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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What is Field Research: Definition, Methods, Examples and Advantages

What is Field Research?

Field research is defined as a qualitative method of data collection that aims to observe, interact and understand people while they are in a natural environment. For example, nature conservationists observe behavior of animals in their natural surroundings and the way they react to certain scenarios. In the same way, social scientists conducting field research may conduct interviews or observe people from a distance to understand how they behave in a social environment and how they react to situations around them.

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Field research encompasses a diverse range of social research methods including direct observation, limited participation, analysis of documents and other information, informal interviews, surveys etc. Although field research is generally characterized as qualitative research, it often involves multiple aspects of quantitative research in it.

Field research typically begins in a specific setting although the end objective of the study is to observe and analyze the specific behavior of a subject in that setting. The cause and effect of a certain behavior, though, is tough to analyze due to presence of multiple variables in a natural environment. Most of the data collection is based not entirely on cause and effect but mostly on correlation. While field research looks for correlation, the small sample size makes it difficult to establish a causal relationship between two or more variables.

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Methods of Field Research

Field research is typically conducted in 5 distinctive methods. They are:

• Direct Observation

In this method, the data is collected via an observational method or subjects in a natural environment. In this method, the behavior or outcome of situation is not interfered in any way by the researcher. The advantage of direct observation is that it offers contextual data on people management , situations, interactions and the surroundings. This method of field research is widely used in a public setting or environment but not in a private environment as it raises an ethical dilemma.

• Participant Observation

In this method of field research, the researcher is deeply involved in the research process, not just purely as an observer, but also as a participant. This method too is conducted in a natural environment but the only difference is the researcher gets involved in the discussions and can mould the direction of the discussions. In this method, researchers live in a comfortable environment with the participants of the research design , to make them comfortable and open up to in-depth discussions.

• Ethnography

Ethnography is an expanded observation of social research and social perspective and the cultural values of an  entire social setting. In ethnography, entire communities are observed objectively. For example,  if a researcher would like to understand how an Amazon tribe lives their life and operates, he/she may chose to observe them or live amongst them and silently observe their day-to-day behavior.

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• Qualitative Interviews

Qualitative interviews are close-ended questions that are asked directly to the research subjects. The qualitative interviews could be either informal and conversational, semi-structured, standardized and open-ended or a mix of all the above three. This provides a wealth of data to the researcher that they can sort through. This also helps collect relational data. This method of field research can use a mix of one-on-one interviews, focus groups and text analysis .

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A case study research is an in-depth analysis of a person, situation or event. This method may look difficult to operate, however, it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding the data collection methods and inferring the data.

Steps in Conducting Field Research

Due to the nature of field research, the magnitude of timelines and costs involved, field research can be very tough to plan, implement and measure. Some basic steps in the management of field research are:

• Build the Right Team: To be able to conduct field research, having the right team is important. The role of the researcher and any ancillary team members is very important and defining the tasks they have to carry out with defined relevant milestones is important. It is important that the upper management too is vested in the field research for its success.
• Recruiting People for the Study: The success of the field research depends on the people that the study is being conducted on. Using sampling methods , it is important to derive the people that will be a part of the study.
• Data Collection Methodology: As spoken in length about above, data collection methods for field research are varied. They could be a mix of surveys, interviews, case studies and observation. All these methods have to be chalked out and the milestones for each method too have to be chalked out at the outset. For example, in the case of a survey, the survey design is important that it is created and tested even before the research begins.
• Site Visit: A site visit is important to the success of the field research and it is always conducted outside of traditional locations and in the actual natural environment of the respondent/s. Hence, planning a site visit alongwith the methods of data collection is important.
• Data Analysis: Analysis of the data that is collected is important to validate the premise of the field research and  decide the outcome of the field research.
• Communicating Results: Once the data is analyzed, it is important to communicate the results to the stakeholders of the research so that it could be actioned upon.

LEARN ABOUT: Research Process Steps

Field Research Notes

Keeping an ethnographic record is very important in conducting field research. Field notes make up one of the most important aspects of the ethnographic record. The process of field notes begins as the researcher is involved in the observational research process that is to be written down later.

Types of Field Research Notes

The four different kinds of field notes are:

• Job Notes: This method of taking notes is while the researcher is in the study. This could be in close proximity and in open sight with the subject in study. The notes here are short, concise and in condensed form that can be built on by the researcher later. Most researchers do not prefer this method though due to the fear of feeling that the respondent may not take them seriously.
• Field Notes Proper: These notes are to be expanded on immediately after the completion of events. The notes have to be detailed and the words have to be as close to possible as the subject being studied.
• Methodological Notes: These notes contain methods on the research methods used by the researcher, any new proposed research methods and the way to monitor their progress. Methodological notes can be kept with field notes or filed separately but they find their way to the end report of a study.
• Journals and Diaries: This method of field notes is an insight into the life of the researcher. This tracks all aspects of the researchers life and helps eliminate the Halo effect or any research bias that may have cropped up during the field research.

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Reasons to Conduct Field Research

Field research has been commonly used in the 20th century in the social sciences. But in general, it takes a lot of time to conduct and complete, is expensive and in a lot of cases invasive. So why then is this commonly used and is preferred by researchers to validate data? We look at 4 major reasons:

• Overcoming lack of data: Field research resolves the major issue of gaps in data. Very often, there is limited to no data about a topic in study, especially in a specific environment analysis . The research problem might be known or suspected but there is no way to validate this without primary research and data. Conducting field research helps not only plug-in gaps in data but collect supporting material and hence is a preferred research method of researchers.
• Understanding context of the study: In many cases, the data collected is adequate but field research is still conducted. This helps gain insight into the existing data. For example, if the data states that horses from a stable farm generally win races because the horses are pedigreed and the stable owner hires the best jockeys. But conducting field research can throw light into other factors that influence the success like quality of fodder and care provided and conducive weather conditions.
• Increasing the quality of data: Since this research method uses more than one tool to collect data, the data is of higher quality. Inferences can be made from the data collected and can be statistically analyzed via the triangulation of data.
• Collecting ancillary data: Field research puts the researchers in a position of localized thinking which opens them new lines of thinking. This can help collect data that the study didn’t account to collect.

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Examples of Field Research

Some examples of field research are:

• Decipher social metrics in a slum Purely by using observational methods and in-depth interviews, researchers can be part of a community to understand the social metrics and social hierarchy of a slum. This study can also understand the financial independence and day-to-day operational nuances of a slum. The analysis of this data can provide an insight into how different a slum is from structured societies.
• U nderstand the impact of sports on a child’s development This method of field research takes multiple years to conduct and the sample size can be very large. The data analysis of this research provides insights into how the kids of different geographical locations and backgrounds respond to sports and the impact of sports on their all round development.
• Study animal migration patterns Field research is used extensively to study flora and fauna. A major use case is scientists monitoring and studying animal migration patterns with the change of seasons. Field research helps collect data across years and that helps draw conclusions about how to safely expedite the safe passage of animals.

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Advantages of Field Research

The advantages of field research are:

• It is conducted in a real-world and natural environment where there is no tampering of variables and the environment is not doctored.
• Due to the study being conducted in a comfortable environment, data can be collected even about ancillary topics.
• The researcher gains a deep understanding into the research subjects due to the proximity to them and hence the research is extensive, thorough and accurate.

Disadvantages of Field Research

The disadvantages of field research are:

• The studies are expensive and time-consuming and can take years to complete.
• It is very difficult for the researcher to distance themselves from a bias in the research study.
• The notes have to be exactly what the researcher says but the nomenclature is very tough to follow.
• It is an interpretive method and this is subjective and entirely dependent on the ability of the researcher.
• In this method, it is impossible to control external variables and this constantly alters the nature of the research.

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Methodology

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

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

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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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Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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World Leaders in Research-Based User Experience

Field studies.

January 12, 2024 2024-01-12

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UX researchers are responsible for learning about users, their goals, challenges, and activities, and for bringing that understanding to the organization. If you notice gaps in your knowledge and you want to understand what user behavior is like in real life, then it might be time to leave the office to run a field study.

In This Article:

What is a field study, types of field studies, when is the best time to run a field study, when should you consider other methods, tips for planning field studies.

A field study is a type of context research that takes place in the user's natural environment (sometimes referred to as in situ , Latin for "in place") as opposed to a lab or an orchestrated setting.

Other research methods like secondary (desk) research , diary studies , unmoderated usability testing , remote - or lab-moderated (in-person) usability research  are often popular because they are either easier to set up or they are less resource-intensive (or both) compared to a field study. However, field studies can fill the gaps left by these other methods:

• Observing users in real scenarios will provide you with specific data that directly applies to your audience. Field studies that focus on specific tasks help researchers learn how to best support these tasks. For example, do people tend to use the product or service in the car? While checking in at a facility? At a kiosk? Field studies can reveal how well (or not well) the design supports realistic use cases.
• The context in which people do their tasks can reveal things you wouldn’t know to ask about, such as problems that crop up when new tools or processes are introduced into existing work practices. It also allows you to understand how well systems work in their normal context of use: when people are, say, distracted, in noisy places, or interacting with other people.

The range of possible field studies is very wide. Field studies can be either entirely immersive and open-ended or less immersive and more directed, involving prototypes or usage of specific existing systems.

Direct Observation

Direct observation  is a purely observational study in which the researcher is a “fly on the wall;" they do not intervene in the participants’ activities, nor do they ask any questions. This method is useful for conducting research into user processes — for instance, to help create natural task flows. It is also great for learning users' vocabularies and mental models , understanding businesses’ interactions with customers, and discovering common workarounds — for example by listening in on support calls, watching people moving through amusement parks, or observing sales staff and customers in stores.

Contextual Inquiry

Contextual inquiry  involves a combination of in-depth observation and interviews of a small sample of users to gain a robust understanding of work practices and behaviors. Most qualitative usability tests   in the field fall under this category.

Customer-Site Visits

Customer-site visits are a combination of direct observations and customer interviews, often led by the customer or client. For example, you might take a tour of a facility or walk through a system with them. These visits can help you understand usability issues that arise in particular industries or business contexts, or at certain scales.

Ethnography

Ethnography  requires complete immersion within a person’s or group’s natural setting for a sustained period, in some cases, living as a member of the group. It allows you to gain insight into mental models and social situations that can help products and services fit into people’s lives. This type of research is particularly helpful when your target audience lives in a culture or environment that is different from yours.

Field studies can be done at any time , but it often makes sense to do them before design (or redesign) begins, because such research can lead to fundamental shifts in understanding your users and can change what you would design for them. In particular, it makes sense to use these in the discovery phase of research, while you are still understanding the problem space.

Field studies can also be used in later stages of design or development, as an evaluative research technique . Sometimes this is referred to as “field testing” or “beta testing.” Field testing is a form of field research in which an existing prototype is utilized in its typical context.

If money were no object, we would probably all do much more field research. Unfortunately, field methods have not become cheaper at the same rate as other usability methods, and they can be challenging to facilitate. Beyond reasons of resource constraint, you might decide to stay out of the field in certain other cases.

Remote, Moderated Usability Research

With the advent of digital meeting tools and video chat, field studies can somewhat be facilitated remotely , with participants and facilitators each in their chosen locations. This remote, interactive approach can often be  cheaper and faster  than field or lab studies, since everyone avoids expensive and time-consuming travel to unfamiliar places. Being in your own space also offers comfort, familiar tools, and convenience.

Remote, moderated studies  make sense when:

• Your  participants are all over the map , and traveling to meet in person is too difficult or expensive.
• It’s important to get answers quickly and cheaply, and  you already understand the people, tasks, and contexts in depth .
• You need to conduct a few sessions at a time , for example when testing early designs with only a couple of users for each iteration.
• Many stakeholders or interested parties wish to observe the session , which would be impractical and disruptive during a field study, either by limiting rapport or literally crowding the room. These folks could be “hidden” from participants’ eyes with digital-meeting tools.

Still, remote moderated studies are often limited in how much external context is observable. In other words: you can’t see what the user’s camera doesn’t show you. That missing context is often important when you are trying to understand people and their environment, and extra steps need to be taken  to ensure these studies yield fruitful insights.

Lab Research (Including Traditional and XR or Simulation-Based Research)

You might wish to conduct in-person research in labs, conference rooms, or other spaces when:

• What you are testing or researching is particularly confidential, sensitive, or private.
• You need to record the session (but cannot do so remotely or in the users’ secured location).
• You have several observers who wish to observe these sessions and you can place them into an observer room with a one-way mirror.
• The scenario you need to study is impossible, impractical, or unethical to observe in person (for example: natural disasters, traumatic events, or high-risk scenarios), and must be simulated with extended-reality (XR) headsets or other technology.

While planning your field study , there are steps you can take to optimize your time spent observing users in their context. Ensure your research plan considers the following:

What Are Your Research Questions ?

Carefully consider what your team wants to learn, and how that (and other contextual factors) might factor into the field study’s setup.

• Participants: Who are your target users? Depending on the research method you use, you might need a professional recruiter or a team member to help you  screen and schedule  people.
• Setting: Go where your potential users are most likely doing the tasks you would like to observe: workplaces, schools, shopping centers, airports, and so on. Is there a specific environment or scenario that would be most realistic for your target users? Are there travel considerations (for you and the participants)? Do you have a private room where you can debrief with fellow researchers and observers?
• Timing: What time of day are these activities typically happening (or, alternatively, when in the customer journey)? Will you need to coordinate these sessions outside your normal working hours to accommodate participant schedules?
• Method: How much (or how little) do your participants reveal about their workflow? Does probing seem to significantly disrupt your users’ workflows? Will you need to prepare followup questions for after the observational portion to limit disruptions in users’ natural process? Or, are these questions better asked contextually, in the moment?

Who Is Accompanying You During the Field Study?

While there are certainly cases where a sole researcher will conduct field research alone, it’s far more common to be accompanied by other people, be it fellow researchers (either taking notes or running sessions concurrently) or observers.

Fellow Researchers

During a field study, side chatter can not only be distracting, but it can also bias the results of your study. Similarly, lack of alignment about research questions and intent behind studying tasks can result in researchers observing the wrong things or missing key details. To reduce chatter and increase alignment with others, consider having a research plan and facilitator guide available, with research questions clearly outlined. That way, researchers can not only follow quietly and confidently, but can run sessions in a consistent manner that reduces bias.

Decide whether to allow stakeholders to watch, and if so, what logistical constraints need to be communicated to them. Although it’s often  strategically important and desirable to involve stakeholders in observing user research , it’s not always possible with field studies. Sometimes observers won’t fit in the space, or they would make the research situation too intimidating or otherwise create an awkward situation for the participants. When that happens, you won’t get to observe the most natural behavior and you might not get the candid information that you need.

However, sometimes outside researchers can’t be left alone with participants as a matter of organizational policy, so observers  must  be present. In any case, consider having “slots” for observers to claim, and provide clear guidelines during signup to ensure observers know how to observe and how to help collect data , so they won’t  behave badly .

Do You Have the Right Permissions?

Make sure you have permission to run the study; not just from supervisors or participants, but also from the facility managers. When applicable, work with an ally onsite. When visiting a business, for example, you might need help recruiting, scheduling, reminding, rewarding, and briefing participants. An onsite helper can escort you, introduce you, and help you with equipment or space issues. You may need to get permission in advance to conduct research in public or commercial spaces.

When you encounter problems or behavior that you don’t understand around existing products or services, field studies can help you take a step back and find a new perspective, based on realistic user behavior in realistic contexts.

Doing research where people are can also be crucial to understanding whether new products and services will help, hinder, or fall flat for the people you aim to assist. Set aside assumptions and allow insights to reframe what you’re creating and how it will affect the experiences of the people you’re designing for.

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• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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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.

Peer Review 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 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

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 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.

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 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 2 , 3 and 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 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 2 and 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 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 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 ].

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 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 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 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 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 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 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 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 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 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 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 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 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 9 )[ 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.

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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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Article Contents

Introduction, what is fieldwork, purpose of fieldwork, physical safety, mental wellbeing and affect, ethical considerations, remote fieldwork, concluding thoughts, acknowledgments, funder information.

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Field Research: A Graduate Student's Guide

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Ezgi Irgil, Anne-Kathrin Kreft, Myunghee Lee, Charmaine N Willis, Kelebogile Zvobgo, Field Research: A Graduate Student's Guide, International Studies Review , Volume 23, Issue 4, December 2021, Pages 1495–1517, https://doi.org/10.1093/isr/viab023

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What is field research? Is it just for qualitative scholars? Must it be done in a foreign country? How much time in the field is “enough”? A lack of disciplinary consensus on what constitutes “field research” or “fieldwork” has left graduate students in political science underinformed and thus underequipped to leverage site-intensive research to address issues of interest and urgency across the subfields. Uneven training in Ph.D. programs has also left early-career researchers underprepared for the logistics of fieldwork, from developing networks and effective sampling strategies to building respondents’ trust, and related issues of funding, physical safety, mental health, research ethics, and crisis response. Based on the experience of five junior scholars, this paper offers answers to questions that graduate students puzzle over, often without the benefit of others’ “lessons learned.” This practical guide engages theory and praxis, in support of an epistemologically and methodologically pluralistic discipline.

¿Qué es la investigación de campo? ¿Es solo para académicos cualitativos? ¿Debe realizarse en un país extranjero? ¿Cuánto tiempo en el terreno es “suficiente”? La falta de consenso disciplinario con respecto a qué constituye la “investigación de campo” o el “trabajo de campo” ha causado que los estudiantes de posgrado en ciencias políticas estén poco informados y, por lo tanto, capacitados de manera insuficiente para aprovechar la investigación exhaustiva en el sitio con el objetivo de abordar los asuntos urgentes y de interés en los subcampos. La capacitación desigual en los programas de doctorado también ha provocado que los investigadores en las primeras etapas de su carrera estén poco preparados para la logística del trabajo de campo, desde desarrollar redes y estrategias de muestreo efectivas hasta generar la confianza de las personas que facilitan la información, y las cuestiones relacionadas con la financiación, la seguridad física, la salud mental, la ética de la investigación y la respuesta a las situaciones de crisis. Con base en la experiencia de cinco académicos novatos, este artículo ofrece respuestas a las preguntas que desconciertan a los estudiantes de posgrado, a menudo, sin el beneficio de las “lecciones aprendidas” de otras personas. Esta guía práctica incluye teoría y praxis, en apoyo de una disciplina pluralista desde el punto de vista epistemológico y metodológico.

En quoi consiste la recherche de terain ? Est-elle uniquement réservée aux chercheurs qualitatifs ? Doit-elle être effectuée dans un pays étranger ? Combien de temps faut-il passer sur le terrain pour que ce soit « suffisant » ? Le manque de consensus disciplinaire sur ce qui constitue une « recherche de terrain » ou un « travail de terrain » a laissé les étudiants diplômés en sciences politiques sous-informés et donc sous-équipés pour tirer parti des recherches de terrain intensives afin d'aborder les questions d'intérêt et d'urgence dans les sous-domaines. L'inégalité de formation des programmes de doctorat a mené à une préparation insuffisante des chercheurs en début de carrière à la logistique du travail de terrain, qu'il s'agisse du développement de réseaux et de stratégies d’échantillonnage efficaces, de l'acquisition de la confiance des personnes interrogées ou des questions de financement, de sécurité physique, de santé mentale, d’éthique de recherche et de réponse aux crises qui y sont associées. Cet article s'appuie sur l'expérience de cinq jeunes chercheurs pour proposer des réponses aux questions que les étudiants diplômés se posent, souvent sans bénéficier des « enseignements tirés » par les autres. Ce guide pratique engage théorie et pratique en soutien à une discipline épistémologiquement et méthodologiquement pluraliste.

Days before embarking on her first field research trip, a Ph.D. student worries about whether she will be able to collect the qualitative data that she needs for her dissertation. Despite sending dozens of emails, she has received only a handful of responses to her interview requests. She wonders if she will be able to gain more traction in-country. Meanwhile, in the midst of drafting her thesis proposal, an M.A. student speculates about the feasibility of his project, given a modest budget. Thousands of miles away from home, a postdoc is concerned about their safety, as protests erupt outside their window and state security forces descend into the streets.

