Sage Research Methods Community

Case Study Methods and Examples

By Janet Salmons, PhD Manager, Sage Research Methods Community

What is Case Study Methodology ?

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

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

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

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

The Encyclopedia of case study research provides an overview:

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

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

A case study inquiry could include multiple types of data:

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

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

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

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

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

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

analysis and hypothesis in case study

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

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

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

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

Open-Access Articles Using Case Study Methodology

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

Case Study Research

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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Organizing Your Social Sciences Research Assignments

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

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

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

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

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

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

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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  • How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

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Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

  • The relevant variables
  • The specific group being studied
  • The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

Research question Hypothesis Null hypothesis
What are the health benefits of eating an apple a day? Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits. Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits.
Which airlines have the most delays? Low-cost airlines are more likely to have delays than premium airlines. Low-cost and premium airlines are equally likely to have delays.
Can flexible work arrangements improve job satisfaction? Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours. There is no relationship between working hour flexibility and job satisfaction.
How effective is secondary school sex education at reducing teen pregnancies? Teenagers who received sex education lessons throughout secondary school will have lower rates of unplanned pregnancy than teenagers who did not receive any sex education. Secondary school sex education has no effect on teen pregnancy rates.
What effect does daily use of social media have on the attention span of under-16s? There is a negative correlation between time spent on social media and attention span in under-16s. There is no relationship between social media use and attention span in under-16s.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

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Shona McCombes

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Other students also liked, operationalisation | a guide with examples, pros & cons, what is a conceptual framework | tips & examples, a quick guide to experimental design | 5 steps & examples.

Understanding hypothesis testing through an end to end case study

Subramanian Hariharan

This article was published as a part of the Data Science Blogathon.

” The only way to test the hyp othesis is to look for all the information that disagrees with it – Karl Popper “

Hypothesis Testing comes under a broader subject of Inferential Statistics where we use data samples to draw inferences on the population parameters. The hypothesis testing can be used to compare a population parameter to a particular value, compare two populations and check whether a population follows a probability distribution, etc. The topic of hypothesis testing is quite detailed and it would not be possible to full justice to the study in a short article. However, let’s do a sincere attempt to get an overall view of the hypothesis process through an end-to-end case study. I have focused more on the practical implementation and requisite basic theory has been highlighted as required.

Hypothesis Testing- An Overview

The overall flow process involved in hypothesis testing is as follows :

hypothesis testing process

Another aspect we note in the hypothesis testing is Independent and Dependent samples. The two samples may be independent if they are not related to each other and they can be dependent if one sample can be used to estimate other samples. The hypothesis testing has multiple approaches considering whether we are dealing with dependent or independent samples or on the number of samples available(z-test or t-test), etc. The example of a dependent samples hypothesis testing may be analyzing the weight of a group before and after a weight loss program or a corn, flake manufacturer want to test whether the average weight of packets being manufactured is equal to a specified value of say,500 gms.

In our end to the end case study, we shall take independent samples to study the methodology of hypothesis testing. We will make use of python code to make our life easier rather than go through the grind to do the testing part ( please feel free to trace back method through classical statistics process . It will strengthen your understanding).

Problem Definition for Hypothesis Testing

While having a casual talk with your friend, he mentions that the average cost of iPhones at an eCommerce website A is not equal to eCommerce website B. As a Data Scientist, you trust in evidence provided by data and gets on to analyze the problem scientifically. Let’s define Ho and Ha, 

          H0: µ1 = µ2 (the two population means are equal)

          HA: µ1 ≠µ2 (the two population means are not equal)

Data Analysis and Hypothesis Testing

Of course, we need data to test the above hypothesis and we choose a level of significance of 0.05 for our test. For our case study we have chosen amazon.co.in and flipkart.com, two eCommerce websites in India(just a random choice). At the cost of keeping the code simple, I have collected the prices of iPhones shown on the first search page on both websites for testing. This has limitations in respect of data collected but let’s try and keep things simple. Let’s dive into the code,

We take the help of requests and the BeautifulSoup library to scrape the data from the website, use Pandas to present the data, and use scipy and numpy to do the hypothesis testing. Many websites have protocols in place for blocking access by robots. To extract data we need to create a user agent which carries information about the host sending request to the server. We have created a function to retrieve the price data from the website. The URL of our website is passed to ‘get method’ from the requests library and the response is passed to BautifulSoup along with an HTML parser to construct a soup object. One of the difficult tasks is to identify HTML tags and ids where the price information is stored. We can go to the website page and hover the mouse on top of the price and right-click to navigate to inspect the webpage and retrieve HTML tags.

web scraping for hypothesis testing

We see that the price information is under the tag and class = ‘a-price-whole’ for the amazon search page for iPhones. We use the find_all() method to get all price data on the page. Similarly, we can get similar information for ‘flipkart.com ‘ as well(the URL, tags, and attrs will be different and we get it by inspecting the webpage)

The call of function returns a list containing the price from the  amazon website. We can use the same function to retrieve price info from flipkart as well.

We can create a dataframe to present our data nicely. As length of price obtained from amazon and flipkart is different, we need little tweaking in our code. We use pd.DataFrame_from_dict() function to create a dataframe from dictionary and take Transpose to structure our dataframe and then fill NaN values with value 0(commands have been chained , Feel free to split if you like)

data to be used for hypothesis testing

The job of a Data Scientist involves cleaning the data so that we can do further processing. It is to be noted that the data scraped from the website is an object type and needs formatting before we do the hypothesis testing. The rows where data is not available for one website to have been filled with 0 by using the fillna() method. The following code will take care of preprocessing and be ready for hypothesis testing.

data processing for hypothesis testing

The post-processing of data is shown above and both columns contain float datatypes. We need to check whether both samples follow normal distribution to understand the type of hypothesis test to be performed on the data. If the samples are normal or if the sample size is quite large (n>30) we can go for a t-test from scipy.ttest_ind(). If the samples are normal we need to further test samples for equal variance and generally as a rule of thumb, if the ratio of variances is less than 4:1 we can assume equal variance else we have to test with equal_variance=False. In our case, it is noted that we will use pandas slicing for the shorter data(data with lesser rows) We will test for normality using Shapiro-Wilks Test.

shapiro

The Null hypothesis in the Shapiro-Wilks test assumes normal distribution and we get test statistic and p-value from running the above code. As the p-value is less than a generally used reference value of 0.05, we conclude that the samples do not come from a normal distribution. As we do not have large sample sizes, we can’t use a t-test for this problem. Hence, we go for a non-parametric test like Mann–Whitney U test, which can be applied on unknown distributions and is found to be as efficient as the t-test on normal distributions. If we look at our Ha, we say µ1 ≠µ2, and hence we need to carry out the two-tailed test and if the Ha statement talks about then we limit our test to a one-sided test. We again take help from scipy library to carry out this test,

whitney test result

The results are as shown and it is seen that the test statistic is 153 and the p-value is 0.11. As the   p-value is found to be greater than the significance level of 0.05, we fail to reject Null Hypothesis ,Ho . At a 95% confidence level, we do not have the evide nce to say that the mean price of iPhones from eCommerce A(amazon) and B(Flipkart) are different. The results of this test vary from one code run to another as the data is dynamic,

The Case Study was used to understand the overview of the hypothesis testing for data analysis on two independent samples. I feel the case study approach can help cement your understanding of hypothesis testing theory and look at real-life problems. As a disclaimer, I would like to highlight that this was purely an academic project and the source of data was chosen at random No practical conclusions can be drawn from above to compare the prices in the shortlisted eCommerce websites, as this is purely a limited academic effort. I would recommend to the readers to explore other facets of the hypothesis testing as statistics is one of the major pillars of Data Science as well as try analysis with more data.

The Author, Subramanian Hariharan is a Marine Engineer with more than 30 Years of Experience and is very passionate about leveraging Data for Business Solutions.

Basics of Machine Learning

Machine learning lifecycle, importance of stats and eda, understanding data, probability, exploring continuous variable, exploring categorical variables, missing values and outliers, central limit theorem, bivariate analysis introduction, continuous - continuous variables, continuous categorical, categorical categorical, multivariate analysis, different tasks in machine learning, build your first predictive model, evaluation metrics, preprocessing data, linear models, selecting the right model, feature selection techniques, decision tree, feature engineering, naã¯ve bayes, multiclass and multilabel, basics of ensemble techniques, advance ensemble techniques, hyperparameter tuning, support vector machine, advance dimensionality reduction, unsupervised machine learning methods, recommendation engines, improving ml models, working with large datasets, interpretability of machine learning models, automated machine learning, model deployment, deploying ml models, embedded devices, frequently asked questions.

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Statistics By Jim

Making statistics intuitive

What is a Case Study? Definition & Examples

By Jim Frost Leave a Comment

Case Study Definition

A case study is an in-depth investigation of a single person, group, event, or community. This research method involves intensively analyzing a subject to understand its complexity and context. The richness of a case study comes from its ability to capture detailed, qualitative data that can offer insights into a process or subject matter that other research methods might miss.

A case study involves drawing lots of connections.

A case study strives for a holistic understanding of events or situations by examining all relevant variables. They are ideal for exploring ‘how’ or ‘why’ questions in contexts where the researcher has limited control over events in real-life settings. Unlike narrowly focused experiments, these projects seek a comprehensive understanding of events or situations.

In a case study, researchers gather data through various methods such as participant observation, interviews, tests, record examinations, and writing samples. Unlike statistically-based studies that seek only quantifiable data, a case study attempts to uncover new variables and pose questions for subsequent research.

A case study is particularly beneficial when your research:

  • Requires a deep, contextual understanding of a specific case.
  • Needs to explore or generate hypotheses rather than test them.
  • Focuses on a contemporary phenomenon within a real-life context.

Learn more about Other Types of Experimental Design .

Case Study Examples

Various fields utilize case studies, including the following:

  • Social sciences : For understanding complex social phenomena.
  • Business : For analyzing corporate strategies and business decisions.
  • Healthcare : For detailed patient studies and medical research.
  • Education : For understanding educational methods and policies.
  • Law : For in-depth analysis of legal cases.

For example, consider a case study in a business setting where a startup struggles to scale. Researchers might examine the startup’s strategies, market conditions, management decisions, and competition. Interviews with the CEO, employees, and customers, alongside an analysis of financial data, could offer insights into the challenges and potential solutions for the startup. This research could serve as a valuable lesson for other emerging businesses.

See below for other examples.

What impact does urban green space have on mental health in high-density cities? Assess a green space development in Tokyo and its effects on resident mental health.
How do small businesses adapt to rapid technological changes? Examine a small business in Silicon Valley adapting to new tech trends.
What strategies are effective in reducing plastic waste in coastal cities? Study plastic waste management initiatives in Barcelona.
How do educational approaches differ in addressing diverse learning needs? Investigate a specialized school’s approach to inclusive education in Sweden.
How does community involvement influence the success of public health initiatives? Evaluate a community-led health program in rural India.
What are the challenges and successes of renewable energy adoption in developing countries? Assess solar power implementation in a Kenyan village.

Types of Case Studies

Several standard types of case studies exist that vary based on the objectives and specific research needs.

Illustrative Case Study : Descriptive in nature, these studies use one or two instances to depict a situation, helping to familiarize the unfamiliar and establish a common understanding of the topic.

Exploratory Case Study : Conducted as precursors to large-scale investigations, they assist in raising relevant questions, choosing measurement types, and identifying hypotheses to test.

Cumulative Case Study : These studies compile information from various sources over time to enhance generalization without the need for costly, repetitive new studies.

Critical Instance Case Study : Focused on specific sites, they either explore unique situations with limited generalizability or challenge broad assertions, to identify potential cause-and-effect issues.

Pros and Cons

As with any research study, case studies have a set of benefits and drawbacks.

  • Provides comprehensive and detailed data.
  • Offers a real-life perspective.
  • Flexible and can adapt to discoveries during the study.
  • Enables investigation of scenarios that are hard to assess in laboratory settings.
  • Facilitates studying rare or unique cases.
  • Generates hypotheses for future experimental research.
  • Time-consuming and may require a lot of resources.
  • Hard to generalize findings to a broader context.
  • Potential for researcher bias.
  • Cannot establish causality .
  • Lacks scientific rigor compared to more controlled research methods .

Crafting a Good Case Study: Methodology

While case studies emphasize specific details over broad theories, they should connect to theoretical frameworks in the field. This approach ensures that these projects contribute to the existing body of knowledge on the subject, rather than standing as an isolated entity.

The following are critical steps in developing a case study:

  • Define the Research Questions : Clearly outline what you want to explore. Define specific, achievable objectives.
  • Select the Case : Choose a case that best suits the research questions. Consider using a typical case for general understanding or an atypical subject for unique insights.
  • Data Collection : Use a variety of data sources, such as interviews, observations, documents, and archival records, to provide multiple perspectives on the issue.
  • Data Analysis : Identify patterns and themes in the data.
  • Report Findings : Present the findings in a structured and clear manner.

Analysts typically use thematic analysis to identify patterns and themes within the data and compare different cases.

  • Qualitative Analysis : Such as coding and thematic analysis for narrative data.
  • Quantitative Analysis : In cases where numerical data is involved.
  • Triangulation : Combining multiple methods or data sources to enhance accuracy.

A good case study requires a balanced approach, often using both qualitative and quantitative methods.

The researcher should constantly reflect on their biases and how they might influence the research. Documenting personal reflections can provide transparency.

Avoid over-generalization. One common mistake is to overstate the implications of a case study. Remember that these studies provide an in-depth insights into a specific case and might not be widely applicable.

Don’t ignore contradictory data. All data, even that which contradicts your hypothesis, is valuable. Ignoring it can lead to skewed results.

Finally, in the report, researchers provide comprehensive insight for a case study through “thick description,” which entails a detailed portrayal of the subject, its usage context, the attributes of involved individuals, and the community environment. Thick description extends to interpreting various data, including demographic details, cultural norms, societal values, prevailing attitudes, and underlying motivations. This approach ensures a nuanced and in-depth comprehension of the case in question.

Learn more about Qualitative Research and Qualitative vs. Quantitative Data .

Morland, J. & Feagin, Joe & Orum, Anthony & Sjoberg, Gideon. (1992). A Case for the Case Study . Social Forces. 71(1):240.

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Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

  • State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a  or H 1 ).
  • Collect data in a way designed to test the hypothesis.
  • Perform an appropriate statistical test .
  • Decide whether to reject or fail to reject your null hypothesis.
  • Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Table of contents

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

  • H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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analysis and hypothesis in case study

For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

  • an estimate of the difference in average height between the two groups.
  • a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

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The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

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

  • Normal distribution
  • Descriptive statistics
  • Measures of central tendency
  • Correlation coefficient

Methodology

  • Cluster sampling
  • Stratified sampling
  • Types of interviews
  • Cohort study
  • Thematic analysis

Research bias

  • Implicit bias
  • Cognitive bias
  • Survivorship bias
  • Availability heuristic
  • Nonresponse bias
  • Regression to the mean

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

Cite this Scribbr article

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Bevans, R. (2023, June 22). Hypothesis Testing | A Step-by-Step Guide with Easy Examples. Scribbr. Retrieved September 2, 2024, from https://www.scribbr.com/statistics/hypothesis-testing/

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Case Study Analysis: Examples + How-to Guide & Writing Tips

A case study analysis is a typical assignment in business management courses. The task aims to show high school and college students how to analyze a current situation, determine what problems exist, and develop the best possible strategy to achieve the desired outcome.

Many students feel anxious about writing case analyses because being told to analyze a case study and provide a solution can seem like a big task. That is especially so when working with real-life scenarios. However, you can rest assured writing a case analysis paper is easier than you think. Just keep reading this article and you will find case study examples for students and the advice provided by Custom-writing experts!

