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Case Study – Methods, Examples and Guide

Table of Contents

A case study is an in-depth examination of a single case or a few selected cases within a real-world context. Case study research is widely used across disciplines such as psychology, sociology, business, and education to explore complex phenomena in detail. Unlike other research methods that aim for broad generalizations, case studies offer an intensive understanding of a specific individual, group, event, or situation.

A case study is a research method that involves a detailed examination of a subject (the “case”) within its real-life context. Case studies are used to explore the causes of underlying principles, behaviors, or outcomes, providing insights into the nuances of the studied phenomena. This approach allows researchers to capture a wide array of factors and interactions that may not be visible in other methods, such as experiments or surveys.

Key Characteristics of Case Studies :

• Focus on a specific case, individual, or event.
• Provide in-depth analysis and contextual understanding.
• Useful for exploring new or complex phenomena.
• Generate rich qualitative data that contributes to theory building.

Types of Case Studies

Case studies can be classified into different types depending on their purpose and methodology. Common types include exploratory , descriptive , explanatory , intrinsic , and instrumental case studies.

1. Exploratory Case Study

Definition : An exploratory case study investigates an area where little is known. It helps to identify questions, variables, and hypotheses for future research.

Characteristics :

• Often used in the early stages of research.
• Focuses on discovery and hypothesis generation.
• Helps clarify research questions.

Example : Examining how remote work affects team dynamics in an organization that has recently transitioned to a work-from-home model.

2. Descriptive Case Study

Definition : A descriptive case study provides a detailed account of a particular case, describing it within its context. The goal is to provide a complete and accurate depiction without necessarily exploring underlying causes.

• Focuses on describing the case in detail.
• Provides comprehensive data to paint a clear picture of the phenomenon.
• Helps understand “what” happened without delving into “why.”

Example : Documenting the process and outcomes of a corporate restructuring within a company, describing the actions taken and their immediate effects.

3. Explanatory Case Study

Definition : An explanatory case study aims to explain the cause-and-effect relationships of a particular case. It focuses on understanding “how” or “why” something happened.

• Useful for causal analysis.
• Aims to provide insights into mechanisms and processes.
• Often used in social sciences and psychology to study behavior and interactions.

Example : Investigating why a school’s test scores improved significantly after implementing a new teaching method.

4. Intrinsic Case Study

Definition : An intrinsic case study focuses on a unique or interesting case, not because of what it represents but because of its intrinsic value. The researcher’s interest lies in understanding the case itself.

• Driven by the researcher’s interest in the particular case.
• Not meant to generalize findings to broader contexts.
• Focuses on gaining a deep understanding of the specific case.

Example : Studying a particularly successful start-up to understand its founder’s unique leadership style.

5. Instrumental Case Study

Definition : An instrumental case study examines a particular case to gain insights into a broader issue. The case serves as a tool for understanding something more general.

• The case itself is not the focus; rather, it is a vehicle for exploring broader principles or theories.
• Helps apply findings to similar situations or cases.
• Useful for theory testing or development.

Example : Studying a well-known patient’s therapy process to understand the general principles of effective psychological treatment.

Methods of Conducting a Case Study

Case studies can involve various research methods to collect data and analyze the case comprehensively. The primary methods include interviews , observations , document analysis , and surveys .

1. Interviews

Definition : Interviews allow researchers to gather in-depth information from individuals involved in the case. These interviews can be structured, semi-structured, or unstructured, depending on the study’s goals.

• Develop a list of open-ended questions aligned with the study’s objectives.
• Conduct interviews with individuals directly or indirectly involved in the case.
• Record, transcribe, and analyze the responses to identify key themes.

Example : Interviewing employees, managers, and clients in a company to understand the effects of a new business strategy.

2. Observations

Definition : Observations involve watching and recording behaviors, actions, and events within the case’s natural setting. This method provides first-hand data on interactions, routines, and environmental factors.

• Define the behaviors and interactions to observe.
• Conduct observations systematically, noting relevant details.
• Analyze patterns and connections in the observed data.

Example : Observing interactions between teachers and students in a classroom to evaluate the effectiveness of a teaching method.

3. Document Analysis

Definition : Document analysis involves reviewing existing documents related to the case, such as reports, emails, memos, policies, or archival records. This provides historical and contextual data that can complement other data sources.

• Identify relevant documents that offer insights into the case.
• Systematically review and code the documents for themes or categories.
• Compare document findings with data from interviews and observations.

Example : Analyzing company policies, performance reports, and emails to study the process of implementing a new organizational structure.

Definition : Surveys are structured questionnaires administered to a group of people involved in the case. Surveys are especially useful for gathering quantitative data that supports or complements qualitative findings.

• Design survey questions that align with the research goals.
• Distribute the survey to a sample of participants.
• Analyze the survey responses, often using statistical methods.

Example : Conducting a survey among customers to measure satisfaction levels after a service redesign.

Case Study Guide: Step-by-Step Process

Step 1: define the research questions.

• Clearly outline what you aim to understand or explain.
• Define specific questions that the case study will answer, such as “What factors led to X outcome?”

Step 2: Select the Case(s)

• Choose a case (or cases) that are relevant to your research question.
• Ensure that the case is feasible to study, accessible, and likely to yield meaningful data.

Step 3: Determine the Data Collection Methods

• Decide which methods (e.g., interviews, observations, document analysis) will best capture the information needed.
• Consider combining multiple methods to gather rich, well-rounded data.

Step 4: Collect Data

• Gather data using your chosen methods, following ethical guidelines such as informed consent and confidentiality.
• Take comprehensive notes and record interviews or observations when possible.

Step 5: Analyze the Data

• Organize the data into themes, patterns, or categories.
• Use qualitative or quantitative analysis methods, depending on the nature of the data.
• Compare findings across data sources to identify consistencies and discrepancies.

Step 6: Interpret Findings

• Draw conclusions based on the analysis, relating the findings to your research questions.
• Consider alternative explanations and assess the generalizability of your findings.

Step 7: Report Results

• Write a detailed report that presents your findings and explains their implications.
• Discuss the limitations of the case study and potential directions for future research.

Examples of Case Study Applications

• Objective : To understand the success factors of a high-growth tech company.
• Methods : Interviews with key executives, analysis of internal reports, and customer satisfaction surveys.
• Outcome : Insights into unique management practices and customer engagement strategies.
• Objective : To examine the impact of project-based learning on student engagement.
• Methods : Observations in classrooms, interviews with teachers, and analysis of student performance data.
• Outcome : Evidence of increased engagement and enhanced critical thinking skills among students.
• Objective : To explore the effectiveness of a new mental health intervention.
• Methods : Interviews with patients, assessment of clinical outcomes, and reviews of therapist notes.
• Outcome : Identification of factors that contribute to successful treatment outcomes.
• Objective : To assess the impact of urban development on local wildlife.
• Methods : Observations of wildlife, analysis of environmental data, and interviews with residents.
• Outcome : Findings showing the effects of urban sprawl on species distribution and biodiversity.