These anecdotes provide a small glimpse into the concerns of early-career researchers undertaking significant projects with a field research component. Many of these fieldwork-related concerns arise from an unfortunate shortage in curricular offerings for qualitative and mixed-method research in political science graduate programs ( Emmons and Moravcsik 2020 ), 1 as well as the scarcity of instructional materials for qualitative and mixed-method research, relative to those available for quantitative research ( Elman, Kapiszewski, and Kirilova 2015 ; Kapiszewski, MacLean, and Read 2015 ; Mosley 2013 ). A recent survey among the leading United States Political Science programs in Comparative Politics and International Relations found that among graduate students who have carried out international fieldwork, 62 percent had not received any formal fieldwork training and only 20 percent felt very or mostly prepared for their fieldwork ( Schwartz and Cronin-Furman 2020 , 7–8). This shortfall in training and instruction means that many young researchers are underprepared for the logistics of fieldwork, from developing networks and effective sampling strategies to building respondents’ trust. In addition, there is a notable lack of preparation around issues of funding, physical safety, mental health, research ethics, and crisis response. This is troubling, as field research is highly valued and, in some parts of the field, it is all but expected, for instance in comparative politics.

Beyond subfield-specific expectations, research that leverages multiple types of data and methods, including fieldwork, is one of the ways that scholars throughout the discipline can more fully answer questions of interest and urgency. Indeed, multimethod work, a critical means by which scholars can parse and evaluate causal pathways, is on the rise ( Weller and Barnes 2016 ). The growing appearance of multimethod research in leading journals and university presses makes adequate training and preparation all the more significant ( Seawright 2016 ; Nexon 2019 ).

We are five political scientists interested in providing graduate students and other early-career researchers helpful resources for field research that we lacked when we first began our work. Each of us has recently completed or will soon complete a Ph.D. at a United States or Swedish university, though we come from many different national backgrounds. We have conducted field research in our home countries and abroad. From Colombia and Guatemala to the United States, from Europe to Turkey, and throughout East and Southeast Asia, we have spanned the globe to investigate civil society activism and transitional justice in post-violence societies, conflict-related sexual violence, social movements, authoritarianism and contentious politics, and the everyday politics and interactions between refugees and host-country citizens.

While some of us have studied in departments that offer strong training in field research methods, most of us have had to self-teach, learning through trial and error. Some of us have also been fortunate to participate in short courses and workshops hosted by universities such as the Consortium for Qualitative Research Methods and interdisciplinary institutions such as the Peace Research Institute Oslo. Recognizing that these opportunities are not available to or feasible for all, and hoping to ease the concerns of our more junior colleagues, we decided to compile our experiences and recommendations for first-time field researchers.

Our experiences in the field differ in several key respects, from the time we spent in the field to the locations we visited, and how we conducted our research. The diversity of our experiences, we hope, will help us reach and assist the broadest possible swath of graduate students interested in field research. Some of us have spent as little as ten days in a given country or as much as several months, in some instances visiting a given field site location just once and in other instances returning several times. At times, we have been able to plan weeks and months in advance. Other times, we have quickly arranged focus groups and impromptu interviews. Other times still, we have completed interviews virtually, when research participants were in remote locations or when we ourselves were unable to travel, of note during the coronavirus pandemic. We have worked in countries where we are fluent or have professional proficiency in the language, and in countries where we have relied on interpreters. We have worked in settings with precarious security as well as in locations that feel as comfortable as home. Our guide is not intended to be prescriptive or exhaustive. What we offer is a set of experience-based suggestions to be implemented as deemed relevant and appropriate by the researcher and their advisor(s).

In terms of the types of research and data sources and collection, we have conducted archival research, interviews, focus groups, and ethnographies with diplomats, bureaucrats, military personnel, ex-combatants, civil society advocates, survivors of political violence, refugees, and ordinary citizens. We have grappled with ethical dilemmas, chief among them how to get useful data for our research projects in ways that exceed the minimal standards of human subjects’ research evaluation panels. Relatedly, we have contemplated how to use our platforms to give back to the individuals and communities who have so generously lent us their time and knowledge, and shared with us their personal and sometimes harrowing stories.

Our target audience is first and foremost graduate students and early-career researchers who are interested in possibly conducting fieldwork but who either (1) do not know the full potential or value of fieldwork, (2) know the potential and value of fieldwork but think that it is excessively cost-prohibitive or otherwise infeasible, or (3) who have the interest, the will, and the means but not necessarily the know-how. We also hope that this resource will be of value to graduate programs, as they endeavor to better support students interested in or already conducting field research. Further, we target instructional faculty and graduate advisors (and other institutional gatekeepers like journal and book reviewers), to show that fieldwork does not have to be year-long, to give just one example. Instead, the length of time spent in the field is a function of the aims and scope of a given project. We also seek to formalize and normalize the idea of remote field research, whether conducted because of security concerns in conflict zones, for instance, or because of health and safety concerns, like the Covid-19 pandemic. Accordingly, researchers in the field for shorter stints or who conduct fieldwork remotely should not be penalized.

We note that several excellent resources on fieldwork such as the bibliography compiled by Advancing Conflict Research (2020) catalogue an impressive list of articles addressing questions such as ethics, safety, mental health, reflexivity, and methods. Further resources can be found about the positionality of the researcher in the field while engaging vulnerable communities, such as in the research field of migration ( Jacobsen and Landau 2003 ; Carling, Bivand Erdal, and Ezzati 2014 ; Nowicka and Cieslik 2014 ; Zapata-Barrero and Yalaz 2019 ). However, little has been written beyond conflict-affected contexts, fragile settings, and vulnerable communities. Moreover, as we consulted different texts and resources, we found no comprehensive guide to fieldwork explicitly written with graduate students in mind. It is this gap that we aim to fill.

In this paper, we address five general categories of questions that graduate students puzzle over, often without the benefit of others’ “lessons learned.” First, What is field research? Is it just for qualitative scholars? Must it be conducted in a foreign country? How much time in the field is “enough”? Second, What is the purpose of fieldwork? When does it make sense to travel to a field site to collect data? How can fieldwork data be used? Third, What are the nuts and bolts? How does one get ready and how can one optimize limited time and financial resources? Fourth, How does one conduct fieldwork safely? What should a researcher do to keep themselves, research assistants, and research subjects safe? What measures should they take to protect their mental health? Fifth, How does one conduct ethical, beneficent field research?

Finally, the Covid-19 pandemic has impressed upon the discipline the volatility of research projects centered around in-person fieldwork. Lockdowns and closed borders left researchers sequestered at home and unable to travel, forced others to cut short any trips already begun, and unexpectedly confined others still to their fieldwork sites. Other factors that may necessitate a (spontaneous) readjustment of planned field research include natural disasters, a deteriorating security situation in the field site, researcher illness, and unexpected changes in personal circumstances. We, therefore, conclude with a section on the promise and potential pitfalls of remote (or virtual) fieldwork. Throughout this guide, we engage theory and praxis to support an epistemologically and methodologically pluralistic discipline.

The concept of “fieldwork” is not well defined in political science. While several symposia discuss the “nuts and bolts” of conducting research in the field within the pages of political science journals, few ever define it ( Ortbals and Rincker 2009 ; Hsueh, Jensenius, and Newsome 2014 ). Defining the concept of fieldwork is important because assumptions about what it is and what it is not underpin any suggestions for conducting it. A lack of disciplinary consensus about what constitutes “fieldwork,” we believe, explains the lack of a unified definition. Below, we discuss three areas of current disagreement about what “fieldwork” is, including the purpose of fieldwork, where it occurs, and how long it should be. We follow this by offering our definition of fieldwork.

First, we find that many in the discipline view fieldwork as squarely in the domain of qualitative research, whether interpretivist or positivist. However, field research can also serve quantitative projects—for example, by providing crucial context, supporting triangulation, or illustrating causal mechanisms. For instance, Kreft (2019) elaborated her theory of women's civil society mobilization in response to conflict-related sexual violence based on interviews she carried out in Colombia. She then examined cross-national patterns through statistical analysis. Conversely, Willis's research on the United States military in East Asia began with quantitative data collection and analysis of protest events before turning to fieldwork to understand why protests occurred in some instances but not others. Researchers can also find quantifiable data in the field that is otherwise unavailable to them at home ( Read 2006 ; Chambers-Ju 2014 ; Jensenius 2014 ). Accordingly, fieldwork is not in the domain of any particular epistemology or methodology as its purpose is to acquire data for further information.

Second, comparative politics and international relations scholars often opine that fieldwork requires leaving the country in which one's institution is based. Instead, we propose that what matters most is the nature of the research project, not the locale. For instance, some of us in the international relations subfield have interviewed representatives of intergovernmental organizations (IGOs) and international nongovernmental organizations (INGOs), whose headquarters are generally located in Global North countries. For someone pursuing a Ph.D. in the United States and writing on transnational advocacy networks, interviews with INGO representatives in New York certainly count as fieldwork ( Zvobgo 2020 ). Similarly, a graduate student who returns to her home country to interview refugees and native citizens is conducting a field study as much as a researcher for whom the context is wholly foreign. Such interviews can provide necessary insights and information that would not have been gained otherwise—one of the key reasons researchers conduct fieldwork in the first place. In other instances, conducting any in-person research is simply not possible, due to financial constraints, safety concerns, or other reasons. For example, the Covid-19 pandemic has forced many researchers to shift their face-to-face research plans to remote data collection, either over the phone or virtually ( Howlett 2021 , 2). For some research projects, gathering data through remote methods may yield the same if not similar information than in-person research ( Howlett 2021 , 3–4). As Howlett (2021 , 11) notes, digital platforms may offer researchers the ability to “embed ourselves in other contexts from a distance” and glimpse into our subjects’ lives in ways similar to in-person research. By adopting a broader definition of fieldwork, researchers can be more flexible in getting access to data sources and interacting with research subjects.

Third, there is a tendency, especially among comparativists, to only count fieldwork that spans the better part of a year; even “surgical strike” field research entails one to three months, according to some scholars ( Ortbals and Rincker 2009 ; Weiss, Hicken, and Kuhonta 2017 ). The emphasis on spending as much time as possible in the field is likely due to ethnographic research traditions, reflected in classics such as James Scott's Weapons of the Weak , which entail year-long stints of research. However, we suggest that the appropriate amount of time in the field should be assessed on a project-by-project basis. Some studies require the researcher to be in the field for long periods; others do not. For example, Willis's research on the discourse around the United States’ military presence in overseas host communities has required months in the field. By contrast, Kreft only needed ten days in New York to carry out interviews with diplomats and United Nations staff, in a context with which she already had some familiarity from a prior internship. Likewise, Zvobgo spent a couple of weeks in her field research sites, conducting interviews with directors and managers of prominent human rights nongovernmental organizations. This population is not so large as to require a whole month or even a few months. This has also been the case for Irgil, as she had spent one month in the field site conducting interviews with ordinary citizens. The goal of the project was to acquire information on citizens’ perceptions of refugees. As we discuss in the next section, when deciding how long to spend in the field, scholars must consider the information their project requires and consider the practicalities of fieldwork, notably cost.

Thus, we highlight three essential points in fieldwork and offer a definition accordingly: fieldwork involves acquiring information, using any set of appropriate data collection techniques, for qualitative, quantitative, or experimental analysis through embedded research whose location and duration is dependent on the project. We argue that adopting such a definition of “fieldwork” is necessary to include the multitude of forms fieldwork can take, including remote methods, whose value and challenges the Covid-19 pandemic has impressed upon the discipline.

When does a researcher need to conduct fieldwork? Fieldwork can be effective for (1) data collection, (2) theory building, and (3) theory testing. First, when a researcher is interested in a research topic, yet they could not find an available and/or reliable data source for the topic, fieldwork could provide the researcher with plenty of options. Some research agendas can require researchers to visit archives to review historical documents. For example, Greitens (2016) visited national archives in the Philippines, South Korea, Taiwan, and the United States to find historical documents about the development of coercive institutions in past authoritarian governments for her book, Dictators and Their Secret Police . Also, newly declassified archival documents can open new possibilities for researchers to examine restricted topics. To illustrate, thanks to the newly released archival records of the Chinese Communist Party's communications, and exchange of visits with the European communist world, Sarotte (2012) was able to study the Party's decision to crack down on Tiananmen protesters, which had previously been deemed as an unstudiable topic due to the limited data.

Other research agendas can require researchers to conduct (semistructured) in-depth interviews to understand human behavior or a situation more closely, for example, by revealing the meanings of concepts for people and showing how people perceive the world. For example, O'Brien and Li (2005) conducted in-depth interviews with activists, elites, and villagers to understand how these actors interact with each other and what are the outcomes of the interaction in contentious movements in rural China. Through research, they revealed that protests have deeply influenced all these actors’ minds, a fact not directly observable without in-depth interviews.

Finally, data collection through fieldwork should not be confined to qualitative data ( Jensenius 2014 ). While some quantitative datasets can be easily compiled or accessed through use of the internet or contact with data-collection agencies, other datasets can only be built or obtained through relationships with “gatekeepers” such as government officials, and thus require researchers to visit the field ( Jensenius 2014 ). Researchers can even collect their own quantitative datasets by launching surveys or quantifying data contained in archives. In a nutshell, fieldwork will allow researchers to use different techniques to collect and access original/primary data sources, whether these are qualitative, quantitative, or experimental in nature, and regardless of the intended method of analysis. 2

But fieldwork is not just for data collection as such. Researchers can accomplish two other fundamental elements of the research process: theory building and theory testing. When a researcher finds a case where existing theories about a phenomenon do not provide plausible explanations, they can build a theory through fieldwork ( Geddes 2003 ). Lee's experience provides a good example. When studying the rise of a protest movement in South Korea for her dissertation, Lee applied commonly discussed social movement theories, grievances, political opportunity, resource mobilization, and repression, to explain the movement's eruption and found that these theories do not offer a convincing explanation for the protest movement. She then moved on to fieldwork and conducted interviews with the movement participants to understand their motivations. Finally, through those interviews, she offered an alternative theory that the protest participants’ collective identity shaped during the authoritarian past played a unifying factor and eventually led them to participate in the movement. Her example shows that theorization can take place through careful review and rigorous inference during fieldwork.

Moreover, researchers can test their theory through fieldwork. Quantitative observational data has limitations in revealing causal mechanisms ( Esarey 2017 ). Therefore, many political scientists turn their attention to conducting field experiments or lab-in-the-field experiments to reveal causality ( Druckman et al. 2006 ; Beath, Christia, and Enikolopov 2013 ; Finseraas and Kotsadam 2017 ), or to leveraging in-depth insights or historical records gained through qualitative or archival research in process-tracing ( Collier 2011 ; Ricks and Liu 2018 ). Surveys and survey experiments may also be useful tools to substantiate a theoretical story or test a theory ( Marston 2020 ). Of course, for most Ph.D. students, especially those not affiliated with more extensive research projects, some of these options will be financially prohibitive.

A central concern for graduate students, especially those working with a small budget and limited time, is optimizing time in the field and integrating remote work. We offer three pieces of advice: have a plan, build in flexibility, and be strategic, focusing on collecting data that are unavailable at home. We also discuss working with local translators or research assistants. Before we turn to these more practical issues arising during fieldwork, we address a no less important issue: funding.

The challenge of securing funds is often overlooked in discussions of what constitutes field research. Months- or year-long in-person research can be cost-prohibitive, something academic gatekeepers must consider when evaluating “what counts” and “what is enough.” Unlike their predecessors, many graduate students today have a significant amount of debt and little savings. 3 Additionally, if researchers are not able to procure funding, they have to pay out of pocket and possibly take on more debt. Not only is in-person fieldwork costly, but researchers may also have to forego working while they are in the field, making long stretches in the field infeasible for some.

For researchers whose fieldwork involves travelling to another location, procuring funding via grants, fellowships, or other sources is a necessity, regardless of how long one plans to be in the field. A good mantra for applying for research funding is “apply early and often” ( Kelsky 2015 , 110). Funding applications take a considerable amount of time to prepare, from writing research statements to requesting letters of recommendation. Even adapting one's materials for different applications takes time. Not only is the application process itself time-consuming, but the time between applying for and receiving funds, if successful, can be quite long, from several months to a year. For example, after defending her prospectus in May 2019, Willis began applying to funding sources for her dissertation, all of which had deadlines between June and September. She received notifications between November and January; however, funds from her successful applications were not available until March and April, almost a year later. 4 Accordingly, we recommend applying for funding as early as possible; this not only increases one's chances of hitting the ground running in the field, but the application process can also help clarify the goals and parameters of one's research.

Graduate students should also apply often for funding opportunities. There are different types of funding for fieldwork: some are larger, more competitive grants such as the National Science Foundation Political Science Doctoral Dissertation Improvement Grant in the United States, others, including sources through one's own institution, are smaller. Some countries, like Sweden, boast a plethora of smaller funding agencies that disburse grants of 20,000–30,0000 Swedish Kronor (approx. 2,500–3,500 U.S. dollars) to Ph.D. students in the social sciences. Listings of potential funding sources are often found on various websites including those belonging to universities, professional organizations (such as the American Political Science Association or the European Consortium for Political Research), and governmental institutions dealing with foreign affairs. Once you have identified fellowships and grants for which you and your project are a good match, we highly recommend soliciting information and advice from colleagues who have successfully applied for them. This can include asking them to share their applications with you, and if possible, to have them, another colleague or set of colleagues read through your project description and research plan (especially for bigger awards) to ensure that you have made the best possible case for why you should be selected. While both large and small pots of funding are worth applying for, many researchers end up funding their fieldwork through several small grants or fellowships. One small award may not be sufficient to fund the entirety of one's fieldwork, but several may. For example, Willis's fieldwork in Japan and South Korea was supported through fellowships within each country. Similarly, Irgil was able to conduct her fieldwork abroad through two different and relatively smaller grants by applying to them each year.

Of course, situations vary in different countries with respect to what kinds of grants from what kinds of funders are available. An essential part of preparing for fieldwork is researching the funding landscape well in advance, even as early as the start of the Ph.D. We encourage first-time field researchers to be aware that universities and departments may themselves not be aware of the full range of possible funds available, so it is always a good idea to do your own research and watch research-related social media channels. The amount of funding needed thereby depends on the nature of one's project and how long one intends to be in the field. As we elaborate in the next section, scholars should think carefully about their project goals, the data required to meet those goals, and the requisite time to attain them. For some projects, even a couple of weeks in the field is sufficient to get the needed information.

Preparing to Enter “the field”

It is important to prepare for the field as much as possible. What kind of preparations do researchers need? For someone conducting interviews with NGO representatives, this might involve identifying the largest possible pool of potential respondents, securing their contact information, sending them study invitation letters, finding a mutually agreeable time to meet, and pulling together short biographies for each interviewee in order to use your time together most effectively. If you plan to travel to conduct interviews, you should reach out to potential respondents roughly four to six weeks prior to your arrival. For individuals who do not respond, you can follow up one to two weeks before you arrive and, if needed, once more when you are there. This is still no guarantee for success, of course. For Kreft, contacting potential interviewees in Colombia initially proved more challenging than anticipated, as many of the people she targeted did not respond to her emails. It turned out that many Colombians have a preference for communicating via phone or, in particular, WhatsApp. Some of those who responded to her emails sent in advance of her field trip asked her to simply be in touch once she was in the country, to set up appointments on short notice. This made planning and arranging her interview schedule more complicated. Therefore, a general piece of advice is to research your target population's preferred communication channels and mediums in the field site if email requests yield no or few responses.

In general, we note for the reader that contacting potential research participants should come after one has designed an interview questionnaire (plus an informed consent protocol) and sought and received, where applicable, approval from institutional review boards (IRBs) or other ethical review procedures in place (both at one's home institution/in the country of the home institution as well as in the country where one plans to conduct research if travelling abroad). The most obvious advantage of having the interview questionnaire in place and having secured all necessary institutional approvals before you start contacting potential interviewees is that you have a clearer idea of the universe of individuals you would like to interview, and for what purpose. Therefore, it is better to start sooner rather than later and be mindful of “high seasons,” when institutional and ethical review boards are receiving, processing, and making decisions on numerous proposals. It may take a few months for them to issue approvals.

