Four types: single holistic, single embedded, multiple holistic, multiple embedded
The post-positive paradigm postulates there is one reality that can be objectively described and understood by “bracketing” oneself from the research to remove prejudice or bias. 27 Yin focuses on general explanation and prediction, emphasizing the formulation of propositions, akin to hypothesis testing. This approach is best suited for structured and objective data collection 9 , 11 and is often used for mixed-method studies.
Constructivism assumes that the phenomenon of interest is constructed and influenced by local contexts, including the interaction between researchers, individuals, and their environment. 27 It acknowledges multiple interpretations of reality 24 constructed within the context by the researcher and participants which are unlikely to be replicated, should either change. 5 , 20 Stake and Merriam’s constructivist approaches emphasize a story-like rendering of a problem and an iterative process of constructing the case study. 7 This stance values researcher reflexivity and transparency, 28 acknowledging how researchers’ experiences and disciplinary lenses influence their assumptions and beliefs about the nature of the phenomenon and development of the findings.
A key tenet of case study methodology often underemphasized in literature is the importance of defining the case and phenomenon. Researches should clearly describe the case with sufficient detail to allow readers to fully understand the setting and context and determine applicability. Trying to answer a question that is too broad often leads to an unclear definition of the case and phenomenon. 20 Cases should therefore be bound by time and place to ensure rigor and feasibility. 6
Yin 22 defines a case as “a contemporary phenomenon within its real-life context,” (p13) which may contain a single unit of analysis, including individuals, programs, corporations, or clinics 29 (holistic), or be broken into sub-units of analysis, such as projects, meetings, roles, or locations within the case (embedded). 30 Merriam 24 and Stake 5 similarly define a case as a single unit studied within a bounded system. Stake 5 , 23 suggests bounding cases by contexts and experiences where the phenomenon of interest can be a program, process, or experience. However, the line between the case and phenomenon can become muddy. For guidance, Stake 5 , 23 describes the case as the noun or entity and the phenomenon of interest as the verb, functioning, or activity of the case.
Yin’s approach to a case study is rooted in a formal proposition or theory which guides the case and is used to test the outcome. 1 Stake 5 advocates for a flexible design and explicitly states that data collection and analysis may commence at any point. Merriam’s 24 approach blends both Yin and Stake’s, allowing the necessary flexibility in data collection and analysis to meet the needs.
Yin 30 proposed three types of case study approaches—descriptive, explanatory, and exploratory. Each can be designed around single or multiple cases, creating six basic case study methodologies. Descriptive studies provide a rich description of the phenomenon within its context, which can be helpful in developing theories. To test a theory or determine cause and effect relationships, researchers can use an explanatory design. An exploratory model is typically used in the pilot-test phase to develop propositions (eg, Sibbald et al. 31 used this approach to explore interprofessional network complexity). Despite having distinct characteristics, the boundaries between case study types are flexible with significant overlap. 30 Each has five key components: (1) research question; (2) proposition; (3) unit of analysis; (4) logical linking that connects the theory with proposition; and (5) criteria for analyzing findings.
Contrary to Yin, Stake 5 believes the research process cannot be planned in its entirety because research evolves as it is performed. Consequently, researchers can adjust the design of their methods even after data collection has begun. Stake 5 classifies case studies into three categories: intrinsic, instrumental, and collective/multiple. Intrinsic case studies focus on gaining a better understanding of the case. These are often undertaken when the researcher has an interest in a specific case. Instrumental case study is used when the case itself is not of the utmost importance, and the issue or phenomenon (ie, the research question) being explored becomes the focus instead (eg, Paciocco 32 used an instrumental case study to evaluate the implementation of a chronic disease management program). 5 Collective designs are rooted in an instrumental case study and include multiple cases to gain an in-depth understanding of the complexity and particularity of a phenomenon across diverse contexts. 5 , 23 In collective designs, studying similarities and differences between the cases allows the phenomenon to be understood more intimately (for examples of this in the field, see van Zelm et al. 33 and Burrows et al. 34 In addition, Sibbald et al. 35 present an example where a cross-case analysis method is used to compare instrumental cases).
Merriam’s approach is flexible (similar to Stake) as well as stepwise and linear (similar to Yin). She advocates for conducting a literature review before designing the study to better understand the theoretical underpinnings. 24 , 25 Unlike Stake or Yin, Merriam proposes a step-by-step guide for researchers to design a case study. These steps include performing a literature review, creating a theoretical framework, identifying the problem, creating and refining the research question(s), and selecting a study sample that fits the question(s). 24 , 25 , 36
Using multiple data collection methods is a key characteristic of all case study methodology; it enhances the credibility of the findings by allowing different facets and views of the phenomenon to be explored. 23 Common methods include interviews, focus groups, observation, and document analysis. 5 , 37 By seeking patterns within and across data sources, a thick description of the case can be generated to support a greater understanding and interpretation of the whole phenomenon. 5 , 17 , 20 , 23 This technique is called triangulation and is used to explore cases with greater accuracy. 5 Although Stake 5 maintains case study is most often used in qualitative research, Yin 17 supports a mix of both quantitative and qualitative methods to triangulate data. This deliberate convergence of data sources (or mixed methods) allows researchers to find greater depth in their analysis and develop converging lines of inquiry. For example, case studies evaluating interventions commonly use qualitative interviews to describe the implementation process, barriers, and facilitators paired with a quantitative survey of comparative outcomes and effectiveness. 33 , 38 , 39
Yin 30 describes analysis as dependent on the chosen approach, whether it be (1) deductive and rely on theoretical propositions; (2) inductive and analyze data from the “ground up”; (3) organized to create a case description; or (4) used to examine plausible rival explanations. According to Yin’s 40 approach to descriptive case studies, carefully considering theory development is an important part of study design. “Theory” refers to field-relevant propositions, commonly agreed upon assumptions, or fully developed theories. 40 Stake 5 advocates for using the researcher’s intuition and impression to guide analysis through a categorical aggregation and direct interpretation. Merriam 24 uses six different methods to guide the “process of making meaning” (p178) : (1) ethnographic analysis; (2) narrative analysis; (3) phenomenological analysis; (4) constant comparative method; (5) content analysis; and (6) analytic induction.