Case studies are valuable for in-depth exploration and understanding of complex phenomena within their real-life contexts. By using methods such as interviews, observations, document analysis, and surveys, researchers can obtain comprehensive data and generate insights that are specific to the case. Whether exploratory, descriptive, or explanatory, case studies offer unique opportunities for understanding and discovering practical applications for theories.

• Baxter, P., & Jack, S. (2008). Qualitative Case Study Methodology: Study Design and Implementation for Novice Researchers . The Qualitative Report, 13(4), 544–559.
• Creswell, J. W., & Poth, C. N. (2017). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (4th ed.). SAGE Publications.
• Stake, R. E. (1995). The Art of Case Study Research . SAGE Publications.
• Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). SAGE Publications.
• Thomas, G. (2016). How to Do Your Case Study (2nd ed.). SAGE Publications.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What is a Case Study in Research? Definition, Methods, and Examples

Case study methodology offers researchers an exciting opportunity to explore intricate phenomena within specific contexts using a wide range of data sources and collection methods. It is highly pertinent in health and social sciences, environmental studies, social work, education, and business studies. Its diverse applications, such as advancing theory, program evaluation, and intervention development, make it an invaluable tool for driving meaningful research and fostering positive change.[ 1]  

Table of Contents

What is a Case Study?  

A case study method involves a detailed examination of a single subject, such as an individual, group, organization, event, or community, to explore and understand complex issues in real-life contexts. By focusing on one specific case, researchers can gain a deep understanding of the factors and dynamics at play, understanding their complex relationships, which might be missed in broader, more quantitative studies.  

When to do a Case Study?  

A case study design is useful when you want to explore a phenomenon in-depth and in its natural context. Here are some examples of when to use a case study :[ 2]  

• Exploratory Research: When you want to explore a new topic or phenomenon, a case study can help you understand the subject deeply. For example , a researcher studying a newly discovered plant species might use a case study to document its characteristics and behavior.  
• Descriptive Research: If you want to describe a complex phenomenon or process, a case study can provide a detailed and comprehensive description. For instance, a case study design   could describe the experiences of a group of individuals living with a rare disease.  
• Explanatory Research: When you want to understand why a particular phenomenon occurs, a case study can help you identify causal relationships. A case study design could investigate the reasons behind the success or failure of a particular business strategy.  
• Theory Building: Case studies can also be used to develop or refine theories. By systematically analyzing a series of cases, researchers can identify patterns and relationships that can contribute to developing new theories or refining existing ones.  
• Critical Instance: Sometimes, a single case can be used to study a rare or unusual phenomenon, but it is important for theoretical or practical reasons. For example , the case of Phineas Gage, a man who survived a severe brain injury, has been widely studied to understand the relationship between the brain and behavior.  
• Comparative Analysis: Case studies can also compare different cases or contexts. A case study example involves comparing the implementation of a particular policy in different countries to understand its effectiveness and identifying best practices.  

How to Create a Case Study – Step by Step  

Step 1: select a case  .

Careful case selection ensures relevance, insight, and meaningful contribution to existing knowledge in your field. Here’s how you can choose a case study design :[ 3]  

• Define Your Objectives: Clarify the purpose of your case study and what you hope to achieve. Do you want to provide new insights, challenge existing theories, propose solutions to a problem, or explore new research directions?  
• Consider Unusual or Outlying Cases: Focus on unusual, neglected, or outlying cases that can provide unique insights.  
• Choose a Representative Case: Alternatively, select a common or representative case to exemplify a particular category, experience, or phenomenon.   
• Avoid Bias: Ensure your selection process is unbiased using random or criteria-based selection.  
• Be Clear and Specific: Clearly define the boundaries of your study design , including the scope, timeframe, and key stakeholders.   
• Ethical Considerations: Consider ethical issues, such as confidentiality and informed consent.  

Step 2: Build a Theoretical Framework  

To ensure your case study has a solid academic foundation, it’s important to build a theoretical framework:   

• Conduct a Literature Review: Identify key concepts and theories relevant to your case study .  
• Establish Connections with Theory: Connect your case study with existing theories in the field.  
• Guide Your Analysis and Interpretation: Use your theoretical framework to guide your analysis, ensuring your findings are grounded in established theories and concepts.   

Step 3: Collect Your Data  

To conduct a comprehensive case study , you can use various research methods. These include interviews, observations, primary and secondary sources analysis, surveys, and a mixed methods approach. The aim is to gather rich and diverse data to enable a detailed analysis of your case study .  

Step 4: Describe and Analyze the Case  

How you report your findings will depend on the type of research you’re conducting. Here are two approaches:   

• Structured Approach: Follows a scientific paper format, making it easier for readers to follow your argument.  
• Narrative Approach: A more exploratory style aiming to analyze meanings and implications.  

Regardless of the approach you choose, it’s important to include the following elements in your case study :   

• Contextual Details: Provide background information about the case, including relevant historical, cultural, and social factors that may have influenced the outcome.  
• Literature and Theory: Connect your case study to existing literature and theory in the field. Discuss how your findings contribute to or challenge existing knowledge.  
• Wider Patterns or Debates: Consider how your case study fits into wider patterns or debates within the field. Discuss any implications your findings may have for future research or practice.  

What Are the Benefits of a Case Study   

Case studies offer a range of benefits , making them a powerful tool in research.  

1. In-Depth Analysis  

• Comprehensive Understanding: Case studies allow researchers to thoroughly explore a subject, understanding the complexities and nuances involved.  
• Rich Data: They offer rich qualitative and sometimes quantitative data, capturing the intricacies of real-life contexts.  

2. Contextual Insight  

• Real-World Application: Case studies provide insights into real-world applications, making the findings highly relevant and practical.  
• Context-Specific: They highlight how various factors interact within a specific context, offering a detailed picture of the situation.  

3. Flexibility  

• Methodological Diversity: Case studies can use various data collection methods, including interviews, observations, document analysis, and surveys.  
• Adaptability: Researchers can adapt the case study approach to fit the specific needs and circumstances of the research.  

4. Practical Solutions  

• Actionable Insights: The detailed findings from case studies can inform practical solutions and recommendations for practitioners and policymakers.  
• Problem-Solving: They help understand the root causes of problems and devise effective strategies to address them.  

5. Unique Cases  

• Rare Phenomena: Case studies are particularly valuable for studying rare or unique cases that other research methods may not capture.  
• Detailed Documentation: They document and preserve detailed information about specific instances that might otherwise be overlooked.  

What Are the Limitations of a Case Study   

While case studies offer valuable insights and a detailed understanding of complex issues, they have several limitations .  

1. Limited Generalizability  

• Specific Context: Case studies often focus on a single case or a small number of cases, which may limit the generalization of findings to broader populations or different contexts.  
• Unique Situations: The unique characteristics of the case may not be representative of other situations, reducing the applicability of the results.  

2. Subjectivity  

• Researcher Bias: The researcher’s perspectives and interpretations can influence the analysis and conclusions, potentially introducing bias.  
• Participant Bias: Participants’ responses and behaviors may be influenced by their awareness of being studied, known as the Hawthorne effect.  

