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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.

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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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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.

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Case Study – Methods, Examples and Guide

Table of Contents

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.

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22 Case Study Research: In-Depth Understanding in Context

Helen Simons, School of Education, University of Southampton

Published: 01 July 2014
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This chapter explores case study as a major approach to research and evaluation. After first noting various contexts in which case studies are commonly used, the chapter focuses on case study research directly Strengths and potential problematic issues are outlined and then key phases of the process. The chapter emphasizes how important it is to design the case, to collect and interpret data in ways that highlight the qualitative, to have an ethical practice that values multiple perspectives and political interests, and to report creatively to facilitate use in policy making and practice. Finally, it explores how to generalize from the single case. Concluding questions center on the need to think more imaginatively about design and the range of methods and forms of reporting requiredto persuade audiences to value qualitative ways of knowing in case study research.

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Case Study Observational Research: A Framework for Conducting Case Study Research Where Observation Data Are the Focus

Affiliation.

1 1 University of Otago, Wellington, New Zealand.
PMID: 27217290
DOI: 10.1177/1049732316649160

Case study research is a comprehensive method that incorporates multiple sources of data to provide detailed accounts of complex research phenomena in real-life contexts. However, current models of case study research do not particularly distinguish the unique contribution observation data can make. Observation methods have the potential to reach beyond other methods that rely largely or solely on self-report. This article describes the distinctive characteristics of case study observational research, a modified form of Yin's 2014 model of case study research the authors used in a study exploring interprofessional collaboration in primary care. In this approach, observation data are positioned as the central component of the research design. Case study observational research offers a promising approach for researchers in a wide range of health care settings seeking more complete understandings of complex topics, where contextual influences are of primary concern. Future research is needed to refine and evaluate the approach.

Keywords: New Zealand; appreciative inquiry; case studies; case study observational research; health care; interprofessional collaboration; naturalistic inquiry; observation; primary health care; qualitative; research design.

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Methodology
What Is a Conceptual Framework? | Tips & Examples

What Is a Conceptual Framework? | Tips & Examples

Published on August 2, 2022 by Bas Swaen and Tegan George. Revised on March 18, 2024.

A conceptual framework illustrates the expected relationship between your variables. It defines the relevant objectives for your research process and maps out how they come together to draw coherent conclusions.

Keep reading for a step-by-step guide to help you construct your own conceptual framework.

Developing a conceptual framework in research, step 1: choose your research question, step 2: select your independent and dependent variables, step 3: visualize your cause-and-effect relationship, step 4: identify other influencing variables, frequently asked questions about conceptual models.

A conceptual framework is a representation of the relationship you expect to see between your variables, or the characteristics or properties that you want to study.

Conceptual frameworks can be written or visual and are generally developed based on a literature review of existing studies about your topic.

Your research question guides your work by determining exactly what you want to find out, giving your research process a clear focus.

However, before you start collecting your data, consider constructing a conceptual framework. This will help you map out which variables you will measure and how you expect them to relate to one another.

In order to move forward with your research question and test a cause-and-effect relationship, you must first identify at least two key variables: your independent and dependent variables .

The expected cause, “hours of study,” is the independent variable (the predictor, or explanatory variable)
The expected effect, “exam score,” is the dependent variable (the response, or outcome variable).

Note that causal relationships often involve several independent variables that affect the dependent variable. For the purpose of this example, we’ll work with just one independent variable (“hours of study”).

Now that you’ve figured out your research question and variables, the first step in designing your conceptual framework is visualizing your expected cause-and-effect relationship.

We demonstrate this using basic design components of boxes and arrows. Here, each variable appears in a box. To indicate a causal relationship, each arrow should start from the independent variable (the cause) and point to the dependent variable (the effect).

Sample-conceptual-framework-using-an-independent-variable-and-a-dependent-variable

It’s crucial to identify other variables that can influence the relationship between your independent and dependent variables early in your research process.

Some common variables to include are moderating, mediating, and control variables.

Moderating variables

Moderating variable (or moderators) alter the effect that an independent variable has on a dependent variable. In other words, moderators change the “effect” component of the cause-and-effect relationship.

Let’s add the moderator “IQ.” Here, a student’s IQ level can change the effect that the variable “hours of study” has on the exam score. The higher the IQ, the fewer hours of study are needed to do well on the exam.

Sample-conceptual-framework-with-a-moderator-variable

Let’s take a look at how this might work. The graph below shows how the number of hours spent studying affects exam score. As expected, the more hours you study, the better your results. Here, a student who studies for 20 hours will get a perfect score.

But the graph looks different when we add our “IQ” moderator of 120. A student with this IQ will achieve a perfect score after just 15 hours of study.

Below, the value of the “IQ” moderator has been increased to 150. A student with this IQ will only need to invest five hours of study in order to get a perfect score.