Drawing upon a theoretical or conceptual framework to inform analysis improves the quality of case study and avoids the risk of description without meaning. 18 Using Stake’s 5 approach, researchers rely on protocols and previous knowledge to help make sense of new ideas; theory can guide the research and assist researchers in understanding how new information fits into existing knowledge.
Columbia University has recently demonstrated how case studies can help train future health leaders. 41 Case studies encompass components of systems thinking—considering connections and interactions between components of a system, alongside the implications and consequences of those relationships—to equip health leaders with tools to tackle global health issues. 41 Greenwood 42 evaluated Indigenous peoples’ relationship with the healthcare system in British Columbia and used a case study to challenge and educate health leaders across the country to enhance culturally sensitive health service environments.
An important but often omitted step in case study research is an assessment of quality and rigour. We recommend using a framework or set of criteria to assess the rigour of the qualitative research. Suitable resources include Caelli et al., 43 Houghten et al., 44 Ravenek and Rudman, 45 and Tracy. 46
Although “pragmatic” case studies (ie, utilizing practical and applicable methods) have existed within psychotherapy for some time, 47 , 48 only recently has the applicability of pragmatism as an underlying paradigmatic perspective been considered in HSR. 49 This is marked by uptake of pragmatism in Randomized Control Trials, recognizing that “gold standard” testing conditions do not reflect the reality of clinical settings 50 , 51 nor do a handful of epistemologically guided methodologies suit every research inquiry.
Pragmatism positions the research question as the basis for methodological choices, rather than a theory or epistemology, allowing researchers to pursue the most practical approach to understanding a problem or discovering an actionable solution. 52 Mixed methods are commonly used to create a deeper understanding of the case through converging qualitative and quantitative data. 52 Pragmatic case study is suited to HSR because its flexibility throughout the research process accommodates complexity, ever-changing systems, and disruptions to research plans. 49 , 50 Much like case study, pragmatism has been criticized for its flexibility and use when other approaches are seemingly ill-fit. 53 , 54 Similarly, authors argue that this results from a lack of investigation and proper application rather than a reflection of validity, legitimizing the need for more exploration and conversation among researchers and practitioners. 55
Although occasionally misunderstood as a less rigourous research methodology, 8 case study research is highly flexible and allows for contextual nuances. 5 , 6 Its use is valuable when the researcher desires a thorough understanding of a phenomenon or case bound by context. 11 If needed, multiple similar cases can be studied simultaneously, or one case within another. 16 , 17 There are currently three main approaches to case study, 5 , 17 , 24 each with their own definitions of a case, ontological and epistemological paradigms, methodologies, and data collection and analysis procedures. 37
Individuals’ experiences within health systems are influenced heavily by contextual factors, participant experience, and intricate relationships between different organizations and actors. 55 Case study research is well suited for HSR because it can track and examine these complex relationships and systems as they evolve over time. 6 , 7 It is important that researchers and health leaders using this methodology understand its key tenets and how to conduct a proper case study. Although there are many examples of case study in action, they are often under-reported and, when reported, not rigorously conducted. 9 Thus, decision-makers and health leaders should use these examples with caution. The proper reporting of case studies is necessary to bolster their credibility in HSR literature and provide readers sufficient information to critically assess the methodology. We also call on health leaders who frequently use case studies 56 – 58 to report them in the primary research literature.
The purpose of this article is to advocate for the continued and advanced use of case study in HSR and to provide literature-based guidance for decision-makers, policy-makers, and health leaders on how to engage in, read, and interpret findings from case study research. As health systems progress and evolve, the application of case study research will continue to increase as researchers and health leaders aim to capture the inherent complexities, nuances, and contextual factors. 7
Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization.
According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.
Explanatory case studies aim to answer ‘how’ or ’why’ questions with little control on behalf of researcher over occurrence of events. This type of case studies focus on phenomena within the contexts of real-life situations. Example: “An investigation into the reasons of the global financial and economic crisis of 2008 – 2010.”
Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Studies in business research belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena. Example: “Impact of increasing levels of multiculturalism on marketing practices: A case study of McDonald’s Indonesia.”
Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc. Example: “A study into differences of leadership practices between private and public sector organizations in Atlanta, USA.”
Advantages of case study method include data collection and analysis within the context of phenomenon, integration of qualitative and quantitative data in data analysis, and the ability to capture complexities of real-life situations so that the phenomenon can be studied in greater levels of depth. Case studies do have certain disadvantages that may include lack of rigor, challenges associated with data analysis and very little basis for generalizations of findings and conclusions.
John Dudovskiy
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Learning objectives.
There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions; to extensive, in-depth interviews; to well-controlled experiments.
The three main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. It aims to determine if one variable directly impacts and causes another. Correlational and experimental research both typically use hypothesis testing, whereas descriptive research does not.
Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While surveys allow results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While existing records can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected.
Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later, there is a tremendous amount of control over variables of interest. While performing an experiment is a powerful approach, experiments are often conducted in very artificial settings, which calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.
The three main types of descriptive studies are case studies, naturalistic observation, and surveys.
Psychologists can use a detailed description of one person or a small group based on careful observation. Case studies are intensive studies of individuals and have commonly been seen as a fruitful way to come up with hypotheses and generate theories. Case studies add descriptive richness. Case studies are also useful for formulating concepts, which are an important aspect of theory construction. Through fine-grained knowledge and description, case studies can fully specify the causal mechanisms in a way that may be harder in a large study.
Sigmund Freud developed many theories from case studies (Anna O., Little Hans, Wolf Man, Dora, etc.). F or example, he conducted a case study of a man, nicknamed “Rat Man,” in which he claimed that this patient had been cured by psychoanalysis. T he nickname derives from the fact that among the patient’s many compulsions, he had an obsession with nightmarish fantasies about rats.
Today, more commonly, case studies reflect an up-close, in-depth, and detailed examination of an individual’s course of treatment. Case studies typically include a complete history of the subject’s background and response to treatment. From the particular client’s experience in therapy, the therapist’s goal is to provide information that may help other therapists who treat similar clients.
Case studies are generally a single-case design, but can also be a multiple-case design, where replication instead of sampling is the criterion for inclusion. Like other research methodologies within psychology, the case study must produce valid and reliable results in order to be useful for the development of future research. Distinct advantages and disadvantages are associated with the case study in psychology.
A commonly described limit of case studies is that they do not lend themselves to generalizability . The other issue is that the case study is subject to the bias of the researcher in terms of how the case is written, and that cases are chosen because they are consistent with the researcher’s preconceived notions, resulting in biased research. Another common problem in case study research is that of reconciling conflicting interpretations of the same case history.
Despite these limitations, there are advantages to using case studies. One major advantage of the case study in psychology is the potential for the development of novel hypotheses of the cause of abnormal behavior for later testing. Second, the case study can provide detailed descriptions of specific and rare cases and help us study unusual conditions that occur too infrequently to study with large sample sizes. The major disadvantage is that case studies cannot be used to determine causation, as is the case in experimental research, where the factors or variables hypothesized to play a causal role are manipulated or controlled by the researcher.
Some well-known case studies that related to abnormal psychology include the following:
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?
This is very similar to the phenomenon mentioned earlier in this module: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about handwashing, we have other options available to us.
Suppose we send a researcher to a school playground to observe how aggressive or socially anxious children interact with peers. Will our observer blend into the playground environment by wearing a white lab coat, sitting with a clipboard, and staring at the swings? We want our researcher to be inconspicuous and unobtrusively positioned—perhaps pretending to be a school monitor while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).
It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. For example, psychologists have spent weeks observing the behavior of homeless people on the streets, in train stations, and bus terminals. They try to ensure that their naturalistic observations are unobtrusive, so as to minimize interference with the behavior they observe. Nevertheless, the presence of the observer may distort the behavior that is observed, and this must be taken into consideration (Figure 1).
The greatest benefit of naturalistic observation is the validity, or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.
The major downside of naturalistic observation is that they are often difficult to set up and control. Although something as simple as observation may seem like it would be a part of all research methods, participant observation is a distinct methodology that involves the researcher embedding themselves into a group in order to study its dynamics. For example, Festinger, Riecken, and Shacter (1956) were very interested in the psychology of a particular cult. However, this cult was very secretive and wouldn’t grant interviews to outside members. So, in order to study these people, Festinger and his colleagues pretended to be cult members, allowing them access to the behavior and psychology of the cult. Despite this example, it should be noted that the people being observed in a participant observation study usually know that the researcher is there to study them. [1]
Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.
Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population.
There is both strength and weakness in surveys when compared to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.
Another potential weakness of surveys is something we touched on earlier in this module: people do not always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.
Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the U.S. Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).