On the subject of ethics and review panels, we encourage you to consider talking openly and honestly with your supervisors and/or funders about the situations where a written consent form may not be suitable and might need to be replaced with “verbal consent.” For instance, doing fieldwork in politically unstable contexts, highly scrutinized environments, or vulnerable communities, like refugees, might create obstacles for the interviewees as well as the researcher. The literature discusses the dilemma in offering the interviewees anonymity and requesting signed written consent in addition to the emphasis on total confidentiality ( Jacobsen and Landau 2003 ; Mackenzie, McDowell, and Pittaway 2007 ; Saunders, Kitzinger, and Kitzinger 2015 ). Therefore, in those situations, the researcher might need to take the initiative on how to act while doing the interviews as rigorously as possible. In her fieldwork, Irgil faced this situation as the political context of Turkey did not guarantee that there would not be any adverse consequences for interviewees on both sides of her story: citizens of Turkey and Syrian refugees. Consequently, she took hand-written notes and asked interviewees for their verbal consent in a safe interview atmosphere. This is something respondents greatly appreciated ( Irgil 2020 ).

Ethical considerations, of course, also affect the research design itself, with ramifications for fieldwork. When Kreft began developing her Ph.D. proposal to study women's political and civil society mobilization in response to conflict-related sexual violence, she initially aimed to recruit interviewees from the universe of victims of this violence, to examine variation among those who did and those who did not mobilize politically. As a result of deeper engagement with the literature on researching conflict-related sexual violence, conversations with senior colleagues who had interviewed victims, and critical self-reflection of her status as a researcher (with no background in psychology or social work), she decided to change focus and shift toward representatives of civil society organizations and victims’ associations. This constituted a major reconfiguration of her research design, from one geared toward identifying the factors that drive mobilization of victims toward using insights from interviews to understand better how those mobilize perceive and “make sense” of conflict-related sexual violence. Needless to say, this required alterations to research strategies and interview guides, including reassessing her planned fieldwork. Kreft's primary consideration was not to cause harm to her research participants, particularly in the form of re-traumatization. She opted to speak only with those women who on account of their work are used to speaking about conflict-related sexual violence. In no instance did she inquire about interviewees’ personal experiences with sexual violence, although several brought this up on their own during the interviews.

Finally, if you are conducting research in another country where you have less-than-professional fluency in the language, pre-fieldwork planning should include hiring a translator or research assistant, for example, through an online hiring platform like Upwork, or a local university. Your national embassy or consulate is another option; many diplomatic offices have lists of individuals who they have previously contracted. More generally, establishing contact with a local university can be beneficial, either in the form of a visiting researcher arrangement, which grants access to research groups and facilities like libraries or informally contacting individual researchers. The latter may have valuable insights into the local context, contacts to potential research participants, and they may even be able to recommend translators or research assistants. Kreft, for example, hired local research assistants recommended by researchers at a Bogotá-based university and remunerated them equivalent to the salary they would have received as graduate research assistants at the university, while also covering necessary travel expenses. Irgil, on the other hand, established contacts with native citizens and Syrian gatekeepers, who are shop owners in the area where she conducted her research because she had the opportunity to visit the fieldwork site multiple times.

Depending on the research agenda, researchers may visit national archives, local government offices, etc. Before visiting, researchers should contact these facilities and make sure the materials that they need are accessible. For example, Lee visited the Ronald Reagan Presidential Library Archives to find the United States’ strategic evaluations on South Korea's dictator in the 1980s. Before her visit, she contacted librarians in the archives, telling them her visit plans and her research purpose. Librarians made suggestions on which categories she should start to review based on her research goal, and thus she was able to make a list of categories of the materials she needed, saving her a lot of her time.

Accessibility of and access to certain facilities/libraries can differ depending on locations/countries and types of facilities. Facilities in authoritarian countries might not be easily accessible to foreign researchers. Within democratic countries, some facilities are more restrictive than others. Situations like the pandemic or national holidays can also restrict accessibility. Therefore, researchers are well advised to do preliminary research on whether a certain facility opens during the time they visit and is accessible to researchers regardless of their citizenship status. Moreover, researchers must contact the staff of facilities to know whether identity verification is needed and if so, what kind of documents (photo I.D. or passport) should be exhibited.

Adapting to the Reality of the Field

Researchers need to be flexible because you may meet people you did not make appointments with, come across opportunities you did not expect, or stumble upon new ideas about collecting data in the field. These happenings will enrich your field experience and will ultimately be beneficial for your research. Similarly, researchers should not be discouraged by interviews that do not go according to plan; they present an opportunity to pursue relevant people who can provide an alternative path to your work. Note that planning ahead does not preclude fortuitous encounters or epiphanies. Rather, it provides a structure for them to happen.

If your fieldwork entails travelling abroad, you will also be able to recruit more interviewees once you arrive at your research site. In fact, you may have greater success in-country; not everyone is willing to respond to a cold email from an unknown researcher in a foreign country. In Irgil's fieldwork, she contacted store owners that are known in the area and who know the community. This eased her process of introduction into the community and recruiting interviewees. For Zvobgo, she had fewer than a dozen interviews scheduled when she travelled to Guatemala to study civil society activism and transitional justice since the internal armed conflict. But she was able to recruit additional participants in-country. Interviewees with whom she built a rapport connected her to other NGOs, government offices, and the United Nations country office, sometimes even making the call and scheduling interviews for her. Through snowball sampling, she was able to triple the number of participants. Likewise, snowball sampling was central to Kreft's recruitment of interview partners. Several of her interviewees connected her to highly relevant individuals she would never have been able to identify and contact based on web searches alone.

While in the field, you may nonetheless encounter obstacles that necessitate adjustments to your original plans. Once Kreft had arrived in Colombia, for example, it transpired quickly that carrying out in-person interviews in more remote/rural areas was near impossible given her means, as these were not easily accessible by bus/coach, further complicated by a complex security situation. Instead, she adjusted her research design and shifted her focus to the big cities, where most of the major civil society organizations are based. She complemented the in-person interviews carried out there with a smaller number of phone interviews with civil society activists in rural areas, and she was also able to meet a few activists operating in rural or otherwise inaccessible areas as they were visiting the major cities. The resulting focus on urban settings changed the kinds of generalizations she was able to make based on her fieldwork data and produced a somewhat different study than initially anticipated.

This also has been the case for Irgil, despite her prior arrangements with the Syrian gatekeepers, which required adjustments as in the case of Kreft. Irgil acquired research clearance one year before, during the interviews with native citizens, conducting the interviews with Syrian refugees. She also had her questionnaire ready based on the previously collected data and the media search she had conducted for over a year before travelling to the field site. As she was able to visit the field site multiple times, two months before conducting interviews with Syrian refugees, she developed a schedule with the Syrian gatekeepers and informants. Yet, once she was in the field, influenced by Turkey's recent political events and the policy of increasing control over Syrian refugees, half of the previously agreed informants changed their minds or did not want to participate in interviews. As Irgil was following the policies and the news related to Syrian refugees in Turkey closely, this did not come as that big of a surprise but challenged the previously developed strategy to recruit interviewees. Thus, she changed the strategy of finding interviewees in the field site, such as asking people, almost one by one, whether they would like to participate in the interview. Eventually, she could not find willing Syrian women refugees as she had planned, which resulted in a male-dominant sample. As researchers encounter such situations, it is essential to remind oneself that not everything can go according to plan, that “different” does not equate to “worse,” but that it is important to consider what changes to fieldwork data collection and sampling imply for the study's overall findings and the contribution it makes to the literature.

We should note that conducting interviews is very taxing—especially when opportunities multiply, as in Zvobgo's case. Depending on the project, each interview can take an hour, if not two or more. Hence, you should make a reasonable schedule: we recommend no more than two interviews per day. You do not want to have to cut off an interview because you need to rush to another one, whether the interviews are in-person or remote. And you do not want to be too exhausted to have a robust engagement with your respondent who is generously lending you their time. Limiting the number of interviews per day is also important to ensure that you can write comprehensive and meaningful fieldnotes, which becomes even more essential where it is not possible to audio-record your interviews. Also, be sure to remember to eat, stay hydrated, and try to get enough sleep.

Finally, whether to provide gifts or payments to the subject also requires adapting to the reality of the field. You must think about payments beforehand when you apply for IRB approval (or whatever other ethical review processes may be in place) since these applications usually contain questions about payments. Obviously, the first step is to carefully evaluate whether the gifts and payments provided can harm the subject or are likely to unduly affect the responses they will give in response to your questions. If that is not the case, you have to make payment decisions based on your budget, field situation, and difficulties in recruitment. Usually, payment of respondents is more common in survey research, whereas it is less common in interviews and focus groups.

Nevertheless, payment practices vary depending on the field and the target group. In some cases, it may become a custom to provide small gifts or payments when interviewing a certain group. In other cases, interviewees might be offended if they are provided with money. Therefore, knowing past practices and field situations is important. For example, Lee provided small coffee gift cards to one group while she did not to the other based on previous practices of other researchers. That is, for a particular group, it has become a custom for interviewers to pay interviewees. Sometimes, you may want to reimburse your subject's interview costs such as travel expenses and provide beverages and snacks during the conduct of research, as Kreft did when conducting focus groups in Colombia. To express your gratitude to your respondents, you can prepare small gifts such as your university memorabilia (e.g., notebooks and pens). Since past practices about payments can affect your interactions and interviews with a target group, you want to seek advice from your colleagues and other researchers who had experiences interacting with the target group. If you cannot find researchers who have this knowledge, you can search for published works on the target population to find if the authors share their interview experiences. You may also consider contacting the authors for advice before your interviews.

Researching Strategically

Distinguishing between things that can only be done in person at a particular site and things that can be accomplished later at home is vital. Prioritize the former over the latter. Lee's fieldwork experience serves as a good example. She studied a conservative protest movement called the Taegeukgi Rally in South Korea. She planned to conduct interviews with the rally participants to examine their motivations for participating. But she only had one month in South Korea. So, she focused on things that could only be done in the field: she went to the rally sites, she observed how protests proceeded, which tactics and chants were used, and she met participants and had some casual conversations with them. Then, she used the contacts she made while attending the rallies to create a social network to solicit interviews from ordinary protesters, her target population. She was able to recruit twenty-five interviewees through good rapport with the people she met. The actual interviews proceeded via phone after she returned to the United States. In a nutshell, we advise you not to be obsessed with finishing interviews in the field. Sometimes, it is more beneficial to use your time in the field to build relationships and networks.

Working With Assistants and Translators

A final consideration on logistics is working with research assistants or translators; it affects how you can carry out interviews, focus groups, etc. To what extent constant back-and-forth translation is necessary or advisable depends on the researcher's skills in the interview language and considerations about time and efficiency. For example, Kreft soon realized that she was generally able to follow along quite well during her interviews in Colombia. In order to avoid precious time being lost to translation, she had her research assistant follow the interview guide Kreft had developed, and interjected follow-up questions in Spanish or English (then to be translated) as they arose.

Irgil's and Zvobgo's interviews went a little differently. Irgil's Syrian refugee interviewees in Turkey were native Arabic speakers, and Zvobgo's interviewees in Guatemala were native Spanish speakers. Both Irgil and Zvobgo worked with research assistants. In Irgil's case, her assistant was a Syrian man, who was outside of the area. Meanwhile, Zvobgo's assistant was an undergraduate from her home institution with a Spanish language background. Irgil and Zvobgo began preparing their assistants a couple of months before entering the field, over Skype for Irgil and in-person for Zvobgo. They offered their assistants readings and other resources to provide them with the necessary background to work well. Both Irgil and Zvobgo's research assistants joined them in the interviews and actually did most of the speaking, introducing the principal investigator, explaining the research, and then asking the questions. In Zvobgo's case, interviewee responses were relayed via a professional interpreter whom she had also hired. After every interview, Irgil and Zvobgo and their respective assistants discussed the answers of the interviewees, potential improvements in phrasing, and elaborated on their hand-written interview notes. As a backup, Zvobgo, with the consent of her respondents, had accompanying audio recordings.

Researchers may carry out fieldwork in a country that is considerably less safe than what they are used to, a setting affected by conflict violence or high crime rates, for instance. Feelings of insecurity can be compounded by linguistic barriers, cultural particularities, and being far away from friends and family. Insecurity is also often gendered, differentially affecting women and raising the specter of unwanted sexual advances, street harassment, or even sexual assault ( Gifford and Hall-Clifford 2008 ; Mügge 2013 ). In a recent survey of Political Science graduate students in the United States, about half of those who had done fieldwork internationally reported having encountered safety issues in the field, (54 percent female, 47 percent male), and only 21 percent agreed that their Ph.D. programs had prepared them to carry out their fieldwork safely ( Schwartz and Cronin-Furman 2020 , 8–9).

Preventative measures scholars may adopt in an unsafe context may involve, at their most fundamental, adjustments to everyday routines and habits, restricting one's movements temporally and spatially. Reliance on gatekeepers may also necessitate adopting new strategies, such as a less vehement and cold rejection of unwanted sexual advances than one ordinarily would exhibit, as Mügge (2013) illustratively discusses. At the same time, a competitive academic job market, imperatives to collect novel and useful data, and harmful discourses surrounding dangerous fieldwork also, problematically, shape incentives for junior researchers to relax their own standards of what constitutes acceptable risk ( Gallien 2021 ).

Others have carefully collected a range of safety precautions that field researchers in fragile or conflict-affected settings may take before and during fieldwork ( Hilhorst et al. 2016 ). Therefore, we are more concise in our discussion of recommendations, focusing on the specific situations of graduate students. Apart from ensuring that supervisors and university administrators have the researcher's contact information in the field (and possibly also that of a local contact person), researchers can register with their country's embassy or foreign office and any crisis monitoring and prevention systems it has in place. That way, they will be informed of any possible unfolding emergencies and the authorities have a record of them being in the country.

It may also be advisable to set up more individualized safety protocols with one or two trusted individuals, such as friends, supervisors, or colleagues at home or in the fieldwork setting itself. The latter option makes sense in particular if one has an official affiliation with a local institution for the duration of the fieldwork, which is often advisable. Still, we would also recommend establishing relationships with local researchers in the absence of a formal affiliation. To keep others informed of her whereabouts, Kreft, for instance, made arrangements with her supervisors to be in touch via email at regular intervals to report on progress and wellbeing. This kept her supervisors in the loop, while an interruption in communication would have alerted them early if something were wrong. In addition, she announced planned trips to other parts of the country and granted her supervisors and a colleague at her home institution emergency reading access to her digital calendar. To most of her interviews, she was moreover accompanied by her local research assistant/translator. If the nature of the research, ethical considerations, and the safety situation allow, it might also be possible to bring a local friend along to interviews as an “assistant,” purely for safety reasons. This option needs to be carefully considered already in the planning stage and should, particularly in settings of fragility or if carrying out research on politically exposed individuals, be noted in any ethical and institutional review processes where these are required. Adequate compensation for such an assistant should be ensured. It may also be advisable to put in place an emergency plan, that is, choose emergency contacts back home and “in the field,” know whom to contact if something happens, and know how to get to the nearest hospital or clinic.

We would be remiss if we did not mention that, when in an unfamiliar context, one's safety radar may be misguided, so it is essential to listen to people who know the context. For example, locals can give advice on which means of transport are safe and which are not, a question that is of the utmost importance when traveling to appointments. For example, Kreft was warned that in Colombia regular taxis are often unsafe, especially if waved down in the streets, and that to get to her interviews safely, she should rely on a ride-share service. In one instance, a Colombian friend suggested that when there was no alternative to a regular taxi, Kreft should book through the app and share the order details, including the taxi registration number or license plate, with a friend. Likewise, sharing one's cell phone location with a trusted friend while traveling or when one feels unsafe may be a viable option. Finally, it is prudent to heed the safety recommendations and travel advisories provided by state authorities and embassies to determine when and where it is safe to travel. Especially if researchers have a responsibility not only for themselves but also for research assistants and research participants, safety must be a top priority.

This does not mean that a researcher should be careless in a context they know either. Of course, conducting fieldwork in a context that is known to the researcher offers many advantages. However, one should be prepared to encounter unwanted events too. For instance, Irgil has conducted fieldwork in her country of origin in a city she knows very well. Therefore, access to the site, moving around the site, and blending in has not been a problem; she also has the advantage of speaking the native language. Yet, she took notes of the streets she walked in, as she often returned from the field site after dark and thought she might get confused after a tiring day. She also established a closer relationship with two or three store owners in different parts of the field site if she needed something urgent, like running out of battery. Above all, one should always be aware of one's surroundings and use common sense. If something feels unsafe, chances are it is.

Fieldwork may negatively affect the researcher's mental health and mental wellbeing regardless of where one's “field” is, whether related to concerns about crime and insecurity, linguistic barriers, social isolation, or the practicalities of identifying, contacting and interviewing research participants. Coping with these different sources of stress can be both mentally and physically exhausting. Then there are the things you may hear, see and learn during the research itself, such as gruesome accounts of violence and suffering conveyed in interviews or archival documents one peruses. Kreft and Zvobgo have spoken with women victims of conflict-related sexual violence, who sometimes displayed strong emotions of pain and anger during the interviews. Likewise, Irgil and Willis have spoken with members of other vulnerable populations such as refugees and former sex workers ( Willis 2020 ).

Prior accounts ( Wood 2006 ; Loyle and Simoni 2017 ; Skjelsbæk 2018 ; Hummel and El Kurd 2020 ; Williamson et al. 2020 ; Schulz and Kreft 2021 ) show that it is natural for sensitive research and fieldwork challenges to affect or even (vicariously) traumatize the researcher. By removing researchers from their regular routines and support networks, fieldwork may also exacerbate existing mental health conditions ( Hummel and El Kurd 2020 ). Nonetheless, mental wellbeing is rarely incorporated into fieldwork courses and guidelines, where these exist at all. But even if you know to anticipate some sort of reaction, you rarely know what that reaction will be until you experience it. When researching sensitive or difficult topics, for example, reactions can include sadness, frustration, anger, fear, helplessness, and flashbacks to personal experiences of violence ( Williamson et al. 2020 ). For example, Kreft responded with episodic feelings of depression and both mental and physical exhaustion. But curiously, these reactions emerged most strongly after she had returned from fieldwork and in particular as she spent extended periods analyzing her interview data, reliving some of the more emotional scenes during the interviews and being confronted with accounts of (sexual) violence against women in a concentrated fashion. This is a crucial reminder that fieldwork does not end when one returns home; the after-effects may linger. Likewise, Zvobgo was physically and mentally drained upon her return from the field. Both Kreft and Zvobgo were unable to concentrate for long periods of time and experienced lower-than-normal levels of productivity for weeks afterward, patterns that formal and informal conversations with other scholars confirm to be common ( Schulz and Kreft 2021 ). Furthermore, the boundaries between “field” and “home” are blurred when conducting remote fieldwork ( Howlett 2021 , 11).

Nor are these adverse reactions limited to cases where the researcher has carried out the interviews themselves. Accounts of violence, pain, and suffering transported in reports, secondary literature, or other sources can evoke similar emotional stress, as Kreft experienced when engaging in a concentrated fashion with additional accounts of conflict-related sexual violence in Colombia and with the feminist literature on sexual and gender-based violence in the comfort of her Swedish office. This could also be applicable to Irgil's fieldwork as she interviewed refugees whose traumas have come out during the interviews or recall specific events triggered by the questions. Likewise, Lee has reviewed primary and secondary materials on North Korean defectors in the national archives and these materials contain violent, intense, emotional narratives.

