define case study process

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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• Knowledge Base
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• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, 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 analyse the case.

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

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.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

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

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 .

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

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 analyse 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.

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Your Step-By-Step Guide To Writing a Case Study

Creating a case study is both an art and a science. It requires making an in-depth exploration of your chosen subject in order to extract meaningful insights and understand the dynamics that more general surveys or statistical research might not uncover. At the same time, your case study also needs to be a compelling read to ensure those insights get attention from other people!

Unsurprisingly, the prospect of crafting an effective case study can be daunting. It calls for strategic planning, careful organization, and clear communication, all of which can be challenging even for experienced researchers. That's why we've created this step-by-step guide, which breaks the process down into manageable steps, demystifying the journey from defining your research question to sharing your findings. Whether you're a seasoned researcher or a first-timer, this guide aims to equip you with the necessary tools and tips to create a case study that's not just informative, but also engaging and impactful.

Are you ready to unlock the potential of case studies? Let's dive in!

What is a case study?

First, it's important to understand what a case study is – and what it isn't.

A case study is a thorough exploration of a specific subject or event over a certain time frame. Case studies are utilized in numerous fields, including sociology, psychology, education, anthropology, business, and the health sciences, and employ various research techniques to shed light on complex issues.

A case study does not provide absolute proof or conclusions that can be universally applied. Because it concentrates on one particular case or just a few cases, the findings might not apply to different contexts or subjects. Case studies also aren't ideal for determining cause-and-effect relationships as they do not use controlled conditions to separate and measure the impacts of different factors. Lastly, it must be said that a case study isn't just a random assortment of facts or observations; it necessitates a clear research question, a methodical approach to data collection and analysis, and a thoughtful interpretation of the results.

Getting started

Now that we've established the definition and purpose of a case study, let's explore the process by which one is created. You can produce a case study by following these nine steps:

1. Define the purpose of your case study

Before you start writing a case study, you need to define its purpose clearly. Ask yourself: What is the research question or problem you aim to solve? What insights are you looking to uncover? Your goals will guide your research design and influence your choice of case. This initial stage of introspection and clarification is crucial as it acts as a roadmap for your study.

2. Select the case to study

Once you've defined your research objective, the next step is to choose a suitable case that can help answer your research question. This might be a unique, critical, or representative instance. Unique cases offer the opportunity to observe and analyze a situation that is unusual or not well-understood. In contrast, a representative or typical case is often chosen because it represents other cases or a broader phenomenon.

In any case, be sure to justify your choice. Explain why the case is of interest and how it can contribute to the knowledge or understanding of the issue at hand. For instance, if you're studying the effects of corporate restructuring on employee morale, you might choose to focus on a company that recently underwent a significant restructure.

3. Conduct a thorough literature review

Performing a literature review involves a careful examination of relevant scholarly articles, books, and other sources related to your research question or problem. In the process, you identify gaps in the current knowledge and determine how your case study can address them. By critically examining existing research, you will not only gain a comprehensive understanding of your chosen topic but also be able to refine your research question or hypothesis, if necessary.

4. Choose a methodological approach

The methodological approach used in your case study will depend on your research objectives and the nature of the case. Methodologies that can be employed in case studies include qualitative, quantitative, and mixed methods .

Qualitative methods are often used when the goal is to explore, understand, or interpret certain phenomena. These involve approaches like interviews, focus groups, or ethnography. Quantitative methods, on the other hand, are used when the goal is to test hypotheses or examine relationships between variables. Quantitative approaches often include experiments. Also, surveys may be either qualitative or quantitative depending on the question design.

You may choose to use a combination of qualitative and quantitative methods (mixed methods) if it suits your research objectives.

5. Collect and organize your data

Data collection should be systematic and organized to maintain the integrity and reliability of your research. You need to plan how you will record and store your data to ensure that it's accessible and usable.

If you're conducting interviews or observations, consider using recording devices (with participant consent) to capture the data accurately. In addition, you may want to transcribe the recorded material for easier analysis. If you're using documents or archival records, develop a system for coding and categorizing the data.

6. Analyze the data

Analysis involves interpreting your data to draw out meaningful insights; it is in this stage that your findings start to take shape. Depending on the nature of your data and your research question, you might use any of a variety of analysis methods. For qualitative data, you might employ thematic analysis to identify key themes or grounded theory to generate a new theoretical framework. For quantitative data, you might use statistical analysis to identify patterns or correlations.

Always be open to unexpected findings. Your initial hypotheses might not be supported, or you might uncover new insights that you hadn't initially considered. Remember that all data, whether they fit neatly into your analysis or not, provide valuable insights and contribute to the holistic understanding of your case.

7. Write the case study report

After analyzing the data, it's finally time to compose your case study. In terms of structure, a typical case study might consist of an introduction, background information, the collected data (results), analysis of that data, and the conclusion. Here's a brief breakdown of each section:

• Introduction: The introduction should be brief but engaging, providing a clear statement of the research question or problem, explaining why the case was chosen, and outlining what the case study will cover.
• Background: The background provides the context for your case. Describe the case, its history, and any relevant information that will help readers understand the situation.
• Results: This section should provide a comprehensive account of what you found, without interpretation or opinion. Present your findings in a clear, organized manner. Use visuals such as charts or graphs if they aid comprehension.
• Analysis: This section should provide your interpretations and arguments. Discuss the patterns, themes, or relationships you've identified in your data. Explain what these findings mean in relation to your research question.
• Conclusion: Finally, summarize the key insights from your case study along with their implications. Discuss the limitations of your study and propose avenues for future research.

8. Review and revise

The process of writing a case study doesn't actually end when the report is written; you also need to review your writing for coherence, clarity, and correctness. Don't underestimate the importance of this step! Make sure the information flows logically and that your arguments are well-supported. Check for any grammar or spelling errors. Having a peer or mentor review your work can be incredibly helpful as they provide a fresh perspective and can catch mistakes you might have missed.

9. Get approval if required

If your case study involves human subjects, you may need to obtain approval from an ethical review board. You'll also need to obtain informed consent from your subjects and ensure you respect their privacy and confidentiality throughout the research process. Always follow your institution's ethical guidelines and any other relevant legislation .

Practical tips for writing a compelling case study

Getting through all those steps can feel like a formidable challenge, but here are some practical tips to make the process more manageable:

Be systematic and organized

Given the importance of detail in case studies, it's vital to be systematic and organized from the get-go. This means keeping meticulous records of your data, your sources, and any changes to your research design. A good practice is to maintain a research journal or log where you can record your process, thoughts, and reflections.

In addition, use technology to your advantage. Digital tools like citation managers can help you keep track of your sources and make formatting references a breeze, while spreadsheet or database software can assist in managing and organizing your data. Developing a consistent system for labeling and storing information at the outset will save you time and effort later when you need to retrieve data for analysis.

Stay focused

One common pitfall in research and writing is loss of focus: getting sidetracked by interesting but ultimately irrelevant digressions, which can be very easy, especially when you're dealing with a rich and complex case. Always remember your research question and objectives, and let these guide your study at every step. It's perfectly acceptable – and in fact advisable – to delineate what your study will not cover. Setting clear boundaries can help you stay focused and manage the scope of your study effectively.

Use visual aids

Visual aids such as charts, diagrams, or photographs can greatly enhance your case study. They provide readers with a break from the monotony of text and can communicate complex data or relationships more easily. For instance, if you're presenting a lot of numerical data, consider using a chart or graph. If you're describing a process or sequence of events, portraying it in a flowchart or timeline might be useful. Remember, the goal is to aid comprehension, so make sure your visual aids are clear, well-labeled, and integrated into the text.

Include direct quotes

If your case study involves interviews, including direct quotes can add depth and a sense of the personal to your findings. They provide readers with a firsthand perspective and make your case study more engaging.

When using quotes, be sure to integrate them smoothly into your text. Provide enough context so readers understand the quote's relevance. Also, remember to adhere to ethical guidelines– always respect confidentiality and anonymity agreements.

Maintain ethical standards

Ethics is a fundamental consideration in all research, including case studies. Ensure you have proper consent from participants, respect their privacy, and accurately present your findings without manipulation.

Misrepresenting data or failing to respect participants' rights can lead to serious ethical violations. Always follow your institution's ethical guidelines and any other relevant legislation. If in doubt, seek advice from a supervisor or your institution's ethics committee.

Acknowledge limitations

Every research study has limitations, which could relate to the research design, data collection methods, or other aspects of the study. Being transparent about the limitations of your study can enhance its credibility; moreover, not only does identifying limitations demonstrate your critical thinking and honesty, but it also helps readers accurately interpret your findings.

Finally, acknowledging the limitations of your work helps to set the stage for further research. By identifying aspects that your study couldn't address, you provide other researchers with avenues for building on your findings.

Learn from examples

Before you start writing your case study, it can be helpful to review some published case studies in your field. Different fields may have different conventions, and familiarizing yourself with case studies in your own field can help guide your writing. Look at the structure, tone, and style. Pay attention to how the authors present and analyze data, and how they link their findings back to the research question. You can also learn a lot from the strengths and weaknesses of previously published works. However, remember to develop your own unique voice and perspective – don't just mimic what others have done.

Design for triangulation

Triangulation involves using multiple data sources or methods to gain a more comprehensive and balanced understanding of your research topic. By coming at your research question from multiple directions, such as by examining different datasets or using different methods, you can increase the validity of your results and gain more nuanced insights.

For example, if you're studying the impact of a new teaching method in a school, you might observe classes, interview teachers, and also survey students. Each method will provide a slightly different perspective, and together, they allow you to develop a more complete picture of the teaching method's impact.

Practice reflexivity

Reflexivity involves reflecting on how your assumptions, values, or experiences might influence your research process and interpretations. As a researcher, it's essential to be aware of your potential biases and how they might shape your study.

Consider keeping a reflexivity journal where you can note your thoughts, feelings, and reflections throughout the research process. This practice can help you stay aware of your biases and ensure your research is as objective and balanced as possible.

Write for your audience

Always make sure that your writing is on target for your intended audience. If you're writing for an academic audience, for example, you'll likely use a more formal tone and include more detailed methodological information. If you're writing for practitioners or a general audience, you might use a more accessible language and focus more on practical implications.

Remember to define any technical terms or jargon, and provide sufficient context so your readers can understand your research. The goal is to communicate your findings effectively, regardless of who your readers are.

Seek feedback

Feedback is valuable for improving your case study. Consider sharing drafts with your peers, mentors, or supervisors and asking for their input. Fresh eyes can provide different perspectives, catch errors, or suggest ways to strengthen your arguments.

Remember, feedback is not personal; it's about improving your work. Be open to critique and willing to revise your work based on the feedback you receive.

Writing a case study is a meticulous process that requires clear purpose, careful planning, systematic data collection, and thoughtful analysis. Although it can be time-consuming, the rich, detailed insights a well-executed case study can provide make this study design an invaluable tool in research.

By following this guide and adopting its practical tips, you will be well on your way to crafting a compelling case study that contributes meaningful insights to your chosen field. Good luck with your research journey!

Header image by Kateryna Hliznitsova .

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Writing a Case Study

What is a case study?

A Case study is: 

• An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
• Used to examine an identifiable problem confirmed through research.
• Used to investigate an individual, group of people, organization, or event.
• Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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• Last Updated: May 16, 2024 8:25 AM
• URL: https://resources.nu.edu/researchtools

How to Write a Case Study: Bookmarkable Guide & Template

Published: November 30, 2023

Earning the trust of prospective customers can be a struggle. Before you can even begin to expect to earn their business, you need to demonstrate your ability to deliver on what your product or service promises.

Sure, you could say that you're great at X or that you're way ahead of the competition when it comes to Y. But at the end of the day, what you really need to win new business is cold, hard proof.

One of the best ways to prove your worth is through a compelling case study. In fact, HubSpot’s 2020 State of Marketing report found that case studies are so compelling that they are the fifth most commonly used type of content used by marketers.

Below, I'll walk you through what a case study is, how to prepare for writing one, what you need to include in it, and how it can be an effective tactic. To jump to different areas of this post, click on the links below to automatically scroll.

Case Study Definition

Case study templates, how to write a case study.

• How to Format a Case Study

Business Case Study Examples

A case study is a specific challenge a business has faced, and the solution they've chosen to solve it. Case studies can vary greatly in length and focus on several details related to the initial challenge and applied solution, and can be presented in various forms like a video, white paper, blog post, etc.

In professional settings, it's common for a case study to tell the story of a successful business partnership between a vendor and a client. Perhaps the success you're highlighting is in the number of leads your client generated, customers closed, or revenue gained. Any one of these key performance indicators (KPIs) are examples of your company's services in action.

When done correctly, these examples of your work can chronicle the positive impact your business has on existing or previous customers and help you attract new clients.

Free Case Study Templates

Showcase your company's success using these three free case study templates.

• Data-Driven Case Study Template
• Product-Specific Case Study Template
• General Case Study Template

You're all set!

Click this link to access this resource at any time.

Why write a case study? 

I know, you’re thinking “ Okay, but why do I need to write one of these? ” The truth is that while case studies are a huge undertaking, they are powerful marketing tools that allow you to demonstrate the value of your product to potential customers using real-world examples. Here are a few reasons why you should write case studies. 

1. Explain Complex Topics or Concepts

Case studies give you the space to break down complex concepts, ideas, and strategies and show how they can be applied in a practical way. You can use real-world examples, like an existing client, and use their story to create a compelling narrative that shows how your product solved their issue and how those strategies can be repeated to help other customers get similar successful results.  