Research has shown that parental depressive symptoms are linked to a number of negative child outcomes. A classmate of yours is interested in the associations between parental depressive symptoms and actual child behaviors in everyday life [2] because this associations remains largely unknown. After reading this section, what do you think is the best way to better understand such associations? Which method might result in the most valid data?
clinical or case study: observational research study focusing on one or a few people
correlational research: tests whether a relationship exists between two or more variables
descriptive research: research studies that do not test specific relationships between variables; they are used to describe general or specific behaviors and attributes that are observed and measured
experimental research: tests a hypothesis to determine cause-and-effect relationships
generalizability: inferring that the results for a sample apply to the larger population
inter-rater reliability: measure of agreement among observers on how they record and classify a particular event
naturalistic observation: observation of behavior in its natural setting
observer bias: when observations may be skewed to align with observer expectations
population: overall group of individuals that the researchers are interested in
sample: subset of individuals selected from the larger population
survey: list of questions to be answered by research participants—given as paper-and-pencil questionnaires, administered electronically, or conducted verbally—allowing researchers to collect data from a large number of people
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Ever wondered why the case study method is so popular in fields like business, psychology, and education? It’s because case studies offer a unique way to dive deep into real-world scenarios, allowing you to explore complex issues in a detailed manner. By examining specific instances, you gain insights that are often missed in broader surveys or theoretical research.
But like any other research method, the case study approach has its pros and cons. While it provides in-depth understanding and rich qualitative data, it can also be time-consuming and sometimes lacks generalizability. So, how do you decide if it’s the right method for your research? Let’s explore the advantages and disadvantages to help you make an informed choice.
Curious about how the case study method can enhance your entrepreneurial journey? Let’s break it down.
A case study is an in-depth investigation of a single entity, such as an individual, group, organization, or event. By focusing on real-life contexts, it provides comprehensive insights that can unveil unique patterns typically missed by broader research methods. This method involves a mix of qualitative and quantitative data collection techniques, including interviews, observations, and document analysis.
Researchers use case studies extensively across various fields due to their flexibility and depth of analysis. In business, they help you understand market trends, customer behavior, and effective strategies by examining real-life examples. Successful startups often serve as case studies, providing valuable lessons for budding entrepreneurs. In education, case studies contextualize theories, making learning more relatable. In psychology, they offer detailed explorations of specific issues or treatments, which can inform broader practices.
The case study method stands out in business and entrepreneurial research, offering in-depth insights and practical lessons.
You gather comprehensive data through case studies, using techniques like interviews, observations, and document reviews. By employing both qualitative and quantitative methods, you gain a thorough understanding of real-world applications and business strategies. This approach lets you explore each aspect of a business scenario, providing detailed evidence for your insights.
Case studies reveal unique patterns and hidden details often missed by broader research methods. When you analyze a successful startup, you uncover specific strategies that contributed to its success. This method helps you understand the context behind decisions, market conditions, and customer behavior, offering actionable insights for your entrepreneurial endeavors. By focusing on the nuances, you can apply these learnings to your own business and side-hustles, refining your strategies for better outcomes.
Despite the many advantages, the case study method also presents several challenges that can impact its effectiveness in business contexts.
Case studies provide in-depth insights into specific scenarios; however, they often lack broad applicability. When focusing on a single business or entrepreneur, findings may not represent the experiences of others. For instance, a strategy that worked for a particular online startup might not yield the same results for a different venture due to varying market conditions and business models. Limited sample sizes in case studies further constrain their generalizability, making it difficult to formulate universal conclusions or industry-wide trends.
Conducting case studies requires significant time and effort. Collecting data through interviews, observations, and document reviews can be particularly exhaustive. As an entrepreneur juggling multiple side-hustles, dedicating time to such detailed research might detract from hands-on activities that directly impact your business. Long research durations also delay the availability of insights, making them less timely or relevant in rapidly evolving market conditions. This time-intensive nature can be a deterrent, especially when quick decision-making and agility are crucial for business success.
For entrepreneurs and business enthusiasts like you, the case study method offers a way to dive deep into specific business scenarios. It’s a powerful tool, but it has both benefits and challenges.
Use the case study method when you need detailed, practical insights. This method works well when exploring unique business models, understanding specific customer behaviors, or examining the success strategies of other startups. Large-scale statistics can’t capture the nuances you get from a focused case study.
To mitigate the limitations of case studies, employ these strategies:
These strategies help you get the most out of the case study method while addressing common drawbacks.
The case study method offers a unique way to gain in-depth insights and analyze complex scenarios in various fields. While it has its challenges like time consumption and limited generalizability you can still leverage its strengths by using diverse sources and effective time management. Collaborating with others can also help you make the most out of your case studies. By understanding when and how to use this method you’ll be better equipped to harness its full potential for your business or research endeavors.
What are the primary benefits of the case study method in business.
The case study method offers detailed insights, helps analyze market trends, and understands customer behavior through both qualitative and quantitative data collection techniques.
The case study method is popular in business, psychology, and education for its ability to provide comprehensive and detailed insights.
The main disadvantages include limitations in generalizability and the time-consuming nature of conducting in-depth research.
Businesses can mitigate limitations by diversifying their data sources, managing research time effectively, and collaborating with others to enhance the quality and applicability of their case studies.
Entrepreneurs and business enthusiasts should choose the case study method when they need detailed, qualitative insights that cannot be captured through other research methods.
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A case study on children’s accessibility in urban parks in changsha city, china: developing an improved 2sfca method.