Here, we see that a moderating variable does indeed change the cause-and-effect relationship between two variables.

Mediating variables

Now we’ll expand the framework by adding a mediating variable . Mediating variables link the independent and dependent variables, allowing the relationship between them to be better explained.

Here’s how the conceptual framework might look if a mediator variable were involved:

In this case, the mediator helps explain why studying more hours leads to a higher exam score. The more hours a student studies, the more practice problems they will complete; the more practice problems completed, the higher the student’s exam score will be.

Moderator vs. mediator

It’s important not to confuse moderating and mediating variables. To remember the difference, you can think of them in relation to the independent variable:

A moderating variable is not affected by the independent variable, even though it affects the dependent variable. For example, no matter how many hours you study (the independent variable), your IQ will not get higher.
A mediating variable is affected by the independent variable. In turn, it also affects the dependent variable. Therefore, it links the two variables and helps explain the relationship between them.

Control variables

Lastly, control variables must also be taken into account. These are variables that are held constant so that they don’t interfere with the results. Even though you aren’t interested in measuring them for your study, it’s crucial to be aware of as many of them as you can be.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

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Framework for identifying research and innovation impact case studies from south african universities.

African Population and Health Research Center

1. Introduction and Background

The African Population and Health Research Center (APHRC) is a premier research-to-policy institution, generating evidence, strengthening research and related capacity in the African research and development ecosystem, and engaging policy to inform action on health and development. The Center is Africa-based and African-led, with its headquarters in Nairobi, Kenya, and a West Africa Regional Office (WARO), in Dakar, Senegal. APHRC seeks to drive change by developing strong African research leadership and promoting evidence-informed decision-making (EIDM) across sub-Saharan Africa.

The Center is collaborating with the Southern African Research and Innovation Management Association (SARIMA) on its project on Building it Forward for Research (Management) Leadership in Southern Africa, in which the Center is leading a specific workstream to carry out impact case studies arising out of university research. This collaborative approach ensures effective execution and maximizes the value of the research impact assessment.

2. Project Scope and Focus

University research plays a critical role in improving wellbeing, informing policy decisions, and driving innovation. However, the impact of this research often remains under-communicated, hindering efforts to secure sustained funding and public support. While quantitative data is essential, compelling case studies go beyond mere numbers. They weave narratives that capture the human stories behind the research, highlighting the challenges addressed, the innovative solutions developed, and the real-world impact on societal outcomes. These narratives resonate with audiences, generating greater understanding and appreciation for the value of research. The case studies produced in this workstream target a diverse audience, including:

Funders: Highlighting the transformative power of research investments.
Policymakers: Demonstrating the research-policy nexus and influencing policy decisions.
Public: Raising awareness about the impact of research on their lives.
Media: Generating media interest and amplifying the research's impact.

Led by APHRC, the workstream aims to identify, analyse and document four case studies showcasing the impact of research and innovation projects conducted by South African universities. The case studies will highlight the tangible contributions of university research and innovation to national priorities and broader societal well-being.

3. Criteria for Selecting Case Studies

The preferred sectors for cases include:

Agriculture
Inclusive financial systems

The case studies will demonstrate one or more of the following impact pathways:

Reductions in mortality or morbidity rates for specific diseases.
Increased access to services, particularly for underserved populations.
Improved behaviors through effective interventions.
Economic benefits (e.g., cost savings in systems).
Development of new diagnostic tools or treatments.
Innovative approaches to health promotion or disease prevention.
New technologies that improve quality of life, create jobs and/or uplift communities.
Culturally sensitive interventions addressing specific needs within South Africa.
Research informing policy changes.
Studies influencing policy decisions on public health and other public good interventions.
Research contributing to the development of national legislation, policy or guidelines.
Addressing the needs of underserved and vulnerable populations.
Ensuring research findings can be applied in diverse settings across South Africa and beyond.
Promoting long-term benefits and sustainable impact.
Potential for Scale-Up: The case study should demonstrate the scalability of the research findings, potentially impacting a broader population or region. This can be achieved through:
Adapting the intervention for broader implementation.
Developing clear dissemination strategies for research outputs.
Building partnerships with stakeholders to facilitate scale-up.
Stakeholder Involvement: Evidence of collaboration with diverse stakeholders who contributed to the research impact. These may include:
External enablers: Role of and interactions with ecosystem players – e.g. collaborative research partners, funding from local/national governments and international funders, private sector, civil society, role of regulators and regulatory process, national policies that aided impact (e.g. IP policy), commercialization routes, infrastructure, manufacturing or value delivery (services/processes)
Internal Enablers: The case study should highlight the role of university support structures and policies that facilitated the research's translation into impact. E.g. role of Research Management Office and Technology Transfer Office and the conditions internally that allowed for impact (this could go as far as looking at institutional policies, systems etc.)
Diversity: The case studies will aim to represent a variety of research disciplines, universities, and types of impacts.