Fortunately, there are several strategies to cope with and manage such adverse consequences. In a candid and insightful piece, other researchers have discussed the usefulness of distractions, sharing with colleagues, counseling, exercise, and, probably less advisable in the long term, comfort eating and drinking ( Williamson et al. 2020 ; see also Loyle and Simoni 2017 ; Hummel and El Kurd 2020 ). Our experiences largely tally with their observations. In this section, we explore some of these in more detail.

First, in the face of adverse consequences on your mental wellbeing, whether in the field or after your return, it is essential to be patient and generous with yourself. Negative effects on the researcher's mental wellbeing can hit in unexpected ways and at unexpected times. Even if you think that certain reactions are disproportionate or unwarranted at that specific moment, they may simply have been building up over a long time. They are legitimate. Second, the importance of taking breaks and finding distractions, whether that is exercise, socializing with friends, reading a good book, or watching a new series, cannot be overstated. It is easy to fall into a mode of thinking that you constantly have to be productive while you are “in the field,” to maximize your time. But as with all other areas in life, balance is key and rest is necessary. Taking your mind off your research and the research questions you puzzle over is also a good way to more fully soak up and appreciate the context in which you find yourself, in the case of in-person fieldwork, and about which you ultimately write.

Third, we cannot stress enough the importance of investing in social relations. Before going on fieldwork, researchers may want to consult others who have done it before them. Try to find (junior) scholars who have done fieldwork on similar kinds of topics or in the same country or countries you are planning to visit. Utilizing colleagues’ contacts and forging connections using social media are valuable strategies to expand your networks (in fact, this very paper is the result of a social media conversation and several of the authors have never met in person). Having been in the same situation before, most field researchers are, in our experience, generous with their time and advice. Before embarking on her first trip to Colombia, Kreft contacted other researchers in her immediate and extended network and received useful advice on questions such as how to move around Bogotá, whom to speak to, and how to find a research assistant. After completing her fieldwork, she has passed on her experiences to others who contacted her before their first fieldwork trip. Informal networks are, in the absence of more formalized fieldwork preparation, your best friend.

In the field, seeking the company of locals and of other researchers who are also doing fieldwork alleviates anxiety and makes fieldwork more enjoyable. Exchanging experiences, advice and potential interviewee contacts with peers can be extremely beneficial and make the many challenges inherent in fieldwork (on difficult topics) seem more manageable. While researchers conducting remote fieldwork may be physically isolated from other researchers, even connecting with others doing remote fieldwork may be comforting. And even when there are no precise solutions to be found, it is heartening or even cathartic to meet others who are in the same boat and with whom you can talk through your experiences. When Kreft shared some of her fieldwork-related struggles with another researcher she had just met in Bogotá and realized that they were encountering very similar challenges, it was like a weight was lifted off her shoulders. Similarly, peer support can help with readjustment after the fieldwork trip, even if it serves only to reassure you that a post-fieldwork dip in productivity and mental wellbeing is entirely natural. Bear in mind that certain challenges are part of the fieldwork experience and that they do not result from inadequacy on the part of the researcher.

Finally, we would like to stress a point made by Inger Skjelsbæk (2018 , 509) and which has not received sufficient attention: as a discipline, we need to take the question of researcher mental wellbeing more seriously—not only in graduate education, fieldwork preparation, and at conferences, but also in reflecting on how it affects the research process itself: “When strong emotions arise, through reading about, coding, or talking to people who have been impacted by [conflict-related sexual violence] (as victims or perpetrators), it may create a feeling of being unprofessional, nonscientific, and too subjective.”

We contend that this is a challenge not only for research on sensitive issues but also for fieldwork more generally. To what extent is it possible, and desirable, to uphold the image of the objective researcher during fieldwork, when we are at our foundation human beings? And going even further, how do the (anticipated) effects of our research on our wellbeing, and the safety precautions we take ( Gifford and Hall-Clifford 2008 ), affect the kinds of questions we ask, the kinds of places we visit and with whom we speak? How do they affect the methods we use and how we interpret our findings? An honest discussion of affective responses to our research in methods sections seems utopian, as emotionality in the research process continues to be silenced and relegated to the personal, often in gendered ways, which in turn is considered unconnected to the objective and scientific research process ( Jamar and Chappuis 2016 ). But as Gifford and Hall-Clifford (2008 , 26) aptly put it: “Graduate education should acknowledge the reality that fieldwork is scholarly but also intimately personal,” and we contend that the two shape each other. Therefore, we encourage political science as a discipline to reflect on researcher wellbeing and affective responses to fieldwork more carefully, and we see the need for methods courses that embrace a more holistic notion of the subjectivity of the researcher.

Interacting with people in the field is one of the most challenging yet rewarding parts of the work that we do, especially in comparison to impersonal, often tedious wrangling and analysis of quantitative data. Field researchers often make personal connections with their interviewees. Consequently, maintaining boundaries can be a bit tricky. Here, we recommend being honest with everyone with whom you interact without overstating the abilities of a researcher. This appears as a challenge in the field, particularly when you empathize with people and when they share profound parts of their lives with you for your research in addition to being “human subjects” ( Fujii 2012 ). For instance, when Irgil interviewed native citizens about the changes in their neighborhood following the arrival of Syrian refugees, many interviewees questioned what she would offer them in return for their participation. Irgil responded that her primary contribution would be her published work. She also noted, however, that academic papers can take a year, sometimes longer, to go through the peer-reviewed process and, once published, many studies have a limited audience. The Syrian refugees posed similar questions. Irgil responded not only with honesty but also, given this population's vulnerable status, she provided them contact information for NGOs with which they could connect if they needed help or answers to specific questions.

For her part, Zvobgo was very upfront with her interviewees about her role as a researcher: she recognized that she is not someone who is on the frontlines of the fight for human rights and transitional justice like they are. All she could/can do is use her platform to amplify their stories, bringing attention to their vital work through her future peer-reviewed publications. She also committed to sending them copies of the work, as electronic journal articles are often inaccessible due to paywalls and university press books are very expensive, especially for nonprofits. Interviewees were very receptive; some were even moved by the degree of self-awareness and the commitment to do right by them. In some cases, this prompted them to share even more, because they knew that the researcher was really there to listen and learn. This is something that junior scholars, and all scholars really, should always remember. We enter the field to be taught. Likewise, Kreft circulated among her interviewees Spanish-language versions of an academic article and a policy brief based on the fieldwork she had carried out in Colombia.

As researchers from the Global North, we recognize a possible power differential between us and our research subjects, and certainly an imbalance in power between the countries where we have been trained and some of the countries where we have done and continue to do field research, particularly in politically dynamic contexts ( Knott 2019 ). This is why we are so concerned with being open and transparent with everyone with whom we come into contact in the field and why we are committed to giving back to those who so generously lend us their time and knowledge. Knott (2019 , 148) summarizes this as “Reflexive openness is a form of transparency that is methodologically and ethically superior to providing access to data in its raw form, at least for qualitative data.”

We also recognize that academics, including in the social sciences and especially those hailing from countries in the Global North, have a long and troubled history of exploiting their power over others for the sake of their research—including failing to be upfront about their research goals, misrepresenting the on-the-ground realities of their field research sites (including remote fieldwork), and publishing essentializing, paternalistic, and damaging views and analyses of the people there. No one should build their career on the backs of others, least of all in a field concerned with the possession and exercise of power. Thus, it is highly crucial to acknowledge the power hierarchies between the researcher and the interviewees, and to reflect on them both in the field and beyond the field upon return.

A major challenge to conducting fieldwork is when researchers’ carefully planned designs do not go as planned due to unforeseen events outside of our control, such as pandemics, natural disasters, deteriorating security situations in the field, or even the researcher falling ill. As the Covid-19 pandemic has made painfully clear, researchers may face situations where in-person research is simply not possible. In some cases, researchers may be barred entry to their fieldwork site; in others, the ethical implications of entering the field greatly outweigh the importance of fieldwork. Such barriers to conducting in-person research require us to reconsider conventional notions of what constitutes fieldwork. Researchers may need to shift their data collection methods, for example, conducting interviews remotely instead of in person. Even while researchers are in the field, they may still need to carry out part of their interviews or surveys virtually or by phone. For example, Kreft (2020) carried out a small number of interviews remotely while she was based in Bogotá, because some of the women's civil society activists with whom she intended to speak were based in parts of the country that were difficult and/or dangerous to access.

Remote field research, which we define as the collection of data over the internet or over the phone where in-person fieldwork is not possible due to security, health or other risks, comes with its own sets of challenges. For one, there may be certain populations that researchers cannot reach remotely due to a lack of internet connectivity or technology such as cellphones and computers. In such instances, there will be a sampling bias toward individuals and groups that do have these resources, a point worth noting when scholars interpret their research findings. In the case of virtual research, the risk of online surveillance, hacking, or wiretapping may also produce reluctance on the part of interviewees to discuss sensitive issues that may compromise their safety. Researchers need to carefully consider how the use of digital technology may increase the risk to research participants and what changes to the research design and any interview guides this necessitates. In general, it is imperative that researchers reflect on how they can ethically use digital technology in their fieldwork ( Van Baalen 2018 ). Remote interviews may also be challenging to arrange for researchers who have not made connections in person with people in their community of interest.

Some of the serendipitous happenings we discussed earlier may also be less likely and snowball sampling more difficult. For example, in phone or virtual interviews, it is harder to build good rapport and trust with interviewees as compared to face-to-face interviews. Accordingly, researchers should be more careful in communicating with interviewees and creating a comfortable interview environment. Especially when dealing with sensitive topics, researchers may have to make several phone calls and sometimes have to open themselves to establishing trust with interviewees. Also, researchers must be careful in protecting interviewees in phone or virtual interviews when they deal with sensitive topics of countries interviewees reside in.

The inability to physically visit one's community of interest may also encourage scholars to critically reflect on how much time in the field is essential to completing their research and to consider creative, alternative means for accessing information to complete their projects. While data collection techniques such as face-to-face interviews and archival work in the field may be ideal in normal times, there exist other data sources that can provide comparably useful information. For example, in her research on the role of framing in the United States base politics, Willis found that social media accounts and websites yielded information useful to her project. Many archives across the world have also been digitized. Researchers may also consider crowdsourcing data from the field among their networks, as fellow academics tend to collect much more data in the field than they ever use in their published works. They may also elect to hire someone, perhaps a graduate student, in a city or a country where they cannot travel and have the individual access, scan, and send archival materials. This final suggestion may prove generally useful to researchers with limited time and financial resources.

Remote qualitative data collection techniques, while they will likely never be “the gold-standard,” also pose several advantages. These techniques may help researchers avoid some of the issues mentioned previously. Remote interviews, for example, are less time-consuming in terms of travel to the interview site ( Archibald et al. 2019 ). The implication is that researchers may have less fatigue from conducting interviews and/or may be able to conduct more interviews. For example, while Willis had little energy to do anything else after an in-person interview (or two) in a given day, she had much more energy after completing remote interviews. Second, remote fieldwork also helps researchers avoid potentially dangerous situations in the field mentioned previously. Lastly, remote fieldwork generally presents fewer financial barriers than in-person research ( Archibald et al. 2019 ). In that sense, considering remote qualitative data collection, a type of “fieldwork” may make fieldwork more accessible to a greater number of scholars.

Many of the substantive, methodological and practical challenges that arise during fieldwork can be anticipated. Proper preparation can help you hit the ground running once you enter your fieldwork destination, whether in-person or virtually. Nonetheless, there is no such thing as being perfectly prepared for the field. Some things will simply be beyond your control, and especially as a newcomer to field research, and you should be prepared for things to not go as planned. New questions will arise, interview participants may cancel appointments, and you might not get the answers you expected. Be ready to make adjustments to research plans, interview guides, or questionnaires. And, be mindful of your affective reactions to the overall fieldwork situation and be gentle with yourself.

We recommend approaching fieldwork as a learning experience as much as, or perhaps even more than, a data collection effort. This also applies to your research topic. While it is prudent always to exercise a healthy amount of skepticism about what people tell you and why, the participants in your research will likely have unique perspectives and knowledge that will challenge yours. Be an attentive listener and remember that they are experts of their own experiences.

We encourage more institutions to offer courses that cover field research preparation and planning, practical advice on safety and wellbeing, and discussion of ethics. Specifically, we align with Schwartz and Cronin-Furman's (2020 , 3) contention “that treating fieldwork preparation as the methodology will improve individual scholars’ experiences and research.” In this article, we outline a set of issue areas in which we think formal preparation is necessary, but we note that our discussion is by no means exhaustive. Formal fieldwork preparation should also extend beyond what we have covered in this article, such as issues of data security and preparing for nonqualitative fieldwork methods. We also note that field research is one area that has yet to be comprehensively addressed in conversations on diversity and equity in the political science discipline and the broader academic profession. In a recent article, Brielle Harbin (2021) begins to fill this gap by sharing her experiences conducting in-person election surveys as a Black woman in a conservative and predominantly white region of the United States and the challenges that she encountered. Beyond race and gender, citizenship, immigration status, one's Ph.D. institution and distance to the field also affect who is able to do what type of field research, where, and for how long. Future research should explore these and related questions in greater detail because limits on who is able to conduct field research constrict the sociological imagination of our field.

While Emmons and Moravcsik (2020) focus on leading Political Science Ph.D. programs in the United States, these trends likely obtain, both in lower ranked institutions in the broader United States as well as in graduate education throughout North America and Europe.

As all the authors have carried out qualitative fieldwork, this is the primary focus of this guide. This does not, however, mean that we exclude quantitative or experimental data collection from our definition of fieldwork.

There is great variation in graduate students’ financial situations, even in the Global North. For example, while higher education is tax-funded in most countries in Europe and Ph.D. students in countries such as Sweden, Norway, Denmark, the Netherlands, and Switzerland receive a comparatively generous full-time salary, healthcare and contributions to pension schemes, Ph.D. programs in other contexts like the United States and the United Kingdom have (high) enrollment fees and rely on scholarships, stipends, or departmental duties like teaching to (partially) offset these, while again others, such as Germany, are commonly financed by part-time (50 percent) employment at the university with tasks substantively unrelated to the dissertation. These different preconditions leave many Ph.D. students struggling financially and even incurring debt, while others are in a more comfortable financial position. Likewise, Ph.D. programs around the globe differ in structure, such as required coursework, duration and supervision relationships. Naturally, all of these factors have a bearing on the extent to which fieldwork is feasible. We acknowledge unequal preconditions across institutions and contexts, and trust that those Ph.D. students interested in pursuing fieldwork are best able to assess the structural and institutional context in which they operate and what this implies for how, when, and how long to carry out fieldwork.

In our experience, this is not only the general cycle for graduate students in North America, but also in Europe and likely elsewhere.

For helpful advice and feedback on earlier drafts, we wish to thank the editors and reviewers at International Studies Review , and Cassandra Emmons. We are also grateful to our interlocuters in Argentina, Canada, Colombia, Germany, Guatemala, Japan, Kenya, Norway, the Philippines, Sierra Leone, South Korea, Spain, Sweden, Turkey, the United Kingdom, and the United States, without whom this reflection on fieldwork would not have been possible. All authors contributed equally to this manuscript.

This material is based upon work supported by the Forskraftstiftelsen Theodor Adelswärds Minne, Knut and Alice Wallenberg Foundation(KAW 2013.0178), National Science Foundation Graduate Research Fellowship Program(DGE-1418060), Southeast Asia Research Group (Pre-Dissertation Fellowship), University at Albany (Initiatives for Women and the Benevolent Association), University of Missouri (John D. Bies International Travel Award Program and Kinder Institute on Constitutional Democracy), University of Southern California (Provost Fellowship in the Social Sciences), Vetenskapsrådet(Diarienummer 2019-06298), Wilhelm och Martina Lundgrens Vetenskapsfond(2016-1102; 2018-2272), and William & Mary (Global Research Institute Pre-doctoral Fellowship).

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Qualitative study design: Field research

• Qualitative study design
• Phenomenology
• Grounded theory
• Ethnography
• Narrative inquiry
• Action research
• Case Studies

Field research

• Focus groups
• Observation
• Surveys & questionnaires
• Study Designs Home

To understand attitudes, practices, roles, organisations, groups, or behaviours in their natural setting

In a way you have probably done field research before – when you’ve been in a doctor’s waiting room, or on an aeroplane. Field research is at its core about observing and participating in social behaviour and trying to understand it. Qualitative field research takes these natural skills and curiosities and refines them to address and answer a research question The “field” is vast, consisting of numerous people, activities, events, and words. When undertaking field research, the researcher needs to determine the exact activities or practices that are of interest to the researcher to answer their research question. Instead of the more artificial environment of an interview or survey, field research lets researchers observe subtle communications, cues, or other events that they may not have anticipated or even measured otherwise.

Field research is often referred to interchangeably as “participant observation”. Participant observation is a type of field research where the researcher is an active participant in the everyday life, habits, or beliefs of the field alongside members. An example of this might be where a researcher goes into a hospital and works alongside hospital staff. A contrast to this is “direct observation”, a type of field research where the researcher observes members in the field but doesn’t actively participate. An example might be a researcher who sits at a hospital cafeteria and observes staff who may not realize they’re being studied.

You may be wondering what the difference is between ethnography and field research. The two terms are often used interchangeably, so it can be a really blurred line! Ethnography is about making sense of culture – it’s about making a detailed overview of the social group and organising your information. Field research is going out into the field – so describing “how” you’re going to conduct research. Ethnographical research can be field research (as in, you’re studying the culture of a hospital by observing within the hospital), or field research can be ethnographic (you’re observing staff in a hospital to see how staff handle crisis intervention). It’s a fine line between the two, and even experienced researchers can be unsure of the difference (or even use the terms interchangeably, depending on discipline), so when in doubt, it is best to talk to your supervisor or an experienced researcher in this discipline

Different studies may benefit from different degrees of researcher involvement. Ultimately, the researcher needs to be sensitive to the impact their presence might have on the data and on participants – and also aware of any ethical requirements around this study type, such as informed consent, duties to report (such as if the researcher observes criminal activities), and confidentiality and privacy of participants.

Observation, unstructured interviews

• Allows for observation in a natural setting
• Picks up on subtle cues
• Allows in depth exploration which contributes to a full appreciation of what’s being studied, including “whys” around human behaviour

Limitations

• Requires a high degree of sensitivity by the researcher to the impact of the research and their presence on participants and on the data
• Risk of reactivity, where research subjects may alter their behaviour from what it would have been normally as a result of being studied
• Ethical considerations involved in insider research
• Possible loss of objectivity

Example questions

How do student nurses integrate their training into care provision at end-of-life?

Example studies

• Barber-Parker, E. (2002). Integrating patient teaching into bedside patient care: a participant-observation study of hospital nurses.  Patient Education and Counselling, 48 ( 2): 107-113  
• Shikuku, D., Milimo, B., Ayebare, E., Gisore, P., & Gorrette, N. (2018). Practice and outcomes of neonatal resuscitation for newborns with birth asphyxia at Kakamega County General Hospital, Kenya: a direct observation study, BMC Pediatrics, 18 (1), doi: 10.1186/s12887-018-1127-6  

Babbie, E. (2008). The basics of social research (4th ed). Belmont: Thomson Wadsworth

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Case Study vs. Research

What's the difference.

Case study and research are both methods used in academic and professional settings to gather information and gain insights. However, they differ in their approach and purpose. A case study is an in-depth analysis of a specific individual, group, or situation, aiming to understand the unique characteristics and dynamics involved. It often involves qualitative data collection methods such as interviews, observations, and document analysis. On the other hand, research is a systematic investigation conducted to generate new knowledge or validate existing theories. It typically involves a larger sample size and employs quantitative data collection methods such as surveys, experiments, or statistical analysis. While case studies provide detailed and context-specific information, research aims to generalize findings to a broader population.

Further Detail

Introduction.

When it comes to conducting studies and gathering information, researchers have various methods at their disposal. Two commonly used approaches are case study and research. While both methods aim to explore and understand a particular subject, they differ in their approach, scope, and the type of data they collect. In this article, we will delve into the attributes of case study and research, highlighting their similarities and differences.