2. Show Expertise

Case studies are a great way to demonstrate your knowledge and expertise on a given topic or industry. This is where you get the opportunity to show off your problem-solving skills and how you’ve generated successful outcomes for clients you’ve worked with. 

3. Build Trust and Credibility

In addition to showing off the attributes above, case studies are an excellent way to build credibility. They’re often filled with data and thoroughly researched, which shows readers you’ve done your homework. They can have confidence in the solutions you’ve presented because they’ve read through as you’ve explained the problem and outlined step-by-step what it took to solve it. All of these elements working together enable you to build trust with potential customers.

4. Create Social Proof

Using existing clients that have seen success working with your brand builds social proof . People are more likely to choose your brand if they know that others have found success working with you. Case studies do just that — putting your success on display for potential customers to see. 

All of these attributes work together to help you gain more clients. Plus you can even use quotes from customers featured in these studies and repurpose them in other marketing content. Now that you know more about the benefits of producing a case study, let’s check out how long these documents should be. 

How long should a case study be?

The length of a case study will vary depending on the complexity of the project or topic discussed. However, as a general guideline, case studies typically range from 500 to 1,500 words. 

Whatever length you choose, it should provide a clear understanding of the challenge, the solution you implemented, and the results achieved. This may be easier said than done, but it's important to strike a balance between providing enough detail to make the case study informative and concise enough to keep the reader's interest.

The primary goal here is to effectively communicate the key points and takeaways of the case study. It’s worth noting that this shouldn’t be a wall of text. Use headings, subheadings, bullet points, charts, and other graphics to break up the content and make it more scannable for readers. We’ve also seen brands incorporate video elements into case studies listed on their site for a more engaging experience. 

Ultimately, the length of your case study should be determined by the amount of information necessary to convey the story and its impact without becoming too long. Next, let’s look at some templates to take the guesswork out of creating one. 

To help you arm your prospects with information they can trust, we've put together a step-by-step guide on how to create effective case studies for your business with free case study templates for creating your own.

Tell us a little about yourself below to gain access today:

And to give you more options, we’ll highlight some useful templates that serve different needs. But remember, there are endless possibilities when it comes to demonstrating the work your business has done.

1. General Case Study Template

Do you have a specific product or service that you’re trying to sell, but not enough reviews or success stories? This Product Specific case study template will help.

This template relies less on metrics, and more on highlighting the customer’s experience and satisfaction. As you follow the template instructions, you’ll be prompted to speak more about the benefits of the specific product, rather than your team’s process for working with the customer.

4. Bold Social Media Business Case Study Template

You can find templates that represent different niches, industries, or strategies that your business has found success in — like a bold social media business case study template.

In this template, you can tell the story of how your social media marketing strategy has helped you or your client through collaboration or sale of your service. Customize it to reflect the different marketing channels used in your business and show off how well your business has been able to boost traffic, engagement, follows, and more.

5. Lead Generation Business Case Study Template

It’s important to note that not every case study has to be the product of a sale or customer story, sometimes they can be informative lessons that your own business has experienced. A great example of this is the Lead Generation Business case study template.

If you’re looking to share operational successes regarding how your team has improved processes or content, you should include the stories of different team members involved, how the solution was found, and how it has made a difference in the work your business does.

Now that we’ve discussed different templates and ideas for how to use them, let’s break down how to create your own case study with one.

• Get started with case study templates.
• Determine the case study's objective.
• Establish a case study medium.
• Find the right case study candidate.
• Contact your candidate for permission to write about them.
• Ensure you have all the resources you need to proceed once you get a response.
• Download a case study email template.
• Define the process you want to follow with the client.
• Ensure you're asking the right questions.
• Layout your case study format.
• Publish and promote your case study.

1. Get started with case study templates.

Telling your customer's story is a delicate process — you need to highlight their success while naturally incorporating your business into their story.

If you're just getting started with case studies, we recommend you download HubSpot's Case Study Templates we mentioned before to kickstart the process.

2. Determine the case study's objective.

All business case studies are designed to demonstrate the value of your services, but they can focus on several different client objectives.

Your first step when writing a case study is to determine the objective or goal of the subject you're featuring. In other words, what will the client have succeeded in doing by the end of the piece?

The client objective you focus on will depend on what you want to prove to your future customers as a result of publishing this case study.

Your case study can focus on one of the following client objectives:

• Complying with government regulation
• Lowering business costs
• Becoming profitable
• Generating more leads
• Closing on more customers
• Generating more revenue
• Expanding into a new market
• Becoming more sustainable or energy-efficient

3. Establish a case study medium.

Next, you'll determine the medium in which you'll create the case study. In other words, how will you tell this story?

Case studies don't have to be simple, written one-pagers. Using different media in your case study can allow you to promote your final piece on different channels. For example, while a written case study might just live on your website and get featured in a Facebook post, you can post an infographic case study on Pinterest and a video case study on your YouTube channel.

Here are some different case study mediums to consider:

Written Case Study

Consider writing this case study in the form of an ebook and converting it to a downloadable PDF. Then, gate the PDF behind a landing page and form for readers to fill out before downloading the piece, allowing this case study to generate leads for your business.

Video Case Study

Plan on meeting with the client and shooting an interview. Seeing the subject, in person, talk about the service you provided them can go a long way in the eyes of your potential customers.

Infographic Case Study

Use the long, vertical format of an infographic to tell your success story from top to bottom. As you progress down the infographic, emphasize major KPIs using bigger text and charts that show the successes your client has had since working with you.

Podcast Case Study

Podcasts are a platform for you to have a candid conversation with your client. This type of case study can sound more real and human to your audience — they'll know the partnership between you and your client was a genuine success.

4. Find the right case study candidate.

Writing about your previous projects requires more than picking a client and telling a story. You need permission, quotes, and a plan. To start, here are a few things to look for in potential candidates.

Product Knowledge

It helps to select a customer who's well-versed in the logistics of your product or service. That way, he or she can better speak to the value of what you offer in a way that makes sense for future customers.

Remarkable Results

Clients that have seen the best results are going to make the strongest case studies. If their own businesses have seen an exemplary ROI from your product or service, they're more likely to convey the enthusiasm that you want prospects to feel, too.

One part of this step is to choose clients who have experienced unexpected success from your product or service. When you've provided non-traditional customers — in industries that you don't usually work with, for example — with positive results, it can help to remove doubts from prospects.

Recognizable Names

While small companies can have powerful stories, bigger or more notable brands tend to lend credibility to your own. In fact, 89% of consumers say they'll buy from a brand they already recognize over a competitor, especially if they already follow them on social media.

Customers that came to you after working with a competitor help highlight your competitive advantage and might even sway decisions in your favor.

5. Contact your candidate for permission to write about them.

To get the case study candidate involved, you have to set the stage for clear and open communication. That means outlining expectations and a timeline right away — not having those is one of the biggest culprits in delayed case study creation.

Most importantly at this point, however, is getting your subject's approval. When first reaching out to your case study candidate, provide them with the case study's objective and format — both of which you will have come up with in the first two steps above.

To get this initial permission from your subject, put yourself in their shoes — what would they want out of this case study? Although you're writing this for your own company's benefit, your subject is far more interested in the benefit it has for them.

Benefits to Offer Your Case Study Candidate

Here are four potential benefits you can promise your case study candidate to gain their approval.

Brand Exposure

Explain to your subject to whom this case study will be exposed, and how this exposure can help increase their brand awareness both in and beyond their own industry. In the B2B sector, brand awareness can be hard to collect outside one's own market, making case studies particularly useful to a client looking to expand their name's reach.

Employee Exposure

Allow your subject to provide quotes with credits back to specific employees. When this is an option for them, their brand isn't the only thing expanding its reach — their employees can get their name out there, too. This presents your subject with networking and career development opportunities they might not have otherwise.

Product Discount

This is a more tangible incentive you can offer your case study candidate, especially if they're a current customer of yours. If they agree to be your subject, offer them a product discount — or a free trial of another product — as a thank-you for their help creating your case study.

Backlinks and Website Traffic

Here's a benefit that is sure to resonate with your subject's marketing team: If you publish your case study on your website, and your study links back to your subject's website — known as a "backlink" — this small gesture can give them website traffic from visitors who click through to your subject's website.

Additionally, a backlink from you increases your subject's page authority in the eyes of Google. This helps them rank more highly in search engine results and collect traffic from readers who are already looking for information about their industry.

6. Ensure you have all the resources you need to proceed once you get a response.

So you know what you’re going to offer your candidate, it’s time that you prepare the resources needed for if and when they agree to participate, like a case study release form and success story letter.

Let's break those two down.

Case Study Release Form

This document can vary, depending on factors like the size of your business, the nature of your work, and what you intend to do with the case studies once they are completed. That said, you should typically aim to include the following in the Case Study Release Form:

• A clear explanation of why you are creating this case study and how it will be used.
• A statement defining the information and potentially trademarked information you expect to include about the company — things like names, logos, job titles, and pictures.
• An explanation of what you expect from the participant, beyond the completion of the case study. For example, is this customer willing to act as a reference or share feedback, and do you have permission to pass contact information along for these purposes?
• A note about compensation.

Success Story Letter

As noted in the sample email, this document serves as an outline for the entire case study process. Other than a brief explanation of how the customer will benefit from case study participation, you'll want to be sure to define the following steps in the Success Story Letter.

7. Download a case study email template.

While you gathered your resources, your candidate has gotten time to read over the proposal. When your candidate approves of your case study, it's time to send them a release form.

A case study release form tells you what you'll need from your chosen subject, like permission to use any brand names and share the project information publicly. Kick-off this process with an email that runs through exactly what they can expect from you, as well as what you need from them. To give you an idea of what that might look like, check out this sample email:

8. Define the process you want to follow with the client.

Before you can begin the case study, you have to have a clear outline of the case study process with your client. An example of an effective outline would include the following information.

The Acceptance

First, you'll need to receive internal approval from the company's marketing team. Once approved, the Release Form should be signed and returned to you. It's also a good time to determine a timeline that meets the needs and capabilities of both teams.

The Questionnaire

To ensure that you have a productive interview — which is one of the best ways to collect information for the case study — you'll want to ask the participant to complete a questionnaire before this conversation. That will provide your team with the necessary foundation to organize the interview, and get the most out of it.

The Interview

Once the questionnaire is completed, someone on your team should reach out to the participant to schedule a 30- to 60-minute interview, which should include a series of custom questions related to the customer's experience with your product or service.

The Draft Review

After the case study is composed, you'll want to send a draft to the customer, allowing an opportunity to give you feedback and edits.

The Final Approval

Once any necessary edits are completed, send a revised copy of the case study to the customer for final approval.

Once the case study goes live — on your website or elsewhere — it's best to contact the customer with a link to the page where the case study lives. Don't be afraid to ask your participants to share these links with their own networks, as it not only demonstrates your ability to deliver positive results and impressive growth, as well.

9. Ensure you're asking the right questions.

Before you execute the questionnaire and actual interview, make sure you're setting yourself up for success. A strong case study results from being prepared to ask the right questions. What do those look like? Here are a few examples to get you started:

• What are your goals?
• What challenges were you experiencing before purchasing our product or service?
• What made our product or service stand out against our competitors?
• What did your decision-making process look like?
• How have you benefited from using our product or service? (Where applicable, always ask for data.)

Keep in mind that the questionnaire is designed to help you gain insights into what sort of strong, success-focused questions to ask during the actual interview. And once you get to that stage, we recommend that you follow the "Golden Rule of Interviewing." Sounds fancy, right? It's actually quite simple — ask open-ended questions.

If you're looking to craft a compelling story, "yes" or "no" answers won't provide the details you need. Focus on questions that invite elaboration, such as, "Can you describe ...?" or, "Tell me about ..."

In terms of the interview structure, we recommend categorizing the questions and flowing them into six specific sections that will mirror a successful case study format. Combined, they'll allow you to gather enough information to put together a rich, comprehensive study.

Open with the customer's business.

The goal of this section is to generate a better understanding of the company's current challenges and goals, and how they fit into the landscape of their industry. Sample questions might include:

• How long have you been in business?
• How many employees do you have?
• What are some of the objectives of your department at this time?

Cite a problem or pain point.

To tell a compelling story, you need context. That helps match the customer's need with your solution. Sample questions might include:

• What challenges and objectives led you to look for a solution?
• What might have happened if you did not identify a solution?
• Did you explore other solutions before this that did not work out? If so, what happened?

Discuss the decision process.

Exploring how the customer decided to work with you helps to guide potential customers through their own decision-making processes. Sample questions might include:

• How did you hear about our product or service?
• Who was involved in the selection process?
• What was most important to you when evaluating your options?

Explain how a solution was implemented.

The focus here should be placed on the customer's experience during the onboarding process. Sample questions might include:

• How long did it take to get up and running?
• Did that meet your expectations?
• Who was involved in the process?

Explain how the solution works.

The goal of this section is to better understand how the customer is using your product or service. Sample questions might include:

• Is there a particular aspect of the product or service that you rely on most?
• Who is using the product or service?

End with the results.

In this section, you want to uncover impressive measurable outcomes — the more numbers, the better. Sample questions might include:

• How is the product or service helping you save time and increase productivity?
• In what ways does that enhance your competitive advantage?
• How much have you increased metrics X, Y, and Z?

10. Lay out your case study format.

When it comes time to take all of the information you've collected and actually turn it into something, it's easy to feel overwhelmed. Where should you start? What should you include? What's the best way to structure it?

To help you get a handle on this step, it's important to first understand that there is no one-size-fits-all when it comes to the ways you can present a case study. They can be very visual, which you'll see in some of the examples we've included below, and can sometimes be communicated mostly through video or photos, with a bit of accompanying text.

