned completed questionnaires and non-responders [ 2 ]. We determined this by analysing predictors of returning a completed survey, including age, sex and service branch.

Eligible and consenting veterans were emailed the link to a self-report questionnaire hosted on Survey Monkey, which included demographic questions and the measures described below. Responses were collected between August and October 2020 and participants were emailed not more than five times. The questionnaire took approximately 20 min to complete. Full study procedure has been described previously [ 2 ].

The Adult Executive Function Inventory (ADEXI; [ 37 ]), measures EF on a 14-item self-report scale, with responses on a five-point Likert scale ranging from zero (definitely not true) to four (definitely true). Items 1, 2, 5, 7, 8, 9, 11, 12 and 13 comprise the working memory subscale, e.g.: “I have difficulty remembering lengthy instructions” and “when someone asks me to do several things, I sometimes only remember the first or last”. The remaining items make up the inhibition subscale, e.g.: “I have a tendency to do things without first thinking about what could happen” and “I sometimes have difficulty stopping myself from doing something that I like even though someone tells me that it is not allowed”. A higher score on the scale or each of the subscales indicates greater impairment. The ADEXI has good internal consistency and test-retest reliability, but poor convergent validity with neuropsychological tests of EF [ 37 ]. The ADEXI has good internal consistency (α = 0.68–0.72; [ 37 ]).

Symptoms of PTSD and CPTSD were measured using the International Trauma Questionnaire [ 38 ], an 18-item scale with responses on a 5-point Likert scale ranging from zero (not at all) to four (extremely). Two items measure each of the three PTSD symptom clusters: hyperarousal, re-experiencing and avoidance. Two items measure each of the three disturbances in self-organisation (DSO) symptom clusters that comprise CPTSD: negative self-concept, interpersonal relationships and affect dysregulation. Three identical items then measure functional impairment related to the PTSD and DSO symptom clusters respectively. The ITQ has strong psychometric properties [ 39 ]. Possible caseness for PTSD is indicated by a score of two or higher on at least one of each item measuring each PTSD symptom cluster, as well scoring two or higher on one of the three functional impairment items relating to PTSD symptom clusters. Possible caseness for CPTSD is indicated by meeting the criteria for PTSD, as well as scoring two or higher on at least one of the two items for each DSO symptom cluster, and at least a two on one of the functional impairment items relating to DSO symptoms. The ITQ has good internal consistency (α = 0.90; [ 39 ]).

Symptoms of generalised anxiety and depression were measured with the General Health Questionnaire (GHQ-12; [ 40 ]), a 12-item scale where a score of four or higher is indicative of potential caseness for common mental health difficulties (CMDs). The GHQ-9 has good internal consistency (α = 0.72; [ 41 ]).

Somatic symptoms were measured using the Patient Health Questionnaire (PHQ-15; [ 41 ]), a 15-item scale where a score above 15 indicates higher severity of somatic symptoms. The PHQ-15 has good internal consistency (α = 0.80; [ 42 ]).

Symptoms of poor sleep quality were measured using the Sleep Condition Indicator (SCI; [ 43 ]), an eight-item scale where a score below 16 is indicative of a potential insomnia disorder. The SCI has good internal consistency (α = 0.86; [ 44 ]).

Symptoms of difficulties with anger were measured using the Dimensions of Anger Reactions (DAR-5; [ 45 ]), a five-item scale where a score higher than 12 is indicative of possible anger difficulties. The DAR-5 has good internal consistency (α = 0.89–0.90; [ 46 ]).

Symptoms of alcohol misuse were measured using the Alcohol Use Disorders Identification Test (AUDIT; [ 47 ]), a 10-item scale where scores higher than eight and 16 respectively are classified as possible hazardous and harmful alcohol use. The AUDIT has good internal consistency (α = 0.60–0.80; [ 48 ]).