  • 👣 Main Steps
  • 🕵 Preparing the Case

🔬 Analyzing the Case

  • 📑 Format & Structure
  • 🙅 Things to Avoid
  • 🏁 Conclusion

🔗 References

👣 writing a case study analysis: main steps.

Business management is built on case analysis. Every single economic result shows that the methods and instruments employed were either well-timed and expedient, in the event of success, or not, in case of failure. These two options indicate whether the strategy is efficient (and should be followed) or requires corrections (or complete change). Such an approach to the case study will make your writing piece more proficient and valuable for the reader. The following steps will direct your plan for writing a case study analysis.

Step 1: Preliminary work

  • Make notes and highlight the numbers and ideas that could be quoted.
  • Single out as many problems as you can, and briefly mark their underlying issues. Then make a note of those responsible. In the report, you will use two to five of the problems, so you will have a selection to choose from.
  • Outline a possible solution to each of the problems you found. Course readings and outside research shall be used here. Highlight your best and worst solution for further reference.

Case Study Analysis Includes Three Main Steps: Preparing the Case, Drafring the Case, and Finalizing the Case.

Step 2: Drafting the Case

  • Provide a general description of the situation and its history.
  • Name all the problems you are going to discuss.
  • Specify the theory used for the analysis.
  • Present the assumptions that emerged during the analysis, if any.
  • Describe the detected problems in more detail.
  • Indicate their link to, and effect on, the general situation.
  • Explain why the problems emerged and persist.
  • List realistic and feasible solutions to the problems you outlined, in the order of importance.
  • Specify your predicted results of such changes.
  • Support your choice with reliable evidence (i.e., textbook readings, the experience of famous companies, and other external research).
  • Define the strategies required to fulfill your proposed solution.
  • Indicate the responsible people and the realistic terms for its implementation.
  • Recommend the issues for further analysis and supervision.

Step 3: Finalizing the Case

Like any other piece of writing, a case analysis requires post-editing. Carefully read it through, looking for inconsistencies and gaps in meaning. Your purpose is to make it look complete, precise, and convincing.

🕵 Preparing a Case for Analysis

Your professor might give you various case study examples from which to choose, or they may just assign you a particular case study. To conduct a thorough data analysis, you must first read the case study. This might appear to be obvious. However, you’d be surprised at how many students don’t take adequate time to complete this part.

Read the case study very thoroughly, preferably several times. Highlight, underline, flag key information, and make notes to refer to later when you are writing your analysis report.

If you don’t have a complete knowledge of the case study your professor has assigned, you won’t conduct a proper analysis of it. Even if you make use of a business case study template or refer to a sample analysis, it won’t help if you aren’t intimately familiar with your case study.

You will also have to conduct research. When it comes to research, you will need to do the following:

  • Gather hard, quantitative data (e.g. 67% of the staff participated in the meeting).
  • Design research tools , such as questionnaires and surveys (this will aid in gathering data).
  • Determine and suggest the best specific, workable solutions.

It would be best if you also learned how to analyze a case study. Once you have read through the case study, you need to determine the focus of your analysis. You can do this by doing the following:

Identify E.g., the loss of brand identity as a problem faced by Starbucks
Analyze of the existing problem
Establish between the various factors

Starbucks’ brand image – possible sources of influence:

Formulate to address the problem

Compare your chosen solutions to the solutions offered by the experts who analyzed the case study you were given or to online assignments for students who were dealing with a similar task. The experts’ solutions will probably be more advanced than yours simply because these people are more experienced. However, don’t let this discourage you; the whole point of doing this analysis is to learn. Use the opportunity to learn from others’ valuable experience, and your results will be better next time.

If you are still in doubt, the University of South Carolina offers a great guide on forming a case study analysis.

📑 Case Analysis Format & Structure

When you are learning how to write a case study analysis, it is important to get the format of your analysis right. Understanding the case study format is vital for both the professor and the student. The person planning and handing out such an assignment should ensure that the student doesn’t have to use any external sources .

In turn, students have to remember that a well-written case analysis provides all the data, making it unnecessary for the reader to go elsewhere for information.

Regardless of whether you use a case study template, you will need to follow a clear and concise format when writing your analysis report. There are some possible case study frameworks available. Still, a case study should contain eight sections laid out in the following format:

  • Describe the purpose of the current case study;
  • Provide a summary of the company;
  • Briefly introduce the problems and issues found in the case study
  • Discuss the theory you will be using in the analysis;
  • Present the key points of the study and present any assumptions made during the analysis.
  • Present each problem you have singled out;
  • Justify your inclusion of each problem by providing supporting evidence from the case study and by discussing relevant theory and what you have learned from your course content;
  • Divide the section (and following sections) into subsections, one for each of your selected problems.
  • Present a summary of each problem you have identified;
  • Present plausible solutions for each of the problems, keeping in mind that each problem will likely have more than one possible solution;
  • Provide the pros and cons of each solution in a way that is practical.
  • Conclusion . This is a summary of your findings and discussion.
  • Decide which solution best fits each of the issues you identified;
  • Explain why you chose this solution and how it will effectively solve the problem;
  • Be persuasive when you write this section so that you can drive your point home;
  • Be sure to bring together theory and what you have learned throughout your course to support your recommendations.
  • Provide an explanation of what must be done, who should take action, and when the solution should be carried out;
  • Where relevant, you should provide an estimate of the cost in implementing the solution, including both the financial investment and the cost in terms of time.
  • References. While you generally do not need to refer to many external sources when writing a case study analysis, you might use a few. When you do, you will need to properly reference these sources, which is most often done in one of the main citation styles, including APA, MLA, or Harvard. There is plenty of help when citing references, and you can follow these APA guidelines , these MLA guidelines , or these Harvard guidelines .
  • Appendices. This is the section you include after your case study analysis if you used any original data in the report. These data, presented as charts, graphs, and tables, are included here because to present them in the main body of the analysis would be disruptive to the reader. The University of Southern California provides a great description of appendices and when to make use of them.

When you’ve finished your first draft, be sure to proofread it. Look not only for potential grammar and spelling errors but also for discrepancies or holes in your argument.

You should also know what you need to avoid when writing your analysis.

🙅 Things to Avoid in Case Analysis

Whenever you deal with a case study, remember that there are some pitfalls to avoid! Beware of the following mistakes:

  • Excessive use of colloquial language . Even though it is a study of an actual case, it should sound formal.
  • Lack of statistical data . Give all the important data, both in percentages and in numbers.
  • Excessive details. State only the most significant facts, rather than drowning the reader in every fact you find.
  • Inconsistency in the methods you have used . In a case study, theory plays a relatively small part, so you must develop a specific case study research methodology.
  • Trivial means of research . It is critical that you design your own case study research method in whatever form best suits your analysis, such as questionnaires and surveys.

It is useful to see a few examples of case analysis papers. After all, a sample case study report can provide you with some context so you can see how to approach each aspect of your paper.

👀 Case Study Examples for Students

It might be easier to understand how a case study analysis works if you have an example to look at. Fortunately, examples of case studies are easy to come by. Take a look at this video for a sample case study analysis for the Coca-Cola Company.

If you want another example, then take a look at the one below!

Business Case Analysis: Example

CRM’s primary focus is customers and customer perception of the brand or the company. The focus may shift depending on customers’ needs. The main points that Center Parcs should consider are an increase in customer satisfaction and its market share. Both of these points will enhance customer perception of the product as a product of value. Increased customer satisfaction will indicate that the company provides quality services, and increased market share can reduce the number of switching (or leaving) customers, thus fostering customer loyalty.

Case Study Topics

  • Equifax case study: the importance of cybersecurity measures. 
  • Study a case illustrating ethical issues of medical research.
  • Examine the case describing the complications connected with nursing and residential care.
  • Analyze the competitive strategy of Delta Airlines .
  • Present a case study of an ethical dilemma showing the conflict between the spirit and the letter of the law.  
  • Explore the aspects of Starbucks’ marketing strategyin a case study.  
  • Research a case of community-based clinic organization and development.
  • Customer service of United Airlines: a case study .
  • Analyze a specific schizophrenia case and provide your recommendations.
  • Provide a case study of a patient with hyperglycemia.
  • Examine the growth strategy of United Healthcare.
  • Present a case study demonstrating ethical issues in business.
  • Study a case of the 5% shareholding rule application and its impact on the company.
  • Case study of post-traumatic stress disorder .
  • Analyze a case examining the issues of cross-cultural management .
  • Write a case study exploring the ethical issues the finance manager of a long-term care facility can face and the possible reaction to them.
  • Write a case study analyzing the aspects of a new president of a firm election.
  • Discuss the specifics of supply chain management in the case of Tehindo company.
  • Study a case of a life crisis in a family and the ways to cope with it.
  • Case study of Tea Leaves and More: supply chain issues.   
  • Explore the case of ketogenic diet implementation among sportspeople.  
  • Analyze the case of Webster Jewelry shop and suggest some changes.  
  • Examine the unique aspects of Tea and More brand management.  
  • Adidas case study: an ethical dilemma .
  • Research the challenges of Brazos Valley Food Bank and suggest possible solutions.  
  • Describe the case of dark web monitoring for business.  
  • Study a case of permissive parenting style .
  • Case study of Starbucks employees.
  • Analyze a case of workplace discrimination and suggest a strategy to avoid it.
  • Examine a case of the consumer decision-making process and define the factors that influence it.
  • Present a case study of Netflix illustrating the crucial role of management innovation for company development.  
  • Discuss a case describing a workplace ethical issue and propose ways to resolve it.
  • Case study of the 2008 financial crisis: Graham’s value investing principles in the modern economic climate.
  • Write a case study analyzing the harmful consequences of communication issues in a virtual team.
  • Analyze a case that highlights the importance of a proper functional currency choice. 
  • Examine the case of Hitachi Power Systems management.  
  • Present a case study of medication research in a healthcare facility.
  • Study the case of Fiji Water and the challenges the brand faces.  
  • Research a social problem case and suggest a solution.
  • Analyze a case that reveals the connection between alcohol use and borderline personality disorder.
  • Transglobal Airline case study: break-even analysis.
  • Examine the case of Chiquita Brands International from the moral and business ethics points of view.
  • Present a case study of applying for Social Security benefits. 
  • Study the case of a mass hacker attack on Microsoft clients and suggest possible ways to prevent future attacks.
  • Case study of leadership effectiveness. 
  • Analyze a case presenting a clinical moral dilemma and propose ways to resolve it. 
  • Describe the case of Cowbell Brewing Company and discuss the strategy that made them successful.
  • Write a case study of WeWork company and analyze the strengths and weaknesses of its strategy.
  • Case study of medical ethical decision-making.
  • Study the case of The Georges hotel and suggest ways to overcome its managerial issues.

🏁 Concluding Remarks

Writing a case study analysis can seem incredibly overwhelming, especially if you have never done it before. Just remember, you can do it provided you follow a plan, keep to the format described here, and study at least one case analysis example.

If you still need help analyzing a case study, your professor is always available to answer your questions and point you in the right direction. You can also get help with any aspect of the project from a custom writing company. Just tackle the research and hand over the writing, write a rough draft and have it checked by a professional, or completely hand the project off to an expert writer.

Regardless of the path you choose, you will turn in something of which you can be proud!

✏️ Case Study Analysis FAQ

Students (especially those who study business) often need to write a case study analysis. It is a kind of report that describes a business case. It includes multiple aspects, for example, the problems that exist, possible solutions, forecasts, etc.

There should be 3 main points covered in a case study analysis:

  • The challenge(s) description,
  • Possible solutions,
  • Outcomes (real and/or foreseen).

Firstly, study some examples available online and in the library. Case study analysis should be a well-structured paper with all the integral components in place. Thus, you might want to use a template and/or an outline to start correctly.

A case study analysis is a popular task for business students. They typically hand it in the format of a paper with several integral components:

  • Description of the problem
  • Possible ways out
  • Results and/or forecasts

Students sometimes tell about the outcome of their research within an oral presentation.

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  • How to Outline: Purdue OWL
  • Incorporating Interview Data: UW-Madison Writing Center
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Quite an impressive piece The steps and procedures outlined here are well detailed and the examples facilitates understanding.

it was very helpful. I have an assessment to write where in I need to mention different effective components that are needed to compile a high quality case study assessment.

It is very important and helpful.

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Thanks for this valuable knowledge.I loved this. keep sharing. to know more about click Air India Case Study – Why Air India failed ?

This is going to be a great help in my monthly analysis requirements for my subject. Thank you so much.

Thank you very much for this insightful guidelines… It has really been a great tool for writing my project. Thanks once again.

This article was very helpful, even though I’ll have a clearer mind only after I do the case study myself but I felt very much motivated after reading this, as now I can at least have a plan of what to do compared to the clueless me I was before I read it. I hope if I have any questions or doubts about doing a case study I can clear it out here.

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A case study is an in-depth study of a singular situation, person or event.

What does this mean?

In most disciplines, studies are required to prove a hypothesis. These studies are usually very large in nature, with the goal of proving a hypothesis. With a case study, a narrow topic is chosen that can prove (or disprove) an idea, question or hypothesis. Often, case studies are used alongside a larger formal study, or are used on their own.

An idea or theory that hasn't been proven but has scientific merit and is worthy of a study to prove whether it is true or false.

Case studies are used in most disciplines that use or require statistical or informational data. For example, a well-known case study in the field of psychology is the case of "Genie", a feral child.

Obviously, researchers cannot lock up a child for a decade, and do research on the results. So, when a child was discovered locked up for 13 years, it was a perfect opportunity to do research and try to discover what the effects was of a child being isolated it's entire life.

What information could be garnered from the "Genie" case study? How could the case study be used to help children (or adults) under care today?

Case studies are also commonly used in the business world. For example, one of the most well-known business case studies is the Tylenol cyanide scandal. A quick refresher, in 1982 seven people died after ingesting Tylenol tablets laced with cyanide.

Almost immediately Tylenol's market share dropped from 37% to 7%. Johnson & Johnson, the parent company had to work quickly to save the product. They reintroduced the product with tamper resistant packaging and a large media campaign.

Johnson & Johnson was successful. The Tylenol brand recovered and regained customer trust.

The Tylenol Scandal case study details everything that happened from beginning to end. It also details each step J&J took when turning the scandal around…both positive and negative steps.

This case study is now used in business, marketing, crisis management and other disciplines to help them solve their own problems. They can look at what J&J did to solve their problems, and use that information to fix their own issues.

Who Uses Case Studies?

What makes a case study so valuable is that is it is real-life situation or problem. Dealing with hypothetical issues can be helpful, but using actual historical information and data is often a much better way to learn and fix an organization's problems.

Case studies are used in most disciplines, as well as education, where they are becoming more prevalent. In fact, some of the best universities, such as Harvard Business School, use the case method to educate its students.

Think about it, what better way to learn about a subject than to study real-life examples of similar situations?

Case studies are used in just about every discipline. For this article, case studies will belong to one of the following five groups.

  • Arts, Design, Media and Humanities
  • Business, Hospitality, Law, Sport and Tourism
  • Interdisciplinary
  • Education, Social and Environmental Sciences
  • Science, Technology, Engineering and Mathematics

Case studies are understandably useful for others to learn from, and an effective case study can help people, businesses, and organizations for years to come. However, what exactly goes into a case study, and how is one developed?

Why Develop A Case Study?

People have several reasons for wanting to develop a case study. For example, a technology company might want to learn why certain members of the population buy certain products. Or a psychologist might want to understand what is the best type of therapy for veterans with PTSD. To accomplish this, both would want to develop a case study.

Let's use our psychologist as an example.