Here are the sections we suggest, which we'll cover in more detail down below:

• Title: Keep it short. Develop a succinct but interesting project name you can give the work you did with your subject.
• Subtitle: Use this copy to briefly elaborate on the accomplishment. What was done? The case study itself will explain how you got there.
• Executive Summary : A 2-4 sentence summary of the entire story. You'll want to follow it with 2-3 bullet points that display metrics showcasing success.
• About the Subject: An introduction to the person or company you served, which can be pulled from a LinkedIn Business profile or client website.
• Challenges and Objectives: A 2-3 paragraph description of the customer's challenges, before using your product or service. This section should also include the goals or objectives the customer set out to achieve.
• How Product/Service Helped: A 2-3 paragraph section that describes how your product or service provided a solution to their problem.
• Results: A 2-3 paragraph testimonial that proves how your product or service specifically benefited the person or company and helped achieve its goals. Include numbers to quantify your contributions.
• Supporting Visuals or Quotes: Pick one or two powerful quotes that you would feature at the bottom of the sections above, as well as a visual that supports the story you are telling.
• Future Plans: Everyone likes an epilogue. Comment on what's ahead for your case study subject, whether or not those plans involve you.
• Call to Action (CTA): Not every case study needs a CTA, but putting a passive one at the end of your case study can encourage your readers to take an action on your website after learning about the work you've done.

When laying out your case study, focus on conveying the information you've gathered in the most clear and concise way possible. Make it easy to scan and comprehend, and be sure to provide an attractive call-to-action at the bottom — that should provide readers an opportunity to learn more about your product or service.

11. Publish and promote your case study.

Once you've completed your case study, it's time to publish and promote it. Some case study formats have pretty obvious promotional outlets — a video case study can go on YouTube, just as an infographic case study can go on Pinterest.

But there are still other ways to publish and promote your case study. Here are a couple of ideas:

Lead Gen in a Blog Post

As stated earlier in this article, written case studies make terrific lead-generators if you convert them into a downloadable format, like a PDF. To generate leads from your case study, consider writing a blog post that tells an abbreviated story of your client's success and asking readers to fill out a form with their name and email address if they'd like to read the rest in your PDF.

Then, promote this blog post on social media, through a Facebook post or a tweet.

Published as a Page on Your Website

As a growing business, you might need to display your case study out in the open to gain the trust of your target audience.

Rather than gating it behind a landing page, publish your case study to its own page on your website, and direct people here from your homepage with a "Case Studies" or "Testimonials" button along your homepage's top navigation bar.

Format for a Case Study

The traditional case study format includes the following parts: a title and subtitle, a client profile, a summary of the customer’s challenges and objectives, an account of how your solution helped, and a description of the results. You might also want to include supporting visuals and quotes, future plans, and calls-to-action.

Image Source

The title is one of the most important parts of your case study. It should draw readers in while succinctly describing the potential benefits of working with your company. To that end, your title should:

• State the name of your custome r. Right away, the reader must learn which company used your products and services. This is especially important if your customer has a recognizable brand. If you work with individuals and not companies, you may omit the name and go with professional titles: “A Marketer…”, “A CFO…”, and so forth.
• State which product your customer used . Even if you only offer one product or service, or if your company name is the same as your product name, you should still include the name of your solution. That way, readers who are not familiar with your business can become aware of what you sell.
• Allude to the results achieved . You don’t necessarily need to provide hard numbers, but the title needs to represent the benefits, quickly. That way, if a reader doesn’t stay to read, they can walk away with the most essential information: Your product works.

The example above, “Crunch Fitness Increases Leads and Signups With HubSpot,” achieves all three — without being wordy. Keeping your title short and sweet is also essential.

2. Subtitle

Your subtitle is another essential part of your case study — don’t skip it, even if you think you’ve done the work with the title. In this section, include a brief summary of the challenges your customer was facing before they began to use your products and services. Then, drive the point home by reiterating the benefits your customer experienced by working with you.

The above example reads:

“Crunch Fitness was franchising rapidly when COVID-19 forced fitness clubs around the world to close their doors. But the company stayed agile by using HubSpot to increase leads and free trial signups.”

We like that the case study team expressed the urgency of the problem — opening more locations in the midst of a pandemic — and placed the focus on the customer’s ability to stay agile.

3. Executive Summary

The executive summary should provide a snapshot of your customer, their challenges, and the benefits they enjoyed from working with you. Think it’s too much? Think again — the purpose of the case study is to emphasize, again and again, how well your product works.

The good news is that depending on your design, the executive summary can be mixed with the subtitle or with the “About the Company” section. Many times, this section doesn’t need an explicit “Executive Summary” subheading. You do need, however, to provide a convenient snapshot for readers to scan.

In the above example, ADP included information about its customer in a scannable bullet-point format, then provided two sections: “Business Challenge” and “How ADP Helped.” We love how simple and easy the format is to follow for those who are unfamiliar with ADP or its typical customer.

4. About the Company

Readers need to know and understand who your customer is. This is important for several reasons: It helps your reader potentially relate to your customer, it defines your ideal client profile (which is essential to deter poor-fit prospects who might have reached out without knowing they were a poor fit), and it gives your customer an indirect boon by subtly promoting their products and services.

Feel free to keep this section as simple as possible. You can simply copy and paste information from the company’s LinkedIn, use a quote directly from your customer, or take a more creative storytelling approach.

In the above example, HubSpot included one paragraph of description for Crunch Fitness and a few bullet points. Below, ADP tells the story of its customer using an engaging, personable technique that effectively draws readers in.

5. Challenges and Objectives

The challenges and objectives section of your case study is the place to lay out, in detail, the difficulties your customer faced prior to working with you — and what they hoped to achieve when they enlisted your help.

In this section, you can be as brief or as descriptive as you’d like, but remember: Stress the urgency of the situation. Don’t understate how much your customer needed your solution (but don’t exaggerate and lie, either). Provide contextual information as necessary. For instance, the pandemic and societal factors may have contributed to the urgency of the need.

Take the above example from design consultancy IDEO:

“Educational opportunities for adults have become difficult to access in the United States, just when they’re needed most. To counter this trend, IDEO helped the city of South Bend and the Drucker Institute launch Bendable, a community-powered platform that connects people with opportunities to learn with and from each other.”

We love how IDEO mentions the difficulties the United States faces at large, the efforts its customer is taking to address these issues, and the steps IDEO took to help.

6. How Product/Service Helped

This is where you get your product or service to shine. Cover the specific benefits that your customer enjoyed and the features they gleaned the most use out of. You can also go into detail about how you worked with and for your customer. Maybe you met several times before choosing the right solution, or you consulted with external agencies to create the best package for them.

Whatever the case may be, try to illustrate how easy and pain-free it is to work with the representatives at your company. After all, potential customers aren’t looking to just purchase a product. They’re looking for a dependable provider that will strive to exceed their expectations.

In the above example, IDEO describes how it partnered with research institutes and spoke with learners to create Bendable, a free educational platform. We love how it shows its proactivity and thoroughness. It makes potential customers feel that IDEO might do something similar for them.

The results are essential, and the best part is that you don’t need to write the entirety of the case study before sharing them. Like HubSpot, IDEO, and ADP, you can include the results right below the subtitle or executive summary. Use data and numbers to substantiate the success of your efforts, but if you don’t have numbers, you can provide quotes from your customers.

We can’t overstate the importance of the results. In fact, if you wanted to create a short case study, you could include your title, challenge, solution (how your product helped), and result.

8. Supporting Visuals or Quotes

Let your customer speak for themselves by including quotes from the representatives who directly interfaced with your company.

Visuals can also help, even if they’re stock images. On one side, they can help you convey your customer’s industry, and on the other, they can indirectly convey your successes. For instance, a picture of a happy professional — even if they’re not your customer — will communicate that your product can lead to a happy client.

In this example from IDEO, we see a man standing in a boat. IDEO’s customer is neither the man pictured nor the manufacturer of the boat, but rather Conservation International, an environmental organization. This imagery provides a visually pleasing pattern interrupt to the page, while still conveying what the case study is about.

9. Future Plans

This is optional, but including future plans can help you close on a more positive, personable note than if you were to simply include a quote or the results. In this space, you can show that your product will remain in your customer’s tech stack for years to come, or that your services will continue to be instrumental to your customer’s success.

Alternatively, if you work only on time-bound projects, you can allude to the positive impact your customer will continue to see, even after years of the end of the contract.

10. Call to Action (CTA)

Not every case study needs a CTA, but we’d still encourage it. Putting one at the end of your case study will encourage your readers to take an action on your website after learning about the work you've done.

It will also make it easier for them to reach out, if they’re ready to start immediately. You don’t want to lose business just because they have to scroll all the way back up to reach out to your team.

To help you visualize this case study outline, check out the case study template below, which can also be downloaded here .

You drove the results, made the connection, set the expectations, used the questionnaire to conduct a successful interview, and boiled down your findings into a compelling story. And after all of that, you're left with a little piece of sales enabling gold — a case study.

To show you what a well-executed final product looks like, have a look at some of these marketing case study examples.

1. "Shopify Uses HubSpot CRM to Transform High Volume Sales Organization," by HubSpot

What's interesting about this case study is the way it leads with the customer. This reflects a major HubSpot value, which is to always solve for the customer first. The copy leads with a brief description of why Shopify uses HubSpot and is accompanied by a short video and some basic statistics on the company.

Notice that this case study uses mixed media. Yes, there is a short video, but it's elaborated upon in the additional text on the page. So, while case studies can use one or the other, don't be afraid to combine written copy with visuals to emphasize the project's success.

2. "New England Journal of Medicine," by Corey McPherson Nash

When branding and design studio Corey McPherson Nash showcases its work, it makes sense for it to be visual — after all, that's what they do. So in building the case study for the studio's work on the New England Journal of Medicine's integrated advertising campaign — a project that included the goal of promoting the client's digital presence — Corey McPherson Nash showed its audience what it did, rather than purely telling it.

Notice that the case study does include some light written copy — which includes the major points we've suggested — but lets the visuals do the talking, allowing users to really absorb the studio's services.

3. "Designing the Future of Urban Farming," by IDEO

Here's a design company that knows how to lead with simplicity in its case studies. As soon as the visitor arrives at the page, he or she is greeted with a big, bold photo, and two very simple columns of text — "The Challenge" and "The Outcome."

Immediately, IDEO has communicated two of the case study's major pillars. And while that's great — the company created a solution for vertical farming startup INFARM's challenge — it doesn't stop there. As the user scrolls down, those pillars are elaborated upon with comprehensive (but not overwhelming) copy that outlines what that process looked like, replete with quotes and additional visuals.

4. "Secure Wi-Fi Wins Big for Tournament," by WatchGuard

Then, there are the cases when visuals can tell almost the entire story — when executed correctly. Network security provider WatchGuard can do that through this video, which tells the story of how its services enhanced the attendee and vendor experience at the Windmill Ultimate Frisbee tournament.

5. Rock and Roll Hall of Fame Boosts Social Media Engagement and Brand Awareness with HubSpot

In the case study above , HubSpot uses photos, videos, screenshots, and helpful stats to tell the story of how the Rock and Roll Hall of Fame used the bot, CRM, and social media tools to gain brand awareness.

6. Small Desk Plant Business Ups Sales by 30% With Trello

This case study from Trello is straightforward and easy to understand. It begins by explaining the background of the company that decided to use it, what its goals were, and how it planned to use Trello to help them.

It then goes on to discuss how the software was implemented and what tasks and teams benefited from it. Towards the end, it explains the sales results that came from implementing the software and includes quotes from decision-makers at the company that implemented it.

7. Facebook's Mercedes Benz Success Story

Facebook's Success Stories page hosts a number of well-designed and easy-to-understand case studies that visually and editorially get to the bottom line quickly.

Each study begins with key stats that draw the reader in. Then it's organized by highlighting a problem or goal in the introduction, the process the company took to reach its goals, and the results. Then, in the end, Facebook notes the tools used in the case study.

Showcasing Your Work

You work hard at what you do. Now, it's time to show it to the world — and, perhaps more important, to potential customers. Before you show off the projects that make you the proudest, we hope you follow these important steps that will help you effectively communicate that work and leave all parties feeling good about it.

Editor's Note: This blog post was originally published in February 2017 but was updated for comprehensiveness and freshness in July 2021.

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The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

2 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Ann Robertson

3 School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

Anthony Avery

Aziz sheikh.

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables ​ Tables1, 1 , ​ ,2, 2 , ​ ,3 3 and ​ and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table ​ (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table ​ (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables ​ Tables2, 2 , ​ ,3 3 and ​ and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table ​ (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables ​ Tables2 2 and ​ and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table ​ (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table ​ (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table ​ Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table ​ (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table ​ (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table ​ Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table ​ (Table2 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table ​ (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table ​ (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table ​ (Table4 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table ​ Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table ​ (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table ​ Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table ​ (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 8 ]

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Short and sweet: multiple mini case studies as a form of rigorous case study research

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• Published: 15 May 2024

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• Sebastian Käss   ORCID: orcid.org/0000-0002-0640-3500 1 ,
• Christoph Brosig   ORCID: orcid.org/0000-0001-7809-0796 1 ,
• Markus Westner   ORCID: orcid.org/0000-0002-6623-880X 2 &
• Susanne Strahringer   ORCID: orcid.org/0000-0002-9465-9679 1  

Case study research is one of the most widely used research methods in Information Systems (IS). In recent years, an increasing number of publications have used case studies with few sources of evidence, such as single interviews per case. While there is much methodological guidance on rigorously conducting multiple case studies, it remains unclear how researchers can achieve an acceptable level of rigour for this emerging type of multiple case study with few sources of evidence, i.e., multiple mini case studies. In this context, we synthesise methodological guidance for multiple case study research from a cross-disciplinary perspective to develop an analytical framework. Furthermore, we calibrate this analytical framework to multiple mini case studies by reviewing previous IS publications that use multiple mini case studies to provide guidelines to conduct multiple mini case studies rigorously. We also offer a conceptual definition of multiple mini case studies, distinguish them from other research approaches, and position multiple mini case studies as a pragmatic and rigorous approach to research emerging and innovative phenomena in IS.