Data analysis

Data were prepared in STATA 13.0 and analysed in SPSS v.26. Continuous variables were ADEXI scores and subscale scores. These were averaged so that comparisons could be made across scores calculated from different numbers of items. All other variables were categorical, divided into case and no case or high severity and lower severity for each health outcome, and no PTSD, PTSD, and CPTSD for the ITQ variable. To understand the relationship between mental health variables, including PTSD and EF, single linear regression models were used with demographic and mental health caseness variables as predictors, and ADEXI and inhibition and working memory subscale scores as outcome variables in separate analyses. This was to understand possible confounding variables for any relationship between PTSD and CPTSD with EF. Multiple linear regression models were then used with PTSD and CPTSD caseness as predictor variables, and ADEXI score, and subscale scores as outcome variables. Those variables which were significant in the single linear regression models were included in the multiple regression models to adjust for possible confounding factors. Single linear regression models explored the relationships between individual PTSD and DSO symptom clusters with EF. ‘Caseness’ for each symptom cluster was calculated as a score of two or higher on at least one of the two items measuring each cluster. The sample met assumptions for multiple linear regression: the data were normally distributed (W = 0.96, p  = 0.23), there was low multicollinearity and there is a linear relationship between the variables used in the regression models. As described in [ 2 ], analyses were restricted to responders only and missing data were not included in the models due to the assumption that data were missing at random. A power analysis was not conducted for the present study as the analysis was exploratory and data were collected through convenience sampling [ 49 ]. In regression analysis, B values below 0.1. between 0.1 and 0.5 and above 0.5 are broadly considered small, medium and high respectively [ 50 ].

Demographic characteristics are described in Table  1 , as well as descriptive statistics for the variables included in regression models.

Single regression models

Single linear regression models for demographic and mental health factors are presented in Table  2 . Being unemployed and having an ethnicity other than white were significantly associated with higher overall EF, inhibition and working memory impairment. Having high somatic symptoms and meeting caseness for probable common mental health difficulties were also associated with higher overall EF, inhibition and working memory impairment. In addition, scores indicating hazardous alcohol use were associated with working memory and inhibition impairment, and sleep disturbances were associated with a higher working memory impairment.

Multiple regression models

Multiple regression models for PTSD adjusted for all other significant variables besides CPTSD caseness observed in the single regression models. The same models were analysed including CPTSD as a predictor and not PTSD caseness. These models are displayed in Table  3 . Across all adjusted models, both PTSD and CPTSD remained significant predictors for EF, inhibition and working memory.

PTSD and DSO symptom clusters

Linear regression models for each of the PTSD and DSO symptom clusters and EF, inhibition and working memory are displayed in Table  4 . In line with our hypothesis, each symptom cluster was significantly associated with EF, as well as inhibition and working memory subscales.

The aim of the current study was to explore the associations between CPTSD symptom clusters and EF in a clinical sample of UK veterans. Both PTSD and CPTSD caseness were significantly associated with greater impairment in inhibition and working memory, in line with our hypothesis. All PTSD symptom clusters, and the DSO symptom clusters which encompass CPTSD, were associated with inhibition and working memory. In particular, the DSO symptom emotion dysregulation was most strongly associated with EF impairment. PTSD encompasses symptoms hyperarousal, re-experiencing and avoidance. CPTSD is a relatively new separate diagnosis which includes PTSD symptoms as well as DSO symptoms: emotion dysregulation, negative self-concept and interpersonal difficulties, as well as functional impairment relating to these domains [ 4 ].

These associations remained after controlling for the following possible confounders, which were also found to be associated with greater EF impairment: employment status, ethnicity, somatisation severity, common mental health disorders, alcohol misuse and for working memory, sleep function. The finding that EF impairment is associated with worse health coheres with previous research, which has observed relationships between EF deficits and both depression [ 51 ] and somatisation disorder [ 52 ]. Additionally, sleep deprivation is consistently associated with impairments in working memory [ 53 , 54 ].