4. Call for Submission of Qualifying Projects for Case Studies

South African Universities are invited to submit examples of research and innovation projects conducted by their institutions that could be suitable subjects for impact case studies predicated on the criteria outlined in paragraph 3 above.

5. Role of the Consultant

The APHRC wishes to appoint a qualified and experienced Consultant in case study analysis and development, for the production and dissemination of knowledge products to lead APHRC’s effort to deliver on this workstream. The Consultant will be required to perform the following tasks:

5.1 Selection of Case Studies

A Consultant in collaboration with APHRC will review submissions and select promising research projects for case study development. Selected universities will be contacted by the dedicated consultant to collaborate on developing a comprehensive case study report.

Evaluation and selection of Case Studies: The Consultant will develop the criteria for scoring and selection of potential case studies submitted by South African universities for further analysis, development and documentation.
**Collaboration with Universities:**If necessary, the Consultant will collaborate with the relevant research and support departments and units at South African universities to identify and select potential case studies for consideration.
**Desktop Research:**The Consultant will conduct a literature review of published research from South African universities in relevant fields in order to identify suitable projects. This will involve searching academic databases, government reports, media articles and online resources (e.g. Databases such as ResearchGate and institutional websites of universities canbe explored by the Consultant to find relevant research projects.)
**Expert Consultation:**The Consultant will consult with relevant experts and stakeholders to identify/further refine impactful research projects. Working with APHRC, the Consultant will further determine and implement simple criteria to review potential case studies submitted by South African universities and/or identified by the Consultant. This may include:
Scientific merit and methodological rigor of the research.
Potential for broader impact and scalability of the findings.
Alignment of the research with national policy priorities and the funder's interests.

5.2 Developing Strong Case Studies

The Consultant will identify a short list of case studies and will collaborate with the qualifying universities to conduct a detailed analysis of each case study to further elaborate on how each case study addresses the criteria set out in paragraph 3. In terms of methodology, the Consultant will use the Theory of Change framework and employ – without limitation - the following techniques:

In-depth Interviews: The Consultant will conduct interviews with researchers and other role players and stakeholders to capture a detailed narrative of the research journey, key role players, the research outcomes, the impact of the research, and future potential.
Data Analysis and Storytelling: The Consultant will assist with analyzing data and crafting a compelling narrative that showcases the research's significance and impact.
Identifying Visuals: Working with the selected universities, the Consultant will identify relevant visuals (charts, photos) to enhance the case study report.

5.2.1. Focus on Storytelling

Crafting a captivating narrative is central to a strong case study. This narrative should:

Research focus and objectives
Measurable impact on relevant areas (sector e.g. health, agriculture, inclusive financial systems; economy; society)
Alignment with national/provincial priorities
Set the Stage: Introduce the challenge addressed by the research and highlight its significance for South Africa's population.
Describe the Research Journey: Explain the research approach, methodology, and key findings in clear and concise language.
Showcase Innovation: Emphasize the novel aspects of the research and how it addressed existing limitations or offered new solutions.
Demonstrate Impact: Quantify the impact of the research on societal outcomes using relevant data (e.g. surveys, statistics).
Highlight Policy Influence: If applicable, detail how the research findings informed policy changes or national guidelines.
Focus on Equity and Sustainability: Explain how the research addressed the needs of underserved populations and how its impact can be sustained over time.
Showcase Potential for Scale-Up: Describe plans or ongoing efforts to scale-up the intervention and reach a wider population.

5.2.2. Data and Evidence:

Strong narratives are bolstered by robust evidence. Case studies should incorporate a combination of:

Reductions in mortality or morbidity rates.
Increased access to services (e.g. number of people reached).
Improved health behaviors (e.g. changes in dietary habits, vaccination rates).
Economic benefits (e.g. cost savings).
Creation of jobs.
Improved efficiency.
Interviews with researchers, policymakers, healthcare providers, and community members impacted by the research.
Focus group discussions to understand perceptions and experiences.
Case studies of individual beneficiaries who have demonstrably benefited from the research.
Policy Documents: Documents such as policy briefs, white papers, or government reports showcasing how research findings influenced policy decisions.

5.2.3. Engaging Visuals and Multimedia

Incorporating visuals can significantly enhance the case study's impact and accessibility. Examples include:

Charts and Infographics: Visualize data and trends to make complex information more easily understood by the audience.
Photographs: Images of researchers, healthcare providers, community members, or interventions in action can personalize the narrative.
Short Video Clips: Short videos can capture the essence of the research and its impact in a compelling way.