A case study is an in-depth analysis of a specific individual, group, event, or phenomenon. It involves a detailed examination of a particular case to gain insights into its unique characteristics, context, and dynamics. Case studies often employ multiple sources of data, such as interviews, observations, and documents, to provide a comprehensive understanding of the subject under investigation.

One of the key attributes of a case study is its focus on a specific case, which allows researchers to explore complex and nuanced aspects of the subject. By examining a single case in detail, researchers can uncover rich and detailed information that may not be possible with broader research methods. Case studies are particularly useful when studying rare or unique phenomena, as they provide an opportunity to deeply analyze and understand them.

Furthermore, case studies often employ qualitative research methods, emphasizing the collection of non-numerical data. This qualitative approach allows researchers to capture the subjective experiences, perspectives, and motivations of the individuals or groups involved in the case. By using open-ended interviews and observations, researchers can gather rich and detailed data that provides a holistic view of the subject.

However, it is important to note that case studies have limitations. Due to their focus on a specific case, the findings may not be easily generalized to a larger population or context. The small sample size and unique characteristics of the case may limit the generalizability of the results. Additionally, the subjective nature of qualitative data collection in case studies may introduce bias or interpretation challenges.

Research, on the other hand, is a systematic investigation aimed at discovering new knowledge or validating existing theories. It involves the collection, analysis, and interpretation of data to answer research questions or test hypotheses. Research can be conducted using various methods, including surveys, experiments, and statistical analysis, depending on the nature of the study.

One of the primary attributes of research is its emphasis on generating generalizable knowledge. By using representative samples and statistical techniques, researchers aim to draw conclusions that can be applied to a larger population or context. This allows for the identification of patterns, trends, and relationships that can inform theories, policies, or practices.

Research often employs quantitative methods, focusing on the collection of numerical data that can be analyzed using statistical techniques. Surveys, experiments, and statistical analysis allow researchers to measure variables, establish correlations, and test hypotheses. This objective approach provides a level of objectivity and replicability that is crucial for scientific inquiry.

However, research also has its limitations. The focus on generalizability may sometimes sacrifice the depth and richness of understanding that case studies offer. The reliance on quantitative data may overlook important qualitative aspects of the subject, such as individual experiences or contextual factors. Additionally, the controlled nature of research settings may not fully capture the complexity and dynamics of real-world situations.

Similarities

Despite their differences, case studies and research share some common attributes. Both methods aim to gather information and generate knowledge about a particular subject. They require careful planning, data collection, analysis, and interpretation. Both case studies and research contribute to the advancement of knowledge in their respective fields.

Furthermore, both case studies and research can be used in various disciplines, including social sciences, psychology, business, and healthcare. They provide valuable insights and contribute to evidence-based decision-making. Whether it is understanding the impact of a new treatment, exploring consumer behavior, or investigating social phenomena, both case studies and research play a crucial role in expanding our understanding of the world.

In conclusion, case study and research are two distinct yet valuable approaches to studying and understanding a subject. Case studies offer an in-depth analysis of a specific case, providing rich and detailed information that may not be possible with broader research methods. On the other hand, research aims to generate generalizable knowledge by using representative samples and quantitative methods. While case studies emphasize qualitative data collection, research focuses on quantitative analysis. Both methods have their strengths and limitations, and their choice depends on the research objectives, scope, and context. By utilizing the appropriate method, researchers can gain valuable insights and contribute to the advancement of knowledge in their respective fields.

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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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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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Field Guide to Case Study Research in Tourism, Hospitality and Leisure: Volume 6

Table of contents

Field guide to case study research in tourism, hospitality and leisure, advances in culture, tourism and hospitality research, copyright page, list of contributors, why case study research introduction to the field guide to case study research in tourism, hospitality, and leisure.

This chapter is a general introduction to the field of case study research in tourism, hospitality, and leisure. The chapter presents a brief review of the literature on the intra-individual logic of case study research. The chapter describes the “four horsemen” for doing case study research: accuracy, generality, complexity/coverage, and value/impact. Examples in the chapter that illustrate this perspective for undertaking case study research may impassion the reader to read through the field guide and personally engage in case study research – at least that is the hope of the editors of this field guide.

Analysis of Texts – Introduction

The Field Guide opens with a series of chapters addressing somewhat disparate issues – touristification of the countryside, emotions experienced in a secular pilgrimage, assessment of museum performance, tourists’ packing for travel and the role of the hospitality receptionist. Yet, what these chapters hold in common is their broad approach to case study research. Each chapter presents findings based on the analysis of texts. Here we use the term texts in its broadest sense, to mean the written word, spoken word or visual image intended to express meaning. Thus, amongst these chapters we see research findings generated from the analysis of words and images in tourism promotional materials; analysis of the diaries of tourists; computer software analysis of concepts generated from focus group discussions amongst museum stakeholders; verbal protocol analysis and videotape analysis of a tourist packing for travel; analysis of story, poetry and metaphor used by hospitality reception staff to express their lived experiences of their jobs. Each of the chapters concludes with comment on lessons learned about the processes of data gathering and analysis.

Immersed in Green? Reconfiguring the Italian Countryside Through Rural Tourism Promotional Materials

Rural tourism agents and operators occupy a central role in the use and diffusion of certain social representations of rurality through the mobilization and utilization of specific (yet increasingly global) signs and symbols that, in the urban imaginary, characterize typical and traditional rural settings. Rural tourism promotional materials may contribute to the reconfiguration of the countryside more in accordance with an idealized rural than with the reality of local features. This chapter examines how rural areas and rurality are presented and commodified, using an exploratory content analysis of online and offline materials combined with a survey directed at rural tourism entrepreneurs in five municipalities of two different Italian regions – Campania and Tuscany. Evidence strongly suggests a discrepancy between the real and the portrayed rurality, pointing at the emergence or reinforcement of rural reconfiguration processes, shaped by external and often global images and imaginaries.

Evoked Emotions: Textual Analysis Within the Context of Pilgrimage Tourism to Gallipoli

This chapter focuses on tourism from Australia to Gallipoli to attend Anzac Day commemorations. The research examines diary excerpts of tourists to Gallipoli using theory on emotions to gain insights into the consumption experience. We describe this tourist experience as a pilgrimage, as it is purposeful and is aimed at reaching a specific destination that has spiritual meaning for the consumer. We found that this tourist experience elicits both positively and negatively valanced emotions. The findings highlight that not all tourism experiences elicit hedonically related emotions; however, the outcome of the experience can be positive. Further research on emotions that explores this paradox between emotions in consumption and emotions in post-consumption will assist to understand the ways in which consumers process their emotions within this context.

Using Concept Mapping and Stakeholder Focus Groups in a Museum Management Case Study

This chapter describes a participatory case study undertaken at a museum in New Zealand, involving a varied range of museum stakeholders. The research investigated aspects of museum performance assessment in the context of public accountability from the perspectives of different communities of interest, including Maori, the indigenous people of New Zealand. The complex research design involved identifying key stakeholders, and then conducting focus groups with a diversity of stakeholder types. Through a brainstorming process, these groups co-created texts which formed the raw data for the study. The stakeholder-generated texts were interpreted at various stages to produce ‘Possible Performance Statements’ which reflected the understandings and concerns of the various stakeholders in relation to the case museum's performance. Adopting the concept mapping approach developed by Trochim, the focus group participants then sorted the statements into conceptual constructs which made sense to them, and also rated the statements according to their relative importance as criteria for assessing their museum's performance. Proprietary software that is used to analyse the sorting and rating data produced concept maps and pattern matches which facilitated interpretation of the participants’ perspectives. The visual representations of the quantitative analyses enabled qualitative consideration leading to the development of a framework for museum performance assessment which would be more holistic and locally relevant and which would address stakeholder concerns.

The application of this intricate hybrid research design provided lessons which suggested other ways to gain richer data and deeper insights from the concept mapping approach, especially in a cross-cultural context. Participatory approaches which allow collective, as opposed to individual, interpretation of the co-created texts may be more suitable in certain cultural contexts, in this instance among Maori participants. The approach adopted was resource-intensive, requiring tight organisation and flexibility, greatly assisted by piloting the processes and using a professional editor to prepare the texts for interpretation by the participants. To maximise the insights from the focus groups, audio-recording of the research participants’ discussions as they generated their texts relating to museum performance assessment should be considered, as well as involving participants in the interpretation of the concept maps.

Assessing the Grounded Theory of Packing for Air Travel Using a Video-Ethnographic Case Study

Packing for travel is an intriguing aspect of tourist behavior. Until recently, no research has sought to explain what the modern traveler packs for air journeys or why these items are packed. Perhaps for some observers these questions appear mundane, and the answers appear obvious, yet these issues attract a great volume on commentary on websites, blogs, in travel books, in magazines, and conversations between travelers. From these sources, Hyde and Olesen (2011) developed a grounded theory of packing for air travel. The purpose of this article is to test the grounded theory of packing for air travel using video-ethnographic case study data. The findings are that the grounded theory for air travel is able to explain what possessions are packed and the motives for these items being packed. The emphasis that any individual places on the possessions they pack and the role these possessions play during a journey will differ by traveler. This adds to extant literature on packing for travel.

Using Expressive Text in Research to Interpret and Portray Lived Experience: Lived Experience in Hospitality Receptionist Work

This chapter examines how hospitality and tourism researchers can use ‘expressive text’ (or writing) to express the lived quality of an experience in order to ‘show what an experience is really like’ rather than ‘tell what it is like’. Expressive text refers to written language forms such as narrative, poetry and metaphor that can be used as tools in research to vividly represent the meaning and feeling conveyed in an experience. The expressive text-based approach to researching lived experience provides a textual link between experience and its expression. For this reason, it is especially useful when working with lived experience accounts of phenomenological and hermeneutic research.

The expressive text-based approach suggested here is still a relatively under explored arena within hospitality and tourism research. As a relatively under explored arena, the rich insightful knowledge that can be gained from understanding practitioner experience is rarely a central focus of scholarly writings about the workplace in hospitality and tourism contexts. However, in order to be fully appreciated as a discipline in its own right and to advance knowledge of the field, understanding the typical and significant attributes of hospitality and tourism work will be decidedly helpful.

One of the difficulties of working with lived experience accounts is finding a suitable research approach that helps to both retain the lived elements of the experience and ensure the rigour of the inquiry. An expressive text-based methodological framework that has a phenomenological and hermeneutic philosophical underpinning is argued to be suitable for this purpose. Therefore, the focus of this study is to discuss such a methodology and explain the reasons for its content, style and structure in researching lived experience. The approach that is proposed here consists of a five-tiered textually expressive methodology that is employed to contextualise, portray and interpret the lived experience meanings in order to understand the significance of the experience in relation to relevant discourses in hospitality and tourism studies, and to consider implications for policy and professional practice. The guiding questions of the five-tiered framework cover the following issues: (1) What is the context of the lived experience? (2) What is the lived experience of this practice like? (3) What is the meaning of this experience for the practitioner? (4) What is the significance of the experience in contributing to the advancement of knowledge within the field? (5) What are the implications for practice and professional development?

To illustrate uses of this methodology in research, the study here includes an example showing portrayals and interpretations of the typical and significant lived nature of hospitality reception work. This shows and communicates the full meaning of the episode, circumstances or situation. The chapter then concludes with some reflections on benefits as well as tensions in working within an expressive text-based phenomenological and hermeneutic framework.

Executive Interviews – Introduction

Each of the three chapters in this part of the Field Guide has, as its primary data source, interviews with tourism and hospitality executives. Sushma Seth Bhat (2012) , in her chapter titled Single Case Study Research: The Development of www.purenz.com , explains how she compiled a single case on the development of a destination website, based on interviews with tourism industry executives in New Zealand. In her chapter titled Fashions in Tourism: The Views of Russian Tourists and Experts , Olga Lysikova (2012) utilises information from interviews with travel industry executives to address the question, are there fashions in tourist behaviour? Cindia Ching-Chi Lam and Clara Weng-Si Lei's (2012) chapter, Case Studies in Multicultural Contexts in Asia , presents experiences acquired in undertaking two case study projects in Macao, with much of the data gathered from interviews with executives in the Macao hotel industry.

Single Case Study Research: The Development of www.purenz.com

This chapter shares with readers the author's reflections on the process of deciding upon and carrying out research using a single case study. The purpose of the research was to understand the nature and dynamics of co-operation in destination marketing and to contribute to the development of a relevant theoretical framework for the study of co-operation in destination marketing. Fig. 1 summarises the process used to carry out this study; each stage of this process is further elaborated upon in the chapter. The chapter concludes with the author's reflections on what has been learned from this project about the joys and perils of case study research.

Fashions in Tourism: The Views of Russian Tourists and Experts

It is fashionable among Russians to travel all over the world. The author researches the social and cultural phenomenon of fashions in tourism based on analysis of the views of Russian tourists and experts from the tourism sphere. The criteria for prestige of a tourism destination are considered. Fashion trends in the practices of Russian tourists are analyzed.

Case Studies in Multicultural Contexts in Asia

Networking, gatekeeper access, understanding of “localized talks,” and jargon are revealed to be influential factors on the quality and richness of case study research (CSR) data. Rapport between the researcher and the interviewee not only affect the depth of the data collected but also the credibility and completeness of the final research output. This chapter discusses these features of CSR by employing two different CSR studies. The chapter provides practical insights to promote the interviewee's confidence in revealing sensitive data, through a three-step procedure.

Field Research – Introduction

In the first chapter in Part Three, Jan Louise Jones provides useful practical advice for the first-time tourism researcher for doing participant observation research. Keep a daily journal and actually talk with participant actors to learn their plans, actions, and interpretations of outcomes are two takeaway proposals to look for when reading Jones’ contribution. The references are very useful sources that expand of Jones’ recommendations. The mistake to avoid is thinking that you will be able to remember all the daily details and nuances of your observations without a written daily journal.

Practical Tips for Conducting Research Abroad

The purpose of this research is to highlight some of the experiences and lessons learned from participating in qualitative research abroad for the first time. The chapter provides an overview of an international research trip to Cuba to study the impact of tourism on a tourist's value stance and highlights some of the feelings and emotions a researcher may experience when embarking on this type of trip. Tips for conducting research before, during and after a trip, are provided throughout the chapter.

Knowledge Spillovers and Entrepreneurial Opportunities: The Case of Sannio FilmFest

Scholars tend to examine knowledge spillover particularly with reference to science-based and hi-tech industries, but little is known about this phenomenon within cultural industries. Some entrepreneurship scholars try to figure out how new ventures can arise starting from knowledge spillovers. This chapter shows how knowledge spillovers can occur within cultural industries and why it is usually difficult for these moments to give rise to entrepreneurial initiatives. The chapter offers a case study to provide a deep understanding of the phenomenon and to identify areas for future research.

Epiphany Travel and Assisted-Subjective Personal Introspection

The study uses assisted-subjective personal introspection (ASPI) to analyze, assess, and critique a traveler's adventure as well as uncover the rationale behind why participating in a long trip with global implications was important to this traveler. Coupled with a thorough ASPI analysis, the study constructs an autoethnography: a form of autobiographical personal narrative that explores a traveler's experience of life. To equip the traveler with the necessary skills and tools to perform this analysis, the study includes research using ASPI and autoethnography. Finally, participating in Harvard University's “Implicit Association Test” (IAT) provides an external analysis and better understanding of own conscious–unconscious divergences. Using causal mapping, the study delineates a 14-week trip into weekly increments identifying positive and negative relationships while assessing the strengths of those relationships. The goal of this exercise is twofold: (1) to increase understanding of the human condition and (2) how that understanding can influence international marketing.

Functions and Behaviors of Tourists in Experience Management Process: Case of Three Independent Business Tourists

Tourism literature tends to focus on passive tourists, who constitute the majority of tourists today. However, there is a growing number of individuals who overlap their study, work, and business with tourism activities. These independent tourists have created a new segment in the tourism industry, where tourists develop and experience their own tourism activities. However, there is a lack of current research on these independent tourists, especially in terms of how they function in the experience management process and how this can be translated into various new types of offers.

This study investigates the functions, experiences, and behaviors of this type of tourists. Accordingly, this study makes use of purposive sampling, employing direct observation, in-depth interviews, and analysis of personal social media (e.g., blogs). The findings show that while some independent tourists function in a multitude of ways, from searching for ideas to composing, creating, and experiencing their own products, others are less active and tend to piggyback their efforts on those of more active tourists. The study finds that the motivational matrix is highly important for individuals who combine work and tourism. Working persons with a strong motivation for tourism relative to work maintain high levels of commitment, activity, and creativity in the tourism sphere, especially when they face problems with their work. Highly satisfied independent tourists initiate future actions by either revisiting the same destination or leading others to have similar experiences at the same location. Finally, the chapter discusses some methodological lessons learned from direct observation and in-depth interviews and studying social media.

Case Studies of International Tourists’ in-Destination Decision-Making Processes in New Zealand

We report field research undertaken in five sites in New Zealand in which we explored the process of tourists’ in-destination decision-making. We then critique our experiences of conducting this project.

Stakeholder Participatory Research – Introduction

This section of the Field Guide presents an alternative paradigm for case study research, stakeholder participatory research. Such research takes an alternative viewpoint from that of researcher as owner of the research process, or researcher as disinterested creator of knowledge for general consumption. Instead, the four chapters here present an alternative view on who should own the research process and who should benefit from the knowledge that research generates. In answer to both of these questions, stakeholder participatory research has a singular answer: the local community-based stakeholder should own and benefit from case study research.

Participatory Action Research for Stakeholder Collaboration: Lessons from a Rural Area in Piedmont, Italy

Participatory Action Research, or PAR, draws on the paradigms of critical theory and constructivism (Whyte, W. F. (1989). Advancing scientific knowledge through participatory action research. Sociological Forum, 32(5), 499–623) and aims to influence the design and outcomes of behaviours occurring in a case study (Woodside, A. G. (2010a). Case study research: Theory, methods and practice (p. 13). Bingley, UK: Emerald). In tourism studies, this methodology is relevant for renewing research orientation and paradigms for stakeholder collaboration, as the approach focuses on the principle of empowering local actors in community-based development processes.

This chapter explores PAR with an exploratory case study in a rural area of Piedmont, Italy. The case study demonstrates that PAR is a valid approach when the research purposes are not only to produce a deep understanding of forms of collaborations but also to create a co-operative climate by planning actions with local actors. The research approach involves evaluating deliberated actions and thereby stimulating strategic thinking in resource allocation processes.

Protecting Social and Cultural Identity in Sustainable Tourism: The Case of Gökçeada, Turkey

Sustainable tourism development is a concept that recognizes both environmental and socio-cultural limits to development. It also recognizes that as tourist numbers increase, socio-cultural and environmental costs increase. As such, sustainable tourism considers social and cultural liability, economic productivity and ecological sensibility in all its processes. The sustainability of the tourism industry can only be assured through maintaining the natural, social and cultural values of regional areas that rely on a tourism industry.

In this case study of tourism on Gökçeada (Imbros) Island in Turkey, a model is developed which explains the maintenance of social, cultural, natural and architectural environments to achieve sustainability in tourism. The case study research employs interviews, observation and Delphi techniques. A SWOT analysis on how best to protect and develop the social and cultural identity of Gökçeada is completed based on the findings of the interviews, observations, Delphi analysis and literature. A Sustainable Tourism Tree Model is presented for tourism in Gökçeada. Future applications of the Sustainable Tourism Tree Model, both for generating development of tourist destinations in a sustainable way and for resolving socio-cultural challenges in development, are discussed.

Accessibility as Competitive Advantage of a Tourism Destination: The Case of Lousã

Tourism destinations are facing intense and increasing competition worldwide, while consumers are ever more demanding, requiring not only service quality but also socially responsible and sustainable destinations. In this context, developing accessible tourism at a destination may help gain competitiveness in an underserved, typically most loyal market. Developing accessible tourism may also create a culture of social responsibility. This would enhance a shared, human and involving vision of the destination amongst stakeholders, including tourists who increasingly value socially responsible positions of economic actors in the tourism industry. The development of this approach is shown for Lousã, a small tourism destination focusing on accessible tourism as a core of its development strategy, a strategy developed through a stakeholder participatory approach. In this chapter, we present a study that helped develop the strategic positioning of Lousã, combining qualitative and quantitative methods and integrating visions of several relevant stakeholders.