3. Time-Consuming  

• Data Collection and Analysis: Gathering detailed, in-depth data requires significant time and effort, making case studies more time-consuming than other research methods.  
• Longitudinal Studies: If the case study observes changes over time, it can become even more prolonged.  

4. Resource Intensive  

• Financial and Human Resources: Conducting comprehensive case studies may require significant financial investment and human resources, including trained researchers and participant access.  
• Access to Data: Accessing relevant and reliable data sources can be challenging, particularly in sensitive or proprietary contexts.  

5. Replication Difficulties  

• Unique Contexts: A case study’s specific and detailed context makes it difficult to replicate the study exactly, limiting the ability to validate findings through repetition.  
• Variability: Differences in contexts, researchers, and methodologies can lead to variations in findings, complicating efforts to achieve consistent results.  

By acknowledging and addressing these limitations , researchers can enhance the rigor and reliability of their case study findings.  

Key Takeaways  

Case studies are valuable in research because they provide an in-depth, contextual analysis of a single subject, event, or organization. They allow researchers to explore complex issues in real-world settings, capturing detailed qualitative and quantitative data. This method is useful for generating insights, developing theories, and offering practical solutions to problems. They are versatile, applicable in diverse fields such as business, education, and health, and can complement other research methods by providing rich, contextual evidence. However, their findings may have limited generalizability due to the focus on a specific case.  

Frequently Asked Questions  

Q: What is a case study in research?  

A case study in research is an impactful tool for gaining a deep understanding of complex issues within their real-life context. It combines various data collection methods and provides rich, detailed insights that can inform theory development and practical applications.  

Q: What are the advantages of using case studies in research?  

Case studies are a powerful research method, offering advantages such as in-depth analysis, contextual insights, flexibility, rich data, and the ability to handle complex issues. They are particularly valuable for exploring new areas, generating hypotheses, and providing detailed, illustrative examples that can inform theory and practice.  

Q: Can case studies be used in quantitative research?  

While case studies are predominantly associated with qualitative research, they can effectively incorporate quantitative methods to provide a more comprehensive analysis. A mixed-methods approach leverages qualitative and quantitative research strengths, offering a powerful tool for exploring complex issues in a real-world context. For example , a new medical treatment case study can incorporate quantitative clinical outcomes (e.g., patient recovery rates and dosage levels) along with qualitative patient interviews.  

Q: What are the key components of a case study?  

A case study typically includes several key components:   

• Introductio n, which provides an overview and sets the context by presenting the problem statement and research objectives;  
• Literature review , which connects the study to existing theories and prior research;  
• Methodology , which details the case study design , data collection methods, and analysis techniques;   
• Findings , which present the data and results, including descriptions, patterns, and themes;   
• Discussion and conclusion , which interpret the findings, discuss their implications, and offer conclusions, practical applications, limitations, and suggestions for future research.  

Together, these components ensure a comprehensive, systematic, and insightful exploration of the case.  

References  

• de Vries, K. (2020). Case study methodology. In  Critical qualitative health research  (pp. 41-52). Routledge.  
• Fidel, R. (1984). The case study method: A case study.  Library and Information Science Research ,  6 (3), 273-288.  
• Thomas, G. (2021). How to do your case study.  How to do your case study , 1-320.  

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Case Study Methods and Examples

By Janet Salmons, PhD Manager, Sage Research Methods Community

What is Case Study Methodology ?

Case studies in research are both unique and uniquely confusing. The term case study is confusing because the same term is used multiple ways. The term can refer to the methodology, that is, a system of frameworks used to design a study, or the methods used to conduct it. Or, case study can refer to a type of academic writing that typically delves into a problem, process, or situation.

Case study methodology can entail the study of one or more "cases," that could be described as instances, examples, or settings where the problem or phenomenon can be examined. The researcher is tasked with defining the parameters of the case, that is, what is included and excluded. This process is called bounding the case , or setting boundaries.

Case study can be combined with other methodologies, such as ethnography, grounded theory, or phenomenology. In such studies the research on the case uses another framework to further define the study and refine the approach.

Case study is also described as a method, given particular approaches used to collect and analyze data. Case study research is conducted by almost every social science discipline: business, education, sociology, psychology. Case study research, with its reliance on multiple sources, is also a natural choice for researchers interested in trans-, inter-, or cross-disciplinary studies.

The Encyclopedia of case study research provides an overview:

The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case.

It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed methods because this they use either more than one form of data within a research paradigm, or more than one form of data from different paradigms.

A case study inquiry could include multiple types of data:

multiple forms of quantitative data sources, such as Big Data + a survey

multiple forms of qualitative data sources, such as interviews + observations + documents

multiple forms of quantitative and qualitative data sources, such as surveys + interviews

Case study methodology can be used to achieve different research purposes.

Robert Yin , methodologist most associated with case study research, differentiates between descriptive , exploratory and explanatory case studies:

Descriptive : A case study whose purpose is to describe a phenomenon. Explanatory : A case study whose purpose is to explain how or why some condition came to be, or why some sequence of events occurred or did not occur. Exploratory: A case study whose purpose is to identify the research questions or procedures to be used in a subsequent study.

Robert Yin’s book is a comprehensive guide for case study researchers!

You can read the preface and Chapter 1 of Yin's book here . See the open-access articles below for some published examples of qualitative, quantitative, and mixed methods case study research.

Mills, A. J., Durepos, G., & Wiebe, E. (2010).  Encyclopedia of case study research (Vols. 1-0). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412957397

Yin, R. K. (2018). Case study research and applications (6th ed.). Thousand Oaks: SAGE Publications.

Open-Access Articles Using Case Study Methodology

As you can see from this collection, case study methods are used in qualitative, quantitative and mixed methods research.

Ang, C.-S., Lee, K.-F., & Dipolog-Ubanan, G. F. (2019). Determinants of First-Year Student Identity and Satisfaction in Higher Education: A Quantitative Case Study. SAGE Open. https://doi.org/10.1177/2158244019846689

Abstract. First-year undergraduates’ expectations and experience of university and student engagement variables were investigated to determine how these perceptions influence their student identity and overall course satisfaction. Data collected from 554 first-year undergraduates at a large private university were analyzed. Participants were given the adapted version of the Melbourne Centre for the Study of Higher Education Survey to self-report their learning experience and engagement in the university community. The results showed that, in general, the students’ reasons of pursuing tertiary education were to open the door to career opportunities and skill development. Moreover, students’ views on their learning and university engagement were at the moderate level. In relation to student identity and overall student satisfaction, it is encouraging to state that their perceptions of studentship and course satisfaction were rather positive. After controlling for demographics, student engagement appeared to explain more variance in student identity, whereas students’ expectations and experience explained greater variance in students’ overall course satisfaction. Implications for practice, limitations, and recommendation of this study are addressed.