5.2.4. Stakeholder Testimonials

Including testimonials from key stakeholders adds credibility and authenticity to the case studies. This could include:

Researchers: Sharing their insights into the research process and the significance of the findings.
Policymakers: Describing how the research influenced policy decisions.
Healthcare Providers: Highlighting how the research improved their practice or patient care.
Community Members: Sharing their experiences and how the research impacted their health and well-being.

5.2.5. Showcase the Enabling Factors that Contributed to the Research's Success :

External stakeholder collaboration (research partners, funders, regulators)
University support structures (including Research Management Offices, Technology Transfer Offices)
Internal policies and systems promoting research impact.

6. Deliverables

A set of four well-written, compelling case studies demonstrating impactful research and innovation from South African universities.

7. Dissemination and Advocacy Strategies

The final stage involves disseminating the case studies to a wide audience and leveraging them for advocacy and informational purposes.

7.1. Dissemination Channels:

APHRC Website and Social Media: A dedicated webpage will be created on the APHRC website to showcase the case studies. This webpage will be promoted through social media platforms like X, Facebook, and LinkedIn
SARIMA Website and Social Media: The case studies will be showcased on the SARIMA website, and promoted through social media platforms like X and LinkedIn
Other channels and platforms will be discussed and agreed between the funder, APHRC and SARIMA.

7. Reporting and Communication

The Consultant will provide the case studies and periodic progress reports to APHRC as required.

8. Timeline

8.1 Submission of Case Studies: By September 30, 2024 .

8.2 Recruitment of Consultant: By August 31, 2024

8.3 The case study development will be conducted in two phases. It is expected that the first two case studies will be developed by November 30, 2024 and the other two case studies will be developed by June 30, 2025 .

9. Submission of Potential Research for Case Study Development

If you know of any research which aligns with the criteria above, you are encouraged to submit it to be considered for case study development. Follow the following guidelines for submitting your research:

Prepare a Short Summary (2 Pages Maximum):

Briefly describe the research project and its objectives.
Highlight the specific challenge the research addressed.
Summarize the research approach and key findings.
Explain how the research made impact and quantify this impact (if possible).
Include any evidence of policy influence or potential for scale-up.

Provide Supporting Materials (To the Extent Applicable):

Include relevant publications, reports, or presentations related to your research.
Share any data (quantitative or qualitative) that demonstrates impact.
Offer contact details for key individuals involved in the project eg researchers, funders, end-users, beneficiaries and others who played a role in ensuring that impact was achieved (including – without limitation the institutional Research Support Office).

How to apply

Submission Process for Universities Wishing to submit Potential Projects for Case Study Consideration:

Submit your research summary and supporting materials electronically to [email protected] with a copy to [email protected] and [email protected] . Please use “ South Africa University Research Case Study Development ” as subject title in your email submission.
Indicate your university affiliation and the lead researcher/contact person contact information.

Submission Process for Consultancy Bids:

Submit your consultancy bids and supporting materials demonstrating your expertise and qualifications for the assignment electronically to [email protected] with a copy to [email protected] and [email protected]
This should include a detailed proposal addressing all areas identified in the Term of Reference, a detailed budget and evidence of related previous work.
Indicate subject title as “ Consultancy for South Africa University Research Impact Case Study ”.

12. For Further Queries: [email protected]

Special Notice

APHRC is an equal opportunity employer committed to creating a diverse and inclusive workplace. All employment decisions are made based on qualifications and organizational needs. Reasonable accommodation may be provided to applicants with disabilities upon request to support their participation in the recruitment process.

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BMC Med Res Methodol

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.

Introduction

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 ]

Minority ethnic people experience considerably greater morbidity from asthma than the White majority population. Research has shown however that these minority ethnic populations are likely to be under-represented in research undertaken in the UK; there is comparatively less marginalisation in the US.

To investigate approaches to bolster recruitment of South Asians into UK asthma studies through qualitative research with US and UK researchers, and UK community leaders.

Single intrinsic case study

Centred on the issue of recruitment of South Asian people with asthma.

In-depth interviews were conducted with asthma researchers from the UK and US. A supplementary questionnaire was also provided to researchers.

Framework approach.

Barriers to ethnic minority recruitment were found to centre around:

1. The attitudes of the researchers' towards inclusion: The majority of UK researchers interviewed were generally supportive of the idea of recruiting ethnically diverse participants but expressed major concerns about the practicalities of achieving this; in contrast, the US researchers appeared much more committed to the policy of inclusion.

2. Stereotypes and prejudices: We found that some of the UK researchers' perceptions of ethnic minorities may have influenced their decisions on whether to approach individuals from particular ethnic groups. These stereotypes centred on issues to do with, amongst others, language barriers and lack of altruism.