2. literature review, 2.1. children’s accessibility, 2.2. accessibility assessment, 2.3. enhancements to the 2sfca method, 3. methodology: the enhanced 2sfca method based on supply and demand, 3.1. enhancement of supply, 3.2. enhancement of demand, 3.3. spatial accessibility to parks, 4. materials, 4.1. study area, 4.2. data sources and data processing, 5.1. evaluation of park accessibility, 5.2. k-nearest neighbor analysis, 6. discussions, 6.1. research novelty, 6.2. research implications, 6.2.1. relationship between economic development and green space, 6.2.2. multidimensional assessment of green space, 6.2.3. differences in park demand between high-density and low-density areas, 6.2.4. enhancing park design for chlidren engagement and activity, 6.3. research limitations, 7. conclusions, author contributions, data availability statement, conflicts of interest.
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Method | Author(s) | Characteristics | Advantages | Disadvantages | Application Area |
---|---|---|---|---|---|
Buffer Analysis | Bertram et al. (2015) [ ] | Simple calculation | Simple calculation | Ignores the suppressive effects of spatial road networks | Green space accessibility |
Gravity Model | Xia et al.(2018) [ ]; Xia et al. (2022) [ ]; Chang et al. (2011) [ ] | Provides a comprehensive method for calculating park area and distance | Considers both distance and park area | Different metrics are chosen | Green space accessibility |
Network Analysis | Wolff(2021) [ ] | Depends on a complete traffic system network with complex calculations | Accurate results | Depends on a complete traffic system network, complex calculations | Transportation accessibility |
2SFCA | Radke et al. (2000) [ ]; Wu et al. (2020) [ ]; Luo et al. (2003) [ ] | Considers facility supply capacity, resident demand, and spatial impedance, facilitating accessibility calculation | Considers facility supply capacity, resident demand, and spatial impedance, facilitating accessibility calculation | Ignores distance decay effects and actual resistance within the catchment area | Green space accessibility, medical facility accessibility, commercial facility accessibility |
Gaussian Two-Step Floating Catchment Area (G2SFCA) | Dai (2010) [ ]; Xiao et al. (2021) [ ]; Dong et al. (2022) [ ] | Introduces Gaussian function, optimizes the 2SFCA method, considers different spatial decay rules and diverse transportation modes | Improves accessibility calculation accuracy, considers different spatial decay rules and diverse transportation modes | Requires consideration of different spatial decay rules and diverse transportation modes | Medical facility accessibility, commercial facility accessibility, urban open space accessibility |
Improvement Aspect | Method | Proposer(s) | Characteristics | Description |
---|---|---|---|---|
Distance Decay Problem | E2SFCA | Luo et al. (2009) [ ] | Time Interval Segmentation | Divides service areas into multiple time intervals and assigns different weights. |
G2SFCA | Dai (2010) [ ] | Gaussian Function | Uses a Gaussian function to assess potential accessibility, with a continuously decreasing supply–demand ratio based on distance. | |
KD2SFCA | Dai (2011) [ ] | Kernel Density Function | Uses a kernel density function to assess potential accessibility, with a continuously decreasing supply-demand ratio based on distance. | |
E2SFCA | Kanuganti et al. (2016) [ ] | Distance Decay Impedance Function | Introduces a distance decay impedance function to distinguish the accessibility of medical services in rural areas. | |
Search Radius Extension | V2SFCA | Luo et al. (2012) [ ] | Variable Search Radius | Adjusts the search radius to cover a sufficient supply–demand scale. |
D2SFCA | McGrail et al. (2014) [ ] | Dynamic Search Radius | Sets different search radii based on regional population density. | |
MC2SFCA | Tao et al. (2014) [ ] | Multiple Service Area Radii | Sets different search radii based on the scale of public facilities. | |
Supply and Demand Quantification | VFCA | Dony et al. (2015) [ ] | Variable Width FCA | Calculates attraction coefficients based on park size and facilities but does not consider competition between service sites. |
3SFCA | Wan et al. (2012) [ ] | Three-Step Floating Catchment Area Method | Reduces the overestimation of population demand by dividing service areas into several sub-zones and assigning Gaussian weights. | |
Huff Model FCA | Luo (2014) [ ] | Huff Model | Quantifies demand by expressing the probability of service choice. | |
i2SFCA | Wang (2018) [ ] | Inverse 2SFCA | Extends from the Huff model to capture the “congestion” of facilities. | |
Multiple Transportation Modes | MM2SFCA | Mao et al. (2013) [ ]; Xing et al. (2018) [ ] | Multiple Transportation Modes | Traditional 2SFCA methods consider multiple transportation modes using weighted average travel time. |
CB2SFCA | Fransen et al. (2015) [ ] | Commuting-Based 2SFCA | Assumes that demand is not fixed but varies according to commuting behavior. |
Categories | Variables | Maximum Value |
---|---|---|
Playground number | 2 | |
Sport fields | 2 | |
Sport courts | 2 | |
Hiking and walking trails | 1 | |
Public swimming pool | 1 | |
Supporting facilities | 2 | |
Ornamental water features | 1 | |
Recreational water features | 1 | |
Entrances | 1 | |
Boundaries | 1 | |
Supervision areas | 1 | |
Available for all age groups | 1 |
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
Liao, Y.; Furuya, K. A Case Study on Children’s Accessibility in Urban Parks in Changsha City, China: Developing an Improved 2SFCA Method. Land 2024 , 13 , 1522. https://doi.org/10.3390/land13091522
Liao Y, Furuya K. A Case Study on Children’s Accessibility in Urban Parks in Changsha City, China: Developing an Improved 2SFCA Method. Land . 2024; 13(9):1522. https://doi.org/10.3390/land13091522
Liao, Yuhui, and Katsunori Furuya. 2024. "A Case Study on Children’s Accessibility in Urban Parks in Changsha City, China: Developing an Improved 2SFCA Method" Land 13, no. 9: 1522. https://doi.org/10.3390/land13091522
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Bibliometrics & citations, view options, 1 introduction, 2.1 powerwash simulator, 2.2 participants, 2.3 measures, 2.4 data analysis.