A psychologist wants to begin offering specialized treatment for veterans suffering from PTSD. She currently has many veterans as patients, and she has determined that some therapeutic methods are more effective than others. She wants to use the information she is gaining to develop a track record for which methods are most effective. To do this, she will develop a case study.

The psychologist will use data and information from her current patients (using strict privacy rules), as well as professional resources, to develop her case study. This case study could accomplish many things.

1. Pilot Research – If the psychologist wants to do large-scale research, starting with a few case studies is a great way to go. If the case studies show any patterns or trends, that information can be used to determine the best way to do advanced research.

2. Develop New Theories or Ideas – The psychologist may have her own ideas going into the study. Perhaps she believes that a combination of talk and group therapy is the best treatment for veterans with PTSD. Or maybe through her case study, she realizes that group therapy is often effective alone. If she develops a new theory, she can test it with additional research.

3. Change Existing Theories or Ideas – In psychology, ideas and treatments often change with time or new information or research. While conducting the case study, the psychologist might discover that older ideas are not as effective as newer treatments. If the psychologist feels current professional protocol is not as effective as newer treatments, a case study could be developed to challenge those ideas.

Intrinsic Case Study

A study on a topic that is unique in itself. An example of this would be the study of Genie, the feral child.

Instrumental Case Study

A study on a more general phenomenon or similarity. An example of this would be a study to determine what therapies are most effective for war veterans with PTSD.

Types Of Case Studies

There are generally five different types of case studies, and the subjects that they address. These are:

Person – This type of study focuses on one particular individual. This case study would use several types of research to determine an outcome.

Group – This type of study focuses on a group of people. This could be a family, a group or friends, or even coworkers.

Location – This type of study focuses on a place, and how and why people use the place.

Organization/Company – This type of study focuses on a business or an organization. This could include the people who work for the company, or an event that occurred at the organization.

Event – This type of study focuses on an event, whether cultural or societal, and how it affects those that are affected by it.

What kind of case study is the "Genie" study?

What kind of case study is the "Tylenol Scandal" study?

What Is The Process For Developing A Case Study?

While case studies are smaller than larger research-based studies, their development still requires a strict and detailed systematic plan. There are several steps required to complete a full study. The basic plan is as follows:

1. Define The Task, Question or Topic

What is the topic of the case study? What question is the case study supposed to answer?

The first step is to determine what the case study will be about. This is when a researcher will develop their hypothesis.

This is also when research should be done to determine whether any case studies have been written on this topic in the past. This research can be difficult, since many small case studies exist. However, with the advent of the Internet, finding older studies is easier than it was in the past.

2. Do Research, Interviews, Collect Data

The research stage is the longest and most detailed of the case study process.

One of the primary methods used in case studies is an interview. Whether it is one person or several, the interview process is extremely important. Not only must the subject have several interviews, but also other experts in the subject should be interviewed. Their contribution can be invaluable.

When interviewing subjects, questioned should be open-ended so the subject is forced to answer with more than just a "yes" or "no". For example, when interviewing the first responders of "Genie", the researcher shouldn't say:

"When you found Genie, was she afraid of you?"

This question could easily lead to a "yes" or "no" answer. One could easily assume Genie was frightened when found since she had no socialization skills whatsoever. Instead, the researcher should ask questions like:

"When you first found Genie, what was her disposition?"

"When you removed Genie from her home, how did she react to the sunlight and outdoors"?

"When you gave Genie a cookie in the ambulance, how did she react?"

3. Make Recommendations and Form Conclusions

What did the study prove? After gathering all of the data, what conclusions can be made?

Once the researcher has compiled all of the research, it is time to formulate the data and form a thesis. A thesis is a statement that will tell the reader what to expect from the case study. It is a single sentence that usually is within the first paragraph of the report. The thesis must make a claim that can be disputed by others.

The thesis differs from the hypothesis in that the thesis is the statement that is proven true with the case study. The hypothesis is the question or idea that the researcher had going into the study. It is possible the hypothesis and thesis are the same. However, it is also possible that once all the research has been completed, the thesis changes from the initial hypothesis.

4. Write The Report

Writing the report is the final step, but it includes several steps. A case study is a research study that requires a cover page, references, and all of the acquired data and information compiled in a readable and cohesive report.

While a case study might use scientific facts and information, a case study should not read as a scientific research journal or report. It should be easy to read and understand, and should follow the narrative determined in the first step.

Remember, the case study must analyze a case or situation in a clear and concise way, but should also be readable by people not familiar with scientific methods. The study should have four main sections, the introduction , the background of the study and why it was developed, the presentation of findings , and the conclusion .

The introduction should set the stage for the case study, and state the thesis for the report. The intro must clearly articulate what the study's intention is, as well as how you plan on explaining and answering the thesis. Again, remember that a case study is not a formal scientific research report that will only be read by scientists. The case study must be able to be read and understood by the layperson, and should read almost as a story, with a clear narrative.

The background should detail what information brought the researcher to pose his hypothesis. It should clearly explain the subject or subjects, as well as their background information. And lastly, the background must give the reader a full understanding of the issue at hand, and what process will be taken with the study. Photos and videos are always helpful when applicable.

The presentation of findings should clearly explain how the topic was researched, and summarize what the results are. Data should be summarized as simply as possible so that it is understandable by people without a scientific background. The researcher should describe what was learned from the interviews, and how the results answered the questions asked in the introduction.

The final section of the study is the conclusion . The purpose of the study isn't necessarily to solve the problem, only to offer possible solutions. The final summary should be an end to the story. Remember, the case study is about asking and answering questions. The conclusion should answer the question posed by the researcher, but also leave the reader with questions of his own. The researcher wants the reader to think about the questions posed in the study, and be free to come to their own conclusions as well.

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Methodologic and Data-Analysis Triangulation in Case Studies: A Scoping Review

Margarithe charlotte schlunegger.

1 Department of Health Professions, Applied Research & Development in Nursing, Bern University of Applied Sciences, Bern, Switzerland

2 Faculty of Health, School of Nursing Science, Witten/Herdecke University, Witten, Germany

Maya Zumstein-Shaha

Rebecca palm.

3 Department of Health Care Research, Carl von Ossietzky University Oldenburg, Oldenburg, Germany

Associated Data

Supplemental material, sj-docx-1-wjn-10.1177_01939459241263011 for Methodologic and Data-Analysis Triangulation in Case Studies: A Scoping Review by Margarithe Charlotte Schlunegger, Maya Zumstein-Shaha and Rebecca Palm in Western Journal of Nursing Research

We sought to explore the processes of methodologic and data-analysis triangulation in case studies using the example of research on nurse practitioners in primary health care.

Design and methods:

We conducted a scoping review within Arksey and O’Malley’s methodological framework, considering studies that defined a case study design and used 2 or more data sources, published in English or German before August 2023.

Data sources:

The databases searched were MEDLINE and CINAHL, supplemented with hand searching of relevant nursing journals. We also examined the reference list of all the included studies.

In total, 63 reports were assessed for eligibility. Ultimately, we included 8 articles. Five studies described within-method triangulation, whereas 3 provided information on between/across-method triangulation. No study reported within-method triangulation of 2 or more quantitative data-collection procedures. The data-collection procedures were interviews, observation, documentation/documents, service records, and questionnaires/assessments. The data-analysis triangulation involved various qualitative and quantitative methods of analysis. Details about comparing or contrasting results from different qualitative and mixed-methods data were lacking.

Conclusions:

Various processes for methodologic and data-analysis triangulation are described in this scoping review but lack detail, thus hampering standardization in case study research, potentially affecting research traceability. Triangulation is complicated by terminological confusion. To advance case study research in nursing, authors should reflect critically on the processes of triangulation and employ existing tools, like a protocol or mixed-methods matrix, for transparent reporting. The only existing reporting guideline should be complemented with directions on methodologic and data-analysis triangulation.

Case study research is defined as “an empirical method that investigates a contemporary phenomenon (the ‘case’) in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident. A case study relies on multiple sources of evidence, with data needing to converge in a triangulating fashion.” 1 (p15) This design is described as a stand-alone research approach equivalent to grounded theory and can entail single and multiple cases. 1 , 2 However, case study research should not be confused with single clinical case reports. “Case reports are familiar ways of sharing events of intervening with single patients with previously unreported features.” 3 (p107) As a methodology, case study research encompasses substantially more complexity than a typical clinical case report. 1 , 3

A particular characteristic of case study research is the use of various data sources, such as quantitative data originating from questionnaires as well as qualitative data emerging from interviews, observations, or documents. Therefore, a case study always draws on multiple sources of evidence, and the data must converge in a triangulating manner. 1 When using multiple data sources, a case or cases can be examined more convincingly and accurately, compensating for the weaknesses of the respective data sources. 1 Another characteristic is the interaction of various perspectives. This involves comparing or contrasting perspectives of people with different points of view, eg, patients, staff, or leaders. 4 Through triangulation, case studies contribute to the completeness of the research on complex topics, such as role implementation in clinical practice. 1 , 5 Triangulation involves a combination of researchers from various disciplines, of theories, of methods, and/or of data sources. By creating connections between these sources (ie, investigator, theories, methods, data sources, and/or data analysis), a new understanding of the phenomenon under study can be obtained. 6 , 7

This scoping review focuses on methodologic and data-analysis triangulation because concrete procedures are missing, eg, in reporting guidelines. Methodologic triangulation has been called methods, mixed methods, or multimethods. 6 It can encompass within-method triangulation and between/across-method triangulation. 7 “Researchers using within-method triangulation use at least 2 data-collection procedures from the same design approach.” 6 (p254) Within-method triangulation is either qualitative or quantitative but not both. Therefore, within-method triangulation can also be considered data source triangulation. 8 In contrast, “researchers using between/across-method triangulation employ both qualitative and quantitative data-collection methods in the same study.” 6 (p254) Hence, methodologic approaches are combined as well as various data sources. For this scoping review, the term “methodologic triangulation” is maintained to denote between/across-method triangulation. “Data-analysis triangulation is the combination of 2 or more methods of analyzing data.” 6 (p254)

Although much has been published on case studies, there is little consensus on the quality of the various data sources, the most appropriate methods, or the procedures for conducting methodologic and data-analysis triangulation. 5 According to the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) clearinghouse for reporting guidelines, one standard exists for organizational case studies. 9 Organizational case studies provide insights into organizational change in health care services. 9 Rodgers et al 9 pointed out that, although high-quality studies are being funded and published, they are sometimes poorly articulated and methodologically inadequate. In the reporting checklist by Rodgers et al, 9 a description of the data collection is included, but reporting directions on methodologic and data-analysis triangulation are missing. Therefore, the purpose of this study was to examine the process of methodologic and data-analysis triangulation in case studies. Accordingly, we conducted a scoping review to elicit descriptions of and directions for triangulation methods and analysis, drawing on case studies of nurse practitioners (NPs) in primary health care as an example. Case studies are recommended to evaluate the implementation of new roles in (primary) health care, such as that of NPs. 1 , 5 Case studies on new role implementation can generate a unique and in-depth understanding of specific roles (individual), teams (smaller groups), family practices or similar institutions (organization), and social and political processes in health care systems. 1 , 10 The integration of NPs into health care systems is at different stages of progress around the world. 11 Therefore, studies are needed to evaluate this process.

The methodological framework by Arksey and O’Malley 12 guided this scoping review. We examined the current scientific literature on the use of methodologic and data-analysis triangulation in case studies on NPs in primary health care. The review process included the following stages: (1) establishing the research question; (2) identifying relevant studies; (3) selecting the studies for inclusion; (4) charting the data; (5) collating, summarizing, and reporting the results; and (6) consulting experts in the field. 12 Stage 6 was not performed due to a lack of financial resources. The reporting of the review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review) guideline by Tricco et al 13 (guidelines for reporting systematic reviews and meta-analyses [ Supplementary Table A ]). Scoping reviews are not eligible for registration in PROSPERO.

Stage 1: Establishing the Research Question

The aim of this scoping review was to examine the process of triangulating methods and analysis in case studies on NPs in primary health care to improve the reporting. We sought to answer the following question: How have methodologic and data-analysis triangulation been conducted in case studies on NPs in primary health care? To answer the research question, we examined the following elements of the selected studies: the research question, the study design, the case definition, the selected data sources, and the methodologic and data-analysis triangulation.

Stage 2: Identifying Relevant Studies

A systematic database search was performed in the MEDLINE (via PubMed) and CINAHL (via EBSCO) databases between July and September 2020 to identify relevant articles. The following terms were used as keyword search strategies: (“Advanced Practice Nursing” OR “nurse practitioners”) AND (“primary health care” OR “Primary Care Nursing”) AND (“case study” OR “case studies”). Searches were limited to English- and German-language articles. Hand searches were conducted in the journals Nursing Inquiry , BMJ Open , and BioMed Central ( BMC ). We also screened the reference lists of the studies included. The database search was updated in August 2023. The complete search strategy for all the databases is presented in Supplementary Table B .

Stage 3: Selecting the Studies

Inclusion and exclusion criteria.

We used the inclusion and exclusion criteria reported in Table 1 . We included studies of NPs who had at least a master’s degree in nursing according to the definition of the International Council of Nurses. 14 This scoping review considered studies that were conducted in primary health care practices in rural, urban, and suburban regions. We excluded reviews and study protocols in which no data collection had occurred. Articles were included without limitations on the time period or country of origin.

Inclusion and Exclusion Criteria.

CriteriaInclusionExclusion
Population- NPs with a master’s degree in nursing or higher - Nurses with a bachelor’s degree in nursing or lower
- Pre-registration nursing students
- No definition of master’s degree in nursing described in the publication
Interest- Description/definition of a case study design
- Two or more data sources
- Reviews
- Study protocols
- Summaries/comments/discussions
Context- Primary health care
- Family practices and home visits (including adult practices, internal medicine practices, community health centers)
- Nursing homes, hospital, hospice

Screening process

After the search, we collated and uploaded all the identified records into EndNote v.X8 (Clarivate Analytics, Philadelphia, Pennsylvania) and removed any duplicates. Two independent reviewers (MCS and SA) screened the titles and abstracts for assessment in line with the inclusion criteria. They retrieved and assessed the full texts of the selected studies while applying the inclusion criteria. Any disagreements about the eligibility of studies were resolved by discussion or, if no consensus could be reached, by involving experienced researchers (MZ-S and RP).

Stages 4 and 5: Charting the Data and Collating, Summarizing, and Reporting the Results

The first reviewer (MCS) extracted data from the selected publications. For this purpose, an extraction tool developed by the authors was used. This tool comprised the following criteria: author(s), year of publication, country, research question, design, case definition, data sources, and methodologic and data-analysis triangulation. First, we extracted and summarized information about the case study design. Second, we narratively summarized the way in which the data and methodological triangulation were described. Finally, we summarized the information on within-case or cross-case analysis. This process was performed using Microsoft Excel. One reviewer (MCS) extracted data, whereas another reviewer (SA) cross-checked the data extraction, making suggestions for additions or edits. Any disagreements between the reviewers were resolved through discussion.

A total of 149 records were identified in 2 databases. We removed 20 duplicates and screened 129 reports by title and abstract. A total of 46 reports were assessed for eligibility. Through hand searches, we identified 117 additional records. Of these, we excluded 98 reports after title and abstract screening. A total of 17 reports were assessed for eligibility. From the 2 databases and the hand search, 63 reports were assessed for eligibility. Ultimately, we included 8 articles for data extraction. No further articles were included after the reference list screening of the included studies. A PRISMA flow diagram of the study selection and inclusion process is presented in Figure 1 . As shown in Tables 2 and ​ and3, 3 , the articles included in this scoping review were published between 2010 and 2022 in Canada (n = 3), the United States (n = 2), Australia (n = 2), and Scotland (n = 1).