3. Demographic, political and socioeconomic contexts of the two countries: Researchers suggested that the demographic profile of ethnic minorities, their political engagement and the different configuration of the health services in the UK and the US may have contributed to differential rates.

4. Above all, however, it appeared that the overriding importance of the US National Institute of Health's policy to mandate the inclusion of minority ethnic people (and women) had a major impact on shaping the attitudes and in turn the experiences of US researchers'; the absence of any similar mandate in the UK meant that UK-based researchers had not been forced to challenge their existing practices and they were hence unable to overcome any stereotypical/prejudicial attitudes through experiential learning.

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

Health work forces globally are needing to reorganise and reconfigure in order to meet the challenges posed by the increased numbers of people living with long-term conditions in an efficient and sustainable manner. Through studying the introduction of General Practitioners with a Special Interest in respiratory disorders, this study aimed to provide insights into this important issue by focusing on community respiratory service development.

To understand and compare the process of workforce change in respiratory services and the impact on patient experience (specifically in relation to the role of general practitioners with special interests) in a theoretically selected sample of Primary Care Organisations (PCOs), in order to derive models of good practice in planning and the implementation of a broad range of workforce issues.

Multiple-case design of respiratory services in health regions in England and Wales.

Four PCOs.

Face-to-face and telephone interviews, e-mail discussions, local documents, patient diaries, news items identified from local and national websites, national workshop.

Reading, coding and comparison progressed iteratively.

1. In the screening phase of this study (which involved semi-structured telephone interviews with the person responsible for driving the reconfiguration of respiratory services in 30 PCOs), the barriers of financial deficit, organisational uncertainty, disengaged clinicians and contradictory policies proved insurmountable for many PCOs to developing sustainable services. A key rationale for PCO re-organisation in 2006 was to strengthen their commissioning function and those of clinicians through Practice-Based Commissioning. However, the turbulence, which surrounded reorganisation was found to have the opposite desired effect.

2. Implementing workforce reconfiguration was strongly influenced by the negotiation and contest among local clinicians and managers about "ownership" of work and income.

3. Despite the intention to make the commissioning system more transparent, personal relationships based on common professional interests, past work history, friendships and collegiality, remained as key drivers for sustainable innovation in service development.

It was only possible to undertake in-depth work in a selective number of PCOs and, even within these selected PCOs, it was not possible to interview all informants of potential interest and/or obtain all relevant documents. This work was conducted in the early stages of a major NHS reorganisation in England and Wales and thus, events are likely to have continued to evolve beyond the study period; we therefore cannot claim to have seen any of the stories through to their conclusion.

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

Healthcare systems globally are moving from paper-based record systems to electronic health record systems. In 2002, the NHS in England embarked on the most ambitious and expensive IT-based transformation in healthcare in history seeking to introduce electronic health records into all hospitals in England by 2010.

To describe and evaluate the implementation and adoption of detailed electronic health records in secondary care in England and thereby provide formative feedback for local and national rollout of the NHS Care Records Service.

A mixed methods, longitudinal, multi-site, socio-technical collective case study.

Five NHS acute hospital and mental health Trusts that have been the focus of early implementation efforts.

Semi-structured interviews, documentary data and field notes, observations and quantitative data.

Qualitative data were analysed thematically using a socio-technical coding matrix, combined with additional themes that emerged from the data.

1. Hospital electronic health record systems have developed and been implemented far more slowly than was originally envisioned.

2. The top-down, government-led standardised approach needed to evolve to admit more variation and greater local choice for hospitals in order to support local service delivery.

3. A range of adverse consequences were associated with the centrally negotiated contracts, which excluded the hospitals in question.

4. The unrealistic, politically driven, timeline (implementation over 10 years) was found to be a major source of frustration for developers, implementers and healthcare managers and professionals alike.

We were unable to access details of the contracts between government departments and the Local Service Providers responsible for delivering and implementing the software systems. This, in turn, made it difficult to develop a holistic understanding of some key issues impacting on the overall slow roll-out of the NHS Care Record Service. Early adopters may also have differed in important ways from NHS hospitals that planned to join the National Programme for Information Technology and implement the NHS Care Records Service at a later point in time.

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

There is a need to reduce the disease burden associated with iatrogenic harm and considering that healthcare education represents perhaps the most sustained patient safety initiative ever undertaken, it is important to develop a better appreciation of the ways in which undergraduate and newly qualified professionals receive and make sense of the education they receive.
To investigate the formal and informal ways pre-registration students from a range of healthcare professions (medicine, nursing, physiotherapy and pharmacy) learn about patient safety in order to become safe practitioners.
Multi-site, mixed method collective case study.
: Eight case studies (two for each professional group) were carried out in educational provider sites considering different programmes, practice environments and models of teaching and learning.
Structured in phases relevant to the three knowledge contexts:
	Documentary evidence (including undergraduate curricula, handbooks and module outlines), complemented with a range of views (from course leads, tutors and students) and observations in a range of academic settings.