Variable | Estimate |
---|---|
Pre-play | 0.749 (0.745, 0.753) |
During play | 0.783 (0.779, 0.787) |
Difference | 0.034 (0.032, 0.036) |
Difference (scaled) | 0.073 (0.069, 0.078) |
(SD) Difference | 0.058 (0.056, 0.060) |
Positive shifts | 72.1% (70.8%, 73.5%) |
3.3 rq3: time course of mood changes during play.
4.1 limitations, 4.2 conclusion, data and material availability, author contributions, declaration of conflicting interests, supplementary material, index terms.
Human-centered computing
Human computer interaction (HCI)
HCI theory, concepts and models
Is cheating a human function the roles of presence, state hostility, and enjoyment in an unfair video game.
In sports and board games, when an opponent cheats, the other players typically greet it with disdain, anger, and disengagement. However, work has yet to fully address the role of the computer cheating in video games. In this study, participants played ...
The present study explores the relation among different characteristics of preadolescents and their video game habits and preferences. Specifically, the predictive power of age, gender, and psychological adjustment on time spent playing video games and ...
Despite enormous resource investment, researchers lack consensus on seemingly simple questions about how video games affect players. Topics such as violent games and aggression, playtime and wellbeing, and more are characterized by deeply divided opinions ...
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Roblox/Edinburgh Napier U, USA
Association for Computing Machinery
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September 18, 2024
Ian Barlow, Sandeep Pai, Rishi Kishore, Deeksha Pande | September 2024
Executive summary.
Coal production and consumption are under pressure worldwide. This pressure is largely due to the need to address climate change, or concerns about coal’s economic viability, or both. In the United States, coal production has fallen by 47% since 2001 owing in large part to competition from natural gas and renewables.1 In India, a commitment to coal phase-down has been made, but its production and consumption continue to grow rapidly to meet development needs—conservative estimates put annual coal production at 1.3 billion tons by 2030, i.e. a 300 million ton increase in current production levels.2
Addressing climate change successfully may require shuttering hundreds of coal mines and power plants globally, affecting coal-reliant communities on an unprecedented scale. For these communities, managing the sector’s decline is an enormous—and often existential—undertaking.
To address this challenge, policymakers and scholars worldwide have proposed and enacted frameworks and mechanisms for a ‘just transition’ of coal-reliant communities, to mitigate the economic losses of coal decline. Diversification of coal-dependent economies is a goal often included in these just transition proposals meant to reduce coal dependencies and create more local economic resilience.
Economic diversification is generally enabled through economic development, which includes activities ranging from redeveloping legacy infrastructure for prospective investments to increasing literacy for local workforce readiness. These activities can both help attract new sectors to a community and expand smaller pre-existing ones.
Focusing on three local regions (counties/districts) each in the United States and India, we conducted a mixed-methods study to understand the scale and type of coal dependencies in these local regions, and economic diversification options for the future.
Based on the study, we have several recommendations for advancing just transition understanding and policy work:
1. Governments, philanthropies, academia, international organizations, and civil society need to holistically consider coal dependencies when navigating just transition. How the coal sector is integrated in communities varies substantially. These dependencies differ spatially, by degree, and by type. While all case studies show a dependence on the coal industry for employment and government revenues, the degree of dependence for either varies considerably. Other dependencies also vary; for example, in India informal coal jobs are prominent in some communities, but this is not the case in the United States. Holistic consideration of the coal industry’s role in these communities can help foster more robust transition planning and management that account for essential, though perhaps less obvious, impacts.
2.Governments, philanthropies, academia, international organizations, and civil society should support long-term economic diversification beyond the energy sector. Coal decline in coal-reliant communities is experienced acutely as an economic issue. Non-energy sector alternatives to coal may prove as or more beneficial to these communities, leading to a local economic future beyond or separate from energy. Funders should foster activities beyond greenhouse gas emissions mitigation in communities transitioning away from coal. Transition funding should support broader economic development activities that can help these communities diversify beyond clean energy deployment and repurposing of fossil fuel assets for alternative uses within the energy sector.
3. Governments, philanthropies, IGOs, and other funders should increase longer-term funding opportunities for development activities that foster diversification. Strategies can take a decade or more to bear fruit, thus making stable funding a huge boon to diversification efforts. Funding should not only be made available for clean energy projects. Our analysis shows that communities across the United States and India aspire to diversify into sectors ranging from tourism to food products. Activities destined to help coal-reliant communities should involve programming or funding that is guaranteed over longer periods, in order to help foster stability in the community’s transition efforts.