Emotion dysregulation and EF impairment

Our finding that emotion dysregulation was the CPTSD symptom cluster most associated with EF coheres with and builds on neurocognitive models espoused in the literature. Previous research has suggested functional connectivity between the PFC and limbic system is key in the overlap observed between PTSD chronicity, severity, and EF impairment [ 10 , 55 ]. In one study, those with greater functional connectivity in this system - termed the frontal parietal control and limbic network (FPCN) - were observed to have less chronicity of and greater reduction in PTSD symptoms [ 56 ]. The FPCN underlies emotion processing [ 57 ], mind wandering [ 58 ] and is neurally connected with the default mode network (DMN; [ 59 ]), all of which are associated with PTSD [ 60 ]. Moreover, the development of the DMN is particularly sensitive during childhood, with research suggesting its development could be affected by early and prolonged trauma [ 61 , 62 ]. Given these factors are more strongly associated with CPTSD than PTSD [ 5 ], the finding that DSO symptom cluster emotion dysregulation was most related to EF suggests similar neurobiological mechanisms may be involved in CPTSD as those espoused for the overlap between EF and PTSD.

Limitations

A number of limitations to the present study should be noted. Firstly, whilst the self-report measure of EF facilitated the collection of data from a larger sample, it has limited convergent validity with neuropsychological measures of EF [ 37 ]. However, as a self-report measure, the scale has strong psychometric properties [ 37 ] and self-report EF measures are strongly related to functional impairment [ 63 ]. Secondly, the scale does not include items measuring cognitive flexibility, although this would be difficult to capture on a self-report measure. Data were collected during the Covid-19 pandemic, and environmental factors related to restrictive measures at the time could have affected participants’ responses. However, our research suggests veterans’ mental health difficulties remained relatively stable throughout the pandemic. Finally, no causal relationships can be interpreted from the current findings due to the cross-sectional design of the study. However, the observed finding of an association between DSO symptom clusters and EF impairment builds on previous findings of similar association with PTSD clusters and this can inform future research and clinical studies.

Implications for treatment

Taken together, the findings of the present study suggest that CPTSD interventions may – as observed with PTSD treatment outcomes [ 22 ] – result in better symptom improvement in patients who display greater inhibitory control in neuropsychological tests. By separately analysing both PTSD and DSO symptom clusters, the current study has highlighted the potential role of emotion dysregulation in the overlap between EF impairment and PTSD observed in previous studies [ 10 , 11 , 12 ]. Future research might explore whether veterans with better inhibitory control and working memory respond better to CPTSD interventions. For example, Enhanced Skills Training in Affective and Interpersonal Regulation (ESTAIR; [ 64 ]) is a modular CPTSD treatment which sequentially targets each DSO symptom – including emotion dysregulation. Future studies might explore whether building skills in emotion regulation reduces impairment in EF and subsequently improves recovery trajectories.

This was the first study to explore the relationship between EF and CPTSD symptom clusters in a clinical sample of UK Armed Forces veterans. That DSO symptom clusters, in addition to PTSD clusters, were associated with EF builds on previous findings and suggests that CPTSD treatment outcomes could similarly be affected by levels of EF impairment in veteran patients. Future research should explore the clinical implications of these findings further.

Data availability

The datasets analysed during the current study are not publicly available due to patient confidentiality.

Abbreviations

Complex posttraumatic stress disorder

Default mode network

Disturbances in self-organisation

• Executive function

Posttraumatic stress disorder

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DM conceptualised the study and prepared the data. NB analysed the data and drafted the manuscript. EN drafted the manuscript. All authors contributed to manuscript revision.

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Biscoe, N., New, E. & Murphy, D. Complex PTSD symptom clusters and executive function in UK Armed Forces veterans: a cross-sectional study. BMC Psychol 12 , 209 (2024). https://doi.org/10.1186/s40359-024-01713-w

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Received : 23 October 2023

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DOI : https://doi.org/10.1186/s40359-024-01713-w

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