	Policy and management views of patient safety and influences on patient safety education and practice. NHS policies included, for example, implementation of the National Patient Safety Agency's , which encourages organisations to develop an organisational safety culture in which staff members feel comfortable identifying dangers and reporting hazards.

	The cultures to which students are exposed i.e. patient safety in relation to day-to-day working. NHS initiatives included, for example, a hand washing initiative or introduction of infection control measures.


1. Practical, informal, learning opportunities were valued by students. On the whole, however, students were not exposed to nor engaged with important NHS initiatives such as risk management activities and incident reporting schemes.
2. NHS policy appeared to have been taken seriously by course leaders. Patient safety materials were incorporated into both formal and informal curricula, albeit largely implicit rather than explicit.
3. Resource issues and peer pressure were found to influence safe practice. Variations were also found to exist in students' experiences and the quality of the supervision available.
The curriculum and organisational documents collected differed between sites, which possibly reflected gatekeeper influences at each site. The recruitment of participants for focus group discussions proved difficult, so interviews or paired discussions were used as a substitute.

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

Author	Definition
Stake[ ]	(p.237)
Yin[ , , ]	(Yin 1999 p. 1211, Yin 1994 p. 13)

	•
	• (Yin 2009 p18)
Miles and Huberman[ ]	(p. 25)
Green and Thorogood[ ]	(p. 284)
George and Bennett[ ]	(p. 17)"

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

Characteristics	Criticisms	Key references
Involves questioning one's own assumptions taking into account the wider political and social environment.	It can possibly neglect other factors by focussing only on power relationships and may give the researcher a position that is too privileged.	Howcroft and Trauth[ ] Blakie[ ] Doolin[ , ]
Interprets the limiting conditions in relation to power and control that are thought to influence behaviour.		Bloomfield and Best[ ]
Involves understanding meanings/contexts and processes as perceived from different perspectives, trying to understand individual and shared social meanings. Focus is on theory building.	Often difficult to explain unintended consequences and for neglecting surrounding historical contexts	Stake[ ] Doolin[ ]
Involves establishing which variables one wishes to study in advance and seeing whether they fit in with the findings. Focus is often on testing and refining theory on the basis of case study findings.	It does not take into account the role of the researcher in influencing findings.	Yin[ , , ] Shanks and Parr[ ]

How are case studies conducted?

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 ]

	Clarity: Does the proposal read well?
	Integrity: Do its pieces fit together?
	Attractiveness: Does it pique the reader's interest?
	The case: Is the case adequately defined?
	The issues: Are major research questions identified?
	Data Resource: Are sufficient data sources identified?
	Case Selection: Is the selection plan reasonable?
	Data Gathering: Are data-gathering activities outlined?
	Validation: Is the need and opportunity for triangulation indicated?
	Access: Are arrangements for start-up anticipated?
	Confidentiality: Is there sensitivity to the protection of people?
	Cost: Are time and resource estimates reasonable?

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.

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.

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 ].

Analysing, interpreting and reporting case studies

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 ].

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

Potential pitfall	Mitigating action
Selecting/conceptualising the wrong case(s) resulting in lack of theoretical generalisations	Developing in-depth knowledge of theoretical and empirical literature, justifying choices made
Collecting large volumes of data that are not relevant to the case or too little to be of any value	Focus data collection in line with research questions, whilst being flexible and allowing different paths to be explored
Defining/bounding the case	Focus on related components (either by time and/or space), be clear what is outside the scope of the case
Lack of rigour	Triangulation, respondent validation, the use of theoretical sampling, transparency throughout the research process
Ethical issues	Anonymise appropriately as cases are often easily identifiable to insiders, informed consent of participants
Integration with theoretical framework	Allow for unexpected issues to emerge and do not force fit, test out preliminary explanations, be clear about epistemological positions in advance

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

1. Is this report easy to read?

2. Does it fit together, each sentence contributing to the whole?

3. Does this report have a conceptual structure (i.e. themes or issues)?

4. Are its issues developed in a series and scholarly way?

5. Is the case adequately defined?

6. Is there a sense of story to the presentation?

7. Is the reader provided some vicarious experience?

8. Have quotations been used effectively?

9. Are headings, figures, artefacts, appendices, indexes effectively used?

10. Was it edited well, then again with a last minute polish?

11. Has the writer made sound assertions, neither over- or under-interpreting?

12. Has adequate attention been paid to various contexts?

13. Were sufficient raw data presented?

14. Were data sources well chosen and in sufficient number?

15. Do observations and interpretations appear to have been triangulated?

16. Is the role and point of view of the researcher nicely apparent?

17. Is the nature of the intended audience apparent?

18. Is empathy shown for all sides?

19. Are personal intentions examined?

20. Does it appear individuals were put at risk?

Conclusions

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

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Enhancing space management through digital twin: a case study of the lazio region headquarters.