An external file that holds a picture, illustration, etc.
Object name is 10.1177_01939459241263011-fig1.jpg

PRISMA flow diagram.

Characteristics of Articles Included.

AuthorContandriopoulos et al Flinter Hogan et al Hungerford et al O’Rourke Roots and MacDonald Schadewaldt et al Strachan et al
CountryCanadaThe United StatesThe United StatesAustraliaCanadaCanadaAustraliaScotland
How or why research questionNo information on the research questionSeveral how or why research questionsWhat and how research questionNo information on the research questionSeveral how or why research questionsNo information on the research questionWhat research questionWhat and why research questions
Design and referenced author of methodological guidanceSix qualitative case studies
Robert K. Yin
Multiple-case studies design
Robert K. Yin
Multiple-case studies design
Robert E. Stake
Case study design
Robert K. Yin
Qualitative single-case study
Robert K. Yin
Robert E. Stake
Sharan Merriam
Single-case study design
Robert K. Yin
Sharan Merriam
Multiple-case studies design
Robert K. Yin
Robert E. Stake
Multiple-case studies design
Case definitionTeam of health professionals
(Small group)
Nurse practitioners
(Individuals)
Primary care practices (Organization)Community-based NP model of practice
(Organization)
NP-led practice
(Organization)
Primary care practices
(Organization)
No information on case definitionHealth board (Organization)

Overview of Within-Method, Between/Across-Method, and Data-Analysis Triangulation.

AuthorContandriopoulos et al Flinter Hogan et al Hungerford et al O’Rourke Roots and MacDonald Schadewaldt et al Strachan et al
Within-method triangulation (using within-method triangulation use at least 2 data-collection procedures from the same design approach)
:
 InterviewsXxxxx
 Observationsxx
 Public documentsxxx
 Electronic health recordsx
Between/across-method (using both qualitative and quantitative data-collection procedures in the same study)
:
:
 Interviewsxxx
 Observationsxx
 Public documentsxx
 Electronic health recordsx
:
 Self-assessmentx
 Service recordsx
 Questionnairesx
Data-analysis triangulation (combination of 2 or more methods of analyzing data)
:
:
 Deductivexxx
 Inductivexx
 Thematicxx
 Content
:
 Descriptive analysisxxx
:
:
 Deductivexxxx
 Inductivexx
 Thematicx
 Contentx

Research Question, Case Definition, and Case Study Design

The following sections describe the research question, case definition, and case study design. Case studies are most appropriate when asking “how” or “why” questions. 1 According to Yin, 1 how and why questions are explanatory and lead to the use of case studies, histories, and experiments as the preferred research methods. In 1 study from Canada, eg, the following research question was presented: “How and why did stakeholders participate in the system change process that led to the introduction of the first nurse practitioner-led Clinic in Ontario?” (p7) 19 Once the research question has been formulated, the case should be defined and, subsequently, the case study design chosen. 1 In typical case studies with mixed methods, the 2 types of data are gathered concurrently in a convergent design and the results merged to examine a case and/or compare multiple cases. 10

Research question

“How” or “why” questions were found in 4 studies. 16 , 17 , 19 , 22 Two studies additionally asked “what” questions. Three studies described an exploratory approach, and 1 study presented an explanatory approach. Of these 4 studies, 3 studies chose a qualitative approach 17 , 19 , 22 and 1 opted for mixed methods with a convergent design. 16

In the remaining studies, either the research questions were not clearly stated or no “how” or “why” questions were formulated. For example, “what” questions were found in 1 study. 21 No information was provided on exploratory, descriptive, and explanatory approaches. Schadewaldt et al 21 chose mixed methods with a convergent design.

Case definition and case study design

A total of 5 studies defined the case as an organizational unit. 17 , 18 - 20 , 22 Of the 8 articles, 4 reported multiple-case studies. 16 , 17 , 22 , 23 Another 2 publications involved single-case studies. 19 , 20 Moreover, 2 publications did not state the case study design explicitly.

Within-Method Triangulation

This section describes within-method triangulation, which involves employing at least 2 data-collection procedures within the same design approach. 6 , 7 This can also be called data source triangulation. 8 Next, we present the single data-collection procedures in detail. In 5 studies, information on within-method triangulation was found. 15 , 17 - 19 , 22 Studies describing a quantitative approach and the triangulation of 2 or more quantitative data-collection procedures could not be included in this scoping review.

Qualitative approach

Five studies used qualitative data-collection procedures. Two studies combined face-to-face interviews and documents. 15 , 19 One study mixed in-depth interviews with observations, 18 and 1 study combined face-to-face interviews and documentation. 22 One study contained face-to-face interviews, observations, and documentation. 17 The combination of different qualitative data-collection procedures was used to present the case context in an authentic and complex way, to elicit the perspectives of the participants, and to obtain a holistic description and explanation of the cases under study.

All 5 studies used qualitative interviews as the primary data-collection procedure. 15 , 17 - 19 , 22 Face-to-face, in-depth, and semi-structured interviews were conducted. The topics covered in the interviews included processes in the introduction of new care services and experiences of barriers and facilitators to collaborative work in general practices. Two studies did not specify the type of interviews conducted and did not report sample questions. 15 , 18

Observations

In 2 studies, qualitative observations were carried out. 17 , 18 During the observations, the physical design of the clinical patients’ rooms and office spaces was examined. 17 Hungerford et al 18 did not explain what information was collected during the observations. In both studies, the type of observation was not specified. Observations were generally recorded as field notes.

Public documents

In 3 studies, various qualitative public documents were studied. 15 , 19 , 22 These documents included role description, education curriculum, governance frameworks, websites, and newspapers with information about the implementation of the role and general practice. Only 1 study failed to specify the type of document and the collected data. 15

Electronic health records

In 1 study, qualitative documentation was investigated. 17 This included a review of dashboards (eg, provider productivity reports or provider quality dashboards in the electronic health record) and quality performance reports (eg, practice-wide or co-management team-wide performance reports).

Between/Across-Method Triangulation

This section describes the between/across methods, which involve employing both qualitative and quantitative data-collection procedures in the same study. 6 , 7 This procedure can also be denoted “methodologic triangulation.” 8 Subsequently, we present the individual data-collection procedures. In 3 studies, information on between/across triangulation was found. 16 , 20 , 21

Mixed methods

Three studies used qualitative and quantitative data-collection procedures. One study combined face-to-face interviews, documentation, and self-assessments. 16 One study employed semi-structured interviews, direct observation, documents, and service records, 20 and another study combined face-to-face interviews, non-participant observation, documents, and questionnaires. 23

All 3 studies used qualitative interviews as the primary data-collection procedure. 16 , 20 , 23 Face-to-face and semi-structured interviews were conducted. In the interviews, data were collected on the introduction of new care services and experiences of barriers to and facilitators of collaborative work in general practices.

Observation

In 2 studies, direct and non-participant qualitative observations were conducted. 20 , 23 During the observations, the interaction between health professionals or the organization and the clinical context was observed. Observations were generally recorded as field notes.

In 2 studies, various qualitative public documents were examined. 20 , 23 These documents included role description, newspapers, websites, and practice documents (eg, flyers). In the documents, information on the role implementation and role description of NPs was collected.

Individual journals

In 1 study, qualitative individual journals were studied. 16 These included reflective journals from NPs, who performed the role in primary health care.

Service records

Only 1 study involved quantitative service records. 20 These service records were obtained from the primary care practices and the respective health authorities. They were collected before and after the implementation of an NP role to identify changes in patients’ access to health care, the volume of patients served, and patients’ use of acute care services.

Questionnaires/Assessment

In 2 studies, quantitative questionnaires were used to gather information about the teams’ satisfaction with collaboration. 16 , 21 In 1 study, 3 validated scales were used. The scales measured experience, satisfaction, and belief in the benefits of collaboration. 21 Psychometric performance indicators of these scales were provided. However, the time points of data collection were not specified; similarly, whether the questionnaires were completed online or by hand was not mentioned. A competency self-assessment tool was used in another study. 16 The assessment comprised 70 items and included topics such as health promotion, protection, disease prevention and treatment, the NP-patient relationship, the teaching-coaching function, the professional role, managing and negotiating health care delivery systems, monitoring and ensuring the quality of health care practice, and cultural competence. Psychometric performance indicators were provided. The assessment was completed online with 2 measurement time points (pre self-assessment and post self-assessment).

Data-Analysis Triangulation

This section describes data-analysis triangulation, which involves the combination of 2 or more methods of analyzing data. 6 Subsequently, we present within-case analysis and cross-case analysis.

Mixed-methods analysis

Three studies combined qualitative and quantitative methods of analysis. 16 , 20 , 21 Two studies involved deductive and inductive qualitative analysis, and qualitative data were analyzed thematically. 20 , 21 One used deductive qualitative analysis. 16 The method of analysis was not specified in the studies. Quantitative data were analyzed using descriptive statistics in 3 studies. 16 , 20 , 23 The descriptive statistics comprised the calculation of the mean, median, and frequencies.

Qualitative methods of analysis

Two studies combined deductive and inductive qualitative analysis, 19 , 22 and 2 studies only used deductive qualitative analysis. 15 , 18 Qualitative data were analyzed thematically in 1 study, 22 and data were treated with content analysis in the other. 19 The method of analysis was not specified in the 2 studies.

Within-case analysis

In 7 studies, a within-case analysis was performed. 15 - 20 , 22 Six studies used qualitative data for the within-case analysis, and 1 study employed qualitative and quantitative data. Data were analyzed separately, consecutively, or in parallel. The themes generated from qualitative data were compared and then summarized. The individual cases were presented mostly as a narrative description. Quantitative data were integrated into the qualitative description with tables and graphs. Qualitative and quantitative data were also presented as a narrative description.

Cross-case analyses

Of the multiple-case studies, 5 carried out cross-case analyses. 15 - 17 , 20 , 22 Three studies described the cross-case analysis using qualitative data. Two studies reported a combination of qualitative and quantitative data for the cross-case analysis. In each multiple-case study, the individual cases were contrasted to identify the differences and similarities between the cases. One study did not specify whether a within-case or a cross-case analysis was conducted. 23

Confirmation or contradiction of data

This section describes confirmation or contradiction through qualitative and quantitative data. 1 , 4 Qualitative and quantitative data were reported separately, with little connection between them. As a result, the conclusions on neither the comparisons nor the contradictions could be clearly determined.

Confirmation or contradiction among qualitative data

In 3 studies, the consistency of the results of different types of qualitative data was highlighted. 16 , 19 , 21 In particular, documentation and interviews or interviews and observations were contrasted:

  • Confirmation between interviews and documentation: The data from these sources corroborated the existence of a common vision for an NP-led clinic. 19
  • Confirmation among interviews and observation: NPs experienced pressure to find and maintain their position within the existing system. Nurse practitioners and general practitioners performed complete episodes of care, each without collaborative interaction. 21
  • Contradiction among interviews and documentation: For example, interviewees mentioned that differentiating the scope of practice between NPs and physicians is difficult as there are too many areas of overlap. However, a clear description of the scope of practice for the 2 roles was provided. 21

Confirmation through a combination of qualitative and quantitative data

Both types of data showed that NPs and general practitioners wanted to have more time in common to discuss patient cases and engage in personal exchanges. 21 In addition, the qualitative and quantitative data confirmed the individual progression of NPs from less competent to more competent. 16 One study pointed out that qualitative and quantitative data obtained similar results for the cases. 20 For example, integrating NPs improved patient access by increasing appointment availability.

Contradiction through a combination of qualitative and quantitative data

Although questionnaire results indicated that NPs and general practitioners experienced high levels of collaboration and satisfaction with the collaborative relationship, the qualitative results drew a more ambivalent picture of NPs’ and general practitioners’ experiences with collaboration. 21

Research Question and Design

The studies included in this scoping review evidenced various research questions. The recommended formats (ie, how or why questions) were not applied consistently. Therefore, no case study design should be applied because the research question is the major guide for determining the research design. 2 Furthermore, case definitions and designs were applied variably. The lack of standardization is reflected in differences in the reporting of these case studies. Generally, case study research is viewed as allowing much more freedom and flexibility. 5 , 24 However, this flexibility and the lack of uniform specifications lead to confusion.

Methodologic Triangulation

Methodologic triangulation, as described in the literature, can be somewhat confusing as it can refer to either data-collection methods or research designs. 6 , 8 For example, methodologic triangulation can allude to qualitative and quantitative methods, indicating a paradigmatic connection. Methodologic triangulation can also point to qualitative and quantitative data-collection methods, analysis, and interpretation without specific philosophical stances. 6 , 8 Regarding “data-collection methods with no philosophical stances,” we would recommend using the wording “data source triangulation” instead. Thus, the demarcation between the method and the data-collection procedures will be clearer.

Within-Method and Between/Across-Method Triangulation

Yin 1 advocated the use of multiple sources of evidence so that a case or cases can be investigated more comprehensively and accurately. Most studies included multiple data-collection procedures. Five studies employed a variety of qualitative data-collection procedures, and 3 studies used qualitative and quantitative data-collection procedures (mixed methods). In contrast, no study contained 2 or more quantitative data-collection procedures. In particular, quantitative data-collection procedures—such as validated, reliable questionnaires, scales, or assessments—were not used exhaustively. The prerequisites for using multiple data-collection procedures are availability, the knowledge and skill of the researcher, and sufficient financial funds. 1 To meet these prerequisites, research teams consisting of members with different levels of training and experience are necessary. Multidisciplinary research teams need to be aware of the strengths and weaknesses of different data sources and collection procedures. 1

Qualitative methods of analysis and results

When using multiple data sources and analysis methods, it is necessary to present the results in a coherent manner. Although the importance of multiple data sources and analysis has been emphasized, 1 , 5 the description of triangulation has tended to be brief. Thus, traceability of the research process is not always ensured. The sparse description of the data-analysis triangulation procedure may be due to the limited number of words in publications or the complexity involved in merging the different data sources.

Only a few concrete recommendations regarding the operationalization of the data-analysis triangulation with the qualitative data process were found. 25 A total of 3 approaches have been proposed 25 : (1) the intuitive approach, in which researchers intuitively connect information from different data sources; (2) the procedural approach, in which each comparative or contrasting step in triangulation is documented to ensure transparency and replicability; and (3) the intersubjective approach, which necessitates a group of researchers agreeing on the steps in the triangulation process. For each case study, one of these 3 approaches needs to be selected, carefully carried out, and documented. Thus, in-depth examination of the data can take place. Farmer et al 25 concluded that most researchers take the intuitive approach; therefore, triangulation is not clearly articulated. This trend is also evident in our scoping review.

Mixed-methods analysis and results

Few studies in this scoping review used a combination of qualitative and quantitative analysis. However, creating a comprehensive stand-alone picture of a case from both qualitative and quantitative methods is challenging. Findings derived from different data types may not automatically coalesce into a coherent whole. 4 O’Cathain et al 26 described 3 techniques for combining the results of qualitative and quantitative methods: (1) developing a triangulation protocol; (2) following a thread by selecting a theme from 1 component and following it across the other components; and (3) developing a mixed-methods matrix.

The most detailed description of the conducting of triangulation is the triangulation protocol. The triangulation protocol takes place at the interpretation stage of the research process. 26 This protocol was developed for multiple qualitative data but can also be applied to a combination of qualitative and quantitative data. 25 , 26 It is possible to determine agreement, partial agreement, “silence,” or dissonance between the results of qualitative and quantitative data. The protocol is intended to bring together the various themes from the qualitative and quantitative results and identify overarching meta-themes. 25 , 26

The “following a thread” technique is used in the analysis stage of the research process. To begin, each data source is analyzed to identify the most important themes that need further investigation. Subsequently, the research team selects 1 theme from 1 data source and follows it up in the other data source, thereby creating a thread. The individual steps of this technique are not specified. 26 , 27

A mixed-methods matrix is used at the end of the analysis. 26 All the data collected on a defined case are examined together in 1 large matrix, paying attention to cases rather than variables or themes. In a mixed-methods matrix (eg, a table), the rows represent the cases for which both qualitative and quantitative data exist. The columns show the findings for each case. This technique allows the research team to look for congruency, surprises, and paradoxes among the findings as well as patterns across multiple cases. In our review, we identified only one of these 3 approaches in the study by Roots and MacDonald. 20 These authors mentioned that a causal network analysis was performed using a matrix. However, no further details were given, and reference was made to a later publication. We could not find this publication.