DIT-ACHIEV Model for Sustainable Tourism Management: Lessons Learned from Implementing a Holistic Model of Sustainable Tourism Indicators

The DIT-ACHIEV Model recognises that tourism is an important source of revenue, investment and employment throughout Ireland. It is particularly important in rural regions, given the unique selling point provided by the beauty and character of rural Ireland that must be managed correctly and in a sustainable manner to ensure its success and longevity. Tourism's impacts (direct and indirect) on areas such as the environment, transport, regional planning, business and trade mean that policies and plans must be coordinated and integrated to avoid one area of policy pressurising or hindering the success of another.

The main thrust of this chapter is on learnings from piloting the Model, which is an indicators-based tool for evaluating the state of tourism in a destination. In developing appropriate methodologies, a variety of innovative research approaches have been tested and the resultant efforts to reach appropriate and valid results in each instance are the focus of this chapter. All of the research tools require local participation in varying degrees from volunteers, residents, students, businesses, organisations, etc. In some instances, these processes have proven to be highly successful; in others, more challenging. One of the key outcomes of developing the methodologies is increased learning in the area of local agency empowerment/facilitation. These are lessons that can be transferred in a practical and real way to any local-level tourism research project.

Researching Indigenous and Marginal Peoples – Introduction

Those promoting tourism often seek to highlight that which is unique about their destinations in order to attract tourists. Many countries have beautiful landscapes, rich histories and heritage, and the tourist may come to see linkages of landscape and history across different countries and indeed possibly across continents. However, in the search for the unique, those countries with ethnic minority or other minority groups demarcated by factors other than ethnicity but characterised by special belief systems or ways of life living within their borders (e.g. the Amish) are truly able to offer the tourist a glimpse of something that will not be found in other parts of the world. Accordingly, and being aware that holiday makers are not lay anthropologists and may be seeking little more than an entertainment, minorities and their culture have become in many places a staged show based primarily on song and dance. Indeed, such has been the process that Xie (2011, p. 196) provides an example from the island of Hainan, China, where tourism promoters have created ‘the authentic Chiyou tribe’ to entertain tourists – a tribe developed purely for entertainment based on concepts of the exotic and primitive and only loosely based on the culture of the native Li people. One partial result described by Xie (2011) has been that the Li themselves have become confused as to their own culture.

Fieldwork in Remote Communities: An Ethnographic Case Study of Pitcairn Island

This research examines, in a case study of Pitcairn Island, the meaning of community. Such meanings emerge in the empirical field whereby the ‘field’ offers its own cues to both issue and method. The main lesson learned from this ethnographic study stems from the experiential nature of fieldwork whereby ‘community’ is viewed as a cluster of embodied dispositions and practices. Influenced by Anthony Cohen's ethnographic work (1978, 1985) the case study demonstrates the centrality of the symbolic dimensions of community as a defining characteristic. Described as one of the most isolated islands in the world accessible only by sea, Pitcairn is the last remaining British ‘colony’ in the Pacific, settled in 1790 by English mutineers and Tahitians following the (in)famous mutiny on the Bounty. It represents in an anthropological sense a unique microcosm of social structure, studied ethnographically only a handful of times. Results show symbolic referents contribute to a sense of ‘exclusivity’ of Pitcairn culture that facilitates co-operation and collectivity whilst also recognizing the internal–external dialectics of boundaries of identification. The study reveals culture as a symbolic rather than structural construct as experienced by its members, seeing the community as a cultural field with a complex of symbols whose meanings vary amongst its members. Thus, connection and contiguity of culture continually transform the meaning of community, space and place. As such, community continues to be of both practical and ideological significance to the practice of anthropology.

Stakeholders, High Stakes and High Tides: Quality of Life in a Small Island Festival Context

The aim of this chapter is to reflect on some of the implications in doing fieldwork in a small and relatively isolated island community. In 2009, a Danish island in the Wadden Sea National Park, only reachable by motor vehicles when the tide is out, was selected to host one of the many events taking place during the biannual Wadden Sea Festival. The aim of the project was to create vanishing art depicting the quality of life (QoL) on the island by use of materials found in the island's natural environment. Prior to the implementation of the event and as a part of the project, the authors were invited to qualitatively investigate the QoL among island residents, specifically focusing on subjective well-being. Through a description of stakeholder connections and conflicts, a number of lessons are discerned and pondered upon. In addition to applying the case to demonstrate and discuss how researchers can investigate QoL in tourism and how research(ers) impact small communities, we also reflect on the unforeseen consequences and entanglements of a seemingly (because of its size) ‘straightforward’ field of research. It is argued that field studies in very small communities more easily expose not only ‘outside’ interference, but also controversies and conflicts between neighbours, within families and between dwellers and professions of multiple sorts. Consequently we argue that researchers must continuously reflect on their own role in and relations to the places and communities – the ‘cases’ – which they investigate.

Use of Mixed-Methods Case Study to Research Sustainable Tourism Development in South Pacific SIDS

Triangulation of research methods is crucial to thoroughly explore how tourism can be better linked to the local economy in the Pacific's ‘Small Island Developing States’ (SIDS) because it includes the use of multiple data collections, analytical methods, data sources and theories or perspectives (Rocco et al., 2003). The exploration of the interactions between the various stakeholders in tourism and the wider economy will help linkages to be understood and enhanced. The research focuses on the following stakeholders: tourists, growers, small and medium tourism enterprises (SMTEs), government officials and village councils. The study explores the ways in which each of these stakeholder groups interacts with each other and their perspectives on the issues surrounding the linkages between tourism and agriculture.

The purpose of this chapter is to demonstrate the use of a case study of Niue and multiple data-gathering techniques to collect critical information on the linkages between tourism and agriculture in Pacific SIDS. The findings and lessons learned from a single case study of Niue using a mixed-methods approach potentially benefit other island nations in the region. This chapter begins with a discussion on the usefulness of case study research and then justifies the use of a mixed-methods approach and multiple stakeholders to better understand the linkages between tourism and agriculture in SIDS. The complexities of the inter-sectoral analysis being undertaken and the lack of prior data in this area necessitated a mixed-methods approach to the research. The chapter thoroughly discusses the research process and participants, including the design of research tools and the conduct of field work. Then the chapter focuses on research findings and concludes by reviewing the lessons learned from this research approach and its use of a case study and mixed methods to gain a holistic insight into the potential for enhancing the linkages between tourism and agriculture on Niue.

Culturally Sustainable Entrepreneurship: A Case Study for Hopi Tourism

This chapter examines how values relating to sustainability of indigenous cultures together with values relating to establishing economic autonomy through entrepreneurial initiatives can be accommodated in developing tourism policy. Specifically, the Hopi tribe of Arizona in the United States is investigated. Sustainable entrepreneurship, cultural sustainability, and cultural citizenship are used as theoretical frameworks to comprehend capacities for tourism policy that consider social, economic, and cultural impacts, as well as the integrated nature of these impacts on the Hopi tribe. Survey data was used to operationalize the concepts. Embodying core principles for protection of culture within a tourism policy along with procedural elements for compliance has the best chance for achieving the aims of preservation and development of cultural identity.

Cross-Case Analysis – Introduction

This section of the book comprises three chapters written by Oksana Grybovych, Susan Slocum, Ken Backman, Elisabeth Baldwin and Chris Ryan. The first two by Grybovych (2012) and Slocum, Backman, and Baldwin (2012) respectively report research processes related to specific projects, while the last seeks to provide an analysis associated with cross-case study research. By definition cross-case analysis relates to comparisons being made across different places, or of the same place across different times (a longitudinal analysis such as that by Gu & Ryan, 2008, 2011, in their studies of Shi Chi Hai Hutong in Beijing) or indeed of different places at different times, but related to each other by the commonality of a theme identified by the researcher.

Designing a Qualitative Multi-Case Research Study to Examine Participatory Community Tourism Planning Practices

This chapter explores methodological aspects of designing a qualitative multi-case research study to examine the issues of citizen participation, new democratic forms of planning, and community tourism planning. The study discussed below took place during the months of June 2007–March 2008 in three North American communities – two in the United States and one in Canada. The purposes of the study were to compare and contrast the current practices of citizen involvement in community tourism planning with the framework of deliberative democracy, to expand the literature on tourism planning, and to contribute to the development of a model of participatory community tourism planning to be adopted by communities and planners pursuing tourism as a development tool. This chapter focuses on methodological intricacies of designing a qualitative multi-case research study, those wishing to explore the project more are referred to Grybovych (2008).

Independent Instrumental Case Studies: Allowing for the Autonomy of Cultural, Social and Business Networks in Tanzania

Tourism is being utilized as a key economic development tool of the 21st century. Serious concern over the benefit of tourism for the poor has contributed to discussion on community involvement and community participation in contemporary literature. In particular, sustainable development has become a way to address the long-term viability of income and employment in least-developed countries while attempting to preserve traditional customs and culture in the face of globalization. Sustainability refers to finding solutions to poverty without compromising the natural and cultural resource base needed by future generations to pursue their own economic goals. This task requires attention to the economic, cultural and social needs of all groups while focusing on solutions that are also viable for the long term (Bramwell, 2001; Davidson, 2007; Mfaume & Leonard, 2004). It is also important to note that social structures and cultural references vary noticeably within countries and regions. Therefore, three separate, independent instrumental case studies (also known as collective case studies) were conducted in three distinct Tanzanian communities in or around tourism destinations. The objective was to allow for the autonomy of specific cultural, social and business networks to be reflected in the research methodology.

Case studies allow for the investigation of constraints to economic participation within real-life experiences, as there is no clear distinction between the phenomenon and the context. Instrumental case studies strive to develop theory, or in this case, facilitate understanding of pervasive problems and do not require typical study populations (Stake, 1995). An instrumental case study is utilized where a ‘particular case is examined mainly to provide insight’ into a phenomenon and the case supports understanding of the phenomenon (Denzin & Lincoln, 2005). The emphasis is placed on specific issues rather than on the case itself. The case in then used as a vehicle to develop a better understanding of the situation or problem (Stake, 2003). Single case studies are ideal for investigating a phenomenon that has not been previously studied and can make a significant contribution to knowledge (Yin, 2003). Since constraints to economic participation within Tanzania have not yet been empirically studied, each individual case study is exploratory in nature.

Once the specific case studies were independently derived and themes developed, a cross-case comparison offered insight into reoccurring themes or case-specific constraints. Using an iterative process, the strength of this methodology lies in the inductive approach that provides suggestive rather than definitive analysis (Welch, 1994). The first phase of analysis results in ‘within’ themes specific to a particular region. Using cross-case comparisons, emergent patterns provide similarities and differences between the three communities.

Cross-Case Analysis

Prior to the development of low-cost computing and the ease of completing statistical analysis, case studies played a significant role in the development of the social sciences. However, since the mid-1990s statistical modelling and empirically driven work has come to dominate academic literature; yet there remain epistemological similarities between some forms of case study work and statistical modelling. Nonetheless, issues of the qualitative versus quantitative divide and the purported role of value judgments made by the researchers have in part muddied the waters until quite recently, when the researchers using statistical methods started to adopt the use of the first person in their writing and began to recognise that the choice of a given statistical technique is just as surely a value judgment or exercise of experience and expertise as is any interpretation of text by a qualitative researcher. Similarly, qualitative researchers have become increasingly familiar with textual analysis using software programmes based on neural network theory, and a new generation of researchers have become comfortable with a mixed method mode of analysis.

About the Authors

Maria Amoamo is a post-doctoral fellow in Te Tumu, the School of Māori Pacific and Indigenous Studies at University of Otago in New Zealand. Maria's research interests include the representation of indigenous, cultural and heritage tourism. Her PhD thesis examined the issue of identity in relation to Māori regional tourism within a post-colonial framework. She is currently examining the economic value of identity in relation to determining ‘what is the profile of Māori tourism in Dunedin?’ Maria is also examining the issue of social vulnerability and resilience of Pacific Island communities in relation to tourism.

• Kenneth F. Hyde
• Arch G. Woodside

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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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Predictive monitoring of soil organic carbon using multispectral UAV imagery: a case study on a long-term experimental field

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• Published: 08 June 2024

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• Javier Reyes 1 ,
• Werner Wiedemann 2 ,
• Anna Brand 2 ,
• Jonas Franke 2 &
• Mareike Ließ   ORCID: orcid.org/0000-0001-9325-199X 1 , 3  

Effective monitoring of the soil organic carbon (SOC) content at the field scale is crucial for supporting sustainable agricultural practices. This study evaluates the utility of multispectral data acquired by an unmanned aerial vehicles (UAV) during bare soil conditions for predicting the SOC content of a long-term experimental field site (LTE) in Saxony-Anhalt, Germany. Our methodology involves constructing predictive models using multiple algorithms (CUBIST, MARS, linear regression) and applying image correction techniques to enhance prediction accuracy by mitigating the influence of confounding factors such as crop residuals. Among the tested models, the CUBIST algorithm, combined with a pixel selection strategy employing a 2 m radius and stratified image correction, demonstrates the most promising results, achieving an R-squared value of 0.54 and an RMSE of 1.9 g kg −1 . Spatial distribution maps generated by this optimized model effectively depict the impact of organic fertilization on the SOC content, although the clarity of these patterns varies depending on the image processing method and algorithm used. Our findings highlight the potential of utilizing UAV-derived multispectral data for SOC monitoring at the LTE scale. However, further research is warranted to assess the generalizability of this approach to agricultural fields with lower SOC variability.

Avoid common mistakes on your manuscript.

1 Introduction

Soil organic carbon (SOC) content is one of the key variables due to its influence on soil chemical, physical, and biological processes. The knowledge of SOC spatial and temporal variation could help to improve agricultural management concerning carbon sequestration in the context of climate change mitigation. The Paris COP 21 Climate Change Agreement [ 1 ] inspired the vision of the "4 per 1000" initiative. This initiative highlights the potential of soil organic carbon (SOC) storage in soils as a method to mitigate climate change. However, the practical application of this concept on a global scale poses a significant challenge due to the intricate considerations involved. Various agricultural practices, such as rewetting peatlands and avoiding land-use changes from pastures to croplands, are elements of this comprehensive issue. Therefore, the initiative underscores a complex and global aspiration to augment SOC stocks rather than suggesting definitive, universally applicable agricultural practices. The SOC field-scale variability has been considered in the delimitation of soil fertility management zones [ 2 , 3 ], but it will require to monitor continuously its spatial variation in the context of evaluating agri-environmental measures [ 4 ] regarding soil carbon stock.

Spatially continuous SOC monitoring at the field scale and the larger landscape scale requires an integrated and strategic approach. While conventional chemical laboratory analysis offers accurate SOC estimates, it is not cost-effective for acquiring a sampling density high enough to produce a comprehensive field map. Therefore, the monitoring strategy needs to employ advanced remote sensing technologies, such as satellite imagery and drone-based sensors, for extensive data collection [ 5 ]. Ground-based samples, though less dense, remain necessary for calibration and verification purposes, providing a balance of detailed insight and broad coverage. Sophisticated data analysis methods and modeling tools are also indispensable for interpreting the data and predicting SOC contents with high precision. Regular monitoring over time is crucial for tracking changes, identifying trends, and assessing the impact of various soil management practices on SOC sequestration [ 6 , 7 ]. The association between Visible and Near Infrared (Vis–NIR) spectra and SOC has been extensively researched [ 8 , 9 ], which confirms its utility in developing predictive models. Proximal sensing, characterized by its direct or near-direct contact with the soil, provides an intermediate level of precision and resolution [ 10 ]. This method bridges the gap between intensive, expensive ground-based lab analyses and more extensive remote sensing techniques.

Remote sensing data, which can be gathered from satellites, airborne sources, or unmanned aerial vehicles (UAVs) [ 11 ], further extends the scale of monitoring. Remote sensing multispectral imagery can act as complementary data to SOC estimates, enhancing the resolution and reliability of soil mapping [ 9 , 12 ]. Through the combined application of these techniques, we can achieve an effective compromise among precision, affordability, and extensive coverage in the monitoring of SOC.

Multispectral and RGB cameras onboard UAVs are cost-effective and have shown high functionality for agronomic applications [ 13 ], obtaining high spatial resolution data to cover the entire field [ 14 ]. These optical sensors have access to capture spectral reflectance and information concerning the image but several factors can affect the ideal conditions for data acquisition, including moisture, partial crop, and residue cover, as well as shading by soil clods, and soil surface roughness [ 15 ]. UAV campaigns at field scale are realized at low altitudes with a smaller field of view resulting in a high spatial resolution (i.e. cm-scale). However low-altitude flights may cause image distortion and the appearance of some artifacts [ 16 ]. Thus, it requires data correction to transform their original format of digital numbers to surface reflectance. There are different approaches to correcting and validating the UAV data. Most frequently researchers have used black-and-white targets [ 17 ], or proximal spectral measurements on the field [ 16 ].

Once the sensor data and conventional laboratory measurements are acquired, models are developed to link the spectral information to the SOC content. Sensor data, gathered through drone-based sensors, provide a broad, spatially extensive view of the scene. On the other hand, conventional laboratory measurements, though more time-consuming and expensive, offer a highly accurate estimation of SOC at specific sample locations. Both types of data play essential roles in building an accurate SOC model, with laboratory measurements providing ground truth data for calibrating and validating models built primarily on sensor data. The application of machine learning algorithms to remote sensing data is widely accepted due to their capacity to model intricate class signatures and accommodate diverse data types without presupposing the data distribution [ 18 ]. These methods require parameter tuning to govern the learning process [ 19 ]. One of the considerations of machine learning is its data-driven nature, which may overlook the actual understanding of the physical correlation between the spectral data and the response variable [ 20 ]. This situation could lead to potential misconceptions or inaccurate interpretations. Nevertheless, machine learning holds the promise of further investigating data to discover novel relationships [ 21 ]. This study aims to investigate the potential of UAV spectral information to monitor SOC at the field scale by (1) Developing machine learning models to establish robust relationships between UAV-derived spectral Vis–NIR signals and laboratory measurements of SOC content, (2) Applying these models for continuous field-scale SOC prediction, and (3) Rigorously testing various data processing and image correction procedures to mitigate the influence of soil surface effects. Our hypothesis suggests that through the integration of advanced spectral analysis techniques with UAV-derived data, more accurate and reliable monitoring of SOC content can be achieved, thus contributing to improved soil management practices and enhanced environmental sustainability.

2 Material and methods

2.1 study area.

The data collection took place at the Static Fertilization Experiment, located in Bad Lauchstädt, Saxony-Anhalt, Germany (Fig.  1 a) (51°24ʹ N, 11°53ʹ E, 113 m above sea level). The climatic conditions of the area are marked by an average yearly rainfall ranging from 470 to 540 mm and a mean annual temperature of about 8.5–9.0 °C. The soil, according to the German soil classification system [ 22 ], is identified as Haplic Chernozem, which developed from loess [ 23 ]. The topsoil texture alternates between highly clayey silt (Ut4) and highly silty clay (Tu4), as per the German soil survey system [ 22 ].

Study area located in Bad Lauchstädt. a fertilization treatments and subfield divisions (SF). b UAV orthophoto, crops division of the year 2020, and sampling locations. Coordinate reference system: EPSG 25833

The Static Fertilization Experiment, launched in 1902 by Schneidewind and Gröbler, spans approximately 4 ha [ 24 ]. It comprises eight sections and started with a crop rotation of winter wheat, sugar beet, summer barley, and potato. From 2015 onwards, silage maize replaced sugar beet and potatoes in the rotation to minimize the labor required. Each crop was planted in a staggered fashion across different subfields to ensure their simultaneous growth at the experiment site. Every fourth spring, the first subfield is limed with 30 dt ha −1 . Starting in 1926, legumes were incorporated into the crop rotation on the eighth subfield (not included in Fig. 1 ) every 7th and 8th year. The crop rotation for 2020, which coincided with the UAV flight campaign, is shown in Fig.  1 b.