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The theory contribution of case study research designs

Case Study Research

Avoid common mistakes on your manuscript.

1 Introduction

Case study research has become a widely used research method in Information Systems (IS) research (Palvia et al. 2015 ) that allows for a comprehensive analysis of a contemporary phenomenon in its real-world context (Dubé and Paré, 2003 ). This research method is particularly useful due to its flexibility in covering complex phenomena with multiple contextual variables, different types of evidence, and a wide range of analytical options (Voss et al. 2002 ; Yin 2018 ). Although case study research is particularly useful for studying contemporary phenomena, some researchers feel that it lacks rigour, particularly in terms of the validity of findings (Lee and Hubona 2009 ). In response to these criticisms, Yin ( 2018 ) provides comprehensive methodological steps to conduct case studies rigorously. In addition, many other publications with a partly discipline-specific view on case study research, offer guidelines for achieving rigour in case study research, e.g., Benbasat et al. ( 1987 ), Dubé and Paré ( 2003 ), Pan and Tan ( 2011 ), or Voss et al. ( 2002 ). Most publications on case study methodology converge on four criteria for ensuring rigour in case study research: (1) construct validity, (2) internal validity, (3) external validity, and (4) reliability (Gibbert et al. 2008 ; Voss et al. 2002 ; Yin 2018 ).

A key element of rigour in case study research is to look at the unit of analysis of a case from multiple perspectives in order to draw informed conclusions (Dubois and Gadde 2002 ). Case study researchers refer to this as triangulation, for example, by using multiple sources of evidence per case to support findings (Benbasat et al. 1987 ; Yin 2018 ). However, in our own research experience, we have come across numerous IS publications with a limited number of sources of evidence per case, such as a single interview per case. Some researchers refer to these studies as mini case studies (e.g., McBride 2009 ; Weill and Olson 1989 ), while others refer to them as multiple mini cases (e.g., Eisenhardt 1989 ). We were unable to find a definition or conceptualisation of this type of case study. Therefore, we will refer to this type of case study as a multiple mini case study (MMCS). Interestingly, many researchers use these MMCSs to study emerging and innovative phenomena.

From a methodological perspective, multiple case study publications with limited sources of evidence, also known as MMCSs, may face criticism for their lack of rigour (Dubé and Paré 2003 ). Alternatively, they may be referred to as “marginal case studies” (Piekkari et al. 2009 , p. 575) if they fail to establish a connection between theory and empirical evidence, provide only limited context, or merely offer illustrative aspects (Piekkari et al. 2009 ). IS scholars advocate conducting case study research in a mindful manner by balancing methodological blueprints and justified design choices (Keutel et al. 2014 ). Consequently, we propose MMCSs as a mindful approach with the potential for rigour, distinguishing them from marginal case studies. The following research question guides our study:

RQ: How can researchers rigorously conduct MMCSs in the IS discipline?

As shown in Fig.  1 , we develop an analytical framework by synthesising methodological guidance on how to rigorously conduct multiple case study research. We then address three aspects of our research question: For aspect (1), we analyse published MMCSs in the IS discipline to derive a "Research in Practice" definition of MMCSs and research situations for MMCSs. For aspect (2), we use the analytical framework to analyse how researchers in the IS discipline ensure that existing MMCSs follow a rigorous methodology. For aspect (3), we discuss the methodological findings about rigorous MMCSs in order to derive methodological guidelines for MMCSs that researchers in the IS discipline can follow.

Overview of the research approach

We approach these aspects by introducing the conceptual foundation for case study research in Sect.  2 . We define commonly accepted criteria for ensuring validity in case study research, introduce the concept of MMCSs, and distinguish them from other types of case studies. Furthermore, as a basis for analysis, we present an analytical framework of methodological steps and options for the rigorous conduct of multiple case study research. Section  3 presents our methodological approach to identifying published MMCSs in the IS discipline. In Sect.  4 , we first define MMCSs from a research in practice perspective (Sect.  4.1 ). Second, we present an overview of methodological options for rigorous MMCSs based on our analytical framework (Sect.  4.2 ). In Sect.  5 , we differentiate MMCSs from other research approaches, identify research situations of MMCSs (i.e., to study emerging and innovative phenomena), and provide guidance on how to ensure rigour in MMCSs. In our conclusion, we clarify the limitations of our study and provide an outlook for future research with MMCSs.

2 Conceptual foundation

2.1 case study research.

Case study research is about understanding phenomena by studying one or multiple cases in their context. Creswell and Poth ( 2016 ) define it as an “approach in which the investigator explores a bounded system (a case) or multiple bounded systems (cases) over time, through detailed, in-depth data collection” (p. 73). Therefore, it is suitable for complex topics with little available knowledge, needing an in-depth investigation, or where the research subject is inseparable from its context (Paré 2004 ). Additionally, Yin ( 2018 ) states that case study research is useful if the research focuses on contemporary events where no control of behavioural events is required. Typically, this type of research is most suitable for how and why research questions (Yin 2018 ). Eventually, the inferences from case study research are based on analytic or logical generalisation (Yin 2018 ). Instead of drawing conclusions from a representative statistical sample towards the population, case study research builds on analytical findings from the observed cases (Dubois and Gadde 2002 ; Eisenhardt and Graebner 2007 ). Case studies can be descriptive, exploratory, or explanatory (Dubé and Paré 2003 ).

The contribution of research to theory can be divided into the steps of theory building , development and testing , which is a continuum (Ridder 2017 ; Welch et al. 2011 ), and case studies are useful at all stages (Ridder 2017 ). In theory building, there is no theory to explain a phenomenon, and the researcher identifies new concepts, constructs, and relationships based on the data (Ridder 2017 ). In theory development, a tentative theory already exists that is extended or refined (e.g., by adding new antecedents, moderators, mediators, and outcomes) (Ridder 2017 ). In theory testing, an existing theory is challenged through empirical investigation (Ridder 2017 ).

In case study research, there are different paradigms for obtaining research results, either positivist or interpretivist (Dubé and Paré 2003 ; Orlikowski and Baroudi 1991 ). The positivist paradigm assumes that a set of variables and relationships can be objectively identified by the researcher (Orlikowski and Baroudi 1991 ). In contrast, the interpretivist paradigm assumes that the results are inherently rooted in the researcher’s worldview (Orlikowski and Baroudi 1991 ). Nowadays, researchers find that there are similar numbers of positivist and interpretivist case studies in the IS discipline compared to almost 20 years ago when positivist research was perceived as dominant (Keutel et al. 2014 ; Klein and Myers 1999 ). As we aim to understand how to conduct MMCSs rigorously, we focus on methodological guidance for positivist case study research.

The literature proposes a four-phased approach to conducting a case study: (1) the definition of the research design, (2) the data collection, (3) the data analysis, and (4) the composition (Yin 2018 ). Table 1 provides an overview and explanation of the four phases.

Case studies can be classified based on their depth and breadth, as shown in Fig.  2 . We can distinguish five types of case studies: in-depth single case studies , marginal case studies , multiple case studies , MMCSs , and extensive in-depth multiple case studies . Each type has distinct characteristics, yet the boundaries between the different types of case studies is blurred. Except for the marginal case studies, the italic references in Fig.  2 are well-established publications that define the respective type and provide methodological guidance. The shading is to visualise the different types of case studies. The italic references in Fig.  2 for marginal case studies refer to publications that conceptualise them.

Simplistic conceptualisation of MMCS

In-depth single case studies focus on a single bounded system as a case (Creswell and Poth 2016 ; Paré 2004 ; Yin 2018 ). According to the literature, a single case study should only be used if a case meets one or more of the following five characteristics: it is a critical, unusual, common, revelatory, or longitudinal case (Benbasat et al. 1987 ; Yin 2018 ). Single case studies are more often used for descriptive research (Dubé and Paré 2003 ).

A second type of case studies are marginal case studies , which generally have low depth (Keutel et al. 2014 ; Piekkari et al. 2009 ). Marginal case studies lack a clear link between theory and empirical evidence, a clear contextualisation of the case, and are often used for illustration purposes (Keutel et al. 2014 ; Piekkari et al. 2009 ). Therefore, marginal case studies provide only marginal insights with a lack of generalisability.

In contrast, multiple case studies employ multiple cases to obtain a broader picture of the researched phenomenon from different perspectives (Creswell and Poth 2016 ; Paré 2004 ; Yin 2018 ). These multiple case studies are often considered to provide more robust results due to the multiplicity of their insights (Eisenhardt and Graebner 2007 ). However, often discussed criticisms of multiple case studies are high costs, difficult access to multiple sources of evidence for each case, and long duration (Dubé and Paré 2003 ; Meredith 1998 ; Voss et al. 2002 ). Eisenhardt ( 1989 ) considers four to ten in-depth cases as a suitable number of cases for multiple case study research. With fewer than four cases, the empirical grounding is less convincing, and with more than ten cases, researchers quickly get overwhelmed by the complexity and volume of data (Eisenhardt 1989 ). Therefore, methodological literature views extensive in-depth multiple case studies as almost infeasible due to their high complexity and resource demands, which can easily overwhelm the research team and the readers (Stake 2013 ). Hence, we could not find a methodological publication outlining the approach for this case study type.

To solve the complexity and resource issues for multiple case studies, a new phenomenon has emerged: MMCS . An MMCS is a special type of multiple case study that focuses on an investigation's breadth by using a relatively high number of cases while having a somewhat limited depth per case. We characterise breadth not only by the number of cases but also by the variety of the cases. Even though there is no formal conceptualisation of the term, we understand MMCSs as a type of multiple case study research with few sources of evidence per case. Due to the limited depth per case, one can overcome the resource and complexity issues of classical multiple case studies. However, having only some sources of evidence per case may be considered a threat to rigour. Therefore, in this publication, we provide suggestions on how to address these threats.

2.2 Rigour in case study research

Rigour is essential for case study research (Dubé and Paré 2003 ; Yin 2018 ) and, in the early 2000s, researchers criticised case study research for inadequate rigour (e.g., Dubé and Paré 2003 ; Gibbert et al. 2008 ). Based on this, various methodological publications provide guidance for rigorous case study research (e.g., Dubé and Paré 2003 ; Gibbert et al. 2008 ).

Methodological literature proposes four criteria to ensure rigour in case study research: Construct validity , internal validity , external validity , and reliability (Dubé and Paré 2003 ; Gibbert et al. 2008 ; Yin 2018 ). Table 2 outlines these criteria and states in which research phase they should be addressed (Yin 2018 ). Methodological literature agrees that all four criteria must be met for rigorous case study research (Dubé and Paré 2003 ).

The methodological literature discusses multiple options for achieving rigour in case study research (e.g., Benbasat et al. 1987 ; Dubé and Paré 2003 ; Eisenhardt 1989 ; Yin 2018 ). We aggregated guidance from multiple sources by conducting a cross-disciplinary literature review to build our analytical foundation (cf. Fig. 1 ). This literature review aims to identify the most relevant multiple case study methodology publications from a cross-disciplinary and IS-specific perspective. We focus on the most cited methodology publications, while being aware that this may over-represent disciplines with a higher number of case study publications. However, this approach helps to capture an implicit consensus among case study researchers on how to conduct multiple case studies rigorously. The literature review produced an analytical framework of methodological steps and options for conducting multiple case studies rigorously. Appendix A Footnote 1 provides a detailed documentation of the literature review process. The analytical framework derived from the set of methodological publications is presented in Table  3 . We identified required and optional steps for each research stage. The analytical framework is the basis for the further analysis of MMCS and an explanation of all methodological steps is provided in Appendix B. Footnote 2

3 Research methodology

For our research, we analysed published MMCSs in the IS discipline with the goal of understanding how these publications ensured rigour. This section outlines the methodology of how we identified our MMCS publications.

First, we searched bibliographic databases and citation indexing services (Vom Brocke et al. 2009 ; Vom Brocke et al. 2015 ) to retrieve IS-specific MMCSs (Hanelt et al. 2015 ). As shown in Fig.  3 , we used two sets of keywords, the first set focusing on multiple case studies and the second set explicitly on mini case studies. We decided to follow this approach as many MMCSs are positioned as multiple case studies, avoiding the connotation “mini” or “short”. We restricted our search to completed research publications written in English from litbaskets.io size “S”, a set of 29 highly ranked IS journals (Boell and Wang 2019 ) Footnote 3 and leading IS conference proceedings from AMCIS, ECIS, HICSS, ICIS, and PACIS (published until end of June 2023). We focused on these outlets, as they can be taken as a representative sample of high quality IS research (Gogan et al. 2014 ; Sørensen and Landau 2015 ).

The search process for published MMCSs in the IS discipline

Second, we screened the obtained set of IS publications to identify MMCSs. We only included publications with positivist multiple cases where the majority of cases was captured with only one primary source of evidence. Further, we excluded all publications which were interview studies rather than case studies (i.e., they do not have a clearly defined case). In some cases, it was unclear from the full text whether a publication fulfils this requirement. Therefore, we contacted the authors and clarified the research methodology with them. Eventually, our final set contained 50 publications using MMCSs.