1. Introduction

1.1. advanced digital technologies, 1.2. space management in smart working adoption, 2. materials and methods.

Variations due to the active interaction of occupants with building systems. The active interaction of occupants with building energy systems is a complex mechanism, where numerous parameters, including the number of occupants, occupant behavior, type of space, type of work, day, and time, exert a significant influence. The aforementioned parameters can be classified into three distinct groups: temporal, spatial, and occupancy. Temporal parameters indicate the time scale, while spatial parameters indicate spatial information. Occupancy parameters, on the other hand, indicate occupant behavior. It can be reasonably argued that psychological and sociological aspects exert a considerable influence on occupant behavior. Given the inherent unpredictability of occupants’ behavior, it remains challenging to identify any specific circumstances that may influence the consumption of energy. This uncertainty has a significant impact on the indoor environment, which in turn contributes to the observed variations in energy consumption. Other factors that influence occupants’ behavior include temperature, humidity, illuminance factor, and several others, which collectively affect the building’s energy consumption. The most common forms of occupant behavior are adjusting the thermostat, dimming the lighting, switching off lights, and using electronic devices.
Variations due to the passive interaction of occupants with building systems. Passive interaction depends on the presence of occupants, reported as hours of occupancy in the building, and the absence of occupants, reported as hours of unoccupied building operation. It is possible that there is inefficient operation of the electrical and mechanical systems, which would result in high energy wastage during the unoccupied/occupied hours; this issue was further investigated to estimate the amount of energy wasted during unoccupied hours, with between 26% and 65% of energy being used during unoccupied/occupied hours, compared to working hours between 7.30 a.m. and 5 p.m. Of the total consumption, between 19% and 28% (mainly electricity and HVAC) is used during the weekend when the building is unoccupied [ 44 ].

2.1. Methodology

Space analysis via the BIM model: Through the use of IoT sensors, which can be easily installed and configured, it is possible to start the occupancy assessment process. - Use analysis: Evaluation of office space use to identify inefficiencies or cases of overutilization. - Occupancy measurement: Determine the occupancy percentage for each floor, with a detailed map of space use.
Space analysis and management (statistics): Using data obtained from a dedicated booking application, through the utilization of BIM-integrated software, facilitates the examination of the actual use of workspaces, with the objective of optimizing their management. The specific objectives are as follows: - Presence forecasting: Estimating building occupancy over the next 30 days based on historical booking data, allowing better maintenance services and the anticipation of space and resource requirements. - Savings analysis: Quantification of potential maintenance cost savings through appropriate operational downsizing. By analyzing space utilization, it is possible to identify areas that can be consolidated or downsized, thus reducing operating costs. - Duration of bookings: Calculation of the average duration of room bookings to optimize space availability. Knowing the typical duration of bookings allows you to better plan the use of meeting rooms, avoiding overlaps and improving efficiency in resource allocation. - Temporal assessment of room use: Examination of meeting room usage by time of day and day of the week and the identification of high- and low-occupancy periods. This provides a better understanding of space utilization patterns, allowing for more flexible and adaptive management.
Insight and automated alerts: Provide automatic alerts to the building manager [ 55 ] to improve space management [ 56 ]. These alerts signal when there is a high probability that a particular floor or the entire building will reach 100% occupancy on a particular day or period, allowing for more efficient planning of the necessary resources.
Machine learning: This stage uses ML to make reliable predictions and generate insights [ 57 ], going beyond the traditional programming approach [ 58 ]. The system learns from the relationships between data and outcomes, identifying patterns and connections that may not be obvious to human intelligence [ 59 ]. This ‘knowledge discovery’ process not only provides useful results, but can also reveal new, previously unknown/ignored/unexpected information.

2.1.1. Analysis of Spaces via the BIM Model—Phase 1

2.1.2. optimizing space management through data analysis (statistics)—phase 2, 2.1.3. insight and automatic alarms—phase 3, 2.1.4. machine learning for enhanced predictive insights—phase 4, 3. results and discussion, 3.1. case study: lazio region headquarters, 3.2. digital transformation in modern work environments, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Click here to enlarge figure

Floor	Available Stations	Maximum Detected	Unused Stations
0	50	36	14
1	120	104	16
2	120	105	15
3	120	97	23
4	120	102	18
5	120	88	32
6	120	91	29
7	120	106	14
8	120	78	42
9	120	58	62
10	120	66	54
11	120	60	60
Total	1370	991	379