Case Studies in Nursing Research and Recommendations

Because it focused on the implementation of NPs in primary health care, the setting of this scoping review was narrow. However, triangulation is essential for research in this area. This type of research was found to provide a good basis for understanding methodologic and data-analysis triangulation. Despite the lack of traceability in the description of the data and methodological triangulation, we believe that case studies are an appropriate design for exploring new nursing roles in existing health care systems. This is evidenced by the fact that case study research is widely used in many social science disciplines as well as in professional practice. 1 To strengthen this research method and increase the traceability in the research process, we recommend using the reporting guideline and reporting checklist by Rodgers et al. 9 This reporting checklist needs to be complemented with methodologic and data-analysis triangulation. A procedural approach needs to be followed in which each comparative step of the triangulation is documented. 25 A triangulation protocol or a mixed-methods matrix can be used for this purpose. 26 If there is a word limit in a publication, the triangulation protocol or mixed-methods matrix needs to be identified. A schematic representation of methodologic and data-analysis triangulation in case studies can be found in Figure 2 .

An external file that holds a picture, illustration, etc.
Object name is 10.1177_01939459241263011-fig2.jpg

Schematic representation of methodologic and data-analysis triangulation in case studies (own work).

Limitations

This study suffered from several limitations that must be acknowledged. Given the nature of scoping reviews, we did not analyze the evidence reported in the studies. However, 2 reviewers independently reviewed all the full-text reports with respect to the inclusion criteria. The focus on the primary care setting with NPs (master’s degree) was very narrow, and only a few studies qualified. Thus, possible important methodological aspects that would have contributed to answering the questions were omitted. Studies describing the triangulation of 2 or more quantitative data-collection procedures could not be included in this scoping review due to the inclusion and exclusion criteria.

Conclusions

Given the various processes described for methodologic and data-analysis triangulation, we can conclude that triangulation in case studies is poorly standardized. Consequently, the traceability of the research process is not always given. Triangulation is complicated by the confusion of terminology. To advance case study research in nursing, we encourage authors to reflect critically on methodologic and data-analysis triangulation and use existing tools, such as the triangulation protocol or mixed-methods matrix and the reporting guideline checklist by Rodgers et al, 9 to ensure more transparent reporting.

Supplemental Material

Acknowledgments.

The authors thank Simona Aeschlimann for her support during the screening process.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

An external file that holds a picture, illustration, etc.
Object name is 10.1177_01939459241263011-img1.jpg

Supplemental Material: Supplemental material for this article is available online.

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What Is A Hypothesis

Case interviews are often challenging because they are open-ended, with limitless possibilities of where you can go. There is some truth to this predicament – there is always more than just one way to crack a case. However, there are also ways to follow a system for every case you encounter that leads to fruitful results. One key component of consistently cracking case interviews involves being hypothesis-driven. But how do you do hypothesis-driven case interviews and, to cover the bases, what is a hypothesis?

What Is A Hypothesis, hypothesis driven approach, hypothesis examples, hypothesis definition

Hypothesis Definition

In the context of a consulting interview, a hypothesis definition is “a testable statement that needs further data for verification”. In other words, the meaning of a hypothesis is that it’s an educated guess that you think could be the answer to your client’s problem.

A hypothesis is therefore not always true. Instead, it is a starting point that ultimately leads you to the end point. Imagine your client comes to you with a problem, and the root cause is A, B, C, D, or E. Forming a hypothesis allows you to start with A, gather data to see if it’s correct, and if not, move onto B. You then keep going until you get to the right “letter” or answer to the case.

To be clear, you don’t always know your options upfront at the start of a case interview. Usually, after you gather data, you may find that option A was completely wrong, somewhat wrong, or right on track. Depending on the data, you either move onto a new hypothesis, revise it, or dig for more data, respectively. But for the purpose of a case interview, we feel this is a good hypothesis definition.

Hypothesis Example

Let’s use an example to shed some more light on what a hypothesis is, and how to use them in case interviews. Imagine your client is a shoe manufacturing company that has experienced a decrease in profitability over the past 12 months.

Non-Hypothesis Driven Approach

An approach without a hypothesis might result in a laundry list of questions like in the following exchange:

I understand that our client is looking to solve its profitability issues. I have identified a few areas that I’d like to look into.

  • Q: Has our client’s customer base declined?
  • A: No, the number of customers has actually increased.
  • Q: Oh, interesting. Has the client’s market share decreased?
  • A: No, market share has actually increased.
  • Q: Got it. Then has there been an increase in costs?
  • A: Yes, the shoe manufacturer recently invested in a new facility and has less negotiating power with its suppliers, driving up costs. Here is the data…

In this exchange, even though the candidate is getting closer to the right answer, there is no structure in the approach. The candidate is merely guessing potential problems rather than systematically getting to a solution.

Hypothesis Driven Approach

Using a hypothesis driven approach requires the following steps:

  • State a hypothesis based on the provided information.
  • Gather data to test the hypothesis.
  • Revise hypothesis as needed or offer a completely new one if the data proves your original hypothesis wrong.
  • Repeat steps 2-3 for additional buckets in your framework.

For example, you might start your hypothesis with a focus on revenue for a profitability issue. If you find that the reason is due to a decrease in volume, you may hypothesize that the issue is due to an increase in competition. You then ask for data regarding the competition, and adjust your hypothesis accordingly to the data or lack thereof.

Hypothesis Driven Approach Example

Let’s next see what a hypothesis driven approach looks like:

I understand that our client is looking to solve its profitability issues. My hypothesis is that the client is experiencing a decrease in revenue due to intense competition in the shoe market.

  • Q: Do we have any data on the sales volume?
  • A: We do, volume has actually been increasing.
  • Q: Oh, interesting. In that case, do we have any information on how prices have changed recently?
  • A: Prices have stayed the same.
  • Q: Got it. In that case, it seems like revenue is not the problem here. I would like to revise my earlier hypothesis and assume that our client is experiencing cost issues. Perhaps the fixed costs have increased due to investments or variable costs have increased due to an increase in raw material costs. Do we have any information on the fixed and variable costs?
  • A: We do, both variable and fixed costs have increased dramatically over the past 12 months. Here is the data…

As you can see, in this exchange, the candidate is drilling down into a hypothesis and sounds structured in his or her approach. The interviewer can be sure that even if the candidate is provided with another problem, he or she would be able to systematically get to the answer.

To be clear, you don’t need to always state “my hypothesis is X.” In fact, it may sound too robotic in an actual interview. This is just an example to show you how the hypothesis-driven approach looks.

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Using this approach ensures that you are displaying some of the key skills that consulting firms care about in the case interview: structure and clarity . If you can be hypothesis-driven in your case interview, you are displaying to your interviewer that you will be hypothesis-driven on the job. This means that you will be a much more efficient data collector, and conduct more efficient data analysis, to arrive at a solution quickly.

Do yourself a favor – use our hypothesis-driven case interview approach as you practice and watch your performance soar.

Additional Reading:

  • The Ladder Of Inference
  • The Pyramid Principle
  • Case Interview: Complete Prep Guide

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Organizing Your Social Sciences Research Paper: Writing a Case Study

  • Purpose of Guide
  • Design Flaws to Avoid
  • Independent and Dependent Variables
  • Glossary of Research Terms
  • Narrowing a Topic Idea
  • Broadening a Topic Idea
  • Extending the Timeliness of a Topic Idea
  • Academic Writing Style
  • Choosing a Title
  • Making an Outline
  • Paragraph Development
  • Executive Summary
  • The C.A.R.S. Model
  • Background Information
  • The Research Problem/Question
  • Theoretical Framework
  • Citation Tracking
  • Content Alert Services
  • Evaluating Sources
  • Reading Research Effectively
  • Primary Sources
  • Secondary Sources
  • Tiertiary Sources
  • What Is Scholarly vs. Popular?
  • Qualitative Methods
  • Quantitative Methods
  • Using Non-Textual Elements
  • Limitations of the Study
  • Common Grammar Mistakes
  • Writing Concisely
  • Avoiding Plagiarism
  • Footnotes or Endnotes?
  • Further Readings
  • Annotated Bibliography
  • Dealing with Nervousness
  • Using Visual Aids
  • Grading Someone Else's Paper
  • Types of Structured Group Activities
  • Group Project Survival Skills
  • Multiple Book Review Essay
  • Reviewing Collected Essays
  • Writing a Case Study
  • About Informed Consent
  • Writing Field Notes
  • Writing a Policy Memo
  • Writing a Research Proposal
  • Bibliography

The term case study refers to both a method of analysis and a specific research design for examining a problem, both of which are used in most circumstances to generalize across populations. This tab focuses on the latter--how to design and organize a research paper in the social sciences that analyzes a specific case.

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work. In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experience he or she has had that provides an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of his/her experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using him or her as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem.

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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2024 Theses Doctoral

Towards a Computational Theory of the Brain: The Simplest Neural Models, and a Hypothesis for Language

Mitropolsky, Daniel

Obtaining a computational understanding of the brain is one of the most important problems in basic science. However, the brain is an incredibly complex organ, and neurobiological research has uncovered enormous amounts of detail at almost every level of analysis (the synapse, the neuron, other brain cells, brain circuits, areas, and so on); it is unclear which of these details are conceptually significant to the basic way in which the brain computes. An essential approach to the eventual resolution of this problem is the definition and study of theoretical computational models, based on varying abstractions and inclusions of such details. This thesis defines and studies a family of models, called NEMO, based on a particular set of well-established facts or well-founded assumptions in neuroscience: atomic neural firing, random connectivity, inhibition as a local dynamic firing threshold, and fully local plasticity. This thesis asks: what sort of algorithms are possible in these computational models? To the extent possible, what seem to be the simplest assumptions where interesting computation becomes possible? Additionally, can we find algorithms for cognitive phenomena that, in addition to serving as a "proof of capacity" of the computational model, otherwise reflect what is known about these processes in the brain? The major contributions of this thesis include: 1. The formal definition of the basic-NEMO and NEMO models, with an explication of their neurobiological underpinnings (that is, realism as abstractions of the brain). 2. Algorithms for the creation of neural \emph{assemblies}, or highly dense interconnected subsets of neurons, and various operations manipulating such assemblies, including reciprocal projection, merge, association, disassociation, and pattern completion, all in the basic-NEMO model. Using these operations, we show the Turing-completeness of the NEMO model (with some specific additional assumptions). 3. An algorithm for parsing a small but non-trivial subset of English and Russian (and more generally any regular language) in the NEMO model, with meta-features of the algorithm broadly in line with what is known about language in the brain. 4. An algorithm for parsing a much larger subset of English (and other languages), in particular handling dependent (embedded) clauses, in the NEMO model with some additional memory assumptions. We prove that an abstraction of this algorithm yields a new characterization of the context-free languages. 5. Algorithms for the blocks-world planning task, which involves outputting a sequence of steps to rearrange a stack of cubes in one order into another target order, in the NEMO model. A side consequence of this work is an algorithm for a chaining operation in basic-NEMO. 6. Algorithms for several of the most basic and initial steps in language acquisition in the baby brain. This includes an algorithm for the learning of the simplest, concrete nouns and action verbs (words like "cat" and "jump") from whole sentences in basic-NEMO with a novel representation of word and contextual inputs. Extending the same model, we present an algorithm for an elementary component of syntax, namely learning the word order of 2-constituent intransitive and 3-constituent transitive sentences. These algorithms are very broadly in line with what is known about language in the brain.

  • Computer science
  • Neurosciences
  • Brain--Physiology
  • Language acquisition
  • Computational linguistics
  • Computational neuroscience
  • English language
  • Russian language

thumnail for Mitropolsky_columbia_0054D_18727.pdf

More About This Work

  • DOI Copy DOI to clipboard
  • DOI: 10.54097/zw1t3y94
  • Corpus ID: 272032426

Analysis of Multimodal Metaphor and Values Representation in Children’s Picture Books

  • Published in International Journal of… 20 August 2024
  • Education, Linguistics

7 References

Conceptual integration networks, reading images: the grammar of visual design, metaphors we live by, comparative analysis of chinese and british children’s death education picture books from multimodal critical analysis—a case study of death in a nut and grandma’s amulet, related papers.

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The adoption of digital technologies by small and medium-sized enterprises for sustainability and value creation in pakistan: the application of a two-staged hybrid sem-ann approach.

analysis and hypothesis in case study

1. Introduction

  • RQ1: What is the impact of SMEs using various digital technologies on the creation of social and economic value?
  • RQ2: How does the creation of social and economic value impact SME performance?

2. Theoretical Background

2.1. social media applications (smas), 2.2. ai-enabled applications (aeas), 2.3. big data analytics (bda), 2.4. iot applications (ioas), 2.5. blockchain applications (bcas), 2.6. economic value (ecv), 2.7. social value (sov), 2.8. sme performance, 3. hypothesis development, 3.1. social media applications (smas) and economic value and social value, 3.2. ai-enabled applications (aeas) and economic value and social value, 3.3. big data analytics (bda) and economic value and social value, 3.4. iot applications (ioas) and economic value and social value, 3.5. blockchain applications (bcas) and economic value and social value, 3.6. economic value (ecv) and sme performance, 3.7. social value (sov) and sme performance, 4. research methodology, 4.1. research design, 4.2. data collection: procedure and sample, 4.3. measures, 4.4. statistical analysis, 5.1. demographic characteristics, 5.2. measurement model evaluation, 5.3. structural model evaluation, 5.4. artificial neural network analysis, 5.5. ranking of predictors, 6. discussion, 6.1. theoretical implications, 6.2. practical implications, 7. conclusions, 7.1. limitations and future research, 7.2. future research directions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