For qualitative data analysis, we employed axial coding (Recker 2012 ) based on the pre-defined analytical framework shown in Table  3 . For the coding, we followed the explanations of the authors in the manuscripts. The coding was conducted and reviewed by two of the authors. We coded the first five publications of the set of IS MMCS publications together and discussed our decisions. After the initial coding was completed, we checked the reliability and validity by re-coding a sample of the other author’s set. In this sample, we achieved inter-coder reliability of 91% as a percent agreement in the decisions made (Nili et al. 2020 ). Hence, we consider our coding as highly consistent.

In the results section, we illustrate the chosen methodological steps for each MMCS type (descriptive, exploratory, and explanatory). For this purpose, we selected three publications based on two criteria: only journal publications, as they have more details about their methodological steps and publications which applied most of the analytical framework’s methodology steps. This led to three exemplary IS MMCS publications: (1) McBride ( 2009 ) for descriptive MMCSs, (2) Baker and Niederman ( 2014 ) for exploratory MMCSs, and (3) van de Weerd et al. ( 2016 ) for explanatory MMCSs.

4.1 MMCS from a “Research in Practice" perspective

In this section, we explain MMCSs from a "Research in Practice" perspective and identify different types based on our sample of 50 MMCS publications. As outlined in Sect.  2.1 , an MMCS is a special type of a multiple case study, which focuses on an investigation’s breadth by using a relatively high number of cases while having a limited depth per case. In the most extreme scenario, an MMCS only has one source of evidence per case. Moreover, breadth is not only characterised by the number of cases, but also by the variety of the cases. MMCSs have been used widely but hardly labelled as such, i.e., only 10 of our analysed 50 MMCS publications explicitly use the terms mini or short case in the manuscript . Multiple case study research distinguishes between descriptive, exploratory, and explanatory case studies (Dubé and Paré 2003 ). The MMCSs in our sample follow the same classification with three descriptive, 40 exploratory, and seven explanatory MMCSs. Descriptive and exploratory MMCSs are used in the early stages of research , and exploratory and explanatory MMCSs are used to corroborate findings .

Descriptive MMCSs provide little information on the methodological steps for the design, data collection, analysis, and presentation of results. They are used to illustrate novel phenomena and create research questions, not solutions, and can be useful for developing research agendas (e.g., McBride 2009 ; Weill and Olson 1989 ). The descriptive MMCS publications analysed contained between four to six cases, with an average of 4.6 cases per publication. Of the descriptive MMCSs analysed, one did not state research questions, one answered a how question and the third answered how and what questions. Descriptive MMCSs are illustrative and have a low depth per case, resulting in the highest risk of being considered a marginal case study.

Exploratory MMCSs are used to explore new phenomena quickly, generate first research results, and corroborate findings. Most of the analysed exploratory MMCSs answer what and how questions or combinations. However, six publications do not explicitly state a research question, and some MMCSs use why, which, or whether research questions. The analysed exploratory MMCSs have three to 27 cases, with an average of 10.2 cases per publication. An example of an exploratory MMCS is the study by Baker and Niederman ( 2014 ), who explore the impacts of strategic alignment during merger and acquisition (M&A) processes. They argue that previous research with multiple case studies (mostly with  three cases) shows some commonalities, but much remains unclear due to the low number of cases. Moreover, they justify the limited depth of their research with the “proprietary and sensitive nature of the questions” (Baker and Niederman 2014 , p. 123).

Explanatory MMCSs use an a priori framework with a relatively high number of cases to find groups of cases that share similar characteristics. Most explanatory MMCSs answer how questions, yet some publications answer what, why, or combinations of the three questions. The analysed explanatory MMCSs have three to 18 cases, with an average of 7.2 cases per publication. An example of an explanatory MMCS publication is van de Weerd et al. ( 2016 ), who researched the influence of organisational factors on the adoption of Software as a Service (SaaS) in Indonesia.

4.2 Applied MMCS methodology in IS publications

4.2.1 overarching.

In the following sections, we present the results of our analysis. For this purpose, we mapped our 50 IS MMCS publications to the methodological options (Table  3 ) and present one example per MMCS type. We extended some methodological steps with options from methodology-in-use. A full coding table can be found in Appendix D Footnote 4 . Tables 4 , 5 , 6 and 7 summarise the absolute and percentual occurrences of each methodological option in descriptive, exploratory, and explanatory IS MMCS publications. All tables are structured in the same way and show the number of absolute and, in parentheses, the percentual occurrences of each methodological option. The percentages may not add up to 100% due to rounding. The bold numbers show the most common methodological option for each MMCS type and step. Most publications were classified in previously identified options. Some IS MMCS publications lacked detail on methodological steps, so we classified them as "step not evident". Only 16% (8 out of 50) explained how they addressed validity and reliability threats.

4.2.2 Research design phase

There are six methodological steps in the research design phase, as shown in Table  4 . Descriptive MMCSs usually define the research question (2 out of 3, 67%), clarify the unit of analysis (2 out of 3, 67%), bound the case (2 out of 3, 67%), or specify an a priori theoretical framework (2 out of 3, 67%). The case replication logic is mostly not evident (2 out of 3, 67%). Descriptive MMCS use a criterion-based selection (1 out of 3, 33%), a maximum variation selection (1 out of 3, 33%), or do not specify the selection logic (1 out of 3, 33%). Descriptive MMCSs have a high risk of becoming a marginal case study due to their illustrative nature–our chosen example is not different. McBride ( 2009 ) does not define the research question, does not have a priori theoretical framework, nor does he justify the case replication and the case selection logic. However, he clarifies the unit of analysis and extensively bounds each case with significant context about the case organisation and its setup.

The majority of exploratory MMCSs define the research question (34 out of 40, 85%) clarify the unit of analysis (35 out of 40, 88%), and specify an a priori theoretical framework (33 out of 40, 83%). However, only a minority (6 out of 40, 15%) follow the instructions of bounding the case or justify the case replication logic (13 out of 40, 33%). The most used case selection logic is the criterion-based selection (23 out of 40, 58%), followed by step not evident (5 out of 40, 13%), other selection approaches (3 of 40, 13%), maximum variation selection (3 out of 40, 13%), a combination of approaches (2 out of 40, 5%), snowball selection (2 out of 40, 5%), typical case selection (1 out of 40, 3%), and convenience-based selection (1 out of 40, 3%). Baker and Niederman ( 2014 ) build their exploratory MMCS on previous multiple case studies with three cases that showed ambiguous results. Hence, Baker and Niederman ( 2014 ) formulate three research objectives instead of defining a research question. They clearly define the unit of analysis (i.e., the integration of the IS function after M&A) but lack the bounding of the case. The authors use a rather complex a priori framework, leading to a high number of required cases. This a priori framework is also used for the “theoretical replication logic [to choose] conforming and disconfirming cases” (Baker and Niederman 2014 , p. 116). A combination of maximum variation and snowball selection is used to select the cases (Baker and Niederman 2014 ). The maximum variation is chosen to get evidence for all elements of their rather complex a priori framework (i.e., the breadth), and the snowball sampling is chosen to get more details for each framework element.

All explanatory MMCS s define the research question, clarify the unit of analysis, and specify an a priori theoretical framework. However, only one (14%) bounds the case. The case replication logic is mostly a mixture of theoretical and literal replication (3 out of 7, 43%) and one (14%) MMCS does a literal replication. For 43% (3 out of 7) of the publications, the step is not evident. Most explanatory MMCSs use criterion-based selection (4 out of 7, 57%), followed by maximum variation selection (2 out of 7, 29%) and snowball selection (1 out of 7, 14%). In their publication, van de Weerd et al. ( 2016 ) define the research question and clarify the unit of analysis (i.e., the influence of organisational factors on SaaS adoption in Indonesian SMEs). Further, they specify an a priori framework (i.e., based on organisational size, organisational readiness, and top management support) to target the research (van de Weerd et al. 2016 ). A combination of theoretical (between the groups of cases) and literal (within the groups of cases) replication was used. To strengthen the findings, van de Weerd et al. ( 2016 ) find at least one other literally replicated case for each theoretically replicated case.

To summarize this phase, we see that in all three types of MMCSs, the majority of publications define the research question, clarify the unit of analysis, and specify an a priori theoretical framework. Moreover, descriptive MMCSs are more likely to bound the case than exploratory and explanatory MMCSs. However, only a minority across all MMCSs justify the case replication logic, whereas the majority does not. Most MMCSs justify the case selection logic, with criterion-based case selection being the most often applied methodological option.

4.2.3 Data collection phase

In the data collection phase, there are four methodological steps, as summarised in Table  5 .

One descriptive MMCS applies triangulation via multiple sources, whereas for the majority (2 out of 3, 67%), the step is not evident. One (33%) of the analysed descriptive MMCSs creates a full chain of evidence, none creates a case study database, and one (33%) uses a case study protocol. McBride ( 2009 ) applies triangulation via multiple sources, as he followed “up practitioner talks delivered at several UK annual conferences” (McBride 2009 , p. 237). Therefore, we view the follow-up interviews as the primary source of evidence per case, as dedicated questions to the unit of analysis can be asked per case. Triangulation via multiple sources was then conducted by combining practitioner talks and documents with follow-up interviews. McBride ( 2009 ) does not create a full chain of evidence, a case study database, nor a case study protocol. This design decision might be rooted in the objective of a descriptive MMCS to illustrate and open up new questions rather than find clear solutions (McBride 2009 ).

Most exploratory MMCSs triangulate via multiple sources (20 out of 40, 50%) or via multiple investigators (4 out of 40, 10%). Eight (20%) exploratory MMCSs apply multiple triangulation types and for eight (20%), no triangulation is evident. At first glance, a triangulation via multiple sources may seem contradictory to the definition of MMCSs–yet it is not. MMCSs that triangulate via multiple sources have one source per case as the primary, detailed evidence (e.g., an interview), which is combined with easily available supplementary sources of evidence (e.g., public reports and documents (Baker and Niederman 2014 ), press articles (Hahn et al. 2015 ), or online data (Kunduru and Bandi 2019 )). As this leads to multiple sources of evidence, we understand this as a triangulation via multiple sources; however, on a different level than triangulating via multiple in-depth interviews per case. Only a minority of exploratory MMCSs create a full chain of evidence (14 out of 40, 35%), and a majority (23 out of 40, 58%) use a case study database or a case study protocol (20 out of 40, 50%). Baker and Niederman ( 2014 ) triangulate with multiple sources (i.e., financial reports as supplementary sources) to increase the validity of their research. Further, the authors create a full chain of evidence from their research question through an identical interview protocol to the case study’s results. For every case, an individual case report is created and stored in the case study database (Baker and Niederman 2014 ).

All explanatory MMCSs triangulate during the data collection phase, either via multiple sources (2 out of 7, 29%) or a combination of multiple investigators and sources (5 out of 7, 71%). Interestingly, only three explanatory MMCSs (43%) create a full chain of evidence. All create a case study database (7 out of 7, 100%) and the majority creates a case study protocol (6 out of 7, 86%). In their explanatory MMCS, van de Weerd et al. ( 2016 ) use semi-structured interviews as the primary data collection method. The interview data is complemented “with field notes and (online) documentation” (van de Weerd et al. 2016 , p. 919), e.g., data from corporate websites or annual reports. Moreover, a case study protocol and a case study database in NVivo are created to increase reliability.

To summarise the data collection phase, we see that most (40 out of 50, 80%) of MMCSs apply some type of triangulation. However, only 36% (18 out of 50) of the analysed MMCSs create a full chain of evidence. Moreover, descriptive MMCSs are less likely to create a case study database (0 out of 3, 0%) or a case study protocol (1 out of 3, 33%). In contrast, most exploratory and explanatory MMCS publications create a case study database and case study protocol.

4.2.4 Data analysis phase

There are three methodological steps (cf. Table 6 ) for the data analysis phase, each with multiple methodological options.

One descriptive MMCS (33%) corroborates findings through triangulation, and two do not (67%). Further, one (33%) uses a rich description of findings as other corroboration approaches, whereas for the majority (2 out of 3, 67%), the corroboration with other approaches is not evident. Descriptive MMCSs mostly do not define their within-case analysis strategy (2 out of 3, 67%). However, pre-defined patterns are used to conduct a cross-case analysis (2 out of 3, 67%). In the data analysis, McBride ( 2009 ) triangulates via multiple sources of evidence (i.e., talks at practitioner conferences and resulting follow-up interviews), but does not apply other corroboration approaches or provides methodological explanations for the within or cross-case analysis. This design decision might be rooted in the illustrative nature of his descriptive MMCS and the focus on analysing each case standalone.

Exploratory MMCSs mostly corroborate findings through a combination of triangulation via multiple investigators and sources (15 out of 40, 38%) or triangulation via multiple sources (9 out of 40, 23%). However, for ten (25%) exploratory MMCSs, this step is not evident. For the other corroboration approaches, a combination of approaches is mostly used (15 out of 40, 38%), followed by rich description of findings (11 out of 40, 28%), peer review (6 out of 40, 15%), and prolonged field visits (1 out of 40, 3%). For five (13%) publications, other corroboration approaches are not evident. Pattern matching (17 out of 40, 43%) and explanation building (5 out of 40, 13%) are the most used methodological options for the within-case analysis. To conduct a cross-case analysis, 11 (28%) MMCSs use a comparison of pairs or groups of cases, nine (23%) pre-defined patterns, and six (15%) structure their data along themes. Interestingly, for 14 (35%) exploratory MMCSs, no methodological step to conduct the cross-case analysis is evident. Baker and Niederman ( 2014 ) use a combination of triangulation via multiple investigators (“The interviews were coded by both researchers independently […], with a subsequent discussion to reach complete agreement” (Baker and Niederman 2014 , p. 117)) and sources to increase internal validity. Moreover, the authors use a rich description of the findings. An explanation-building strategy is used for the within-case analysis, and the cross-case analysis is done based on pre-defined patterns (Baker and Niederman 2014 ). This decision for the cross-case analysis is justified by a citation of Dubé and Paré ( 2003 , p. 619), who see it as “a form of pattern-matching in which the analysis of the case study is carried out by building a textual explanation of the case.”