4. More research is needed by academia, state governments, IGOs, philanthropic organizations, and other stakeholders into finding suitable transition sectors for coal communities. Interviewees and discussants identified sectors in each case study—from pisciculture to data centers—based on local assets, existing sectors, or government incentives; however, whether these sectors can fill the socio-economic gaps left by coal decline is not well understood. More research is needed to determine which sectors would be best suited for coal communities both in terms of filling the gaps left by coal decline, a community’s unique characteristics, and its local assets. Additionally, research should be conducted into balancing sector-specific development efforts with broader economic development activities, given limited resources and to avoid risks of unduly targeting specific sectors.
5. State and national governments should help localities holistically define, track, and assess economic diversification at the local level. There is no universal definition for diversification at the local level. Providing a data-driven, multivariate definition and evaluation of diversification would help communities and external supporters chart a path toward economic diversification at the local level.
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The MA in Research Methods (Developmental Psychology) is an ESRC-accredited Social Sciences & Health Faculty degree in which departments from across the University work together to deliver a tailored study programme that explores human development through a research lens.
It is primarily designed for students who plan to continue their graduate studies at PhD level in the broad area of developmental psychology or work as a research psychologist. It is also relevant for students wishing to pursue careers in applied areas, such as clinical or educational psychology.
Students intending to have a career as a research psychologist need to acquire a high level of research skills at postgraduate level. Research methods training, co-ordinated through the Durham Research Methods Centre, therefore forms a central part of the MA course, including both quantitative and qualitative research methods. One third of the course is also devoted to the dissertation which may be carried out in any area of psychology related to development. The taught course modules include both generic and subject level components, providing an introduction to broad issues and methodological approaches in developmental psychology and the social sciences.
Core modules:.
Interdisciplinary Perspectives and Practices Across Social Research introduces the areas of contemporary social scientific research practice. You will develop an understanding of the intersection where philosophical, methodological and disciplinary contexts meet, including qualitative, quantitative, statistical, computational and historical programmes of research. You will also explore the various issues involved in the application of these methods inside and outside academia and will consider the ethical issues involved such as power and equality.
Qualitative Methods and Analysis supports your preparation for conducting qualitative research equipping you with the knowledge and skills to understand and appraise qualitative social sciences research, including different approaches to research and design and the analysis of qualitative data.
Advanced Developmental Psychology Review teaches the skills to create and deliver literature reviews as well as providing analysis of key topics in the field of developmental psychology, including research skills, data handling, writing styles and methods of presentation.
Research Design in Child and Clinical Psychology provides an introduction to the methods and design used in child and clinical psychology and offers practical training in the transferable skills relevant for professional and personal development.
Current Issues in Developmental Psychology and Psychopathology provides in-depth knowledge of current theoretical stances and methodological issues within the fields of developmental psychology and neurodiversity. The aim is for you to gain a broad understanding of typical development and then consider different development pathways.
Quantitative Methods and Analysis develops your knowledge, critical understanding and skills in quantitative data analysis and teaches you how to use statistical techniques for exploration and description of data sets. You will also learn how to make appropriate statistical inferences about associations between social phenomena.
Advanced Statistics for Psychology and the Behavioural Sciences teaches you a set of advanced statistical methods that are used across psychology and the behavioural sciences, equipping you with the skills to confidently identify appropriate statistical techniques and analyse data using relevant software across a range of different types of research.
The Dissertation enables you to design, implement, analyse and finally discuss an empirical project relevant to your field of study, giving you the opportunity to apply the theoretical knowledge you have acquired and to gain experience of collaborating with other researchers and undertaking research and project management. The Department provides excellent support and opportunities for conducting a significant piece of independent research.
The course is delivered through a mixture of lectures, seminars and practical classes. Lectures provide key information on a particular topic, such as social and emotional development. Seminars are held in order that smaller group teaching can take place, with focused discussion on specific topics. Finally, practical and workshop classes allow you to gain direct experience, particularly in how to use statistical tools.
The balance of this type of activity varies as a function of the module. This is a one year course, with students having the summer term to work on dissertation related activities. You will typically attend approximately 12 hours a week comprising lectures, tutorials and seminars. Outside timetabled contact hours, you are also expected to undertake your own independent study to prepare for your classes and broaden your subject knowledge, as well as conduct your dissertation. Independent study is a key element to the course, with complex factors raised in lectures that do assume some prior knowledge of the topic area.
The course is divided into three parts. One third, comprising three modules, is of subject specific topics related to developmental psychology and developmental psychopathology, including issues relevant to clinical/ educational work throughout development. Across these modules, the material is delivered via a combination of lectures, seminars, practical workshops and discussions.
A further three modules focus on placing psychology in the larger framework of social science research and providing generic research skills, for example, qualitative and quantitative analysis skills.
The final third of the course is the dissertation, which reflects the culmination of learning and practical endeavours from throughout the course via the production of an independent and original body of research material. This is performed under supervision with a member of staff, with meetings varying in duration and frequency throughout the year as a function of the needs of the research project and student.