SMAsSocial media applications are very popular among younger people.12345
I believe different social media applications provide business value to our enterprise.12345
I think SMEs are dependent on social media to fulfill their marketing requirements.12345
I believe that social media helps develop business activities for SMEs.12345
AEAsSMEs apply AI technologies to help them remodel various business activities.12345
I believe applications of AI can help in the supply chain activities of SMEs.12345
Applications of AI can reduce the operational cost of SMEs.12345
I believe that SMEs can use AI applications to develop their customer interaction process.12345
BDAI believe that data analytics has gained huge momentum in recent years.12345
The application of big data analytics helps in the real-time analysis of customer data.12345
I believe that applications of big data analytics help in the decision-making process.12345
I think SMEs should adopt big data analytics technology to gain a competitive advantage.12345
IoTThe IoT can facilitate the rapid exchange of data in a real-time scenario.12345
I believe that applications of the IoT can help in improving the upscaling process in the SMEs.12345
Applications of the IoT can provide a scalable information system that helps SMEs exchange information quickly.12345
Applications of the IoT help SMEs sense, seize, and reconfigure external opportunities.12345
BCAsBlockchain is considered a digital ledger, which presents the detailed history of various transactions.12345
I believe blockchain technology can save operational costs for SMEs.12345
I think applications of blockchain are secured for SMEs.12345
I believe that SMEs should adopt blockchain technology to gain a competitive advantage.12345
ECVSMEs can gain economic value through profit maximization.12345
The adoption of different technologies can provide economic value to SMEs.12345
The economic value changes if the price of the good or the service changes.12345
I believe that SME leadership should focus more on adopting new-edge technologies.12345
I believe product development costs can be significantly reduced if SMEs adopt appropriate technologies.12345
SOVSMEs can gain social benefits if they perform their work to benefit society.12345
I believe that social value emerges from the concept of corporate social responsibility programs.12345
Improving social value is an important aspect of SMEs.12345
Customers may favor those SMEs that spend more to uplift the society.12345
I believe that social values are shared values among the employees of the SMEs.12345
SMPI believe that the performance of SMEs can be improved by appropriately adopting modern technologies.12345
The social value of SMEs can impact the overall performance of SMEs.12345
Leadership support can play a crucial role in improving SME performance.12345
  • Mago, S.; Modiba, F.S. Does Informal Finance Matter for Micro and Small Businesses in Africa? Small Bus. Int. Rev. 2020 , 6 , e415. [ Google Scholar ] [ CrossRef ]
  • Raza, S.A.; Minai, M.S.; Zain, A.Y.M.; Tariq, T.A.; Khuwaja, F.M. Dissection of Small Businesses in Pakistan: Issues and Directions. Int. J. Entrep. 2018 , 22 . [ Google Scholar ]
  • Khan, N.R.; Awang, M.; Zulkifli, C.M. Small and Medium Enterprises and Human Resource Practices in Pakistan. Int. J. Asian Soc. Sci. 2013 , 3 , 460–471. [ Google Scholar ]
  • Dar, M.S.; Ahmed, S.; Raziq, A. Small and Medium-Size Enterprises in Pakistan: Definition and Critical Issues. Pakistan Bus. Rev. 2017 , 19 , 46–70. [ Google Scholar ]
  • Etuk, R.U.; Etuk, G.R.; Michael, B. Small and Medium Scale Enterprises (SMEs) and Nigeria’s Economic Development. Small 2014 , 11 , 35. [ Google Scholar ] [ CrossRef ]
  • Naradda Gamage, S.K.; Ekanayake, E.M.S.; Abeyrathne, G.; Prasanna, R.; Jayasundara, J.; Rajapakshe, P.S.K. A Review of Global Challenges and Survival Strategies of Small and Medium Enterprises (SMEs). Economies 2020 , 8 , 79. [ Google Scholar ] [ CrossRef ]
  • Asgary, A.; Ozdemir, A.I.; Özyürek, H. Small and Medium Enterprises and Global Risks: Evidence from Manufacturing SMEs in Turkey. Int. J. Disaster Risk Sci. 2020 , 11 , 59–73. [ Google Scholar ] [ CrossRef ]
  • Herr, H.; Nettekoven, Z.M. The Role of Small and Medium-Sized Enterprises in Development: What Can Be Learned from the German Experience? Global Labour University Working Paper ; International Labour Organization (ILO): Geneva, Switzerland, 2018. [ Google Scholar ]
  • Bokhari, A. Small and Medium-Sized Enterprises (SMEs) in Pakistan 2020. Available online: https://www.nation.com.pk/27-Nov-2020/small-and-medium-sized-enterprises-smes-in-pakistan (accessed on 5 February 2024).
  • Tribune, T. Efforts on to Boost Sindh SMEs Competitiveness 2021. Available online: https://intracen.org/node/8630 (accessed on 5 February 2024).
  • Gherghina, Ș.C.; Botezatu, M.A.; Hosszu, A.; Simionescu, L.N. Small and Medium-Sized Enterprises (SMEs): The Engine of Economic Growth through Investments and Innovation. Sustainability 2020 , 12 , 347. [ Google Scholar ] [ CrossRef ]
  • Johnson, M.P.; Schaltegger, S. Two Decades of Sustainability Management Tools for SMEs: How Far Have We Come? J. Small Bus. Manag. 2016 , 54 , 481–505. [ Google Scholar ] [ CrossRef ]
  • Costa, J.; Matias, J.C.O. Open Innovation 4.0 as an Enhancer of Sustainable Innovation Ecosystems. Sustainability 2020 , 12 , 8112. [ Google Scholar ] [ CrossRef ]
  • Ukko, J.; Nasiri, M.; Saunila, M.; Rantala, T. Sustainability Strategy as a Moderator in the Relationship between Digital Business Strategy and Financial Performance. J. Clean. Prod. 2019 , 236 , 117626. [ Google Scholar ] [ CrossRef ]
  • Indiparambil, J.J.; Collage, S.; Mullakkanam, K. Strategic to Sustainable Human Resource Management: Shifting Paradigms of Personal Managerial Trends. Int. J. Bus. Manag. Invent. 2019 , 8 , 65–70. [ Google Scholar ]
  • Legner, C.; Eymann, T.; Hess, T.; Matt, C.; Böhmann, T.; Drews, P.; Mädche, A.; Urbach, N.; Ahlemann, F. Digitalization: Opportunity and Challenge for the Business and Information Systems Engineering Community. Bus. Inf. Syst. Eng. 2017 , 59 , 301–308. [ Google Scholar ] [ CrossRef ]
  • Caiazza, R.; Belitski, M.; Audretsch, D.B. From Latent to Emergent Entrepreneurship: The Knowledge Spillover Construction Circle. J. Technol. Transf. 2020 , 45 , 694–704. [ Google Scholar ] [ CrossRef ]
  • Autio, E. Strategic Entrepreneurial Internationalization: A Normative Framework. Strateg. Entrep. J. 2017 , 11 , 211–227. [ Google Scholar ] [ CrossRef ]
  • Baskerville, R.L.; Myers, M.D.; Yoo, Y. Digital First: The Ontological Reversal and New Challenges for IS Research. MIS Q. 2020 , 44 , 509–523. [ Google Scholar ] [ CrossRef ]
  • Autio, E.; Mudambi, R.; Yoo, Y. Digitalization and Globalization in a Turbulent World: Centrifugal and Centripetal Forces. Glob. Strateg. J. 2021 , 11 , 3–16. [ Google Scholar ] [ CrossRef ]
  • Jalil, M.F.; Lynch, P.; Marikan, D.A.B.A.; Isa, A.H.B.M. The Influential Role of Artificial Intelligence (AI) Adoption in Digital Value Creation for Small and Medium Enterprises (SMEs): Does Technological Orientation Mediate This Relationship? AI Soc. 2024 , 1–22. [ Google Scholar ] [ CrossRef ]
  • Hinchcliffe, D.; Kim, P. Social Business by Design: Transformative Social Media Strategies for the Connected Company ; John Wiley & Sons: Hoboken, NJ, USA, 2012; ISBN 1118283627. [ Google Scholar ]
  • Anderson, J.C.; Gerbing, D.W. Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychol. Bull. 1988 , 103 , 411. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Kar, A.K. Why Do Small and Medium Enterprises Use Social Media Marketing and What Is the Impact: Empirical Insights from India. Int. J. Inf. Manag. 2020 , 53 , 102103. [ Google Scholar ] [ CrossRef ]
  • Meske, C.; Stieglitz, S. Adoption and Use of Social Media in Small and Medium-Sized Enterprises. In Proceedings of the Practice-Driven Research on Enterprise Transformation: 6th Working Conference, PRET 2013, Utrecht, The Netherlands, 6 June 2013; Proceedings 6. Springer: Berlin/Heidelberg, Germany, 2013; pp. 61–75. [ Google Scholar ]
  • Sharma, S.; Gahlawat, V.K.; Rahul, K.; Mor, R.S.; Malik, M. Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics. Logistics 2021 , 5 , 66. [ Google Scholar ] [ CrossRef ]
  • Dey, P.K.; Chowdhury, S.; Abadie, A.; Vann Yaroson, E.; Sarkar, S. Artificial Intelligence-Driven Supply Chain Resilience in Vietnamese Manufacturing Small-and Medium-Sized Enterprises. Int. J. Prod. Res. 2023 , 62 , 5417–5456. [ Google Scholar ] [ CrossRef ]
  • Žigienė, G.; Rybakovas, E.; Alzbutas, R. Artificial Intelligence Based Commercial Risk Management Framework for SMEs. Sustainability 2019 , 11 , 4501. [ Google Scholar ] [ CrossRef ]
  • Wang, J.; Lu, Y.; Fan, S.; Hu, P.; Wang, B. How to Survive in the Age of Artificial Intelligence? Exploring the Intelligent Transformations of SMEs in Central China. Int. J. Emerg. Mark. 2022 , 17 , 1143–1162. [ Google Scholar ] [ CrossRef ]
  • Egwuonwu, A.; Mendy, J.; Smart-Oruh, E.; Egwuonwu, A. Drivers of Big Data Analytics’ Adoption and Implications of Management Decision-Making on Big Data Adoption and Firms’ Financial and Nonfinancial Performance: Evidence From Nigeria’s Manufacturing and Service Industries. IEEE Trans. Eng. Manag. 2023 , 71 , 11907–11922. [ Google Scholar ] [ CrossRef ]
  • Babu, M.M.; Rahman, M.; Alam, A.; Dey, B.L. Exploring Big Data-Driven Innovation in the Manufacturing Sector: Evidence from UK Firms. Ann. Oper. Res. 2024 , 333 , 689–716. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Sestino, A.; Prete, M.I.; Piper, L.; Guido, G. Internet of Things and Big Data as Enablers for Business Digitalization Strategies. Technovation 2020 , 98 , 102173. [ Google Scholar ] [ CrossRef ]
  • Struyf, B.; Van Bockhaven, W.; Matthyssens, P. Value-Creation for Industry 4.0 and SMEs Data-Driven Growth: Strategies and Resource Alignment. In Big Data in Small Business ; Edward Elgar Publishing: Cheltenham, UK, 2021; pp. 64–103. ISBN 1839100168. [ Google Scholar ]
  • Hongyun, T.; Sohu, J.M.; Khan, A.U.; Junejo, I.; Shaikh, S.N.; Akhtar, S.; Bilal, M. Navigating the Digital Landscape: Examining the Interdependencies of Digital Transformation and Big Data in Driving SMEs’ Innovation Performance. Kybernetes ahead-of-print. 2023 . [ Google Scholar ] [ CrossRef ]
  • Dutta, P.; Choi, T.-M.; Somani, S.; Butala, R. Blockchain Technology in Supply Chain Operations: Applications, Challenges and Research Opportunities. Transp. Res. Part E Logist. Transp. Rev. 2020 , 142 , 102067. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Purwaningsih, E.; Muslikh, M.; Suhaeri, S.; Basrowi, B. Utilizing Blockchain Technology in Enhancing Supply Chain Efficiency and Export Performance, and Its Implications on the Financial Performance of SMEs. Uncertain Supply Chain. Manag. 2024 , 12 , 449–460. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Al-Rahmi, W.M.; Almogren, A.S.; Yahaya, N.; Vighio, M.S.; Al-maatuok, Q.; Al-Rahmi, A.M.; Al-Adwan, A.S. Acceptance of Mobile Learning Technology by Teachers: Influencing Mobile Self-Efficacy and 21st-Century Skills-Based Training. Sustainability 2023 , 15 , 8514. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Vighio, M.S.; Dahri, M.H. A Survey on Technology Supported Collaborative Learning Tools and Techniques in Teacher Education. In Proceedings of the 2019 International Conference on Information Science and Communication Technology (ICISCT), IEEE, Karachi, Pakistan, 9–10 March 2019; pp. 1–9. [ Google Scholar ]
  • Dahri, N.A.; Yahaya, N.; Al-Rahmi, W.M.; Vighio, M.S.; Alblehai, F.; Soomro, R.B.; Shutaleva, A. Investigating AI-Based Academic Support Acceptance and Its Impact on Students’ Performance in Malaysian and Pakistani Higher Education Institutions. Educ. Inf. Technol. 2024 , 1–50. [ Google Scholar ] [ CrossRef ]
  • Digital Pakistan. 2019. Available online: https://www.dawn.com/news/1520932/digital-pakistan (accessed on 1 July 2020).
  • Ahani, A.; Rahim, N.Z.A.; Nilashi, M. Forecasting Social CRM Adoption in SMEs: A Combined SEM-Neural Network Method. Comput. Human Behav. 2017 , 75 , 560–578. [ Google Scholar ] [ CrossRef ]
  • Barney, J. Firm Resources and Sustained Competitive Advantage. J. Manag. 1991 , 17 , 99–120. [ Google Scholar ] [ CrossRef ]
  • Teece, D.J.; Pisano, G.P.; Shuen, A. Dynamic Capabilities and Strategic Management ; Center for Research in Management, University of California, Berkeley: Berkeley, CA, USA, 1992. [ Google Scholar ]
  • Mikalef, P.; Gupta, M. Artificial Intelligence Capability: Conceptualization, Measurement Calibration, and Empirical Study on Its Impact on Organizational Creativity and Firm Performance. Inf. Manag. 2021 , 58 , 103434. [ Google Scholar ] [ CrossRef ]
  • Ghasemaghaei, M. Understanding the Impact of Big Data on Firm Performance: The Necessity of Conceptually Differentiating among Big Data Characteristics. Int. J. Inf. Manag. 2021 , 57 , 102055. [ Google Scholar ] [ CrossRef ]
  • Rahman, M.S.; Hossain, M.A.; Fattah, F.A.M.A. Does Marketing Analytics Capability Boost Firms’ Competitive Marketing Performance in Data-Rich Business Environment? J. Enterp. Inf. Manag. 2021 , 35 , 455–480. [ Google Scholar ] [ CrossRef ]
  • Hossain, M.A.; Akter, S.; Yanamandram, V. Why Doesn’t Our Value Creation Payoff: Unpacking Customer Analytics-Driven Value Creation Capability to Sustain Competitive Advantage. J. Bus. Res. 2021 , 131 , 287–296. [ Google Scholar ] [ CrossRef ]