Explanatory MMCSs corroborate findings through a triangulation via multiple sources (4 out of 7, 57%) or a combination of multiple investigators and sources (3 out of 7, 43%). For the other corroboration approaches, a rich description of findings (3 out of 7, 43%), a combination of approaches (3 out of 7, 43%), or peer review (1 out of 7, 14%) are used. To conduct a within-case analysis, pattern matching (5 out of 7, 71%) or explanation building (1 out of 7, 14%) are used. For the cross-case analysis, pre-defined patterns (3 out of 7, 43%) and a comparison of pairs or groups of cases (2 out of 7, 29%) are used; yet, for two (29%) explanatory MMCSs a cross-case analysis step is not evident. van de Weerd et al. ( 2016 ) corroborate their findings through a triangulation via multiple sources, a combination of rich description of findings and solicitation of participants’ views (“summarizing the interview results of each case company for feedback and approval” (van de Weerd et al. 2016 , p. 920)) as other corroboration approaches. Moreover, for the within-case analysis, the authors “followed an explanation-building procedure to strengthen […] [the] internal validity” (van de Weerd et al. 2016 , p. 920). For the cross-case, the researchers compare groups of cases. They refer to this approach as an informal qualitative comparative analysis.

To summarize the results of the data analysis phase, we see that some type of triangulation is used by most of the MMCSs, with source triangulation (alone or in combination with another approach) being the most often used methodological option. For the within-case analysis, pattern matching (22 of 50, 44%) is the most often used methodological option. For the cross-case analysis, pre-defined patterns are most often used (14 out of 50, 28%). However, depending on the type of MMCS, there are differences in the options used and some methodological options are never used (e.g., time-series analysis and solicitation of participants’ views).

4.2.5 Composition phase

We can find two methodological steps for the composition phase, as summarized in Table  7 .

Descriptive MMCSs do not apply triangulation in the composition phase (3 out of 3, 100%), nor do they use the methodological step to let key informants review the draft of the case study report (3 of 3, 100%). Also, the descriptive MMCS by McBride ( 2009 ) does not apply any of the methodological steps.

Exploratory MMCSs mostly use triangulation via multiple sources (25 out of 40, 63%), a combination of multiple sources and theories (2 out of 40, 5%), triangulation via multiple investigators (1 out of 40, 3%), and a combination of multiple sources and methods (1 out of 40, 3%). However, for 11 (28%) exploratory MMCS publications, no triangulation step is evident. Moreover, the majority (24 out of 40, 85%) do not let key informants review a draft of the case study report. Baker and Niederman ( 2014 ) do not use triangulation in the composition phase nor let key informants review the draft of the case study report. An example of an exploratory publication that applies both methodological steps is the publication by Kurnia et al. ( 2015 ). The authors triangulate via multiple sources and let key informants review their interview transcripts and the case study report to increase construct validity.

Explanatory MMCSs mostly use triangulation via multiple sources (5 out of 7, 71%) and for two (29%), the step is not evident. Furthermore, only two MMCS (29%) publications let key informants review the draft of the case study report, whereas the majority (5 out of 7, 71%) do not. In their publication , van de Weerd et al. ( 2016 ) use both methodological steps of the composition phase. The authors triangulate via multiple sources by presenting interview snippets from different cases for each result in the case study manuscript. Moreover, each case and the final case study report were shared with key informants for review and approval to reduce the risk of misinterpretations and increase construct validity.

To summarize, most exploratory and explanatory MMCSs use triangulation in the composition phase, whereas descriptive MMCSs do not. Moreover, only a fraction of all MMCSs let key informants review a draft of the case study report (8 out of 50, 16%).

5 Discussion

5.1 mmcs from a “research in practice" perspective, 5.1.1 delineating mmcs from other research approaches.

In this section, we delineate MMCSs from related research approaches. In the subsequent sections, we outline research situations for which MMCSs can be used and the benefits MMCSs provide.

Closely related research approaches from which we delineate MMCSs are multiple case studies , interviews, and vignettes . As shown in Fig.  2 , MMCSs differ from multiple case studies in that they focus on breadth by using a high number of cases with limited depth per case. In the most extreme situation, an MMCS only has one primary source of evidence per case. Moreover, MMCSs can also consider a greater variety of cases. In contrast, multiple case studies have a high depth per case and multiple sources of evidence per case to allow for a source triangulation (Benbasat et al. 1987 ; Yin 2018 ). Moreover, multiple case studies mainly focus on how and why research questions (Yin 2018 ), whereas MMCSs can additionally answer what, whether, and which research questions. The rationale why MMCSs are used for more types of research questions is their breadth, allowing them to also answer rather explorative research questions.

Distinguishing MMCSs from interviews is more difficult . Yet, we see two differences. First, interview studies do not have a clear unit of analysis. Interview studies may choose interviewees based on expertise (expert interviews), whereas case study researchers select informants based on the ability to inform about the case (key informants) (Yin 2018 ). Most of the 50 analysed MMCS (88%) specify their unit of analysis. Second, MMCSs can use multiple data collection methods (e.g., observations, interviews, documents), while interviews only use one (the interview) (Lamnek and Krell 2010 ). An example showing these delineation difficulties between MMCSs and interviews is the publication of Demlehner and Laumer ( 2020 ). The authors claim to take “a multiple case study approach including 39 expert interviews” (Demlehner and Laumer 2020 , p. 1). However, our criteria classify this as an interview study. Demlehner and Laumer ( 2020 ) contend that the interviewees were chosen using a “purposeful sampling strategy” (p. 5). However, case study research selects cases based on replication logic, not sampling (Yin 2018 ). Moreover, the results are not presented on a per-case basis (as usual for case studies); instead, the findings are presented on an aggregated level, similar to expert interviews. Therefore, we would not classify this publication as an MMCS but find that it is a very good example to discuss this delineation.

MMCSs differ from vignettes, which are used for (1) data collection , (2) data analysis , and (3) research communication (Klotz et al. 2022 ; Urquhart 2001 ). Researchers use vignettes for data collection as stimuli to which participants react (Klotz et al. 2022 ), i.e., a carefully constructed description of a person, object, or situation (Atzmüller and Steiner 2010 ; Hughes and Huby 2002 ). We can delineate MMCS from vignettes for data collection based on this definition. First, MMCSs are not used as a stimulus to which participants can react, as in MMCSs, data is collected without the stimulus requirement. Furthermore, vignettes for data collection are carefully constructed, which contradicts the characteristics of MMCS, that are all based on collected empirical data and not constructed descriptions.

A data analysis vignette is used as a retrospective tool (Klotz et al. 2022 ) and is very short, which makes it difficult to analyse deeper relationships between constructs. MMCSs differ from vignettes for data analysis in two ways. First, MMCSs are a complete research methodology with four steps, whereas vignettes for data analysis cover only one step (the data analysis) (e.g., Zamani and Pouloudi 2020 ). Second, vignettes are too short to conduct a thorough analysis of relationships, whereas MMCSs foster a more comprehensive analysis, allowing for a deeper analysis of relationships.

Finally, a vignette used for research communication “(1) is bounded to a short time span, a location, a special situation, or one or a few key actors, (2) provides vivid, authentic, and evocative accounts of the events with a narrative flow, (3) is rather short, and (4) is rooted in empirical data, sometimes inspired by data or constructed.” (Klotz et al. 2022 , p. 347). Based on the four elements for the vignettes’ definition, we can delineate MMCS from vignettes used for research communication. First, MMCSs are not necessarily bounded to a short time span, location, special situation, or key actors; instead, with MMCSs, a clearly defined case bounded in its context is researched. Second, the focus of MMCSs is not on the narrative flow; instead, the focus is on describing (c.f., McBride ( 2009 )), exploring (c.f., Baker and Niederman ( 2014 )), or explaining (c.f., van de Weerd et al. ( 2016 )) a phenomenon. Third, while MMCSs do not have the depth of multiple case studies, they are much more comprehensive than vignettes (e.g., the majority of analysed publications (42 of 50, 84%) specify an a priori theoretical framework). Fourth, every MMCS must be based on empirical data, i.e., all of our 50 MMCSs collect data for their study and base their results on this data. This is a key difference from vignettes, which can be completely fictitious (Klotz et al. 2022 ).

5.1.2 MMCS research situations

The decision to use an MMCS as a research method depends on the research context. MMCSs can be used in the early stages of research (descriptive and exploratory MMCS) and to corroborate findings (exploratory and explanatory MMCS). Academic literature has yet to agree on a uniform categorisation of research questions. For instance, Marshall and Rossman ( 2016 ) distinguish between descriptive, exploratory, explanatory, and emancipatory research questions. In contrast, Yin ( 2018 ) distinguishes between who , what , where , how , and why questions, where he argues that the latter two are especially suitable for explanatory case study research. MMCSs can answer more types of research questions than Yin ( 2018 ) proposed. The reason for this is rooted in the higher breadth of MMCSs, which allows MMCSs to also answer rather exploratory what , whether , or which questions, besides the how and why questions that are suggested by Yin ( 2018 ).

For descriptive MMCSs , the main goal of the how and what questions is to describe the phenomenon. However, in our sample of analysed MMCSs, the analysis stops after the description of the phenomenon. The main goal of the five types of exploratory MMCS research questions is to investigate little-known aspects of a particular phenomenon. The how and why questions analyse operational links between different constructs (e.g., “How do different types of IS assets account for synergies between business units to create business value?” (Mandrella et al. 2016 , p. 2)). Exploratory what questions can be answered by case study research and other research methods (e.g., surveys or archival analysis) (Yin 2018 ). Nevertheless, all whether and which MMCS research questions can also be re-formulated as exploratory what questions. The reason why many MMCSs answer what , whether , or which research questions lies in the breadth (i.e., higher number and variety of cases) of MMCS, that allow them to answer these rather exploratory research questions to a satisfactory level. Finally, the research questions of the explanatory MMCSs aim to analyse operational links (i.e., how or why something is happening). This is also in line with the findings of Yin ( 2018 ) for multiple case study research. However, for MMCSs, this view must be extended, as explanatory MMCSs are also able to answer what questions. We explain this with the higher breadth of MMCS.

To discuss an MMCS’s contribution to theory, we use the idea of the theory continuum proposed by Ridder ( 2017 ) (cf. Section  2.1 ). Despite being used in the early phase of research (descriptive and exploratory), we do not recommend using MMCSs to build theory . We argue that for theory building, data with “as much depth as […] feasible” (Eisenhardt 1989 , p. 539) is required on a per-case basis. However, a key characteristic of MMCSs is the limited depth per case, which conflicts with the in-depth requirements of theory building. Moreover, a criterion for theory building is that there is no theory available which explains the phenomenon (Ridder 2017 ). Nevertheless, in our analysed MMCSs, 84% (42 out of 50) have an a priori theoretical framework. Furthermore, for theory building, the recommendation is to use between four to ten cases; with more, “it quickly becomes difficult to cope with the complexity and volume of the data” (Eisenhardt 1989 , p. 545). However, a characteristic of MMCSs is to have a relatively high number of cases, i.e., the analysed MMCSs often have more than 20 cases, which is significantly above the recommendation for theory building.

The next phase in the theory continuum is theory development , where a tentative theory is extended or refined (Ridder 2017 ). MMCSs should and are used for theory development, i.e., 84% (42 out of 50) of analysed MMCS publications have an a priori theoretical framework extended and refined using the MMCS. An MMCS example for theory development is the research of Karunagaran et al. ( 2016 ), who use a combination of the diffusion of innovation theory and technology organisation environment framework as tentative theories to research the adoption of cloud computing. As Ridder ( 2017 ) outlined, for theory development, literal replication and pattern matching should be used. Both methodological steps are used by Karunagaran et al. ( 2016 ) to identify the mechanisms of cloud adoption more precisely.

The next step in the theory continuum is theory testing , where existing theory is challenged by finding anomalies that existing theory cannot explain (Ridder 2017 ). The boundaries between theory development and testing are often blurred (Ridder 2017 ). In theory testing, the phenomenon is understood, and the research strategy focuses on testing if the theory also holds under different circumstances, i.e., hypotheses can be formed and tested based on existing theory (Ridder 2017 ). In multiple case study research, theory testing uses theoretical replication with pattern matching or addressing rival explanations (Ridder 2017 ). In our MMCS publications, no publication addresses rival explanations, and only a few apply theoretical replication and pattern matching–yet not for theory testing. A few publications claim to test propositions derived from an a priori theoretical framework (e.g., Schäfferling et al. 2011 ; Spiegel and Lazic 2010 ; Wagner and Ettrich-Schmitt 2009 ). However, these publications either do not state their replication logic (e.g., Spiegel and Lazic 2010 ; Wagner and Ettrich-Schmitt 2009 ) or use a literal replication (e.g., Schäfferling et al. 2011 ), both of which weaken the value of their theory testing.

5.1.3 MMCS research benefits

MMCSs are beneficial in multiple research situations and can be an avenue to address the frequent criticism of multiple case study research of being time-consuming and costly (Voss et al. 2002 ; Yin 2018 ).