Baker, A. J. (2017). Algorithms to Assess Music Cities: Case Study—Melbourne as a Music Capital. SAGE Open. https://doi.org/10.1177/2158244017691801

Abstract. The global  Mastering of a Music City  report in 2015 notes that the concept of music cities has penetrated the global political vernacular because it delivers “significant economic, employment, cultural and social benefits.” This article highlights that no empirical study has combined all these values and offers a relevant and comprehensive definition of a music city. Drawing on industry research,1 the article assesses how mathematical flowcharts, such as Algorithm A (Economics), Algorithm B (Four T’s creative index), and Algorithm C (Heritage), have contributed to the definition of a music city. Taking Melbourne as a case study, it illustrates how Algorithms A and B are used as disputed evidence about whether the city is touted as Australia’s music capital. The article connects the three algorithms to an academic framework from musicology, urban studies, cultural economics, and sociology, and proposes a benchmark Algorithm D (Music Cities definition), which offers a more holistic assessment of music activity in any urban context. The article concludes by arguing that Algorithm D offers a much-needed definition of what comprises a music city because it builds on the popular political economy focus and includes the social importance of space and cultural practices.

Brown, K., & Mondon, A. (2020). Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study. Politics. https://doi.org/10.1177/0263395720955036

Abstract. Populism seems to define our current political age. The term is splashed across the headlines, brandished in political speeches and commentaries, and applied extensively in numerous academic publications and conferences. This pervasive usage, or populist hype, has serious implications for our understanding of the meaning of populism itself and for our interpretation of the phenomena to which it is applied. In particular, we argue that its common conflation with far-right politics, as well as its breadth of application to other phenomena, has contributed to the mainstreaming of the far right in three main ways: (1) agenda-setting power and deflection, (2) euphemisation and trivialisation, and (3) amplification. Through a mixed-methods approach to discourse analysis, this article uses  The Guardian  newspaper as a case study to explore the development of the populist hype and the detrimental effects of the logics that it has pushed in public discourse.

Droy, L. T., Goodwin, J., & O’Connor, H. (2020). Methodological Uncertainty and Multi-Strategy Analysis: Case Study of the Long-Term Effects of Government Sponsored Youth Training on Occupational Mobility. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 147–148(1–2), 200–230. https://doi.org/10.1177/0759106320939893

Abstract. Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Ebneyamini, S., & Sadeghi Moghadam, M. R. (2018). Toward Developing a Framework for Conducting Case Study Research .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406918817954

Abstract. This article reviews the use of case study research for both practical and theoretical issues especially in management field with the emphasis on management of technology and innovation. Many researchers commented on the methodological issues of the case study research from their point of view thus, presenting a comprehensive framework was missing. We try representing a general framework with methodological and analytical perspective to design, develop, and conduct case study research. To test the coverage of our framework, we have analyzed articles in three major journals related to the management of technology and innovation to approve our framework. This study represents a general structure to guide, design, and fulfill a case study research with levels and steps necessary for researchers to use in their research.

Lai, D., & Roccu, R. (2019). Case study research and critical IR: the case for the extended case methodology. International Relations , 33 (1), 67-87. https://doi.org/10.1177/0047117818818243

Abstract. Discussions on case study methodology in International Relations (IR) have historically been dominated by positivist and neopositivist approaches. However, these are problematic for critical IR research, pointing to the need for a non-positivist case study methodology. To address this issue, this article introduces and adapts the extended case methodology as a critical, reflexivist approach to case study research, whereby the case is constructed through a dynamic interaction with theory, rather than selected, and knowledge is produced through extensions rather than generalisation. Insofar as it seeks to study the world in complex and non-linear terms, take context and positionality seriously, and generate explicitly political and emancipatory knowledge, the extended case methodology is consistent with the ontological and epistemological commitments of several critical IR approaches. Its potential is illustrated in the final part of the article with reference to researching the socioeconomic dimension of transitional justice in Bosnia and Herzegovina.

Lynch, R., Young, J. C., Boakye-Achampong, S., Jowaisas, C., Sam, J., & Norlander, B. (2020). Benefits of crowdsourcing for libraries: A case study from Africa . IFLA Journal. https://doi.org/10.1177/0340035220944940

Abstract. Many libraries in the Global South do not collect comprehensive data about themselves, which creates challenges in terms of local and international visibility. Crowdsourcing is an effective tool that engages the public to collect missing data, and it has proven to be particularly valuable in countries where governments collect little public data. Whereas crowdsourcing is often used within fields that have high levels of development funding, such as health, the authors believe that this approach would have many benefits for the library field as well. They present qualitative and quantitative evidence from 23 African countries involved in a crowdsourcing project to map libraries. The authors find benefits in terms of increased connections between stakeholders, capacity-building, and increased local visibility. These findings demonstrate the potential of crowdsourced approaches for tasks such as mapping to benefit libraries and similarly positioned institutions in the Global South in multifaceted ways.

Mason, W., Morris, K., Webb, C., Daniels, B., Featherstone, B., Bywaters, P., Mirza, N., Hooper, J., Brady, G., Bunting, L., & Scourfield, J. (2020). Toward Full Integration of Quantitative and Qualitative Methods in Case Study Research: Insights From Investigating Child Welfare Inequalities. Journal of Mixed Methods Research, 14 (2), 164-183. https://doi.org/10.1177/1558689819857972

Abstract. Delineation of the full integration of quantitative and qualitative methods throughout all stages of multisite mixed methods case study projects remains a gap in the methodological literature. This article offers advances to the field of mixed methods by detailing the application and integration of mixed methods throughout all stages of one such project; a study of child welfare inequalities. By offering a critical discussion of site selection and the management of confirmatory, expansionary and discordant data, this article contributes to the limited body of mixed methods exemplars specific to this field. We propose that our mixed methods approach provided distinctive insights into a complex social problem, offering expanded understandings of the relationship between poverty, child abuse, and neglect.

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case Study Method: A Step-by-Step Guide for Business Researchers .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406919862424

Abstract. Qualitative case study methodology enables researchers to conduct an in-depth exploration of intricate phenomena within some specific context. By keeping in mind research students, this article presents a systematic step-by-step guide to conduct a case study in the business discipline. Research students belonging to said discipline face issues in terms of clarity, selection, and operationalization of qualitative case study while doing their final dissertation. These issues often lead to confusion, wastage of valuable time, and wrong decisions that affect the overall outcome of the research. This article presents a checklist comprised of four phases, that is, foundation phase, prefield phase, field phase, and reporting phase. The objective of this article is to provide novice researchers with practical application of this checklist by linking all its four phases with the authors’ experiences and learning from recently conducted in-depth multiple case studies in the organizations of New Zealand. Rather than discussing case study in general, a targeted step-by-step plan with real-time research examples to conduct a case study is given.

VanWynsberghe, R., & Khan, S. (2007). Redefining Case Study. International Journal of Qualitative Methods, 80–94. https://doi.org/10.1177/160940690700600208

Abstract. In this paper the authors propose a more precise and encompassing definition of case study than is usually found. They support their definition by clarifying that case study is neither a method nor a methodology nor a research design as suggested by others. They use a case study prototype of their own design to propose common properties of case study and demonstrate how these properties support their definition. Next, they present several living myths about case study and refute them in relation to their definition. Finally, they discuss the interplay between the terms case study and unit of analysis to further delineate their definition of case study. The target audiences for this paper include case study researchers, research design and methods instructors, and graduate students interested in case study research.