  • Ritter, T.; Lettl, C. The Wider Implications of Business-Model Research. Long Range Plann. 2018 , 51 , 1–8. [ Google Scholar ] [ CrossRef ]
  • Matsuno, K.; Zhu, Z.; Rice, M.P. Innovation Process and Outcomes for Large J Apanese Firms: Roles of Entrepreneurial Proclivity and Customer Equity. J. Prod. Innov. Manag. 2014 , 31 , 1106–1124. [ Google Scholar ] [ CrossRef ]
  • Day, G.S. The Capabilities of Market-Driven Organizations. J. Mark. 1994 , 58 , 37–52. [ Google Scholar ] [ CrossRef ]
  • Nyachanchu, T.O.; Chepkwony, J.; Bonuke, R. Role of Dynamic Capabilities in the Performance of Manufacturing Firms in Nairobi County, Kenya. Eur. Sci. J. ESJ 2017 , 13 , 438. [ Google Scholar ] [ CrossRef ]
  • Land, A.; Gruchmann, T.; Siems, E.; Beske-Janssen, P. Dynamic Capabilities Theory. In Handbook of Theories for Purchasing, Supply Chain and Management Research ; Edward Elgar Publishing: Cheltenham, UK, 2022; pp. 378–398. ISBN 1839104503. [ Google Scholar ]
  • McKevitt, D.; Davis, P. Microenterprises: How They Interact with Public Procurement Processes. Int. J. Public Sect. Manag. 2013 , 26 , 469–480. [ Google Scholar ] [ CrossRef ]
  • Matarazzo, M.; Penco, L.; Profumo, G.; Quaglia, R. Digital Transformation and Customer Value Creation in Made in Italy SMEs: A Dynamic Capabilities Perspective. J. Bus. Res. 2021 , 123 , 642–656. [ Google Scholar ] [ CrossRef ]
  • Dyduch, W.; Chudziński, P.; Cyfert, S.; Zastempowski, M. Dynamic Capabilities, Value Creation and Value Capture: Evidence from SMEs under Covid-19 Lockdown in Poland. PLoS ONE 2021 , 16 , e0252423. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Canhoto, A.I.; Quinton, S.; Pera, R.; Molinillo, S.; Simkin, L. Digital Strategy Aligning in SMEs: A Dynamic Capabilities Perspective. J. Strateg. Inf. Syst. 2021 , 30 , 101682. [ Google Scholar ] [ CrossRef ]
  • Khurana, I.; Dutta, D.K.; Ghura, A.S. SMEs and Digital Transformation during a Crisis: The Emergence of Resilience as a Second-Order Dynamic Capability in an Entrepreneurial Ecosystem. J. Bus. Res. 2022 , 150 , 623–641. [ Google Scholar ] [ CrossRef ]
  • Vrontis, D.; Chaudhuri, R.; Chatterjee, S. Adoption of Digital Technologies by SMEs for Sustainability and Value Creation: Moderating Role of Entrepreneurial Orientation. Sustainability 2022 , 14 , 7949. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Vighio, M.S.; Alismaiel, O.A.; Al-Rahmi, W.M. Assessing the Impact of Mobile-Based Training on Teachers’ Achievement and Usage Attitude. Int. J. Interact. Mob. Technol. 2022 , 66 , 107–129. [ Google Scholar ] [ CrossRef ]
  • Kaplan, A.M.; Haenlein, M. Users of the World, Unite! The Challenges and Opportunities of Social Media. Bus. Horiz. 2010 , 53 , 59–68. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Al-Rahmi, W.M.; Almogren, A.S.; Yahaya, N.; Vighio, M.S.; Al-Maatuok, Q. Mobile-Based Training and Certification Framework for Teachers’ Professional Development. Sustainability 2023 , 15 , 5839. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Vighio, M.S.; Das Bather, J.; Arain, A.A. Factors Influencing the Acceptance of Mobile Collaborative Learning for the Continuous Professional Development of Teachers. Sustainability 2021 , 13 , 13222. [ Google Scholar ] [ CrossRef ]
  • Abed, S.S.; Dwivedi, Y.K.; Williams, M.D. Social Commerce as a Business Tool in Saudi Arabia’s SMEs. Int. J. Indian Cult. Bus. Manag. 2016 , 13 , 1–19. [ Google Scholar ] [ CrossRef ]
  • Salam, M.T.; Imtiaz, H.; Burhan, M. The Perceptions of SME Retailers towards the Usage of Social Media Marketing amid COVID-19 Crisis. J. Entrep. Emerg. Econ. 2021 , 13 , 588–605. [ Google Scholar ] [ CrossRef ]
  • Malita, L. Social Media Time Management Tools and Tips. Procedia Comput. Sci. 2011 , 3 , 747–753. [ Google Scholar ] [ CrossRef ]
  • Walsh, M.F.; Lipinski, J. The Role of the Marketing Function in Small and Medium Sized Enterprises. J. Small Bus. Enterp. Dev. 2009 , 16 , 569–585. [ Google Scholar ] [ CrossRef ]
  • Ware, J. Wearable Technologies and Journalism Ethics: Students’ Perceptions of Google Glass. Teach. J. Mass Commun. 2018 , 8 , 17–24. [ Google Scholar ]
  • Wangler, L.; Botthof, A. E-Governance: Digitalisierung Und KI in Der Öffentlichen Verwaltung. In Künstliche Intelligenz Technologien Anwendung|Gesellschaft ; Springer: Berlin/Heidelberg, Germany, 2019; pp. 122–141. [ Google Scholar ]
  • Oana, O.; Cosmin, T.; Valentin, N.C. Artificial Intelligence-a New Field of Computer Science Which Any Business Should Consider. Ovidius Univ. Ann. Econ. Sci. Ser. 2017 , 17 , 356–360. [ Google Scholar ]
  • Dahri, N.A.; Vighio, M.S.; Al-Rahmi, W.M.; Alismaiel, O.A. Usability Evaluation of Mobile App for the Sustainable Professional Development of Teachers. Int. J. Interact. Mob. Technol. 2022 , 16 , 4–30. [ Google Scholar ] [ CrossRef ]
  • Morabito, V. Big Data and Analytics. In Strategic and Organizational Impacts ; Springer: Cham, Switzerland, 2015. [ Google Scholar ]
  • Barton, D.; Court, D. Making Advanced Analytics Work for You. Harv. Bus. Rev. 2012 , 90 , 78–83. [ Google Scholar ] [ PubMed ]
  • Davenport, T.H.; Harris, J.G. Competing on Analytics: The New Science of Winning ; Harvard Business Review Press: Cambridge, MA, USA, 2007; Volume 15, p. 24. [ Google Scholar ]
  • Sen, D.; Ozturk, M.; Vayvay, O. An Overview of Big Data for Growth in SMEs. Procedia-Social Behav. Sci. 2016 , 235 , 159–167. [ Google Scholar ] [ CrossRef ]
  • Ogbuokiri, B.O.; Udanor, C.N.; Agu, M.N. Implementing Bigdata Analytics for Small and Medium Enterprise (SME) Regional Growth. IOSR J. Comput. Eng. 2015 , 17 , 35–43. [ Google Scholar ]
  • Chatterjee, S.; Rana, N.P.; Dwivedi, Y.K. Social Media as a Tool of Knowledge Sharing in Academia: An Empirical Study Using Valance, Instrumentality and Expectancy (VIE) Approach. J. Knowl. Manag. 2020 , 24 , 2531–2552. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Kar, A.K.; Dwivedi, Y.K. Intention to Use IoT by Aged Indian Consumers. J. Comput. Inf. Syst. 2022 , 62 , 655–666. [ Google Scholar ] [ CrossRef ]
  • Gubbi, J.; Buyya, R.; Marusic, S.; Palaniswami, M. Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions. Futur. Gener. Comput. Syst. 2013 , 29 , 1645–1660. [ Google Scholar ] [ CrossRef ]
  • Chen, H.; Chiang, R.H.L.; Storey, V.C. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Q. 2012 , 36 , 1165–1188. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S. Antecedence of Attitude towards IoT Usage: A Proposed Unified Model for IT Professionals and Its Validation. Int. J. Hum. Cap. Inf. Technol. Prof. 2021 , 12 , 13–34. [ Google Scholar ] [ CrossRef ]
  • Higginbotham, S. Wow, IoT for Small Businesses Can Be so Easy 2018. Available online: https://staceyoniot.com/wow-iot-for-small-businesses-can-be-so-easy/ (accessed on 1 July 2024).
  • Chabani, Z.; Hamouche, S.; Said, R. Is Blockchain Technology Applicable in Small and Medium-Sized Enterprises? In Proceedings of the International Conference on Digital Technologies and Applications, Fez, Morocco, 29–30 January 2021; Springer: Berlin/Heidelberg, Germany, 2021; pp. 505–514. [ Google Scholar ]
  • Gausdal, A.H.; Czachorowski, K.V.; Solesvik, M.Z. Applying Blockchain Technology: Evidence from Norwegian Companies. Sustainability 2018 , 10 , 1985. [ Google Scholar ] [ CrossRef ]
  • Al-Rahmi, W.M.; Yahaya, N.; Aldraiweesh, A.A.; Alamri, M.M.; Aljarboa, N.A.; Alturki, U.; Aljeraiwi, A.A. Integrating Technology Acceptance Model with Innovation Diffusion Theory: An Empirical Investigation on Students’ Intention to Use E-Learning Systems. IEEE Access 2019 , 7 , 26797–26809. [ Google Scholar ] [ CrossRef ]
  • Oh, J.; Shong, I. A Case Study on Business Model Innovations Using Blockchain: Focusing on Financial Institutions. Asia Pacific J. Innov. Entrep. 2017 , 11 , 335–344. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Chaudhuri, R.; Vrontis, D. Investigating the Impacts of Microlevel CSR Activities on Firm Sustainability: Mediating Role of CSR Performance and Moderating Role of Top Management Support. Cross Cult. Strateg. Manag. 2022 , 30 , 123–141. [ Google Scholar ] [ CrossRef ]
  • Ullah, N.; Mugahed Al-Rahmi, W.; Alzahrani, A.I.; Alfarraj, O.; Alblehai, F.M. Blockchain Technology Adoption in Smart Learning Environments. Sustainability 2021 , 13 , 1801. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Chaudhuri, R.; Vrontis, D.; Thrassou, A.; Ghosh, S.K. Adoption of Artificial Intelligence-Integrated CRM Systems in Agile Organizations in India. Technol. Forecast. Soc. Change 2021 , 168 , 120783. [ Google Scholar ] [ CrossRef ]
  • Falck, O.; Heblich, S.; Luedemann, E. Identity and Entrepreneurship: Do School Peers Shape Entrepreneurial Intentions? Small Bus. Econ. 2012 , 39 , 39–59. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Chaudhuri, R.; Shah, M.; Maheshwari, P. Big Data Driven Innovation for Sustaining SME Supply Chain Operation in Post COVID-19 Scenario: Moderating Role of SME Technology Leadership. Comput. Ind. Eng. 2022 , 168 , 108058. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Chatterjee, S.; Nguyen, B. Value Co-Creation and Social Media at Bottom of Pyramid (BOP). Bottom Line 2021 , 34 , 101–123. [ Google Scholar ] [ CrossRef ]
  • Shahedul Quader, M.; Kamal, M.M.; Hassan, A.B.M.E. Sustainability of Positive Relationship between Environmental Performance and Profitability of SMEs: A Case Study in the UK. J. Enterprising Communities People Places Glob. Econ. 2016 , 10 , 138–163. [ Google Scholar ] [ CrossRef ]
  • Santos, M. CSR in SMEs: Strategies, Practices, Motivations and Obstacles. Soc. Responsib. J. 2011 , 7 , 490–508. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S. Security and Privacy Issues in E-Commerce: A Proposed Guidelines to Mitigate the Risk. In Proceedings of the 2015 IEEE International Advance Computing Conference (IACC), IEEE, Banglore, India, 12–13 June 2015; pp. 393–396. [ Google Scholar ]
  • Brouthers, K.D.; Nakos, G.; Dimitratos, P. SME Entrepreneurial Orientation, International Performance, and the Moderating Role of Strategic Alliances. Entrep. Theory Pract. 2015 , 39 , 1161–1187. [ Google Scholar ] [ CrossRef ]
  • Marolt, M.; Zimmermann, H.-D.; Pucihar, A. Social Media Use and Business Performance in SMEs: The Mediating Roles of Relational Social Commerce Capability and Competitive Advantage. Sustainability 2022 , 14 , 15029. [ Google Scholar ] [ CrossRef ]
  • Ali Qalati, S.; Li, W.; Ahmed, N.; Ali Mirani, M.; Khan, A. Examining the Factors Affecting SME Performance: The Mediating Role of Social Media Adoption. Sustainability 2020 , 13 , 75. [ Google Scholar ] [ CrossRef ]
  • Fan, M.; Qalati, S.A.; Khan, M.A.S.; Shah, S.M.M.; Ramzan, M.; Khan, R.S. Effects of Entrepreneurial Orientation on Social Media Adoption and SME Performance: The Moderating Role of Innovation Capabilities. PLoS ONE 2021 , 16 , e0247320. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Sedalo, G.; Boateng, H.; Kosiba, J.P. Exploring Social Media Affordance in Relationship Marketing Practices in SMEs. Digit. Bus. 2022 , 2 , 100017. [ Google Scholar ] [ CrossRef ]
  • Bruce, E.; Keelson, S.; Amoah, J.; Bankuoru Egala, S. Social Media Integration: An Opportunity for SMEs Sustainability. Cogent Bus. Manag. 2023 , 10 , 2173859. [ Google Scholar ] [ CrossRef ]
  • Davenport, T.; Guha, A.; Grewal, D.; Bressgott, T. How Artificial Intelligence Will Change the Future of Marketing. J. Acad. Mark. Sci. 2020 , 48 , 24–42. [ Google Scholar ] [ CrossRef ]
  • Belhadi, A.; Mani, V.; Kamble, S.S.; Khan, S.A.R.; Verma, S. Artificial Intelligence-Driven Innovation for Enhancing Supply Chain Resilience and Performance under the Effect of Supply Chain Dynamism: An Empirical Investigation. Ann. Oper. Res. 2024 , 333 , 627–652. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Necula, S.-C.; Păvăloaia, V.-D. AI-Driven Recommendations: A Systematic Review of the State of the Art in E-Commerce. Appl. Sci. 2023 , 13 , 5531. [ Google Scholar ] [ CrossRef ]
  • Krishnan, C.; Gupta, A.; Gupta, A.; Singh, G. Impact of Artificial Intelligence-Based Chatbots on Customer Engagement and Business Growth. In Deep Learning for Social Media Data Analytics ; Springer: Cham, Switzerland, 2022; pp. 195–210. [ Google Scholar ]
  • Taherdoost, H.; Madanchian, M. Artificial Intelligence and Knowledge Management: Impacts, Benefits, and Implementation. Computers 2023 , 12 , 72. [ Google Scholar ] [ CrossRef ]
  • Rosunee, S.; Unmar, R. AI for Social Good: Opportunities for Inclusive and Sustainable Development. In Artificial Intelligence, Engineering Systems and Sustainable Development ; Emerald Publishing Limited: Bingley, UK, 2024; pp. 245–256. ISBN 1837535418. [ Google Scholar ]
  • Leszkiewicz, A.; Hormann, T.; Krafft, M. Smart Business and the Social Value of AI. In Smart Industry–Better Management ; Emerald Publishing Limited: Bingley, UK, 2022; pp. 19–34. ISBN 1877-6361. [ Google Scholar ]
  • Ashaari, M.A.; Singh, K.S.D.; Abbasi, G.A.; Amran, A.; Liebana-Cabanillas, F.J. Big Data Analytics Capability for Improved Performance of Higher Education Institutions in the Era of IR 4.0: A Multi-Analytical SEM & ANN Perspective. Technol. Forecast. Soc. Change 2021 , 173 , 121119. [ Google Scholar ]
  • Shah, S.; Wiese, J. Reality of Big Data Adoption in Supply Chain for Sustainable Manufacturing SMEs. In Proceedings of the 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), IEEE, Stuttgart, Germany, 17–20 June 2018; pp. 1–6. [ Google Scholar ]
  • Yaqoob, I.; Hashem, I.A.T.; Gani, A.; Mokhtar, S.; Ahmed, E.; Anuar, N.B.; Vasilakos, A. V Big Data: From Beginning to Future. Int. J. Inf. Manag. 2016 , 36 , 1231–1247. [ Google Scholar ] [ CrossRef ]