Firstly, MMCSs can be used for time-critical topics where it is beneficial to publish results quicker and discuss them instead of conducting in-depth multiple case studies (e.g., COVID-19 (e.g., dos Santos Tavares et al. 2021 ) or emergent technology adoption (e.g., Bremser 2017 )). Especially with COVID-19, research publishing saw a significantly higher speed due to special issues of journals and faster review processes. Further, due to the fast technological advancements, there is a higher risk that the results are obsolete and of less practical use when researched with time-consuming multiple in-depth case studies.

Secondly, MMCSs can be used in research situations when it is challenging to gather in-depth data from multiple sources of evidence for each case due to the limited availability of sources of evidence or limited accessibility of sources of evidence. When researching novel phenomena (e.g., the adoption of new technologies in organisations), managers and decision-makers are usually interviewed as sources of evidence. However, in most organisations, only one (or very few) decision-makers have the ability to inform and should be interviewed, limiting the potential sources of evidence per case. These decision-makers often have limited availability for multiple in-depth interviews. Furthermore, the sources of evidence are often difficult to access, as professional organisations have regulations that prevent sharing documents with researchers.

Thirdly, MMCSs can be beneficial when the research framework is complex and requires many cases for validation (e.g., Baker and Niederman ( 2014 ) validate their rather complex a priori framework with 22 cases) or when previous research has led to contradictory results . Therefore, in both situations, a higher breadth of cases is required to also research combinatorial effects (e.g., van de Weerd et al. 2016 ). However, conducting an in-depth multiple case study would take time and effort. Therefore, MMCSs can be a mindful way to collect many cases, but in the same vein, being time and cost-efficient.

5.2 MMCS research rigour

Table 8 outlines two types of methodological steps for MMCSs. The first are methodological steps, where MMCSs should follow multiple case study methodological guidance (e.g., clarify the unit of analysis ), while the second is unique to MMCSs due to its characteristics. This section focuses on the latter, exploring MMCS characteristics, problems, validity threats, and proposed solutions.

The characteristics of MMCSs of having only one primary source of evidence per case prevents MMCSs from using source triangulation, which is often used in multiple case study research (Stake 2013 ; Voss et al. 2002 ; Yin 2018 ). By only having one source of evidence, researchers can fail to develop a sufficient set of operational measures and instead rely on subjective judgements, which threatens construct validity (Yin 2018 ). The threats to construct validity must be addressed throughout the MMCS research process. To do so, we propose to use easily accessible supplementary data or other triangulation approaches to increase construct validity in a MMCS. For the other triangulation approaches, we see that the majority of publications use supplementary data (e.g., publicly available documents) as further sources of evidence, multiple investigators, multiple methods (e.g., quantitative and qualitative), multiple theories, or combinations of these (cf. Tables 5 , 6 and 7 ). Having one or, in the best case, all of them reduces the risk of reporting spurious relationships and subjective judgements of the researchers, as a phenomenon is analysed from multiple perspectives. Besides the above-mentioned types of triangulation, we propose to apply a new type of triangulation, which is specific to MMCSs and triangulates findings across similar cases combined to groups instead of multiple sources per case. We propose that all reported findings have to be found in more than one case in a group of cases. This is also in line with previous methodological guidelines, which suggest that findings should only be reported if they have at least three confirmations (Stake 2013 ). To triangulate across multiple cases in one group, researchers have to identify multiple similar cases by applying a literal case replication logic to reinforce similar results. One should also apply a theoretical replication to compare different groups of literally replicated cases (i.e., searching for contrary results). Therefore, researchers have to justify their case replication logic . However, in our sample of MMCS, the majority (32 of 50, 64%) does not justify their replication logic, whereas the remaining publications use either literal replication (8 of 50, 16%), theoretical replication (6 of 50, 12%), or a combination (4 of 50, 8%). We encourage researchers to use a combination of literal and theoretical replication because it allows triangulation across different groups of cases. An exemplary MMCS that uses this approach is the publication of van de Weerd et al. ( 2016 ), who use theoretical replication to find cases with different outcomes (e.g., adoption and non-adoption) and use literal replication to find cases with similar characteristics and form groups of them.

Two further methodological steps, which are not exclusive to MMCS but recommended for increasing the construct validity, are creating a chain of evidence and letting key informants review a draft of the case study report . Only 36% (18 out of 50) of the analysed MMCS publications establish a chain of evidence. One reason for this lower usage may be that the majority (35 out of 50, 70%) of the publications analysed are conference proceedings. While we understand that these publications face space limitations, we note that no publication offers a supplementary appendix with in-depth insights. However, we encourage researchers to create a full chain of evidence with as much transparency as possible. Therefore, online directories for supplementary appendices could be a valuable addition. As opposed to a few years ago, these repositories today are widely available and using them for such purposes could become a good research practice for qualitative research. Interestingly, only 16% (8 of 50) analysed MMCS publications let key informants review the draft of the case study report . As MMCSs only have one source of evidence per case, misinterpretations and subjective judgement by the researcher have a significantly higher impact on the results compared to multiple case study research. Therefore, MMCS researchers should let key informants review the case study report before publishing.

MMCSs only have few (one) sources of evidence per case, so the risk of focusing on spurious relationships is higher, threatening internal validity (Dubé and Paré 2003 ). This threat to internal validity must be addressed in the data analysis phase. In the context of MMCSs, researchers may aggregate fewer data points to obtain a within-case overview. Therefore, having a clear perspective of the existing data points and rigorously applying the within-case analysis methodological steps (e.g., pattern matching) is even more critical. However, due to the limited depth of data at MMCSs, the within-case analysis must be combined with an analysis across groups of cases (to allow triangulation via multiple groups of cases). For MMCSs, we propose not doing the cross-case analysis on a per-case basis. Instead, we propose to build groups of similar cases across which researchers could conduct an analysis across groups of cases. This solidifies internal validity in case study research (Eisenhardt 1989 ) by viewing and synthesising insights from multiple perspectives (Paré 2004 ; Yin 2018 ).

Another risk of MMCSs is the relatively high number of cases (i.e., we found up to 27 for exploratory MMCSs) that is higher than Eisenhardt’s ( 1989 ) recommendation of maximal ten cases in multiple case study research. With more than ten in-depth cases, researchers struggled to manage the complexity and data volume, resulting in models with low generalisability and reduced external validity (Eisenhardt 1989 ). We propose to use two methodological steps to address the threat to external validity.

First, like Yin’s ( 2018 ) recommendation to use theory for single case studies, we suggest an a priori theoretical framework for MMCSs. 84% (42 out of 50) of the analysed MMCS publications use such a framework. An a priori theoretical framework has two advantages: it simplifies research by pre-defining constructs and relationships, and it enables analytical techniques like pattern matching. Second, instead of doing the within and then cross-case analysis on a per-case basis, for MMCSs, we propose first doing the within-case analysis and then forming groups of similar cases. Then, the cross-case analysis is performed on the formed groups of cases. To form case groups, replication logic (literal and theoretical) must be chosen carefully. Cross-group analysis (with at least two cases per group) can increase the generalisability of results.

To increase MMCS reliability, a case study database and protocol should be created, similar to multiple case studies. To ensure higher reliability, researchers should document MMCS design decisions in more detail. As outlined in the results section, the documentation on why design decisions were taken is often relatively short and should be more detailed. This call for better documentation is not exclusive to MMCSs, as Benbasat et al. ( 1987 ) and Dubé and Paré ( 2003 ) also criticised this for multiple case study research.To ensure rigour in MMCS, we suggest following the steps for multiple case study research. However, MMCSs have unique characteristics, such as an inability to source triangulate on a per-case level, a higher risk of marginal cases, and difficulty in managing a high number of cases. Therefore, for some methodological steps (cf. Table 8 ), we propose MMCS-specific methodological options. First, MMCS should include supplementary data per case (to increase construct validity). Second, instead of doing a cross-case analysis, we propose to form groups of similar cases and focus on the cross-group analysis (i.e., in each group, there must be at least two cases). Third, researchers should justify their case replication logic , i.e., a combination of theoretical replication (to form different groups) and literal replication (to find the same cases within groups) should be conducted to allow for this cross-group analysis.

6 Conclusion

Our publication contributes to case study research in the IS discipline and beyond by making four methodological contributions. First, we provide a conceptual definition of MMCSs and distinguish them from other research approaches. Second, we provide a contemporary collection of exemplary MMCS publications and their methodological choices. Third, we outline methodological guidelines for rigorous MMCS research and provide examples of good practice. Fourth, we identify research situations for which MMCSs can be used as a pragmatic and rigorous approach.

Our findings have three implications for research practice: First, we found that MMCSs can be descriptive, exploratory, or explanatory and can be considered as a type of multiple case study. Our set of IS MMCS publications shows that this pragmatic approach is advantageous in three situations. First, for time-sensitive topics, where rapid discussion of results, especially in the early stages of research, is beneficial. Second, when it is difficult to collect comprehensive data from multiple sources for each case, either because of limited availability or limited accessibility to the data source. Third, in situations where the research setting is complex, many cases are needed to validate effects (e.g., combinatorial effects) or previous research has produced conflicting results. It is important, however, that the pragmatism of the MMCS should not be misunderstood as a lack of methodological rigour.

Second, we have provided guidelines that researchers can follow to conduct MMCSs rigorously. As we observe an increasing number of MMCSs being published, we encourage their authors to clarify their methodological approach by referring to our analytical MMCS framework. Our analytical framework helps researchers to justify their approach and to distinguish it from approaches that lack methodological rigour.

Third, throughout our collection of MMCS publications, we contacted several authors to clarify their case study research methodology. In many cases, these publications lacked critical details that would be important to classify them as MMCS or marginal cases. Many researchers responded that some details were not mentioned due to space limitations. While we understand these constraints, we suggest that researchers still present these details, for example, by considering online appendices in research repositories.

Our paper has five limitations that could be addressed by future research. First, we focus exclusively on methodological guidelines for positivist multiple case study research. Therefore, we have not explicitly covered methodological approaches from other research paradigms.

Second, we aggregated methodological guidance on multiple case study research from the most relevant publications by citation count only. As a result, we did not capture evidence from publications with far fewer citations or that are relevant in specific niches. However, our design choice is still justified as the aim was to identify established and widely accepted methodological strategies to ensure rigour in case study research.

Third, the literature reviews were keyword-based. Therefore, concepts that fall within our understanding of MMCS but do not include the keywords used for the literature search could not be identified. However, due to the different search terms and versatile search approaches, our search should have captured the most relevant contributions.

Fourth, we selected publications from highly ranked IS MMCS publications and proceedings of leading IS conferences to analyse how rigour is ensured in MMCSs in the IS discipline. We therefore excluded all other research outlets. As with the limitations arising from the keyword-based search, we may have omitted IS MMCS publications that refer to short or mini case studies. However, the limitation of our search is justified as it helps us to ensure that all selected publications have undergone a substantial peer review process and qualify as a reference base in IS.

Fifth, we coded our variables based on the characteristics explicitly stated in the manuscript (i.e., if authors position their MMCS as exploratory, we coded it as exploratory). However, for some variables, researchers do not have a consistent understanding (e.g., the discussion of what constitutes exploratory research by cf., Sarker et al. ( 2018 )). Therefore, we took the risk that MMCS may have different understandings of the coded variables.

For the future, our manuscript on positivist MMCSs provides researchers with guidance for an emerging type of case study research. Based on our study, we can identify promising areas for future research. By limiting ourselves to the most established strategies for ensuring rigour, we also invite authors to enrich our methodological guidelines with other, less commonly used steps. In addition, future research could compare the use of MMCSs in IS with other disciplines in order to solidify our findings.

Data availability

Provided at https://doi.org/10.6084/m9.figshare.24916458

The information can be found in the online Appendix: https://doi.org/10.6084/m9.figshare.24916458 .

litbaskets.io is a web interface that allows searching for literature across the top 847 IS journals. It offers ranging from 2XS (Basket of Eight) to 3XL (847) essential IS journals and a full list of 29 journals which are the basis for this study can be found in Appendix C ( https://doi.org/10.6084/m9.figshare.24916458 ).

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Sebastian Käss, Christoph Brosig & Susanne Strahringer

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Käss, S., Brosig, C., Westner, M. et al. Short and sweet: multiple mini case studies as a form of rigorous case study research. Inf Syst E-Bus Manage (2024). https://doi.org/10.1007/s10257-024-00674-2

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Managers spend 20% of their time on average managing team conflict. Over the past three decades, the authors have studied thousands of team conflicts around the world and have identified four common patterns of team conflict. The first occurs when conflict revolves around a single member of a team (20-25% of team conflicts). The second is when two members of a team disagree (the most common team conflict at 35%). The third is when two subgroups in a team are at odds (20-25%). The fourth is when all members of a team are disagreeing in a whole-team conflict (less than 15%). The authors suggest strategies to tailor a conflict resolution approach for each type, so that managers can address conflict as close to its origin as possible.

If you have ever managed a team or worked on one, you know that conflict within a team is as inevitable as it is distracting. Many managers avoid dealing with conflict in their team where possible, hoping reasonable people can work it out. Despite this, research shows that managers spend upwards of 20% of their time on average managing conflict.

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Welcome to our preparation tips for case interviews!  Whether you are just curious about case interviews or are planning to apply for consulting internships or full-time jobs, these tips and resources will help you feel more prepared and confident.