Assessment features examinations, written assignments, oral presentations, and the completion of a dissertation.
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Developmental psychopathology - msc, research methods (behavioural science) - ma.
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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation. It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically ...
The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case. It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed ...
A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...
A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. A case study research design usually involves qualitative methods, but quantitative methods are sometimes also used.
Case study method is the most widely used method in academia for researchers interested in qualitative research (Baskarada, 2014). Research students select the case study as a method without understanding array of factors that can affect the outcome of their research.
The research employs a qualitative methodology, including a comparative case study analysis of a modern 3PL company, a retailer, and a producer of construction materials.
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case. Robert Yin, methodologist most associated with case study research, differentiates between descriptive, exploratory and explanatory case studies:
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 ...
How to do Better Case Studies: (With Illustrations from 20 Exemplary Case Studies) In: The SAGE Handbook of Applied Social Research Methods. By: Robert K. Yin. Edited by: Leonard Bickman & Debra J. Rog Pub. Date: 2013 Access Date: May 18, 2018 Publishing Company: SAGE Publications, Inc. City: Thousand Oaks Print ISBN: 9781412950312 Online ISBN ...
The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies. Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.
A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.
Definitions of qualitative case study research. Case study research is an investigation and analysis of a single or collective case, intended to capture the complexity of the object of study (Stake, 1995).Qualitative case study research, as described by Stake (), draws together "naturalistic, holistic, ethnographic, phenomenological, and biographic research methods" in a bricoleur design ...
From this point on and in further studies, case study in educational research and evaluation came to be a major methodology for understanding complex educational and social programs. It also extended to other practice professions, such as nursing, health, and social care ( Zucker, 2001 ; Greenhalgh & Worrall, 1997 ; Shaw & Gould, 2001 ).
A Case study is: An in-depth research design that primarily uses a qualitative methodology but sometimes includes quantitative methodology. Used to examine an identifiable problem confirmed through research. Used to investigate an individual, group of people, organization, or event. Used to mostly answer "how" and "why" questions.
Introduction. The popularity of case study research methodology in Health Services Research (HSR) has grown over the past 40 years. 1 This may be attributed to a shift towards the use of implementation research and a newfound appreciation of contextual factors affecting the uptake of evidence-based interventions within diverse settings. 2 Incorporating context-specific information on the ...
Case study research is typically extensive; it draws on multiple methods of data collection and involves multiple data sources. The researcher begins by identifying a specific case or set of cases to be studied. Each case is an entity that is described within certain parameters, such as a specific time frame, place, event, and process.
According to the book Understanding Case Study Research, case studies are "small scale research with meaning" that generally involve the following: The study of a particular case, or a number of cases. ... This article defends case study methodology as an appropriate methodology, giving a description, the process and its strengths and weaknesses.
This study employed a qualitative case study methodology. The case study method is a research strategy that aims to gain an in-depth understanding of a specific phenomenon by collecting and ...
Case Studies. Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization. According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.
Learn how to conduct and analyze a case study as a qualitative research method. Download the PDF article from ResearchGate and explore related topics.
Surveys. Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally (Figure 3). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect ...
Bring research methods, statistics and evaluation to life. Introductory overviews to all the major methods to help get you on your way. Find practice datasets to help you master qualitative and quantitative data analysis. Use the Methods Map to browse the resources in Sage Research Methods. Learn how methods are related and find definitions of ...
Advantages of using Cases. Discover methods appropriate for your study - search by discipline for methods used successfully in similar projects to yours. Learn first-hand about the decisions and pivots that researchers often need to make. Easily adapt cases for coursework with the provided learning objectives and discussion questions.
In-Depth Insights: Case studies provide comprehensive and detailed data by exploring specific real-world scenarios, often revealing nuances and contexts missed by broader research methods. Qualitative and Quantitative Data: This method involves gathering a mix of qualitative and quantitative data, enhancing the richness and depth of the research.
As countries develop, the challenge of providing access to the outdoors and nature increases. Consequently, recent environmental justice research has focused on measuring children's access to parks. The results of these analyses better reflect differences in accessibility, but there are discrepancies between different accessibility models. This study aims to explore child-friendly ...
In this case study, we examined 162,325 intensive longitudinal in-game mood reports from 67,328 play sessions of 8,695 players of the popular game PowerWash Simulator. We compared players' moods at the beginning of play sessions with their moods during play and found that the average player reported 0.034 (0.032, 0.036) visual analog scale ...
While all case studies show a dependence on the coal industry for employment and government revenues, the degree of dependence for either varies considerably. Other dependencies also vary; for example, in India informal coal jobs are prominent in some communities, but this is not the case in the United States.
Research methods training, co-ordinated through the Durham Research Methods Centre, therefore forms a central part of the MA course, including both quantitative and qualitative research methods. One third of the course is also devoted to the dissertation which may be carried out in any area of psychology related to development.
Introduction: Sleep is crucial for athletes' recovery and performance while overtraining can negatively affect sleep quantity and sleep quality. We present a case of a 16-year-old female athlete exploring the reciprocal negative effects of overtraining and sleep problems on each other. Methods: A flyer of a high school cheerleading team with a history of injuries, irregular menses, chronic ...