	ANTE, 28.600 m				POST, 20.800 m
	kWh/Year	MWh/Year	Costs [EUR/Year]	t CO /Year	kWh/Year	MWh/Year	Costs [EUR/Year]	t CO /Year
Lighting, electrical devices	400,400.00	400.40	100,100.00	774.77	291,200.00	291.20	72,800.00	563.47
Domestic hot water	286,000,00	286.00	100,100.00	27.17	208,000.00	208.00	72,800.00	19.76
Cooling	143,000,00	143.00	35,750.00	774.77	104,000.00	104.00	26,000.00	563.47
Heating	1,115,400.00	1115.40	278,850.00	774.77	811,200.00	811.20	202,800.00	563.47
Total	1,944,800.00	1944.80	514,800.00	2351.49	1,414,400.00	1414.40	374,400.00	1710.18

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Piras, G.; Muzi, F.; Tiburcio, V.A. Enhancing Space Management through Digital Twin: A Case Study of the Lazio Region Headquarters. Appl. Sci. 2024 , 14 , 7463. https://doi.org/10.3390/app14177463

Piras G, Muzi F, Tiburcio VA. Enhancing Space Management through Digital Twin: A Case Study of the Lazio Region Headquarters. Applied Sciences . 2024; 14(17):7463. https://doi.org/10.3390/app14177463

Piras, Giuseppe, Francesco Muzi, and Virginia Adele Tiburcio. 2024. "Enhancing Space Management through Digital Twin: A Case Study of the Lazio Region Headquarters" Applied Sciences 14, no. 17: 7463. https://doi.org/10.3390/app14177463

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Experimental analysis of dust’s impact on solar photovoltaic system efficiency in arid environments: a case study in Southern Algeria

Research Article
Published: 26 August 2024

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Zineb Chaich ORCID: orcid.org/0000-0002-9325-4776 1 ,
Djamel Belatrache 2 ,
Abdelmadjid Dobbi 1 &
Souad Hadjadj 1

The purpose of this study is to explore the effects of accumulated dust and weather conditions on the energy generated by solar photovoltaic panels in Ouargla, Algeria, between May 3 and August 3, 2023. For this experiment, two monocrystalline panels with a power output of 390 W manufactured by Zergoune Green Energy Company, as well as data-logging equipment, were used. The first panel was perfectly cleaned before starting every test and the second panel remained uncleaned. On day 90, the cleaned panel maintained an average power of 193 W, while the dusty panel exhibited a lower average power of 139 W. The greatest average reduction in efficiency, approximately 36.32%, occurred after 3 months of exposure to weather conditions. The scanning electron microscope (SEM) analysis demonstrates the existence of microscopic dust particles which prevent part of solar radiation away instead of being absorbed by the photovoltaic cells, leading to a drop in the efficiency of the PV module. The primary chemical elements found in dust are oxygen, silicon, aluminum, and magnesium.

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Environmental Chemistry

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Abbreviations

Cleaned panel

Dusty panel

Maximum current, A

Number of the independent variables

Maximum rated power of PV module, W

Solar radiation (W/m 2 )

Area (m 2 )

Temperature (°C)

Time (hour)

Maximum voltage

Uncertainty

Independent variables

Efficiency of system (%)

Efficiency reduction of the system (%)

Abada Z, Bouharkat M (2018) Study of management strategy of energy resources in Algeria. Energy Rep 4:1–7. https://doi.org/10.1016/j.egyr.2017.09.004

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Zineb Chaich, Abdelmadjid Dobbi & Souad Hadjadj

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Zineb Chaich: conceptualization, methodology, software and formal analysis, investigation, writing — original draft. Djamel Belatrache: conceptualization, methodology, formal analysis, writing — review and editing, supervision, project administration. Abdelmadjid Dobbi: conceptualization, methodology. Souad Hadjadj: writing — review and editing.

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• The effect of dust deposition on photovoltaic panel performance is examined under arid climate conditions.

• The impact of dust accumulation on the reduction in PV module efficiency over time was derived from the experimental results.

• An average decline of around 36.32% in solar PV panel performance after 3 months of outdoor exposure due to dust buildup.

• A chemical and physical analysis of dust collected from the surface of the solar PV panel was conducted.

• The primary chemical elements found in dust are oxygen, silicon, aluminum, and magnesium.

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Chaich, Z., Belatrache, D., Dobbi, A. et al. Experimental analysis of dust’s impact on solar photovoltaic system efficiency in arid environments: a case study in Southern Algeria. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-34776-8

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The case study approach

Introduction

What is a case study?

What are case studies used for?

How are case studies conducted?

Defining the case

Selecting the case(s)

Collecting the data

Analysing, interpreting and reporting case studies

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

Conclusions

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Acknowledgements

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