A case interview is a role playing exercise in which an employer assesses how logically and persuasively you can present a case. Rather than seeing if you get the “correct” answer, the objective is to evaluate your thought process. ( Adapted with permission from Case In Point: Complete Case Interview Preparation by Marc Cosentino). 

Case interviews are very commonly used in the interview process for consulting firms and companies in similar industries. In the case interview, you will typically be given a business problem and then asked to solve it in a structured way. Learning this structure takes preparation and practice. You can learn more and practice using the resources listed below.  

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Management Consulted is a FREE resource for Tufts students : case and consulting resources such as 500 sample cases, Case Interview Bootcamp,  Market Sizing Drills, Math Drills, case videos, consulting firm directory, and more

2.) Review additional resources:

• Case in Point – This book, by Marc Cosentino, is a comprehensive guide that walks you through the case interview process from beginning to end. This guide has helped many students over the years and can serve as an excellent foundation for how to approach business problems
• Casequestions.com – The companion website to Marc Cosentino’s book listed above offers preparation for case interviews, along with links to top 50 consulting firms
• Management Consulting Case Interviews: Cracking The Case – tips for case interviews from the other side of the table, from Argopoint, a Boston management consulting firm specializing in legal department consulting for Fortune 500 companies
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Please note you do not have access to teaching notes, development of a dedicated process simulator for the digital twin in apparel manufacturing: a case study.

International Journal of Clothing Science and Technology

ISSN : 0955-6222

Article publication date: 16 May 2024

The purpose of this study is to introduce a dedicated simulator to automatically generate and simulate a balanced apparel assembly line, which is critical to the digital twin concept in apparel manufacturing. Given the low automation level in apparel manufacturing, this is a first step toward the implementation of a smart factory based on cyber-physical systems.

Design/methodology/approach

The mixed task assignment algorithm was implemented to automatically generate a module-based apparel assembly line in the developed simulator. To validate the developed simulator, a case study was conducted using process analysis data of technical jackets obtained from an apparel manufacturer. The case study included three scenarios: calculating the number of workers, selecting orders based on factory capacity and managing unexpected worker absences.

The developed simulator is approximately 97.2% accurate in assigning appropriate tasks to workstations using the mixed task assignment algorithm. The simulator was also found to be effective in supporting decision-making for production planning, order selection and apparel assembly line management. In addition, the module-based line generation algorithm made it easy to modify the assembly line.

Originality/value

This study contributes a novel approach to address the challenge of low automation levels in apparel manufacturing by introducing a dedicated simulator. This dedicated simulator improves the efficiency of virtual apparel assembly line generation and simulation, which distinguishes it from existing commercial simulation software.

• Task assignment algorithm
• Line balancing
• Apparel assembly line
• Automatic assembly line generation
• Apparel manufacturing
• Digital twin

Kim, M. and Kim, S. (2024), "Development of a dedicated process simulator for the digital twin in apparel manufacturing: a case study", International Journal of Clothing Science and Technology , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJCST-01-2024-0017

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Artificial intelligence in strategy

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform .

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?

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Yuval Atsmon: You’re right about the limited adoption. Only 7 percent of respondents to our survey about the use of AI say they use it in strategy or even financial planning, whereas in areas like marketing, supply chain, and service operations, it’s 25 or 30 percent. One reason adoption is lagging is that strategy is one of the most integrative conceptual practices. When executives think about strategy automation, many are looking too far ahead—at AI capabilities that would decide, in place of the business leader, what the right strategy is. They are missing opportunities to use AI in the building blocks of strategy that could significantly improve outcomes.

I like to use the analogy to virtual assistants. Many of us use Alexa or Siri but very few people use these tools to do more than dictate a text message or shut off the lights. We don’t feel comfortable with the technology’s ability to understand the context in more sophisticated applications. AI in strategy is similar: it’s hard for AI to know everything an executive knows, but it can help executives with certain tasks.

When executives think about strategy automation, many are looking too far ahead—at AI deciding the right strategy. They are missing opportunities to use AI in the building blocks of strategy.

Joanna Pachner: What kind of tasks can AI help strategists execute today?

Yuval Atsmon: We talk about six stages of AI development. The earliest is simple analytics, which we refer to as descriptive intelligence. Companies use dashboards for competitive analysis or to study performance in different parts of the business that are automatically updated. Some have interactive capabilities for refinement and testing.

The second level is diagnostic intelligence, which is the ability to look backward at the business and understand root causes and drivers of performance. The level after that is predictive intelligence: being able to anticipate certain scenarios or options and the value of things in the future based on momentum from the past as well as signals picked in the market. Both diagnostics and prediction are areas that AI can greatly improve today. The tools can augment executives’ analysis and become areas where you develop capabilities. For example, on diagnostic intelligence, you can organize your portfolio into segments to understand granularly where performance is coming from and do it in a much more continuous way than analysts could. You can try 20 different ways in an hour versus deploying one hundred analysts to tackle the problem.

Predictive AI is both more difficult and more risky. Executives shouldn’t fully rely on predictive AI, but it provides another systematic viewpoint in the room. Because strategic decisions have significant consequences, a key consideration is to use AI transparently in the sense of understanding why it is making a certain prediction and what extrapolations it is making from which information. You can then assess if you trust the prediction or not. You can even use AI to track the evolution of the assumptions for that prediction.

Those are the levels available today. The next three levels will take time to develop. There are some early examples of AI advising actions for executives’ consideration that would be value-creating based on the analysis. From there, you go to delegating certain decision authority to AI, with constraints and supervision. Eventually, there is the point where fully autonomous AI analyzes and decides with no human interaction.

Because strategic decisions have significant consequences, you need to understand why AI is making a certain prediction and what extrapolations it’s making from which information.

Joanna Pachner: What kind of businesses or industries could gain the greatest benefits from embracing AI at its current level of sophistication?

Yuval Atsmon: Every business probably has some opportunity to use AI more than it does today. The first thing to look at is the availability of data. Do you have performance data that can be organized in a systematic way? Companies that have deep data on their portfolios down to business line, SKU, inventory, and raw ingredients have the biggest opportunities to use machines to gain granular insights that humans could not.

Companies whose strategies rely on a few big decisions with limited data would get less from AI. Likewise, those facing a lot of volatility and vulnerability to external events would benefit less than companies with controlled and systematic portfolios, although they could deploy AI to better predict those external events and identify what they can and cannot control.

Third, the velocity of decisions matters. Most companies develop strategies every three to five years, which then become annual budgets. If you think about strategy in that way, the role of AI is relatively limited other than potentially accelerating analyses that are inputs into the strategy. However, some companies regularly revisit big decisions they made based on assumptions about the world that may have since changed, affecting the projected ROI of initiatives. Such shifts would affect how you deploy talent and executive time, how you spend money and focus sales efforts, and AI can be valuable in guiding that. The value of AI is even bigger when you can make decisions close to the time of deploying resources, because AI can signal that your previous assumptions have changed from when you made your plan.

Joanna Pachner: Can you provide any examples of companies employing AI to address specific strategic challenges?

Yuval Atsmon: Some of the most innovative users of AI, not coincidentally, are AI- and digital-native companies. Some of these companies have seen massive benefits from AI and have increased its usage in other areas of the business. One mobility player adjusts its financial planning based on pricing patterns it observes in the market. Its business has relatively high flexibility to demand but less so to supply, so the company uses AI to continuously signal back when pricing dynamics are trending in a way that would affect profitability or where demand is rising. This allows the company to quickly react to create more capacity because its profitability is highly sensitive to keeping demand and supply in equilibrium.

Joanna Pachner: Given how quickly things change today, doesn’t AI seem to be more a tactical than a strategic tool, providing time-sensitive input on isolated elements of strategy?

Yuval Atsmon: It’s interesting that you make the distinction between strategic and tactical. Of course, every decision can be broken down into smaller ones, and where AI can be affordably used in strategy today is for building blocks of the strategy. It might feel tactical, but it can make a massive difference. One of the world’s leading investment firms, for example, has started to use AI to scan for certain patterns rather than scanning individual companies directly. AI looks for consumer mobile usage that suggests a company’s technology is catching on quickly, giving the firm an opportunity to invest in that company before others do. That created a significant strategic edge for them, even though the tool itself may be relatively tactical.

Joanna Pachner: McKinsey has written a lot about cognitive biases  and social dynamics that can skew decision making. Can AI help with these challenges?

Yuval Atsmon: When we talk to executives about using AI in strategy development, the first reaction we get is, “Those are really big decisions; what if AI gets them wrong?” The first answer is that humans also get them wrong—a lot. [Amos] Tversky, [Daniel] Kahneman, and others have proven that some of those errors are systemic, observable, and predictable. The first thing AI can do is spot situations likely to give rise to biases. For example, imagine that AI is listening in on a strategy session where the CEO proposes something and everyone says “Aye” without debate and discussion. AI could inform the room, “We might have a sunflower bias here,” which could trigger more conversation and remind the CEO that it’s in their own interest to encourage some devil’s advocacy.

We also often see confirmation bias, where people focus their analysis on proving the wisdom of what they already want to do, as opposed to looking for a fact-based reality. Just having AI perform a default analysis that doesn’t aim to satisfy the boss is useful, and the team can then try to understand why that is different than the management hypothesis, triggering a much richer debate.

In terms of social dynamics, agency problems can create conflicts of interest. Every business unit [BU] leader thinks that their BU should get the most resources and will deliver the most value, or at least they feel they should advocate for their business. AI provides a neutral way based on systematic data to manage those debates. It’s also useful for executives with decision authority, since we all know that short-term pressures and the need to make the quarterly and annual numbers lead people to make different decisions on the 31st of December than they do on January 1st or October 1st. Like the story of Ulysses and the sirens, you can use AI to remind you that you wanted something different three months earlier. The CEO still decides; AI can just provide that extra nudge.

Joanna Pachner: It’s like you have Spock next to you, who is dispassionate and purely analytical.

Yuval Atsmon: That is not a bad analogy—for Star Trek fans anyway.

Joanna Pachner: Do you have a favorite application of AI in strategy?

Yuval Atsmon: I have worked a lot on resource allocation, and one of the challenges, which we call the hockey stick phenomenon, is that executives are always overly optimistic about what will happen. They know that resource allocation will inevitably be defined by what you believe about the future, not necessarily by past performance. AI can provide an objective prediction of performance starting from a default momentum case: based on everything that happened in the past and some indicators about the future, what is the forecast of performance if we do nothing? This is before we say, “But I will hire these people and develop this new product and improve my marketing”— things that every executive thinks will help them overdeliver relative to the past. The neutral momentum case, which AI can calculate in a cold, Spock-like manner, can change the dynamics of the resource allocation discussion. It’s a form of predictive intelligence accessible today and while it’s not meant to be definitive, it provides a basis for better decisions.

Joanna Pachner: Do you see access to technology talent as one of the obstacles to the adoption of AI in strategy, especially at large companies?

Yuval Atsmon: I would make a distinction. If you mean machine-learning and data science talent or software engineers who build the digital tools, they are definitely not easy to get. However, companies can increasingly use platforms that provide access to AI tools and require less from individual companies. Also, this domain of strategy is exciting—it’s cutting-edge, so it’s probably easier to get technology talent for that than it might be for manufacturing work.

The bigger challenge, ironically, is finding strategists or people with business expertise to contribute to the effort. You will not solve strategy problems with AI without the involvement of people who understand the customer experience and what you are trying to achieve. Those who know best, like senior executives, don’t have time to be product managers for the AI team. An even bigger constraint is that, in some cases, you are asking people to get involved in an initiative that may make their jobs less important. There could be plenty of opportunities for incorpo­rating AI into existing jobs, but it’s something companies need to reflect on. The best approach may be to create a digital factory where a different team tests and builds AI applications, with oversight from senior stakeholders.

The big challenge is finding strategists to contribute to the AI effort. You are asking people to get involved in an initiative that may make their jobs less important.

Joanna Pachner: Do you think this worry about job security and the potential that AI will automate strategy is realistic?

Yuval Atsmon: The question of whether AI will replace human judgment and put humanity out of its job is a big one that I would leave for other experts.

The pertinent question is shorter-term automation. Because of its complexity, strategy would be one of the later domains to be affected by automation, but we are seeing it in many other domains. However, the trend for more than two hundred years has been that automation creates new jobs, although ones requiring different skills. That doesn’t take away the fear some people have of a machine exposing their mistakes or doing their job better than they do it.

Joanna Pachner: We recently published an article about strategic courage in an age of volatility  that talked about three types of edge business leaders need to develop. One of them is an edge in insights. Do you think AI has a role to play in furnishing a proprietary insight edge?

Yuval Atsmon: One of the challenges most strategists face is the overwhelming complexity of the world we operate in—the number of unknowns, the information overload. At one level, it may seem that AI will provide another layer of complexity. In reality, it can be a sharp knife that cuts through some of the clutter. The question to ask is, Can AI simplify my life by giving me sharper, more timely insights more easily?

Joanna Pachner: You have been working in strategy for a long time. What sparked your interest in exploring this intersection of strategy and new technology?

Yuval Atsmon: I have always been intrigued by things at the boundaries of what seems possible. Science fiction writer Arthur C. Clarke’s second law is that to discover the limits of the possible, you have to venture a little past them into the impossible, and I find that particularly alluring in this arena.

AI in strategy is in very nascent stages but could be very consequential for companies and for the profession. For a top executive, strategic decisions are the biggest way to influence the business, other than maybe building the top team, and it is amazing how little technology is leveraged in that process today. It’s conceivable that competitive advantage will increasingly rest in having executives who know how to apply AI well. In some domains, like investment, that is already happening, and the difference in returns can be staggering. I find helping companies be part of that evolution very exciting.

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