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What is case study research?

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Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

Analyze case study research

Dovetail streamlines case study research to help you uncover and share actionable insights

• What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

• When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

• What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

• What are some case study examples?

What are the best approaches for introducing our product into the Kenyan market?

How does the change in marketing strategy aid in increasing the sales volumes of product Y?

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

Case study of the effects of a marketing strategy change on product Y sales volumes

Case study of X school teachers that encourage active student participation in the classroom

Case study of the effects of poverty on literacy levels in children

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11 Case research

Case research—also called case study—is a method of intensively studying a phenomenon over time within its natural setting in one or a few sites. Multiple methods of data collection, such as interviews, observations, pre-recorded documents, and secondary data, may be employed and inferences about the phenomenon of interest tend to be rich, detailed, and contextualised. Case research can be employed in a positivist manner for the purpose of theory testing or in an interpretive manner for theory building. This method is more popular in business research than in other social science disciplines.

Case research has several unique strengths over competing research methods such as experiments and survey research. First, case research can be used for either theory building or theory testing, while positivist methods can be used for theory testing only. In interpretive case research, the constructs of interest need not be known in advance, but may emerge from the data as the research progresses. Second, the research questions can be modified during the research process if the original questions are found to be less relevant or salient. This is not possible in any positivist method after the data is collected. Third, case research can help derive richer, more contextualised, and more authentic interpretation of the phenomenon of interest than most other research methods by virtue of its ability to capture a rich array of contextual data. Fourth, the phenomenon of interest can be studied from the perspectives of multiple participants and using multiple levels of analysis (e.g., individual and organisational).

At the same time, case research also has some inherent weaknesses. Because it involves no experimental control, internal validity of inferences remain weak. Of course, this is a common problem for all research methods except experiments. However, as described later, the problem of controls may be addressed in case research using ‘natural controls’. Second, the quality of inferences derived from case research depends heavily on the integrative powers of the researcher. An experienced researcher may see concepts and patterns in case data that a novice researcher may miss. Hence, the findings are sometimes criticised as being subjective. Finally, because the inferences are heavily contextualised, it may be difficult to generalise inferences from case research to other contexts or other organisations.

It is important to recognise that case research is different from case descriptions such as Harvard case studies discussed in business classes. While case descriptions typically describe an organisational problem in rich detail with the goal of stimulating classroom discussion and critical thinking among students, or analysing how well an organisation handled a specific problem, case research is a formal research technique that involves a scientific method to derive explanations of organisational phenomena.

Case research is a difficult research method that requires advanced research skills on the part of the researcher, and is therefore often prone to error. Benbasat, Goldstein and Mead (1987) [1] describe five problems frequently encountered in case research studies. First, many case research studies start without specific research questions, and therefore end up without having any specific answers or insightful inferences. Second, case sites are often chosen based on access and convenience, rather than based on the fit with the research questions, and are therefore cannot adequately address the research questions of interest. Third, researchers often do not validate or triangulate data collected using multiple means, which may lead to biased interpretation based on responses from biased interviewees. Fourth, many studies provide very little details on how data was collected (e.g., what interview questions were used, which documents were examined, the organisational positions of each interviewee, etc.) or analysed, which may raise doubts about the reliability of the inferences. Finally, despite its strength as a longitudinal research method, many case research studies do not follow through a phenomenon in a longitudinal manner, and hence present only a cross-sectional and limited view of organisational processes and phenomena that are temporal in nature.

Key decisions in case research

Several key decisions must be made by a researcher when considering a case research method. First, is this the right method for the research questions being studied? The case research method is particularly appropriate for exploratory studies, for discovering relevant constructs in areas where theory building is in the formative stages, for studies where the experiences of participants and context of actions are critical, and for studies aimed at understanding complex, temporal processes (why and how) rather than factors or causes (what). This method is well-suited for studying complex organisational processes that involve multiple participants and interacting sequences of events, such as organisational change and large-scale technology implementation projects.

Second, what is the appropriate unit of analysis for a case research study? Since case research can simultaneously examine multiple units of analyses, the researcher must decide whether she wishes to study a phenomenon at the individual, group, or organisational level or at multiple levels. For instance, a study of group decision-making or group work may combine individual-level constructs such as individual participation in group activities with group-level constructs, such as group cohesion and group leadership, to derive richer understanding than can be achieved from a single level of analysis.

Third, should the researcher employ a single-case or multiple-case design? The single-case design is more appropriate at the outset of theory generation, if the situation is unique or extreme, if it is revelatory (i.e., the situation was previously inaccessible for scientific investigation), or if it represents a critical or contrary case for testing a well-formulated theory. The multiple-case design is more appropriate for theory testing, for establishing generalisability of inferences, and for developing richer and more nuanced interpretations of a phenomenon. Yin (1984) [2] recommends the use of multiple case sites with replication logic, viewing each case site as similar to one experimental study, and following rules of scientific rigor similar to that used in positivist research.

Fourth, what sites should be chosen for case research? Given the contextualised nature of inferences derived from case research, site selection is a particularly critical issue because selecting the wrong site may lead to the wrong inferences. If the goal of the research is to test theories or examine generalisability of inferences, then dissimilar case sites should be selected to increase variance in observations. For instance, if the goal of the research is to understand the process of technology implementation in firms, a mix of large, mid-sized, and small firms should be selected to examine whether the technology implementation process differs with firm size. Site selection should not be opportunistic or based on convenience, but rather based on the fit with research questions though a process called ‘theoretical sampling’.

Fifth, what techniques of data collection should be used in case research? Although interview (either open-ended/unstructured or focused/structured) is by far the most popular data collection technique for case research, interview data can be supplemented or corroborated with other techniques such as direct observation (e.g., attending executive meetings, briefings, and planning sessions), documentation (e.g., internal reports, presentations, and memoranda, as well as external accounts such as newspaper reports), archival records (e.g., organisational charts, financial records, etc.), and physical artefacts (e.g., devices, outputs, tools). Furthermore, the researcher should triangulate or validate observed data by comparing responses between interviewees.

Conducting case research

Most case research studies tend to be interpretive in nature. Interpretive case research is an inductive technique where evidence collected from one or more case sites is systematically analysed and synthesised to allow concepts and patterns to emerge for the purpose of building new theories or expanding existing ones. Eisenhardt (1989) [3] proposed a ‘roadmap’ for building theories from case research—a slightly modified version of which is described below. For positivist case research, some of the following stages may need to be rearranged or modified, however sampling, data collection, and data analytic techniques should generally remain the same.

Define research questions. Like any other scientific research, case research must also start with defining research questions that are theoretically and practically interesting, and identifying some intuitive expectations about possible answers to those research questions or preliminary constructs to guide initial case design. In positivist case research, the preliminary constructs are based on theory, while no such theories or hypotheses should be considered ex ante in interpretive research. These research questions and constructs may be changed in interpretive case research later on, if needed, but not in positivist case research.

Select case sites. The researcher should use a process of ‘theoretical sampling’—not random sampling—to identify case sites. In this approach, case sites are chosen based on theoretical rather than statistical considerations—for instance, to replicate previous cases, to extend preliminary theories, or to fill theoretical categories or polar types. Care should be taken to ensure that the selected sites fit the nature of research questions, minimise extraneous variance or noise due to firm size, industry effects, and so forth, and maximise variance in the dependent variables of interest. For instance, if the goal of the research is to examine how some firms innovate better than others, the researcher should select firms of similar size within the same industry to reduce industry or size effects, and select some more innovative and some less innovative firms to increase variation in firm innovation. Instead of cold-calling or writing to a potential site, it is better to contact someone at executive level inside each firm who has the authority to approve the project, or someone who can identify a person of authority. During initial conversations, the researcher should describe the nature and purpose of the project, any potential benefits to the case site, how the collected data will be used, the people involved in data collection (other researchers, research assistants, etc.), desired interviewees, and the amount of time, effort, and expense required of the sponsoring organisation. The researcher must also assure confidentiality, privacy, and anonymity of both the firm and the individual respondents.

Create instruments and protocols. Since the primary mode of data collection in case research is interviews, an interview protocol should be designed to guide the interview process. This is essentially a list of questions to be asked. Questions may be open-ended (unstructured) or closed-ended (structured) or a combination of both. The interview protocol must be strictly followed, and the interviewer must not change the order of questions or skip any question during the interview process, although some deviations are allowed to probe further into a respondent’s comments if they are ambiguous or interesting. The interviewer must maintain a neutral tone, and not lead respondents in any specific direction—for example, by agreeing or disagreeing with any response. More detailed interviewing techniques are discussed in the chapter on surveys. In addition, additional sources of data—such as internal documents and memorandums, annual reports, financial statements, newspaper articles, and direct observations—should be sought to supplement and validate interview data.

Select respondents. Select interview respondents at different organisational levels, departments, and positions to obtain divergent perspectives on the phenomenon of interest. A random sampling of interviewees is most preferable, however a snowball sample is acceptable, as long as a diversity of perspectives is represented in the sample. Interviewees must be selected based on their personal involvement with the phenomenon under investigation and their ability and willingness to answer the researcher’s questions accurately and adequately, and not based on convenience or access.

Start data collection . It is usually a good idea to electronically record interviews for future reference. However, such recording must only be done with the interviewee’s consent. Even when interviews are being recorded, the interviewer should take notes to capture important comments or critical observations, behavioural responses (e.g., the respondent’s body language), and the researcher’s personal impressions about the respondent and his/her comments. After each interview is completed, the entire interview should be transcribed verbatim into a text document for analysis.

Conduct within-case data analysis. Data analysis may follow or overlap with data collection. Overlapping data collection and analysis has the advantage of adjusting the data collection process based on themes emerging from data analysis, or to further probe into these themes. Data analysis is done in two stages. In the first stage (within-case analysis), the researcher should examine emergent concepts separately at each case site and patterns between these concepts to generate an initial theory of the problem of interest. The researcher can use interview data subjectively to ‘make sense’ of the research problem in conjunction with using his/her personal observations or experience at the case site. Alternatively, a coding strategy such as Glaser and Strauss’ (1967) [4] grounded theory approach, using techniques such as open coding, axial coding, and selective coding, may be used to derive a chain of evidence and inferences. These techniques are discussed in detail in a later chapter. Homegrown techniques, such as graphical representation of data (e.g., network diagram) or sequence analysis (for longitudinal data) may also be used. Note that there is no predefined way of analysing the various types of case data, and the data analytic techniques can be modified to fit the nature of the research project.

Conduct cross-case analysis. Multi-site case research requires cross-case analysis as the second stage of data analysis. In such analysis, the researcher should look for similar concepts and patterns between different case sites, ignoring contextual differences that may lead to idiosyncratic conclusions. Such patterns may be used for validating the initial theory, or for refining it—by adding or dropping concepts and relationships—to develop a more inclusive and generalisable theory. This analysis may take several forms. For instance, the researcher may select categories (e.g., firm size, industry, etc.) and look for within-group similarities and between-group differences (e.g., high versus low performers, innovators versus laggards). Alternatively, they can compare firms in a pairwise manner listing similarities and differences across pairs of firms.

Build and test hypotheses. Tenative hypotheses are constructed based on emergent concepts and themes that are generalisable across case sites. These hypotheses should be compared iteratively with observed evidence to see if they fit the observed data, and if not, the constructs or relationships should be refined. Also the researcher should compare the emergent constructs and hypotheses with those reported in the prior literature to make a case for their internal validity and generalisability. Conflicting findings must not be rejected, but rather reconciled using creative thinking to generate greater insight into the emergent theory. When further iterations between theory and data yield no new insights or changes in the existing theory, ‘theoretical saturation’ is reached and the theory building process is complete.

Write case research report. In writing the report, the researcher should describe very clearly the detailed process used for sampling, data collection, data analysis, and hypotheses development, so that readers can independently assess the reasonableness, strength, and consistency of the reported inferences. A high level of clarity in research methods is needed to ensure that the findings are not biased by the researcher’s preconceptions.

Interpretive case research exemplar

Perhaps the best way to learn about interpretive case research is to examine an illustrative example. One such example is Eisenhardt’s (1989) [5] study of how executives make decisions in high-velocity environments (HVE). Readers are advised to read the original paper published in Academy of Management Journal before reading the synopsis in this chapter. In this study, Eisenhardt examined how executive teams in some HVE firms make fast decisions, while those in other firms cannot, and whether faster decisions improve or worsen firm performance in such environments. HVE was defined as one where demand, competition, and technology changes so rapidly and discontinuously that the information available is often inaccurate, unavailable or obsolete. The implicit assumptions were thatit is hard to make fast decisions with inadequate information in HVE, and fast decisions may not be efficient and may result in poor firm performance.

Reviewing the prior literature on executive decision-making, Eisenhardt found several patterns, although none of these patterns were specific to high-velocity environments. The literature suggested that in the interest of expediency, firms that make faster decisions obtain input from fewer sources, consider fewer alternatives, make limited analysis, restrict user participation in decision-making, centralise decision-making authority, and have limited internal conflicts. However, Eisenhardt contended that these views may not necessarily explain how decision makers make decisions in high-velocity environments, where decisions must be made quickly and with incomplete information, while maintaining high decision quality.

To examine this phenomenon, Eisenhardt conducted an inductive study of eight firms in the personal computing industry. The personal computing industry was undergoing dramatic changes in technology with the introduction of the UNIX operating system, RISC architecture, and 64KB random access memory in the 1980s, increased competition with the entry of IBM into the personal computing business, and growing customer demand with double-digit demand growth, and therefore fit the profile of the high-velocity environment. This was a multiple case design with replication logic, where each case was expected to confirm or disconfirm inferences from other cases. Case sites were selected based on their access and proximity to the researcher, however, all of these firms operated in the high-velocity personal computing industry in California’s Silicon Valley area. The collocation of firms in the same industry and the same area ruled out any ‘noise’ or variance in dependent variables (decision speed or performance) attributable to industry or geographic differences.

The study employed an embedded design with multiple levels of analysis: decision (comparing multiple strategic decisions within each firm), executive teams (comparing different teams responsible for strategic decisions), and the firm (overall firm performance). Data was collected from five sources:

Initial interviews with Chief Executive Officers . CEOs were asked questions about their firm’s competitive strategy, distinctive competencies, major competitors, performance, and recent/ongoing major strategic decisions. Based on these interviews, several strategic decisions were selected in each firm for further investigation. Four criteria were used to select decisions: the decisions must involve the firm’s strategic positioning, the decisions must have high stakes, the decisions must involve multiple functions, and the decisions must be representative of strategic decision-making process in that firm.

Interviews with divisional heads . Each divisional head was asked sixteen open-ended questions, ranging from their firm’s competitive strategy, functional strategy, top management team members, frequency and nature of interaction with team, typical decision-making processes, how each of the decisions were made, and how long it took them to make those decisions. Interviews lasted between one and a half and two hours, and sometimes extended to four hours. To focus on facts and actual events rather than respondents’ perceptions or interpretations, a ‘courtroom’ style questioning was employed, such as ‘When did this happen?’, ‘What did you do?’, etc. Interviews were conducted by two people, and the data was validated by cross-checking facts and impressions made by the interviewer and notetaker. All interview data was recorded, however notes were also taken during each interview, which ended with the interviewer’s overall impressions. Using a ‘24-hour rule’, detailed field notes were completed within 24 hours of the interview, so that some data or impressions were not lost to recall.

Questionnaires . Executive team members at each firm were asked tocomplete a survey questionnaire that captured quantitative data on the extent of conflict and power distribution in their firm.

Secondary data . Industry reports and internal documents such as demographics of the executive teams responsible for strategic decisions, financial performance of firms, and so forth, were examined.

Personal observation . Lastly, the researcher attended a one-day strategy session and a weekly executive meeting at two firms in her sample.

Data analysis involved a combination of quantitative and qualitative techniques. Quantitative data on conflict and power were analysed for patterns across firms/decisions. Qualitative interview data was combined into decision climate profiles, using profile traits (e.g., impatience) mentioned by more than one executive. For within-case analysis, decision stories were created for each strategic decision by combining executive accounts of the key decision events into a timeline. For cross-case analysis, pairs of firms were compared for similarities and differences, categorised along variables of interest such as decision speed and firm performance. Based on these analyses, tentative constructs and propositions were derived inductively from each decision story within firm categories. Each decision case was revisited to confirm the proposed relationships. The inferred propositions were compared with findings from the existing literature to examine differences, and to generate new insights from the case findings. Finally, the validated propositions were synthesised into an inductive theory of strategic decision-making by firms in high-velocity environments.

Inferences derived from this multiple case research contradicted several decision-making patterns expected from the existing literature. First, fast decision-makers in high-velocity environments used more information, and not less information as suggested by the previous literature. However, these decision-makers used more real-time information—an insight not available from prior research—which helped them identify and respond to problems, opportunities, and changing circumstances faster. Second, fast decision-makers examined more—not fewer—alternatives. However, they considered these multiple alternatives in a simultaneous manner, while slower decision-makers examined fewer alternatives in a sequential manner. Third, fast decision-makers did not centralise decision-making or restrict inputs from others as the literature suggested. Rather, these firms used a two-tiered decision process in which experienced counsellors were asked for inputs in the first stage, followed by a rapid comparison and decision selection in the second stage. Fourth, fast decision-makers did not have less conflict—as expected from the literature—but employed better conflict resolution techniques to reduce conflict and improve decision-making speed. Finally, fast decision-makers exhibited superior firm performance by virtue of their built-in cognitive, emotional, and political processes that led to rapid closure of major decisions.

Positivist case research exemplar

Case research can also be used in a positivist manner to test theories or hypotheses. Such studies are rare, but Markus (1983) [6] provides an exemplary illustration in her study of technology implementation at the pseudonymous Golden Triangle Company (GTC). The goal of this study was to understand why a newly implemented financial information system (FIS)—intended to improve the productivity and performance of accountants at GTC—was supported by accountants at GTC’s corporate headquarters, but resisted by divisional accountants at GTC branches. Given the uniqueness of the phenomenon of interest, this was a single-case research study.

To explore the reasons behind user resistance of FIS, Markus posited three alternative explanations:

System-determined theory : The resistance was caused by factors related to an inadequate system, such as its technical deficiencies, poor ergonomic design, or lack of user friendliness.

People-determined theory : The resistance was caused by factors internal to users, such as the accountants’ cognitive styles or personality traits that were incompatible with using the system.

Interaction theory : The resistance was not caused not by factors intrinsic to the system or the people, but by the interaction between the two set of factors. Specifically, interaction theory suggested that the FIS engendered a redistribution of intra-organisational power, and accountants who lost organisational status, relevance, or power as a result of FIS implementation resisted the system while those gaining power favoured it.

In order to test the three theories, Markus predicted alternative outcomes expected from each theoretical explanation and analysed the extent to which those predictions matched with her observations at GTC. For instance, the system-determined theory suggested that since user resistance was caused by an inadequate system, fixing the technical problems of the system would eliminate resistance. The computer running the FIS system was subsequently upgraded with a more powerful operating system, online processing (from initial batch processing, which delayed immediate processing of accounting information), and a simplified software for new account creation by managers. One year after these changes were made, the resistant users were still resisting the system and felt that it should be replaced. Hence, the system-determined theory was rejected.

The people-determined theory predicted that replacing individual resistors or co-opting them with less resistant users would reduce their resistance toward the FIS. Subsequently, GTC started a job rotation and mobility policy, moving accountants in and out of the resistant divisions, but resistance not only persisted, but in some cases increased. In one instance, an accountant who was one of the system’s designers and advocates when he worked for corporate accounting started resisting the system after he was moved to the divisional controller’s office. Failure to realise the predictions of the people-determined theory led to the rejection of this theory.

Finally, the interaction theory predicted that neither changing the system nor the people (i.e., user education or job rotation policies) would reduce resistance until the power imbalance and redistribution from the pre-implementation phase was addressed. Before FIS implementation, divisional accountants at GTC felt that they owned all accounting data related to their divisional operations. They maintained this data in thick, manual ledger books, controlled others’ access to the data, and could reconcile unusual accounting events before releasing those reports. Corporate accountants relied heavily on divisional accountants for access to the divisional data for corporate reporting and consolidation. Because the FIS system automatically collected all data at the source and consolidated it into a single corporate database, it obviated the need for divisional accountants, loosened their control and autonomy over their division’s accounting data, and making their job somewhat irrelevant. Corporate accountants could now query the database and access divisional data directly without going through the divisional accountants, analyse and compare the performance of individual divisions, and report unusual patterns and activities to the executive committee, resulting in further erosion of the divisions’ power. Though Markus did not empirically test this theory, her observations about the redistribution of organisational power, coupled with the rejection of the two alternative theories, led to the justification of interaction theory.

Comparisons with traditional research

Positivist case research, aimed at hypotheses testing, is often criticised by natural science researchers as lacking in controlled observations, controlled deductions, replicability, and generalisability of findings—the traditional principles of positivist research. However, these criticisms can be overcome through appropriate case research designs. For instance, the problem of controlled observations refers to the difficulty of obtaining experimental or statistical control in case research. However, case researchers can compensate for such lack of controls by employing ’natural controls’. This natural control in Markus’ (1983) study was the corporate accountant who was one of the system advocates initially, but started resisting it once he moved to the controlling division. In this instance, the change in his behaviour may be attributed to his new divisional position. However, such natural controls cannot be anticipated in advance, and case researchers may overlook them unless they are proactively looking for such controls. Incidentally, natural controls are also used in natural science disciplines such as astronomy, geology, and human biology—for example, waiting for comets to pass close enough to the earth in order to make inferences about comets and their composition.

Third, the problem of replicability refers to the difficulty of observing the same phenomenon considering the uniqueness and idiosyncrasy of a given case site. However, using Markus’ three theories as an illustration, a different researcher can test the same theories at a different case site, where three different predictions may emerge based on the idiosyncratic nature of the new case site, and the three resulting predictions may be tested accordingly. In other words, it is possible to replicate the inferences of case research, even if the case research site or context may not be replicable.

Fourth, case research tends to examine unique and non-replicable phenomena that may not be generalised to other settings. Generalisability in natural sciences is established through additional studies. Likewise, additional case studies conducted in different contexts with different predictions can establish generalisability of findings if such findings are observed to be consistent across studies.

Lastly, British philosopher Karl Popper described four requirements of scientific theories: theories should be falsifiable, they should be logically consistent, they should have adequate predictive ability, and they should provide better explanation than rival theories. In case research, the first three requirements can be improved by increasing the degrees of freedom of observed findings—for example, by increasing the number of case sites, the number of alternative predictions, and the number of levels of analysis examined. This was accomplished in Markus’ study by examining the behaviour of multiple groups (divisional accountants and corporate accountants) and providing multiple (three) rival explanations. Popper’s fourth condition was accomplished in this study when one hypothesis was found to match observed evidence better than the two rival hypotheses.

• Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS Quarterly , 11(3), 369–386. ↵
• Yin, R. (1984). Case study research: Design and methods . London: Sage Publications. ↵
• Eisenhardt, K. M. (1989). Building theories from case research. Academy of Management Review , 14(4), 532–550 ↵
• Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research . New York: Aldine Pub Co. ↵
• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Markus, M. L. (1983). Power, politics and MIS implementations. Communications of the ACM , 26(6), 430–444. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Research Writing and Analysis

• NVivo Group and Study Sessions
• SPSS This link opens in a new window
• Statistical Analysis Group sessions
• Using Qualtrics
• Research Process Flow Chart
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Analyzing Research Articles
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Sampling Methods
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Systematic Reviews & Meta-Analyses
• Dissertation and Data Analysis Group Sessions
• Defense Schedule - Commons Calendar This link opens in a new window
• Dissertation to Journal Article This link opens in a new window
• Journal of Online Graduate Education (JOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

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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• URL: https://resources.nu.edu/researchtools

What is a case study in research?

What is a Case Study in Research?

A case study is a research methodology that involves an in-depth examination of a single topic, situation, or subject, often used in social sciences, healthcare, business, and other fields. A case study is a detailed analysis of a specific situation, event, or phenomenon, aiming to gain a deeper understanding of the context, dynamics, and underlying factors .

Definition and Characteristics

A case study is a qualitative research method that involves:

• In-depth analysis : A close examination of a single case, situation, or subject, often using primary data such as interviews, observations, and documents.
• Contextualization : The study of the case within its context, considering the broader social, cultural, historical, and environmental factors.
• Holistic understanding : A comprehensive understanding of the case, considering the complex relationships and interconnections between various factors.

Types of Case Studies

There are several types of case studies, including:

• Descriptive case study : A study that seeks to describe a particular situation, event, or phenomenon.
• Exploratory case study : A study that aims to explore a topic, identify patterns and themes, and generate hypotheses.
• Explanatory case study : A study that seeks to explain a particular phenomenon, exploring the underlying factors and causes.
• Times-series case study : A study that examines a single case over a period of time, often used in studing developmental processes.

Advantages and Disadvantages of Case Studies

Advantages:

• In-depth understanding : Case studies provide a detailed and nuanced understanding of the case, allowing for a deeper understanding of the context and underlying factors.
• Rich data : Case studies can generate a wealth of qualitative data, including descriptive data, theoretical insights, and practical recommendations.
• Flexibility : Case studies can be used to study a wide range of topics, from a small, isolated event to a global phenomenon.

Disadvantages:

• Limited generalizability : The findings of a single case study may not be generalizable to other cases or populations.
• Subjective interpretation : Case studies rely heavily on the researcher’s interpretation and analysis, which can be subjective and prone to bias.
• Time-consuming : Conducting a case study can be time-consuming and resource-intensive, requiring significant amounts of time for data collection and analysis.

Data Analysis and Presentation

Data analysis in a case study typically involves:

• Data collection : Gathering data through methods such as interviews, observations, and document analysis.
• Data analysis : Analyzing the data using techniques such as coding, categorization, and theme identification.
• Data presentation : Presenting the findings using a variety of methods, such as case reports, articles, or research papers.

Common Case Study Methods

Some common methods used in case studies include:

• Interviews : In-depth, structured, or semi-structured interviews with key informants and stakeholders.
• Observations : Observations of the case, such as ethnographic or participant observation.
• Document analysis : Analysis of relevant documents, such as reports, emails, or memoranda.
• Surveys : Surveys of relevant stakeholders or participants.

Real-World Applications of Case Studies

Case studies are used in various fields, including:

• Healthcare : Studying patient outcomes, disease progression, or treatment efficacy.
• Business : Analyzing business operations, market trends, or competitive strategies.
• Education : Examining educational practices, student outcomes, or program effectiveness.
• Social Sciences : Investigating social phenomena, such as poverty, inequality, or social justice.

Best Practices for Conducting a Case Study

• Clear research questions : Define clear and concise research questions or objectives.
• Theoretical framework : Utilize a theoretical framework to guide data collection and analysis.
• Data quality control : Ensure data quality through rigorous data collection and analysis procedures.
• Transparency : Ensure transparency in all aspects of the research, including data collection, analysis, and presentation.

In conclusion, case studies are a valuable research methodology for gaining a deep understanding of a specific situation, event, or phenomenon. By understanding the definition, characteristics, advantages, and disadvantages of case studies, researchers can effectively design and conduct a case study that provides rich insights and practical recommendations. By following best practices and utilizing a range of methods, case studies can generate valuable knowledge that can inform policy, practice, and decision-making .

• Yin, R. K. (2014). Case study research: Designs and methods. Sage Publications.
• Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
• Merriam, S. B. (2009). Qualitative research and case study applications in education. Wiley.

Table: Types of Case Studies

• In-depth understanding
• Flexibility
• Limited generalizability
• Subjective interpretation
• Time-consuming
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