There are 288 distinct plots (270 without subfield 8), each differing based on its mineral and organic fertilizer treatments. One-third of each field received either 20 or 30 t ha −1 of farmyard manure, leaving the remaining two-thirds unfertilized. Mineral fertilizers, in varied combinations of N, P, and K, were applied, with certain periods comparing different types of N fertilizers. In 1978, the fourth and fifth subfields were modified to test different fertilizer treatments, involving varying quantities of N paired with adjusted organic fertilizer treatments. For additional details, refer to [ 25 ].

2.2 Data acquisition

Data collection includes UAV flights with a multispectral camera, Vis–NIR spectral contact measurements, soil sampling, and laboratory SOC analysis. In September 2018, soil samples were acquired at 100 locations, at 0–10 cm depth (Fig.  1 b). To cover the spatial soil variability according to the LTE agricultural treatment without having to sample each of the plots, a stratified random sampling algorithm was applied to select 50 sampling points to collect soil samples and conduct spectral contact measurements. Another 50 soil sampling points were selected by using the Kennard-Stone algorithm (see details on [ 26 ]). The soil samples were air-dried, sieved (2 mm), and ground before carbon measurements with dry combustion. Total carbon was measured using the high-end elemental analyzer vario EL cube CN (Elementar Analysensysteme GmbH) with 3 replicates per sample. The measured SOC content has a mean value of 19.6 g kg −1 and a range between 14 and 25 g kg −1 , showing a wide range of SOC values derived from the different fertilization treatments.

The UAV flight campaign was conducted in September 2020 after harvest and tillage with a field cultivator to minimize the remaining crop residuals at the soil surface. A MicaSense RedEdge 3 Multispectral Camera (MicaSense Inc.) mounted on a DJI Inspire 2 multicopter was used. The camera has 5 bands sensitive to Vis–NIR spectra (Table  1 ). Two flights with an altitude of 50 and 100 m above ground level (AGL) were done between 11 am and 2 pm under a clear sky with an average flight speed of 5.5 m s −1 , obtaining images with a pixel resolution of 3.5 and 7 cm respectively. The use of flight planning software ensured that all images were recorded with sufficient overlap for photogrammetric processing, maintaining 85% forward and 65% sideward overlap. Before and after each flight, the "MicaSense radiometric panel" was captured in the field to allow for subsequent reflectance calibration of each image. To optimize the geographic position of the data set, eight Ground Control Points (GCPs) were utilized, which were previously measured in the field using a Differential Global Positioning System (DGPS).

Spectral contact measurements to correct the UAV data were taken using an ASD FieldSpec 4 Hi-Res instrument by Malvern Panalytical (hereinafter will be called ASD). The ASD measures the Vis–NIR range (350–2500 nm), with a Full-Width Half Maximum (FWHM) of 3 nm in the Vis and 10 nm in the NIR, and an output of 1 nm spectral resolution. Field measurements were done after crop harvest in sunny and dry soil conditions in September 2018. The spectra were measured at the soil surface at each sampling point using a 50 × 50 cm frame pointing north. A total of 15 spectra were acquired at each sampling point excluding crop residuals. 5 locations within the frame were measured with 3 external and 25 internal scans.

2.3 Model algorithms

The linear regression model (LM), multivariate adaptive regression splines (MARS), and the cubist regression model (CUBIST) were selected for their suitability and past performance in remote sensing and SOC modeling [ 27 ]. The R-packages ‘earth’ [ 28 ] and ‘Cubist’ [ 29 ] were used to implement these models. They were selected due to their comprehensive functionality, robust performance, and wide usage in the scientific community for similar types of analysis.

2.3.1 Linear model

The LM was selected for its simplicity, interpretability, and efficiency. LM serves as a fundamental statistical technique. Its role in our study is twofold: to provide a readily understandable baseline model and to offer a comparison metric for more complex machine learning models. We utilized LM to establish a relationship between SOC measurements at the sampling sites and the spectral UAV image information.

MARS [ 30 ] is a non-parametric regression technique, adept at modeling complex non-linear relationships. Known for its accuracy and adaptability, MARS skillfully navigates multiple predictors to unveil non-linear interactions.

MARS constructs a relationship between the dependent (response) and independent (predictor) variables using a unique array of coefficients and basis functions. This process, controlled by the regression, undergoes two stages: Initially, piecewise linear or cubic splines are crafted as basis functions, deliberately overfitting the data. Subsequently, these basis functions undergo pruning—a process of reduction based on the optimal fit to the data. Pruning, in this context, refers to the elimination of superfluous terms that contribute to overfitting, thereby improving the model’s generalizability to unseen data [ 31 ].

In this research, we tuned specific MARS parameters, including the maximum number of terms eligible for pruning (experimenting across a spectrum of 2–100) and the degrees of freedom (tested within a range of 1 to 3). The term degrees here refers to the complexity of the basis functions, with a degree of 1 representing a piecewise linear function and higher degrees indicating cubic splines that can capture more complex, non-linear relationships.

2.3.3 CUBIST

CUBIST is a rule-based model that combines decision trees with linear regression models [ 32 ]. A tree is grown with linear regression models in its terminal leaves. These models are constructed using the predictors from earlier splits. At every level of the tree, there are additional intermediate linear models. At each terminal node of the tree, a prediction is made using the linear regression model, but it is smoothed by accounting for the prediction from the linear model in the preceding node of the tree. This unique amalgamation results in an excellent balance between interpretability and predictive power. Capable of effectively managing large datasets and multiple variables, CUBIST presents a suitable option when dealing with the intricate nature of remote sensing data.

Distinguished from other decision tree algorithms, CUBIST utilizes specialized procedures for model smoothing, rule generation, and pruning. A unique characteristic of CUBIST is the optional committees feature, a form of boosting procedure designed to enhance the model’s predictive accuracy. A series of rule-based models can be generated to establish model committees. Based on the previous model fit, the training set outcome is modified, and a new set of rules is then constructed using this pseudo-response. Additionally, the model’s prediction can be fine-tuned based on the characteristics of neighboring data points. In the pruning process, CUBIST employs a weighted linear combination of two decision trees, with the weights computed based on the residuals of each tree, thereby optimizing the model’s simplicity without sacrificing accuracy [ 33 ]

In our study, we tuned specific parameters in the CUBIST model, including the number of neighbors (evaluated from 0 to 10) and the size of committees (tested within a range of 1 to 100). Neighbors refer to the number of nearest data points considered in adjusting the prediction, while committees denote the number of decision trees used in the boosting procedure to enhance the model’s performance.

2.4 Workflow

The workflow including image processing, model building, and spatial SOC prediction follows the flowchart presented in Fig.  2 . The following subsections explain the details.

Flow chart of processing steps for the SOC estimation. UAV: unmanned aerial vehicle, ASD: ASD FieldSpec 4 Hi-Res instrument; BVIS: brightness in the visible range; SOC: soil organic carbon; LTE: long-term experiment, CUBIST: cubist regression model, and MARS: multivariate adaptive regression splines

2.4.1 Image processing and correction

The photogrammetric workflow was carried out using Agisoft Metashape (Agisoft LLC). The initial step of generating multispectral orthophotos involved calibrating the reflectance of each captured image, using respective reflectance calibration images taken both before and after each flight. Subsequently, all images, acquired at altitudes of 50 m AGL and 100 m AGL, were aligned together to achieve the best possible co-registration between the two datasets. To further enhance the alignment, matching features based on fewer than three images were removed and camera alignment was subsequently optimized using Agisoft Metashape’s predefined function. Following this, ground control points were used for manual alignment optimization.

To generate a most detailed Digital Surface Model (DSM) from the available data, images acquired at 50 m AGL were utilized to calculate a dense point cloud. This point cloud was then used to process the DSM and orthophoto from the 50 m AGL dataset. In a separate process, utilizing the previously generated higher-resolution DSM, an orthophoto was derived from the aligned images taken at 100 m AGL. In the context of image correction, several steps are involved. First, a correction process begins with the application of an NDVI mask to account for germination. This mask helps address areas with low vegetation cover. Additionally, a mask based on the brightness in the visible range (BVIS) is applied to handle crop residuals effectively. Determining suitable thresholds for both NDVI and brightness involved analyzing dispersion plots showing the relationship between NDVI and brightness. These plots visually depicted the distribution of points, highlighting areas with typical vegetation and outliers. By examining these plots, we identified clusters representing typical vegetation and outliers like bare soil or dense vegetation cover. The thresholds were selected to distinguish between typical vegetation and outliers, enabling accurate masking of areas with low vegetation cover using NDVI and addressing crop residuals using brightness values.

In the spectral correction process, the ASD field measurements obtained at each sampling location served as reference values for correcting the spectral response obtained from the UAV imagery. Two distinct approaches were employed for this correction: non-stratified and stratified correction. In the non-stratified correction approach, uniform threshold values were applied for both NDVI and brightness masking across the entire study area. Following the masking step, the spectral correction involved calculating the ratio between the ASD field measurements and the corresponding values obtained from the MicaSense spectral response function. This ratio served as a correction factor to adjust the spectral response obtained from the UAV imagery, aligning it with the reference values obtained from the ASD measurements. The stratified correction approach involved applying different threshold values for each specific crop type present in the study area. This allowed for a more specific correction process, where threshold values were determined based on the specific spectral characteristics of each crop. The spectral correction was then applied based on the point locations corresponding to each crop type, ensuring a more accurate alignment between the UAV-derived spectral response and the reference values obtained from the ASD measurements. Table 2 provides detailed information on the specific quantiles used as thresholds for both the non-stratified and stratified corrections.

2.4.2 Model building

Model building requires the formation of a robust predictor-response dataset, an essential component that lays the groundwork for establishing and tuning the desired models. In our study, this dataset was generated by using the mean pixel value at each sampling point location, and this process was carried out using different search radii: 0.25, 0.5, 1, and 2 m. For the MARS and CUBIST models, grid search methods were employed to determine optimal tuning parameter values. In the case of the LM, we sought to identify the model configuration that yielded the lowest Root Mean Squared Error (RMSE). The process of model training, tuning, and evaluation was executed through a stratified fivefold nested cross-validation, as detailed in [ 26 ]. To address potential issues of spatial autocorrelation between test and training sets, neighboring samples within a 5 m distance were grouped into the same fold. Stratification involved two aspects: (1) The data were stratified with regard to the response variable, and (2) With regard to the recently harvested crop. The latter was included due to different soil surface characteristics in dependence on maize versus cereal crops. This approach not only maintains the integrity of our model evaluation by minimizing the spatial correlation between training and testing datasets but also ensures a balanced representation of the target variable across all test and training sets. Model evaluation was done with 5 repetitions. Thus, 25 models were obtained for each dataset. Equal data subdivisions were used to compare models trained on different data (non-stratified and stratified image correction) and by different algorithms (LM, MARS, CUBIST). RMSE and R-squared were used as error metrics of model performance, and the Concordance Correlation Coefficient [ 34 ] is presented in the average predicted versus observed values.

2.4.3 Spatial prediction

The models created using LM, MARS, and CUBIST were deployed to predict SOC from the multispectral UAV images (both non-stratified and stratified). These predictions were carried out on images featuring mean pixel values, with the average computed within the same radii used during model development (0.25, 0.5, 1, 2 m). This strategy was pursued to mitigate the impact of potential image artifacts, shadows, and small-scale variations in soil surface conditions. It is important to note that the predictions were based on averaged data, specifically to counter these influencing factors. The gap-filling of pixels removed by masking was done through spatial interpolation, which is commonly applied in remote sensing studies [ 35 ]. Specifically, two methods were tested: inverse distance weighting (IDW) for all datasets and ordinary kriging (OK) on the models with the best performance. The corresponding experimental semivariograms for OK were applied, testing conventional variogram models: Spherical, Exponential, and Gaussian semivariogram models [ 36 ]. The geospatial analysis was done using the R-package ‘gstat’ [ 37 ], and the plots were done using the R-packages ‘ggplot2’ [ 38 ] and ‘lattice’ [ 39 ].

3 Results and discussion

3.1 performance metrics.

Performance metrics of the LM, MARS, and CUBIST models trained with the various predictor-response datasets are presented in Fig.  3 . Compared to the non-stratified image correction, the stratified method showed a slight improvement in the performance of the best model. Similar trends were observed in RMSE and R 2 . An increase in accuracy was noted with a larger search radius of 2 m for the predictor-response dataset. Conversely, accuracy decreased, and dispersion increased when the predictor-response data were obtained with a smaller search radius. When comparing models, CUBIST is the one that presents the best performance (non-stratified image correction R 2  = 0.53, RMSE = 2.1 g kg −1 ; stratified image correction: R 2  = 0.54, RMSE = 1.9 g kg −1 ), followed by LM and MARS. Positive results of CUBIST in remote sensing applications have also been identified by other studies [ 40 , 41 , 42 ]; meanwhile, MARS did not perform better than a simple LM model. The good performance of CUBIST could be due to the predictions usually outside the domain of the input response and the ability to establish linear and non-linear relationships [ 43 ].

Predictive model performance of the different models. a RMSE; b R-squared. NST: non-stratified correction; ST: stratified correction

Regarding the predictive performance of the three model algorithms, it becomes apparent that the use of corrected images yields better performance in comparison to non-corrected images (R 2  = 0.35, RMSE = 2.3 g kg −1 ). This finding aligns with several other studies in this emerging field of SOC predictions using UAV images at the field scale. For instance, [ 44 ] obtained an RMSE of 2.1 g kg −1 with loamy soil using Support Vector Machines, while [ 11 ] and [ 13 ] reported RMSE values of 2.7 and 2.9 g kg −1 , respectively, for their best models in agricultural fields.

In our study, the RMSE values obtained were higher compared to the performance of ASD laboratory measurements (R 2  = 0.9, RMSE = 0.9 g kg −1 ) and field measurements (R 2  = 0.77, RMSE = 1.4 g kg −1 ) observed by [ 45 ], and Veris on-the-go field measurements (R 2  = 0.84, RMSE = 1.24 g kg −1 ) observed by [ 46 ] at the same study area. A comparison of the average predicted values with the measured values, using a predictor response dataset with a 2 m radius, is displayed in Fig.  4 . The concordance correlation coefficient supports the strong performance of the CUBIST models, even though values in the lower range tend to be overestimated. Upon examining the residuals (Fig.  5 ), no strong differences in variances are evident when comparing methods using a predictor response dataset with a 2 m radius. However, when comparing the largest positive and negative values of LM with MARS and CUBIST, the largest negative residual values appear consistent, while a noticeable shift is observed in the largest positive residual values.

Predicted versus measured observations using a response dataset with a 2 m radius. Non-stratified image correction: a LM, b MARS, c CUBIST. Stratified image correction: d LM, e MARS, f CUBIST

Measured versus residual values using a response dataset with a 2 m radius. The 10 largest positive and negative residual values of the linear model (non-stratified and stratified) are marked for comparison with the corresponding MARS and CUBIST models. Non-stratified image correction: a linear model, b MARS, c CUBIST. Stratified image correction: d Linear model, e MARS, f CUBIST

3.2 SOC spatial prediction

The impact of organic fertilization (Fig.  1 a) is evident in the spatial distribution of SOC. The eastern part of the field, which did not receive farmyard manure, displays lower SOC values. Conversely, the differences in SOC between the sections of the field treated with 20 or 30 t ha −1 of farmyard manure are less significant. Concerning mineral fertilization, its influence on SOC is less apparent. However, plots that did not receive fertilization tend to present lower SOC values compared to those where NPK was applied.

Figure  6 illustrates the spatial predictions from each model using a mean pixel value of 2 m. In the image corrected by stratification, the plot treatments division is more visibly defined in the LM and MARS models (it is slightly less apparent with CUBIST). In contrast, the non-stratified corrected image shows a more homogeneous or smoothed spatial distribution of SOC. This smoothed pattern is especially discernible in the LM and CUBIST models, attributable to the reduction of pixel-level variability through mean pixel values. On the other hand, the MARS model tends to lean more towards higher SOC values, suggesting it may capture more of the smaller-scale variability in SOC. The spatial distribution pattern of the SOC presents similarities with the observations made by [ 46 ], particularly for the LM and CUBIST models. They used a Veris on-the-go spectrometer in the same study area and combined PLSR with ordinary kriging models to predict at a 1 m resolution.

Spatial prediction of the different models using a mean pixel value of 2 m. Pixel gaps are filled using inverse distance weighting. Non-stratified image correction: a LM, b MARS, c CUBIST. Stratified image correction: d LM, e MARS, f CUBIST

Although the literature on SOC estimation is growing, publications that present SOC maps at the field scale using UAV data are even fewer. Studies by [ 13 , 40 , 44 ] at the landscape scale are some of the few examples. This gap in research underscores the need for additional studies projecting UAV-derived model outcomes to obtain spatial distribution maps of soil properties, namely SOC contents.

In this study, we also examined the effect of image pixel averaging based on different radii, with an example using the CUBIST model presented in Fig.  7 . With a 2 m radius, the SOC spatial distribution appears more consistent between the two corrected images. This consistency diminishes as the radius used for mean pixel value calculation decreases, increasing the dispersion of SOC values, and reducing the clarity of the spatial pattern.

SOC spatial prediction using the CUBIST model with different mean pixel values. Pixel gaps are filled using inverse distance weighting. Non-stratified image correction: a 2 m, b 1 m, c 0.5 m, 0.25). stratified image correction: e 2.00 m, f 1.00 m, g 0.50 m, h 0.25 m

This result aligns with our expectations, as models using a smaller radius demonstrated higher uncertainty. It also reflects the impact of individual pixels or localized areas with weak SOC relationships, which were not eliminated during image masking. [ 47 ] employed a smoothing technique over nine adjacent pixels with Airborne Hyperspectral Imagery (2.5 m pixel resolution) to map soil properties in agricultural fields. Their results showed a more accurate average representation of soil properties, which they attributed to noise reduction and signal improvement. This effect becomes more pronounced at higher pixel resolutions.

3.3 Potential use of UAV spectral measurements for SOC monitoring

Our findings emphasize the potential to leverage UAV-derived data for predicting field-scale SOC in a long-term experiment setting, illustrating its utility for the continuous monitoring of SOC variations. The predictive performance of the models is competitive with those reported in similar studies that utilize multispectral UAV data. However, it is important to recognize a noticeable performance gap compared to laboratory spectroscopy performed under controlled conditions. Laboratory spectroscopy generally offers higher accuracy due to controlled conditions, while field spectroscopy, influenced by environmental factors, yields accuracy in SOC prediction that sits between laboratory and UAV measurements. Nevertheless, the scalability of lab measurements is limited. In contrast, field spectroscopy more closely aligns with the UAV’s perspective and data collection conditions, making it more suitable for field application. The quality of data from UAVs can be influenced by various factors such as the specifics of the camera used, the flight parameters, and prevailing environmental conditions [ 11 ]. In our experiment, a flight altitude of 100 m resulted in superior data quality compared to a 50 m flight. This could be due to the increased capture of noise at a higher pixel resolution [ 48 ]. The practice of using mean pixel values helped to smooth out the spatial SOC patterns, minimizing the effect of individual pixel variability, and thus emphasizing the overall trend values within each plot. When using a smaller search radius, both the size of the average pixel values and the use of the worst models caused an unclear representation of the SOC variability. An alternative for improving the results on these smaller mean pixel values could be the application of a model based on a response dataset with a larger search radius (e.g. prediction pixels on the 0.25 m mean pixel values with the 2 m predictor response dataset based models). A direct prediction of a single pixel is more complicated due to the artifacts, shadows, or residues, thus different approaches could be done to create the field maps. For example, [ 13 ] used the predicted values using UAV data at the sampling point locations and then created the SOC map through interpolation, smoothing the spatial pattern although with lower spatial resolution; [ 44 ] used PCA dimensions of the variables to generate the model and then used these values for the spatial prediction. The maps produced with a 1 and 2 m mean pixel value showed a good representation of the field spatial variability and should be sufficient to monitor the SOC variation, thus the potential utilization of meter-scale satellite spectral data should be considered.

The SOC spatial prediction at the field scale can be improved by spectral image correction through laboratory and proximal sensing measurements. The correction through field ASD measurements, which has been used for model calibration and correction in other studies [ 16 , 49 ] improved considerably the model performance compared to using the original orthophoto (decreasing about 18% of the RMSE with the best models). The effect of the plot treatments was observed through the images and was more evident when using the stratified corrected image, which hardly could be observed in the case of using point measurement combined with geostatistical spatial interpolation. Also due to the high spatial resolution, it is possible to identify the spatial variation inside of the plot treatments, which is commonly not considered when using conventional measurements where an average value is considered for each plot. Regarding the gap filling of pixels removed through spatial interpolation, IDW and ordinary kriging were applied but no difference was observed when comparing the same corrected image, possibly due to the high density and short lag distance of close neighbors, where a simple weighted linear relationship like IDW seems to be sufficient. Nevertheless, it needs to be noted that the study was done in an LTE instead of a conventional agricultural field, where the SOC variability is lower, thus a lower performance could be expected.

While the use of UAV-derived data offers substantial potential, it is important to note that the number of variables available for model building is limited. To overcome this limitation, we tested various indices, including the Brightness index, Modified Soil Adjusted Vegetation Index (MSAVI2), Redness index (RI), Color index (CI), Transformed Vegetation Index (TVI), Green–Red-Vegetation-Index (GRVI), Vegetation Index, Green Normalized Vegetation Index (GNDVI), Normalized difference vegetation index (NDVI), Green Soil Adjusted Vegetation Index (GSAVI), Green Optimized Soil Adjusted Vegetation Index (GOSAVI), and Soil Adjusted Vegetation Index (SAVI) [ 50 ]. These indices, which primarily pertain to vegetation and consist of a combination of visible and infrared bands, were compared to other soil-related indices that incorporate short-wave infrared bands (SWIR; 900–1700 nm). However, these SWIR bands are outside the range of those available with the MicaSense camera used in our study. The importance of visible and infrared spectral bands associated with SOC is well documented [ 8 ], and leveraging these could potentially facilitate the development of a more robust model. Despite our efforts, the incorporation of these indices into our models did not substantially improve our SOC estimations (with an RMSE of about 2.0 g kg −1 and R 2 of 0.55 using CUBIST models for both non-stratified and stratified corrections).

Nonetheless, the ever-evolving nature of UAV technology offers considerable optimism for the future. With advancements in image quality and the inclusion of additional spectral information, particularly in the SWIR, we anticipate that this technology will provide increasingly accurate SOC estimations [ 51 ]. This suggests that the deployment of more sophisticated hyperspectral sensors and the incorporation of further spectral information may be key to enhancing our ability to estimate SOC from UAV data.

Our study highlights the fundamental premise of leveraging UAV-derived data to field-scale SOC monitoring. It demonstrates adequate predictive performance, underlining the potential of this approach. Factors such as flight altitude and mean pixel values significantly influence data quality and spatial SOC patterns, emphasizing the need for meticulous data preprocessing. Notably, spectral image correction using field ASD measurements enhances model performance, refining SOC spatial prediction accuracy at the field scale. While various spectral indices yielded limited improvements in SOC estimations, ongoing advancements in UAV technology, particularly with hyperspectral sensors, offer promise for future accuracy enhancements. However, addressing challenges related to image correction and model selection requires ongoing refinement efforts. Moving forward, collaborative endeavors will be essential in crafting robust SOC monitoring frameworks that support sustainable agriculture and climate change mitigation.

4 Conclusions

This study highlights the effectiveness of spectral UAV-derived data in predicting field-scale SOC within a long-term experiment. The accuracy of these predictions improved significantly with spectral correction via ASD data and the masking of germination aspects and crop residuals. Crop stratification offered a distinct delineation of plot divisions, enriching our understanding of SOC field-scale variability.Of all the algorithms tested, the CUBIST model demonstrated the best performance. This was particularly true when a 2 m search radius was used to select average pixels for the predictor response dataset. However, the model’s accuracy decreased as the search radius shrank. Future research should focus on broader agricultural landscapes and conventional agricultural fields with less SOC variability than observed in long-term experiments. The spatial prediction of SOC clearly illustrated the impact of fertilization on plot treatments, but the resulting patterns varied based on the model and the type of image correction applied. When data with different mean pixel values was used, the image provided a meter-scale map that effectively represented spatial variability.

These findings contribute to the growing body of knowledge on UAV data applications in soil science and guide future advancements in SOC monitoring. They highlight the potential to utilize the spectral information captured by remote sensing technologies, which has shown a relationship with SOC content. This suggests that field-scale SOC changes could potentially be monitored through satellite remote sensing data.

Data availability

The data are published as part of the SOCmonit R package on GitHub:  https://github.com/jareym/SOCmonit

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Open Access funding enabled and organized by Projekt DEAL. This work was supported by funds of the Federal Ministry of Food and Agriculture (BMEL) based on a decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture and Food (BLE) under the innovation support program. Project SOCmonit—Monitoring of soil organic carbon with remote and proximal soil sensing methods (Grant number 281B301516). The authors Werner Wiedemann, Anna Brand, and Jonas Franke are employed by RSS—Remote Sensing Solutions GmbH.

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All authors jointly developed the methodology. Javier Reyes, Anna Brand, and Werner Wiedemann carried out programming activities and data analysis. The first draft of the manuscript was written by Javier Reyes and Werner Wiedemann; all authors contributed to the review and editing and approved the final manuscript. Mareike Ließ and Jonas Franke were responsible for conceptualization, supervision, funding acquisition, and project administration.

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Reyes, J., Wiedemann, W., Brand, A. et al. Predictive monitoring of soil organic carbon using multispectral UAV imagery: a case study on a long-term experimental field. Spat. Inf. Res. (2024). https://doi.org/10.1007/s41324-024-00589-7

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Module 2: Sociological Research

Field research, learning outcomes.

• Explain the three types of field research: participant observation, ethnography, and case studies

The work of sociology rarely happens in limited, confined spaces. Sociologists seldom study subjects in their own offices or laboratories. Rather, sociologists go out into the world. They meet subjects where they live, work, and play. Field research refers to gathering primary data from a natural environment without doing a lab experiment or a survey. It is a research method suited to an interpretive framework rather than to the scientific method. To conduct field research, the sociologist must be willing to step into new environments and observe, participate, or experience those worlds. In field work, the sociologists, rather than the subjects, are the ones out of their element.

The researcher interacts with or observes a person or people and gathers data along the way. The key point in field research is that it takes place in the subject’s natural environment, whether it’s a coffee shop or tribal village, a homeless shelter or the DMV, a hospital, airport, mall, or beach resort.

Figure 1. Sociological researchers travel across countries and cultures to interact with and observe subjects in their natural environments. (Photo courtesy of IMLS Digital Collections and Content/flickr and Olympic National Park)

While field research often begins in a specific setting , the study’s purpose is to observe specific behaviors in that setting. Field work is optimal for observing how people behave. It is less useful, however, for understanding why they behave that way. You can’t really narrow down cause and effect when there are so many variables to be factored into a natural environment.

Many of the data gathered in field research are based not on cause and effect but on correlation. And while field research looks for correlation, its small sample size does not allow for establishing a causal relationship between two variables.

BeyoncÉ and LADY gaga as sociological subjects

Figure 2. Researchers have used surveys and participant observations to accumulate data on Lady Gaga and Beyonce as multifaceted performers. (Credit a: John Robert Chartlon/flickr, b: Kristopher Harris/flickr.)

Sociologists have studied Lady Gaga and Beyoncé and their impact on music, movies, social media, fan participation, and social equality. In their studies, researchers have used several research methods including secondary analysis, participant observation, and surveys from concert participants.

In their study, Click, Lee & Holiday (2013) interviewed 45 Lady Gaga fans who utilized social media to communicate with the artist. These fans viewed Lady Gaga as a mirror of themselves and a source of inspiration. Like her, they embrace not being a part of mainstream culture. Many of Lady Gaga’s fans are members of the LGBTQ community. They see the “song “Born This Way” as a rallying cry and answer her calls for “Paws Up” with a physical expression of solidarity—outstretched arms and fingers bent and curled to resemble monster claws.”

Sascha Buchanan (2019) made use of participant observation to study the relationship between two fan groups, that of Beyoncé and that of Rihanna. She observed award shows sponsored by iHeartRadio, MTV EMA, and BET that pit one group against another as they competed for Best Fan Army, Biggest Fans, and FANdemonium. Buchanan argues that the media thus sustains a myth of rivalry between the two most commercially successful Black women vocal artists.

Here, we will look at three types of field research: participant observation, ethnography, and the case study.

Participant Observation

In participant observation  research, a sociologist joins people and participates in a group’s routine activities for the purpose of observing them within that context. This method lets researchers experience a specific aspect of social life. A researcher might go to great lengths to get a firsthand look into a trend, institution, or behavior. Researchers temporarily put themselves into roles and record their observations. A researcher might work as a waitress in a diner, live as a homeless person for several weeks, or ride along with police officers as they patrol their regular beat.

Although these researchers try to blend in seamlessly with the population they study, they are still obligated to obtain IRB approval. In keeping with scholarly objectives, the purpose of their observation is different from simply “people watching” at one’s workplace, on the bus or train, or in a public space.

Figure 3.  Who is the sociologist in this photo? It’s impossible to tell! In participant observation, researchers immerse themselves in an environment for a time.  (Photo courtesy of zoetnet/flickr)

At the beginning of a field study, researchers might have a question: “What   really goes on in the kitchen of the most popular diner on campus?” or “What is it like to experience homelessness?” Participant observation is a useful method if the researcher wants to explore a certain environment from the inside.

Field researchers simply want to observe and learn. In such a setting, the researcher will be alert and open minded to whatever happens, recording all observations accurately. Soon, as patterns emerge, questions will become more specific, observations will lead to hypotheses, and hypotheses will guide the researcher in shaping data into results.

Some sociologists prefer not to alert people to their presence. The main advantage of covert participant observation is that it allows the researcher access to authentic, natural behaviors of a group’s members. The challenge, however, is gaining access to a setting without disrupting the pattern of others’ beha vior. Becoming an inside member of a group, organization, or subculture takes time and effort. Researchers must pretend to be something they are not. The process could involve role playing, making contacts, networking, or applying for a job. Whenever deception is involved in sociological research, it will be intensely scrutinized and may or may not be approved by an institutional IRB.  

Once inside a group, participation observation research can last months or even years. Sociologists have to balance the types of interpersonal relationships that arise from living and/or working with other people with objectivity as a researcher.  They must keep their purpose in mind and apply the sociological perspective. That way, they illuminate social patterns that are often unrecognized. Because information gathered during participant observation is mostly qualitative, rather than quantitative, the e nd results are often descriptive or interpretive. This type of research is well-suited to learning about the kinds of human behavior or social groups that are not known by the scientific community, who are particularly closed or secretive, or when one is attempting to understand societal structures, as we will see in the following example. 

Nickel and Dimed (2001, 2011)

Journalist Barbara Ehrenreich con ducted participation observation research for her book Nickel and Dimed . One day over lunch with her editor, Ehrenreich mentioned an idea. How can people exist on minimum-wage work? How do low-income workers get by? she wondered aloud. Someone should do a study. To her surprise, her editor responded, Why don’t you do it?

That’s how Ehrenreich found herself joining the ranks of the working class. For several months, she left her comfortable home and lived and worked among people who lacked, for the most part, higher education and marketable job skills. Undercover, she applied for and worked minimum wage jobs as a waitress, a cleaning woman, a nursing home aide, and a retail chain employee. During her participant observation, she used only her income from those jobs to pay for food, clothing, transportation, and shelter.

She discovered the obvious, that it’s almost impossible to get by on minimum wage service work. She also experienced and observed attitudes many middle and upper-class people never think about. She witnessed firsthand the treatment of working class employees. She saw the extreme measures people take to make ends meet and to survive. She described fellow employees who held two or three jobs, worked seven days a week, lived in cars, could not pay to treat chronic health conditions, got randomly fired, submitted to drug tests, and moved in and out of homeless shelters. She brought aspects of that life to light, describing difficult working conditions and the poor treatment that low-wage workers suffer.

Nickel and Dimed: On (Not) Getting By in America , the book she w rote upon her return to her real life as a well-paid writer, has been widely read and used in many college classrooms. The first edition was published in 2001 and a follow-up post-recession edition was published with updated information in 2011. 

Figure 4. Field research happens in real locations. What type of environment do work spaces foster? What would a sociologist discover after blending in? (Photo courtesy of drewzhrodague/flickr)

Ethnography

Ethnography is a type of social research that involves the extended observation of the social perspective and cultural values of an entire social setting. Ethnogra phies involve objective observation of an entire community, and they often involve participant observation as a research method.

British anthropologist Bronislaw Malinowski, who studied the Trobriand Islanders near Papua New Guinea during World War I, was one of the first anthropologists to engage with the communities they studied and he became known for this methodological contribution, which differed from the detached observations that took place from a distance (i.e., “on the verandas” or “armchair anthropology”). 

Although anthropologists had been doing ethnographic research longer, sociologists were doing ethnographic research in the 20th century, particularly in what became known as The Chicago School at the University of Chicago. William Foote Whyte’s  Street Corner Society:  The Social Structure of an Italian Slum  (1943) is a seminal work of urban ethnography and a “classic” sociological text. 

The heart of an ethnographic study focuses on how subjects view their own social standing and how they understand themselves in relation to a community. An ethnographic study might observe, for example, a small U.S. fishing town, an Inuit community, a village in Thailand, a Buddhist monastery, a private boarding school, or an amusement park. These places all have borders. People live, work, study, or vacation within those borders. People are there for a certain reason and therefore behave in certain ways and respect certain cultural norms. An ethnographer would commit to spending a predetermined amount of time studying every aspect of the chosen place, taking in as much as possible.

A sociologist studying a tribe in the Amazon might watch the way villagers go about their daily lives and then write a paper about it. To observe a spiritual retreat center, an ethnographer might attend as a guest for an extended stay, observe and record data, and collate the material into results.

The Making of Middletown: A Study in Modern U.S. Culture

In 1924, a young married couple named Robert and Helen Lynd undertook an unprecedented ethnography: to apply sociological methods to the study of one U.S. city in order to discover what “ordinary” people in the United States did and believed. Choosing Muncie, Indiana (population about 30,000), as their subject, they moved to the small town and lived there for eighteen months.

Ethnographers had been examining other cultures for decades—groups considered minority or outsider—like gangs, immigrants, and the poor. But no one had studied the so-called average American.

Recording interviews and using surveys to gather data, the Lynds did not sugarcoat or idealize U.S. life (PBS). They objectively stated what they observed. Researching existing sources, they compared Muncie in 1890 to the Muncie they observed in 1924. Most Muncie adults, they found, had grown up on farms but now lived in homes inside the city. From that discovery, the Lynds focused their study on the impact of industrialization and urbanization.

They observed that the workers of Muncie were divided into business class and working class groups. They defined business class as dealing with abstract concepts and symbols, while working class people used tools to create concrete objects. The two classes led different lives with different goals and hopes. However, the Lynds observed, mass production offered both classes the same amenities. Like wealthy families, the working class was now able to own radios, cars, washing machines, telephones, vacuum cleaners, and refrigerators. This was a newly emerging economic and material reality of the 1920s.

Figure 5. A classroom in Muncie, Indiana, in 1917, five years before John and Helen Lynd began researching this “typical” U.S. community. (Photo courtesy of Don O’Brien/flickr)

As the Lynds worked, they divided their manuscript into six sections: Getting a Living, Making a Home, Training the Young, Using Leisure, Engaging in Religious Practices, and Engaging in Community Activities. Each chapter included subsections such as “The Long Arm of the Job” and “Why Do They Work So Hard?” in the “Getting a Living” chapter.

When the study was completed, the Lynds encountered a big problem. The Rockefeller Foundation, which had commissioned the book, claimed it was useless and refused to publish it. The Lynds asked if they could seek a publisher themselves.

As it turned out, Middletown: A Study in Modern American Culture was not only published in 1929, but also became an instant bestseller, a status unheard of for a sociological study. The book sold out six printings in its first year of publication, and has never gone out of print (PBS).

Nothing like it had ever been done before. Middletown was reviewed on the front page of the New York Times . Readers in the 1920s and 1930s identified with the citizens of Muncie, Indiana, but they were equally fascinated by the sociological methods and the use of scientific data to define ordinary people in the United States. The book was proof that social data were important—and interesting—to the U.S. public.

Institutional Ethnography

Institutional ethnography is an extension of basic ethnographic research principles that focuses intentionally on everyday concrete social relationships. Developed by Canadian sociologist Dorothy E. Smith, institutional ethnography is often considered a feminist-inspired approach to social analysis and primarily considers women’s experiences within male-dominated societies and power structures. Smith’s work challenges sociology’s exclusion of women, both academically and in the study of women’s lives (Fenstermaker, n.d.).

Historically, social science research tended to objectify women and ignore their experiences except as viewed from a male perspective. Modern feminists note that describing women, and other marginalized groups, as subordinates helps those in authority maintain their own dominant positions (Social Sciences and Humanities Research Council of Canada, n.d.). Smith’s three major works explored what she called “the conceptual practices of power” (1990; cited in Fensternmaker, n.d.) and are still considered seminal works in feminist theory and ethnography.

Sometimes a researcher wants to study one specific person or event. A case study is an in-depth analysis of a single event, situation, or individual. To conduct a case study, a researcher examines existing sources like documents and archival records, conducts interviews, or engages in direct observation and even participant observation, if possible.

Researchers might use this method to study a single case of, for example, a foster child, drug lord, cancer patient, criminal, or rape victim. However, a major criticism of the case study method is that a developed study of a single case, while offering depth on a topic, does not provide broad enough evidence to form a generalized conclusion. In other words, it is difficult to make universal claims based on just one person, since one person does not verify a pattern. This is why most sociologists do not use case studies as a primary research method.

However, case studies are useful when the single case is unique. In these instances, a single case study can add tremendous knowledge to a certain discipline. For example, a feral child, also called a “wild child,” is one who grows up isolated from other human beings. Feral children grow up without social contact and language, which are elements crucial to a “civilized” child’s development. These children mimic the behaviors and movements of animals, and often invent their own language. There are only about one hundred cases of “feral children” in the world.

As you may imagine, a feral child is a subject of great interest to researchers. Feral children provide unique information about child development because they have grown up outside of the parameters of “normal” child socialization and language acquisition. And since there are very few feral children, the case study is the most appropriate method for researchers to use in studying the subject.

At age three, a Ukranian girl named Oxana Malaya suffered severe parental neglect. She lived in a shed with dogs, and she ate raw meat and scraps. Five years later, a neighbor called authorities and reported seeing a girl who ran on all fours, barking. Officials brought Oxana into society, where she was cared for and taught some human behaviors, but she never became fully socialized. She has been designated as unable to support herself and now lives in a mental institution (Grice 2011). Case studies like this offer a way for sociologists to collect data that may not be collectable by any other method.

• Modification, adaptation, and original content. Authored by : Sarah Hoiland for Lumen Learning. Provided by : Lumen Learning. License : CC BY: Attribution
• Research Methods. Authored by : OpenStax CNX. Located at : https://cnx.org/contents/[email protected]:5y6RWnGd@14/Research-Methods . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/contents/[email protected]
• Section on content analysis, Introduction to Sociology 2e. Authored by : William Little. Provided by : BC Open Textbooks. Located at : https://opentextbc.ca/introductiontosociology/ . License : CC BY: Attribution
• Sociological Research Beyonce and Lady Gaga Example. Provided by : OpenStax. Located at : https://openstax.org/books/introduction-sociology-3e/pages/2-2-research-methods . Project : Introduction to Sociology 3e. License : CC BY: Attribution . License Terms : Access for free at https://openstax.org/books/introduction-sociology-3e/pages/1-introduction

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