  • Mishra, A.; Maheswarappa, S.S.; Maity, M.; Samu, S. Adolescent’s EWOM Intentions: An Investigation into the Roles of Peers, the Internet and Gender. J. Bus. Res. 2018 , 86 , 394–405. [ Google Scholar ] [ CrossRef ]
  • Chatterjee, S.; Kar, A.K.; Mustafa, S.Z. Securing IoT Devices in Smart Cities of India: From Ethical and Enterprise Information System Management Perspective. Enterp. Inf. Syst. 2021 , 15 , 585–615. [ Google Scholar ] [ CrossRef ]
  • Atieh, A.M.; Cooke, K.O.; Osiyevskyy, O. The Role of Intelligent Manufacturing Systems in the Implementation of Industry 4.0 by Small and Medium Enterprises in Developing Countries. Eng. Reports 2023 , 5 , e12578. [ Google Scholar ] [ CrossRef ]
  • Dutta, G.; Kumar, R.; Sindhwani, R.; Singh, R.K. Digital Transformation Priorities of India’s Discrete Manufacturing SMEs–a Conceptual Study in Perspective of Industry 4.0. Compet. Rev. Int. Bus. J. 2020 , 30 , 289–314. [ Google Scholar ] [ CrossRef ]
  • Muridzi, G. Implication of Internet of Things (IoT) on Organisational Performance for SMEs in Emerging Economies: A Systematic Review. Technol. Audit Prod. Reserv. 2023 , 6 , 27–35. [ Google Scholar ] [ CrossRef ]
  • Widagdo, B.; Rofik, M. Internet of Things as Engine of Economic Growth in Indonesia. Indones. J. Bus. Econ. 2019 , 2 , 255–264. [ Google Scholar ] [ CrossRef ]
  • Amara, K.; Altinay, F.; Altinay, Z.; Dagli, G. Artificial Intelligence and Sustainable Educational Systems. In Computational Intelligence and Blockchain in Complex Systems ; Elsevier: Amsterdam, The Netherlands, 2024; pp. 199–204. [ Google Scholar ]
  • Javaid, M.; Haleem, A.; Singh, R.P.; Khan, S.; Suman, R. Blockchain Technology Applications for Industry 4.0: A Literature-Based Review. Blockchain Res. Appl. 2021 , 2 , 100027. [ Google Scholar ] [ CrossRef ]
  • Chen, J.; Cai, T.; He, W.; Chen, L.; Zhao, G.; Zou, W.; Guo, L. A Blockchain-Driven Supply Chain Finance Application for Auto Retail Industry. Entropy 2020 , 22 , 95. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Mukkamala, R.R.; Vatrapu, R.; Ray, P.K.; Sengupta, G.; Halder, S. Blockchain for Social Business: Principles and Applications. IEEE Eng. Manag. Rev. 2018 , 46 , 94–99. [ Google Scholar ] [ CrossRef ]
  • Gomez-Trujillo, A.M.; Velez-Ocampo, J.; Gonzalez-Perez, M.A. Trust, Transparency, and Technology: Blockchain and Its Relevance in the Context of the 2030 Agenda. In The Palgrave Handbook of Corporate Sustainability in the Digital Era ; Palgrave Macmillan: Cham, Switzerland, 2021; pp. 561–580. [ Google Scholar ]
  • Ronaghi, M.H.; Mosakhani, M. The Effects of Blockchain Technology Adoption on Business Ethics and Social Sustainability: Evidence from the Middle East. Environ. Dev. Sustain. 2022 , 24 , 6834–6859. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Rua, O.; França, A.; Fernández Ortiz, R. Key Drivers of SMEs Export Performance: The Mediating Effect of Competitive Advantage. J. Knowl. Manag. 2018 , 22 , 257–279. [ Google Scholar ] [ CrossRef ]
  • Boers, R.D. Social Responsibility & SME Competitiveness. Bachelor’s Thesis, JAMK Centre for Competitiveness, Jyväskylä, Finland, 2020. [ Google Scholar ]
  • Elkington, J. The Triple Bottom Line for 21st Century Business. J. Exp. Psychol. Gen. 1997 , 136 , 37–51. [ Google Scholar ]
  • Creswell, J.W.; Creswell, J.D. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches ; Sage Publications: Thousand Oaks, CA, USA, 2017; ISBN 1506386717. [ Google Scholar ]
  • Bell, E.; Bryman, A.; Harley, B. Business Research Methods ; Oxford University Press: Oxford, UK, 2022; ISBN 0198869444. [ Google Scholar ]
  • Dlodlo, N.; Dhurup, M. Drivers of E-Marketing Adoption among Small and Medium Enterprises (SMEs) and Variations with Age of Business Owners. Mediterr. J. Soc. Sci. 2013 , 4 , 53–66. [ Google Scholar ] [ CrossRef ]
  • Goodman, L.A. Snowball Sampling. Ann. Math. Stat. 1961 , 32 , 148–170. [ Google Scholar ] [ CrossRef ]
  • Reinartz, W.; Haenlein, M.; Henseler, J. An Empirical Comparison of the Efficacy of Covariance-Based and Variance-Based SEM. Int. J. Res. Mark. 2009 , 26 , 332–344. [ Google Scholar ] [ CrossRef ]
  • Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E.; Tatham, R.L. Multivariate Data Analysis ; Pearson Prentice Hall: Upper Saddle River, NJ, USA, 2006; Volume 6. [ Google Scholar ]
  • Hair, J.F.; Black, W.C.; Babin, B.; Anderson, R.E. Multivariate Data Analysis: A Global Perspective ; Pearson Prentice Hall: Upper Saddle River, NJ, USA, 2010. [ Google Scholar ]
  • D O’Gorman, K.; MacIntosh, R. Research Methods for Business and Management: A Guide to Writing Your Dissertation ; Goodfellow Publishers Ltd.: Oxford, UK, 2015; ISBN 1910158526. [ Google Scholar ]
  • Almogren, A.S.; Al-Rahmi, W.M.; Dahri, N.A. Exploring Factors Influencing the Acceptance of ChatGPT in Higher Education: A Smart Education Perspective. Heliyon 2024 , 10 , e31887. [ Google Scholar ] [ CrossRef ]
  • Dahri, N.A.; Yahaya, N.; Al-Rahmi, W.M.; Aldraiweesh, A.; Alturki, U.; Almutairy, S.; Shutaleva, A.; Soomro, R.B. Extended TAM Based Acceptance of AI-Powered ChatGPT for Supporting Metacognitive Self-Regulated Learning in Education: A Mixed-Methods Study. Heliyon 2024 , 10 , e29317. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Kiani, K. CCI Defers Approval of Census Results until Elections, Dawn News. 2018. Available online: https://www.dawn.com/news/1410447 (accessed on 1 July 2024).
  • Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to Use and How to Report the Results of PLS-SEM. Eur. Bus. Rev. 2019 , 31 , 2–24. [ Google Scholar ] [ CrossRef ]
  • Abbasi, G.A.; Kumaravelu, J.; Goh, Y.-N.; Singh, K.S.D. Understanding the Intention to Revisit a Destination by Expanding the Theory of Planned Behaviour (TPB). Span. J. Mark. 2021 , 25 , 282–311. [ Google Scholar ] [ CrossRef ]
  • Abbasi, S.; Ayoob, T.; Malik, A.; Memon, S.I. Perceptions of Students Regarding E-Learning during Covid-19 at a Private Medical College. Pak. J. Med. Sci. 2020 , 36 , S57. [ Google Scholar ] [ CrossRef ]
  • Moon, K.; Brewer, T.D.; Januchowski-Hartley, S.R.; Adams, V.M.; Blackman, D.A. A Guideline to Improve Qualitative Social Science Publishing in Ecology and Conservation Journals. Ecol. Soc. 2016 , 21 , 17. [ Google Scholar ] [ CrossRef ]
  • Soomro, S.; Soomro, A.B.; Bhatti, T.; Gulzar, Y. Gender-Wise Perception of Students towards Blended Learning in Higher Education: Pakistan. arXiv 2022 , arXiv:2204.07886. [ Google Scholar ] [ CrossRef ]
  • Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a Silver Bullet. J. Mark. Theory Pract. 2011 , 19 , 139–152. [ Google Scholar ] [ CrossRef ]
  • Hair, J.F., Jr.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V.G. Partial Least Squares Structural Equation Modeling (PLS-SEM) An Emerging Tool in Business Research. Eur. Bus. Rev. 2014 , 26 , 106–121. [ Google Scholar ] [ CrossRef ]
  • Sarstedt, M.; Ringle, C.M.; Hair, J.F. Partial Least Squares Structural Equation Modeling. In Handbook of Market Research ; Springer: Cham, Switzerland, 2021; pp. 587–632. [ Google Scholar ]
  • Chin, W.W. The Partial Least Squares Approach to Structural Equation Modeling. Mod. Methods Bus. Res. 1998 , 295 , 295–336. [ Google Scholar ]
  • Chopdar, P.K.; Paul, J.; Korfiatis, N.; Lytras, M.D. Examining the Role of Consumer Impulsiveness in Multiple App Usage Behavior among Mobile Shoppers. J. Bus. Res. 2022 , 140 , 657–669. [ Google Scholar ] [ CrossRef ]
  • Henseler, J.; Ringle, C.M.; Sarstedt, M. A New Criterion for Assessing Discriminant Validity in Variance-Based Structural Equation Modeling. J. Acad. Mark. Sci. 2015 , 43 , 115–135. [ Google Scholar ] [ CrossRef ]
  • Kline, R.B. Principles and Practice of Structural Equation Modeling ; Guilford publications: New York, NY, USA, 2015; ISBN 1462523358. [ Google Scholar ]
  • Fornell, C.; Larcker, D.F. Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. J. Mark. Res. 1981 , 18 , 382–388. [ Google Scholar ] [ CrossRef ]
  • Hair Jr, J.; Hair Jr, J.F.; Hult, G.T.M.; Ringle, C.M.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) ; Sage Publications: Thousand Oaks, NJ, USA, 2021; ISBN 1544396333. [ Google Scholar ]
  • Hair, J.; Hollingsworth, C.L.; Randolph, A.B.; Chong, A.Y.L. An Updated and Expanded Assessment of PLS-SEM in Information Systems Research. Ind. Manag. Data Syst. 2017 , 117 , 442–458. [ Google Scholar ] [ CrossRef ]
  • Henseler, J.; Ringle, C.M.; Sinkovics, R.R. The Use of Partial Least Squares Path Modeling in International Marketing. In New Challenges to International Marketing ; Emerald Group Publishing Limited: Bingley, UK, 2009; Volume 20, pp. 277–319. ISBN 1848554680. [ Google Scholar ]
  • Cohen, J. Statistical Power Analysis for the Behavioral Sciences ; Academic Press: Cambridge, MA, USA, 2013; ISBN 1483276481. [ Google Scholar ]
  • Lakey, B.; Cohen, S. Social Support and Theory. Soc. Support Meas. Interv. A Guid. Health Soc. Sci. 2000 , 29 , 29–49. [ Google Scholar ]
  • Dahri, N.A.; Yahaya, N.; Al-Rahmi, W.M.; Noman, H.A.; Alblehai, F.; Kamin, Y.B.; Soomro, R.B.; Shutaleva, A.; Al-Adwan, A.S. Investigating the Motivating Factors That Influence the Adoption of Blended Learning for Teachers’ Professional Development. Heliyon 2024 , 10 , e34900. [ Google Scholar ] [ CrossRef ]
  • Ooi, K.-B.; Tan, G.W.-H.; Al-Emran, M.; Al-Sharafi, M.A.; Capatina, A.; Chakraborty, A.; Dwivedi, Y.K.; Huang, T.-L.; Kar, A.K.; Lee, V.-H. The Potential of Generative Artificial Intelligence across Disciplines: Perspectives and Future Directions. J. Comput. Inf. Syst. 2023 , 1–32. [ Google Scholar ] [ CrossRef ]
  • Ooi, K.-B.; Tan, G.W.-H. Mobile Technology Acceptance Model: An Investigation Using Mobile Users to Explore Smartphone Credit Card. Expert Syst. Appl. 2016 , 59 , 33–46. [ Google Scholar ] [ CrossRef ]
  • Leong, L.-Y.; Jaafar, N.I.; Ainin, S. Understanding Facebook Commerce (f-Commerce) Actual Purchase from an Artificial Neural Network Perspective. J. Electron. Commer. Res. 2018 , 19 , 75–103. [ Google Scholar ]
  • Cabrera-Sánchez, J.-P.; Villarejo-Ramos, Á.F.; Liébana-Cabanillas, F.; Shaikh, A.A. Identifying Relevant Segments of AI Applications Adopters–Expanding the UTAUT2′s Variables. Telemat. Informatics 2021 , 58 , 101529. [ Google Scholar ] [ CrossRef ]
  • Hyndman, R.J.; Koehler, A.B. Another Look at Measures of Forecast Accuracy. Int. J. Forecast. 2006 , 22 , 679–688. [ Google Scholar ] [ CrossRef ]
  • Karaca, Y.; Moonis, M.; Zhang, Y.-D.; Gezgez, C. Mobile Cloud Computing Based Stroke Healthcare System. Int. J. Inf. Manag. 2019 , 45 , 250–261. [ Google Scholar ] [ CrossRef ]
  • Agnihotri, R.; Dingus, R.; Hu, M.Y.; Krush, M.T. Social Media: Influencing Customer Satisfaction in B2B Sales. Ind. Mark. Manag. 2016 , 53 , 172–180. [ Google Scholar ] [ CrossRef ]
  • Ahmad, S.Z.; Abu Bakar, A.R.; Ahmad, N. Social Media Adoption and Its Impact on Firm Performance: The Case of the UAE. Int. J. Entrep. Behav. Res. 2019 , 25 , 84–111. [ Google Scholar ] [ CrossRef ]
  • Singh, H.P.; Singh, A.; Alam, F.; Agrawal, V. Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training. Sustainability 2022 , 14 , 14119. [ Google Scholar ] [ CrossRef ]
  • Alyoussef, I.Y.; Al-Rahmi, W.M. Big Data Analytics Adoption via Lenses of Technology Acceptance Model: Empirical Study of Higher Education. Entrep. Sustain. Issues 2022 , 9 , 399. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Chatterjee, S.; Chaudhuri, R.; Vrontis, D. Big Data Analytics in Strategic Sales Performance: Mediating Role of CRM Capability and Moderating Role of Leadership Support. EuroMed J. Bus. 2022 , 17 , 295–311. [ Google Scholar ] [ CrossRef ]
  • de Vasconcelos, J.B.; Rocha, Á. Business Analytics and Big Data. Int. J. Inf. Manag. 2019 , 46 , 320–321. [ Google Scholar ] [ CrossRef ]
  • Jiwat, R.; Zhang, Z.L. Adopting Big Data Analytics (BDA) in Business-to-Business (B2B) Organizations–Development of a Model of Needs. J. Eng. Technol. Manag. 2022 , 63 , 101676. [ Google Scholar ] [ CrossRef ]
  • Popovič, A.; Hackney, R.; Tassabehji, R.; Castelli, M. The Impact of Big Data Analytics on Firms’ High Value Business Performance. Inf. Syst. Front. 2018 , 20 , 209–222. [ Google Scholar ] [ CrossRef ]
  • Alkaabi, K.A. Customers’ Purchasing Behavior toward Home-Based SME Products: Evidence from UAE Community. J. Enterprising Communities People Places Glob. Econ. 2022 , 16 , 472–493. [ Google Scholar ] [ CrossRef ]
  • Selamat, M.A.; Windasari, N.A. Chatbot for SMEs: Integrating Customer and Business Owner Perspectives. Technol. Soc. 2021 , 66 , 101685. [ Google Scholar ] [ CrossRef ]
  • Falahat, M.; Cheah, P.K.; Jayabalan, J.; Lee, C.M.J.; Kai, S.B. Big Data Analytics Capability Ecosystem Model for SMEs. Sustainability 2022 , 15 , 360. [ Google Scholar ] [ CrossRef ]
  • Asiri, A.M.; Al-Somali, S.A.; Maghrabi, R.O. The Integration of Sustainable Technology and Big Data Analytics in Saudi Arabian SMEs: A Path to Improved Business Performance. Sustainability 2024 , 16 , 3209. [ Google Scholar ] [ CrossRef ]
  • Al-Emran, M.; Malik, S.I.; Al-Kabi, M.N. Al-Emran, M.; Malik, S.I.; Al-Kabi, M.N. A Survey of Internet of Things (IoT) in Education: Opportunities and Challenges. In Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications. Studies in Computational Intelligence ; Springer: Cham, Switzerland, 2020; pp. 197–209. [ Google Scholar ]
  • Vermesan, O.; Friess, P. Internet of Things Applications-from Research and Innovation to Market Deployment ; Taylor & