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Undertake case study research

Margaret Adolphus talks about what case study research is, and sets out the best approaches to data collection and analysis.

What is case study research?

Case study research, in which the subject of the research is studied within its social, political, organisational, or economic context, is one of the commonest approaches across the social and management sciences.

Many authors cite Yin, who describes case study research as:

" ... an empirical inquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident" (Yin, 2009, location no. 638-650).

In other words, the subject of the research is comprehensively studied as an example of a real live phenomenon, within the context in which it happens.

Another definition is given by Dul and Hak:

"A case study is a study in which a) one case (single case study) or a small number of cases (comparative case study) in their real life context are selected, and b) scores obtained from these cases are analysed in a qualitative manner" (Dul and Hak, 2007, p. 4).

How & when is the case study method used?

According to Yin (2006), case study research is best applied when the research addresses descriptive or explanatory questions: i.e. what happened, how, and why?

It is also good for describing a situation or phenomenon occurring in the present, where in-depth description is useful and where the researcher does not need to manipulate events.

Yin (2003) identifies three types of case studies:

  1. Exploratory: the case study is used to define questions and hypotheses – or to test out a research procedure – for a further piece of research, such as a large-scale survey.
  2. Descriptive: the case study is used to describe a particular phenomenon within its context. It can be used to expand on a particular theme unearthed by a survey.
  3. Explanatory: the case study explores cause-effect relationships, and/or how events happen.

Only the third of these approaches can stand up as a method in its own right, and not as an ancillary to other quantitative approaches such as surveys or field experiments.

Advantages of the case study as a research method

Case studies are "real" – they offer a chance to get a snapshot of real life: a rich and thick picture. As such, they are most appropriate for dealing with a subject that is context dependent, complex, unusual, or where there is some ambiguity.

In direct contrast to positivist approaches, which seek to generalise, the case study offers particularity: i.e. the opportunity for a holistic approach without the distraction of too many variables (Gummesson, 2007).

While it offers depth and specificity, case study research also offers breadth and diversity in terms of methods of data collection and analytical techniques. For example, one case study can incorporate surveys, interviews, direct observation, and archival research. This offers the possibility of several different layers of analysis which can reveal several different perspectives, with the added benefit of triangulation of the results.

According to Woodside (2010, pp. 2-3) the usefulness of case study research lies in the fact that it encourages research methods that help measure thinking over an ongoing period, for example by multiple interviews.

It can also be a useful method when the unit of analysis, or the subject under consideration, is a collective entity such as an organisation or a community.

Disadvantages of the case study as a research method

The most common objection to case study research is that it is insufficiently rigorous. Quite often this criticism relates not to the method as such, but to the way case studies are presented: the author does not leave a clear audit trail detailing his or her research and explaining the conclusions.

Case studies are often seen as a "bolt-on" to a major research project, defining research questions or throwing further light on an issue that has been revealed by a survey. That explanatory research can offer an understanding of a phenomenon is viewed with scepticism by some, on the grounds that a single case study cannot yield a sufficient volume of evidence on which to generalise.

What are the skills needed in case study research?

Case study research is neither a quick nor a soft option. It requires considerable skill on the part of the researcher, who needs to be adept at identifying and analysing data from a number of different sources.

It also requires a skill common to all qualitative researchers: the ability to interpret as well as analyse, to see through spin, and if necessary, check information with another source.

Design issues

What is research design?

A research design is a plan for getting from your original question or hypothesis to obtaining workable results from your research, on which you can base defensible conclusions.

Good case study design involves providing empirical data for analysis and conclusion (Gummesson, 2007), but doing so in such a way that stands up to scrutiny.

Defining the research

The first task is to decide what it is you are trying to find out by defining your research question. Carrying out a literature review is an essential precursor to most research, and is a good way of getting ideas for research questions.

The questions need to be suitable: large enough to provide sufficient scope for research, but new enough not to have already been answered.

Yin (2009, location no. 827) advises narrowing down the research question to something more specific, in order to look for relevant evidence. This may take the form of a proposition.

The role of theory

There is some debate as to whether or not it is appropriate to use theory at this stage, but some initial delving into theory will help you further define the parameters of the case you are investigating.

Note too that it is important to understand your own ontological and epistemological perspective: are you carrying out interpretive or positivist research? Broadly speaking, the positivist approach looks at objective reality, which exists beyond the human mind, whereas the interpretivist approach sees knowledge of the world as inevitably affected by the observer.

Practical considerations

When considering your theoretical position at the outset, it is important not to lose sight of an important practical consideration: will the case you have chosen (or are considering choosing) cooperate with your research? You need a case where people will be helpful, leading you to key informants, providing access to documents, and allowing you to interview or survey staff. For example, a school might illustrate an important theoretical point, but if teachers and pupils refuse to engage and you can't gain access to classrooms, it will not be of much use.

Unit of analysis

The beginning of the research process is all about definition: not only your research question, but also your unit of analysis, which is the actual object or entity being studied. Also, the unit must be at the same level as the object of the proposition (Gerring and McDermott, 2007). For example, a company or business could be the unit of analysis, and the object of the proposition be to examine company performance.

On the other hand, your unit of analysis might be an individual or a small group, for example if you were looking at the effects of a particular social intervention such as whether or not neighbourhood policing could reduce crime. It could even be something less tangible, such as a community, a decision, a project, or even a book marketing campaign.

Population and sampling in case selection

Population – the group of people or the area you are investigating – and the sample (the subset of the population you are studying) are both important research principles (see Sampling techniques). Both apply in case study research.

Seawright and Gerring (2008, pp. 295-296) claim that the selection of cases has the same objectives as random sampling in that what is desired is a representative sample and useful variation on the dimensions of theoretical interest. However, given the difficulties of getting a representative case, on both practical and theoretical grounds, they suggest that purposive sampling may be more appropriate (p. 296).

Developing the instrument – different case designs

The work of defining the research questions and proposition is unique to each study, but when it comes to selecting and developing the instrument, there are a number of different possible research designs for case studies.

Single vs multiple case design

This simply means choosing whether your study will include just one, or several cases.

Both types of case study design have their advantages.

Yin (2009, location no. 1201) lists five rationales for single cases:

  1. A critical case – i.e. one that can test a particular theory.
  2. An extreme or unique case – for example, a study of a rare disorder.
  3. A representative case – a case that is representative, or typical, of a particular situation.
  4. A revelatory case – one that reveals a phenomenon hitherto unexplored.
  5. A longitudinal case – a study of changes over time.

The big advantage of multiple case studies is that evidence is provided from many sources, thus making it easier to generalise. A single case, on the other hand, may be considered idiosyncratic. The use of multiple case designs has therefore become more frequent over recent years.

Another advantage of multiple case design is the methodological similarity with the experiment. This has been pointed out by a number of authors – Gerring and McDermott (2007), Lloyd-Jones (2003) and Yin (2009) – despite the fact that the case study is normally considered a qualitative method.

Its disadvantage, however, is its resource intensiveness.

Holistic vs embedded

Single cases and multiple cases can be holistic or embedded. A holistic case is one where the case is the unit of analysis; an embedded one is where there are several units of analysis in the case. This can be represented by Table I.

Table I. Matrix depicting single and multiple holistic cases versus single and multiple embedded cases




One case with one unit of analysis

Several cases each with one unit of analysis


One case with several units of analysis

Several cases each with several units of analysis

For example, a case could be about a school and its response to a new demographic trend or government edict, in which case it would be holistic. If within the school, several different classes were studied, then these sub-units, or "mini cases", would be embedded within the overall case.

Combining the case method with other methods

Some researchers combine case studies with other methods, such as a survey: for example, you could conduct a survey of several local councils, and provide a case study of one council. This type of approach has the benefit of combining qualitative and quantitative research.

Hitherto it has been assumed that theory is developed as part of the initial research work, drawing from the literature review, and that data are analysed against theory. However, with grounded theory design, the opposite happens: data are collected first of all, then theory developed, then more data are collected and compared with the theory, so the whole becomes an iterative process (see How to... implement grounded theory).

The iterative quality of grounded theory would seem to remove it from consideration in orthodox case study design.

Quality in case study research

All research needs to conform to the following quality criteria:

1. Construct validity – this is all about making sure the research uses the right operational measures, appropriate to what is being studied. Construct validity can be improved by:

  • Multiple sources of evidence, i.e. data collection methods, which can be triangulated against one another.
  • Having a chain of evidence.
  • Letting key informants review the draft (Yin, 2009, location no. 1110).

2. Internal validity – this seeks to establish a causal relationship, and is relevant for explanatory rather than exploratory cases. The researcher needs to establish that x causes y, and show that there are no other factors that could have played a part in y.

3. External validity – the extent to which it is possible to generalise from the findings of case studies. Many would say that it is not, on the grounds that case studies are too particular (although this applies less to multiple case studies).

Surveys, based on a sample of a larger population, allow for statistical generalisation. Case studies, on the other hand, can offer results which can be generalised against a particular theory. This is known as analytical generalisation.

4. Reliability – another researcher should be able to go in and repeat the case study, and come up with the same findings. (Note that this is different from being able to replicate the results in another case.) The way to make this possible is by documenting the procedures in the research.

Using case studies to generate theory

Cepeda and Martin (2005) see theory building as a key stage in the case study research process. After the collection of data, there is a stage for reflection, which enables the researcher to update the initial conceptual framework on which the research was based. The result is a cyclical process of theory, producing a research process giving rise to data from which fresh theory can be formulated, and fresh research carried out. Because research takes place "in the field", there is a close relationship between theory and what is happening on the ground.

Figure 1. Cepeda and Martin's view of conceptual frameworks and the research cycle (2005, p. 861).

Figure 1. Cepeda and Martin's view of conceptual frameworks and the research cycle (2005, p. 861)

Data collection

If case study research is never a soft option, the collection and analysis of data can be particularly challenging.

The data collection process demands that the researcher be actively involved, asking the right questions which link to those that are central to the study, in a manner which does not alienate the subject. He or she needs to be a good listener, paying attention not only to what is said, but also to what is not said explicitly, perhaps indicated by mood or body language.

He or she needs to pay attention to multiple sources of evidence, and be able to handle complexity, and the possibility that new information may lead in a new direction, while at the same time not losing sight of the original research questions.

Preparation for data collection

The amount of preparation required for this stage will depend on the complexity of the research, and on your experience of this type of data collection. A large project with multiple cases, or a complex single case with much data collection, for example, may require a team of research assistants.

There are five aspects to preparation:

1. Ethical guidelines and protection of human subjects

Case studies involve research about humans and their actions, and you need to take special care to protect your subjects from any harm resulting from your research.

You need to gain their informed consent, ensuring that they understand the purpose of your study and are not deceived; will come to no harm as a result of your investigations; and that their privacy and confidentiality is protected. Especial care needs to be taken with vulnerable groups, such as children.

Your institution may well have a review board or committee with guidelines you need to adhere to, and whose approval you need to seek.

2. Training for case study research

If you are not part of a team, you may find it beneficial to attend a course on research methods for case studies, perhaps held by your institution or by an independent body.

You can also talk to experienced case study researchers you know in your department or through your network, and look at relevant scholarly articles. In some cases, the online versions of these articles may contain supplementary documents on which the research was based, such as the protocol.

3. Development of the case study protocol

A protocol is a blueprint for a research instrument: for example, a survey questionnaire, or a set of questions for an interview.

However, a case study protocol is more than an instrument: it is a combination of project outline and management document, research instrument, table as shell for data collection, and guidelines for the report.

Rahim and Baksh (2003, p. 32) define the case study protocol as follows:

"A case study protocol is a record (normally a document) that contains the methods, procedures and general rules that will be followed in using instruments of data collection. It is used to improve the reliability of case study results."

In summary, the protocol should cover the following:

  1. A project overview, including background, main issues to be explored, and a statement which can be presented to those from whom one seeks access, or help with the project.
  2. Field procedures, in other words, guidelines as to how the case study will be conducted. These should cover how the subjects will be accessed (including ethics), the schedule, together with such practical issues as how to handle document collection, etc.
  3. Case study questions: these are the original research questions which should guide the project, and should not be confused with the interview schedule. They should however act as a guide for any questions the researcher poses to human subjects, or which are used in the perusal of documents.
  4. Guidelines for writing the report, which may include a tentative outline.

4. Final selection of case(s)

You should have decided on the type of case, and type of design, and how your case(s) relate to the population studied, etc., at an earlier stage.

The final screening of cases involves selecting the case(s) which best fit your design, where you can obtain the best data, and where you can obtain easy access to documents, people and other information.

5. Pilot case study

If you conduct a pilot case study, this will help you refine your plans for collecting data, for example the type of questions you might want to ask your interview subjects.

The main types of data

Case study researchers are often advised to include more than one source of evidence, in order to facilitate triangulation and increase the richness and multifacetedness of their study. Choosing more than one method also has the advantage that one method's weakness can be balanced out by another's strengths.

The most usual sources of information are:

Documentation and archival records

The most important use of documentation lies in:

  • Providing background to the case.
  • Corroborating, or contradicting, evidence from interviews or other sources.
  • Providing inferential information, for example, about networks, which can be deduced from distribution lists etc. (Yin, 2003, location no. 2168).
  • Helping make sure that people's names are spelt correctly.

See "How to... use secondary data and archive material", especially "Using archival data" for more details


Because of the human element of case studies, interviews are one of the most important methods of case study research, and are almost always an element of the research design. See "How to... conduct interviews".

Direct and participant observation

Direct observation occurs when the researcher observes but does not participate. This way of collecting data is very powerful, because the researcher is unobtrusive, and can therefore freely observe behaviour which is not "edited", as it might be in a laboratory setting, or when the interviewer's questions frame the response (Woodside, 2010, p. 406).

Participant observation involves actually being part of the culture. A notable use has been the study of different cultural or social groups, or urban neighbourhoods (see "How to... use ethnographic methods and participant observation").

Physical artefacts

Physical evidence from objects, including technological devices, tools, instruments, works of art, videos etc.

Visual data collection

Because visual communication precedes verbal, visual data collection methods are a powerful way of helping individuals retrieve unconscious thoughts.

Woodside (2010) provides detailed accounts of several other methods: for example storytelling, visual narrative art, conversational analysis, and forced metaphor elicitation technique. What these methods have in common is the fact that they are designed to probe below the surface of what is being said, in other words to look at unconscious processes.

The three main principles of data collection

The following principles will help increase construct validity and reliability.

Principle 1. Use multiple sources of data

There are numerous ways that data can be collected. While many cases use just one source (usually the interview), it is considered good practice to obtain data by several methods.

This helps with triangulation, where different lines of enquiry converge, with the findings of one set of data corroborating another. As Rowley puts it (2002):

"Triangulation uses evidence from different sources to corroborate the same fact or finding."

Furthermore, different data sources can support one another with complementary strengths: for example, document analysis is good for establishing facts, whereas interviews enable the researcher to probe.

Woodside (2010, p. 107) maintains that a multiple methods approach is essential in order to elicit both conscious and unconscious thinking processes. Methods can include interviewing, and observation, with the researcher concurrently recording his or her thoughts.

This methodological richness is one of the great strengths of case studies as a method.

Principle 2. Create a case study database

According to Yin (2009, location no. 2495) the data from the case study is often merged with the report, whereas it should be stored in such a way that it can easily be accessed and viewed by another researcher. This will increase transparency and hence the reliability of the research.

The database may include the following:

  • Notes, from interviews, observation, document analysis, etc.
  • Documents collected during the case study, which should be accompanied by an annotated bibliography.
  • Tabular materials, including survey and quantitative data.
  • Any narratives composed by the researcher during investigations.

Principle 3. Maintain a chain of evidence

The case study database should contain plenty of evidence that is then referred to in the report. It is also important to have clarity in terms of the trail of evidence that leads from the research questions to the conclusions, and back again.

Opoku and Williams (2011, pp. 256-257) commented on how they maintained a chain of evidence:

"Using multiple researchers, we continually communicated our methodological decisions to respondents and recorded the data mechanically by using a tape recorder. This helped to enhance the reliability of this study. We have also tried to improve the reliability of this study by documenting all the necessary steps which were followed in order to conduct it ... The interviews were transcribed, analysed, and validated with the interviewees. Provisional research conclusions were subsequently sent back to the respondents via e-mail and the resulting feedback discussion was annotated."

Surviving complexity

It will be clear from the above that data collection for case studies is highly complicated. Each type of data collection requires its own skill set which the researcher will have to master.

Another problem is that there is no end point for data collection, unlike, for example, the survey, where the parameters of the investigation are fixed by the number of responses (assuming the researcher considers the response rate to be satisfactory).

With case study evidence coming from so many sources, there is no such fixed cut-off point, so it can be difficult to know when to stop.

Data analysis

If data collection for case studies is difficult, data analysis is no less so. The area is largely uncharted, in contrast to statistical analysis, where there are plenty of established techniques.

While there are software packages available (for example, The Ethnograph, ATLAS.ti, HyperRESEARCH, and NVivo), these do not provide analysable outputs. They may help with the organisation of your material, but you need to come up with your own codes.

The analysis of qualitative data is covered in the guide, "How to ... analyse qualitative data", which may provide some useful hints.

Rowley (2002, p. 24) proposes the following principles for good case study analysis:

The analysis –

  • makes use of all the relevant evidence
  • considers all the major rival interpretations, and explores each of them in turn
  • should address the most significant aspect of the case study
  • should draw on the researcher's prior expert knowledge in the area of the case study, but in an unbiased and objective manner.

Various strategies can be used to code the data into different categories, from simple colour coding to content analysis (according to which data are grouped according to a number of variables), or grounded theory, where categories are established following the first phase of data collection and then used for the next phase of analysis.

The importance of having a general strategy

Yin (2009, location no. 2693) states that it is important to have a general analytic strategy, rather than hoping that patterns will emerge simply through studying and experimenting with the data.

He proposes four such strategies:

  1. Rely on the study's theoretical propositions. These should have informed the data collection, and during the analysis the researcher trawls through the evidence, looking for corroborative (or not) evidence. He or she then makes a judgement as to whether or not the initial propositions have been substantiated.
  2. Develop a descriptive framework for organising the case study. This works well in an explanatory case study, set up to test certain propositions, however it may be less suitable for one that is descriptive or exploratory. An alternative strategy is therefore to consider how one will organise the report, and come up with a number of headings under which evidence will be grouped.
  3. Employ both qualitative and quantitative data. Some case studies employ only qualitative data. Some, however, use quantitative data, perhaps gained from surveys, or from existing statistics (for example crime rates, employees' salaries, student achievement). Providing that these data are central to the case study and to any propositions you are investigating, combining statistical and qualitative analysis will offer a strong strategy.
  4. Examine rival explanations. Your initial literature review may have examined rival hypotheses, which can then be checked against the evidence. This approach can be combined with any one of the other three.

Using analytical techniques

Yin (2009, location no. 2816) mentions five particular analytical techniques:

  1. Pattern matching. This involves comparing a predicted pattern with one revealed by the outcome of the case study. If there is a match, and the patterns coincide, then the initial proposition is confirmed, and the internal validity of the research is strengthened.
  2. Explanation building.
  3. Time-series analysis.
  4. Logic models.
  5. Cross-case synthesis. This method is applicable to any case research which employs at least two cases. Since more than one case will have been used for a reason, it is obviously necessary to compare findings across cases in order to reach valid conclusions. Each case is treated as a separate study, and the resulting data are compared. Tables are commonly used for this purpose, with a framework to suit the relevant data outcomes. Analysis of the tables then enables the researcher to draw conclusions across the data.

Of these, Yin (2009) describes pattern matching as "one of the most desirable" (location no. 2816), while cross-case analysis is obviously important in multiple case studies.


Once you have collected, analysed and formed conclusions from your data. The next step is, obviously, to share your findings with others by writing up your case study.

How you do this will vary according to your target audience. For example, if someone has commissioned you to write a report, the format will be different to that for an academic journal. The latter is covered in part 3 of the author guide, "How to ... write a case study".


Cepeda, G. and Martin, D. (2005), "A review of case studies publishing in Management Decision: guides and criteria for achieving quality in qualitative research", Management Decision, Vol. 43 No. 6, pp. 851-876.

Dul, J. and Hak, T. (2007), Case Study Methodology in Business Research, Butterworth-Heinemann, Oxford.

Gerring, J. and McDermott, R. (2007), "An experimental template for case study research", American Journal of Political Science, Vol. 51 No. 3, pp. 688-701, available at: http://sws.bu.edu/jgerring/documents/Experimental.pdf [accessed 9 December 2010].

Gummesson, E. (2007), "Case study research and network theory: birds of a feather", Qualitative Research in Organizations and Management: An International Journal, Vol. 2 No. 3, pp. 226-248.

Lloyd-Jones, G. (2003), "Design and control issues in qualitative case study research", International Journal of Qualitative Methods, Vol. 2 No. 2, pp. 33-42.

Opoku, R.A. and Williams, E.B. (2010), "Stakeholder management online: an empirical analysis of US and Swedish political party web sites", Journal of Information, Communication and Ethics in Society, Vol. 8 No. 3, pp. 249-269.

Rahim, A.R.A. and Baksh, M.S.N. (2003), "Case study method for new product development in engineer-to-order organizations", Work Study, Vol. 52 No. 1, pp. 25-36.

Rowley, J. (2002), "Using case studies in research", Management Research News, Vol. 25 No. 1, pp. 16-27.

Seawright, J. and Gerring, J. (2008), "Case selection techniques in case study research: a menu of qualitative and quantitative options", Political Research Quarterly, Vol. 61 No. 2, pp. 294-308.

Woodside, A.G. (2010), Case Study Research: Theory, Methods and Practice, Emerald Group Publishing Limited, UK.

Yin, R.K. (2003), Case Study Research: Design and Methods, 3rd ed., Sage, London.

Yin, R.K. (2006), "Case study methods", in Green, J.L., Camilli, G. and Elmore, P.B. (Eds), Handbook of Complementary Methods in Education Research, Lawrence Erlbaum Associates, Inc., NJ.

Yin, R.K. (2009), Case Study Research: Design and Methods, 4th ed., e-book, Sage, CA [accessed 20 December 2010].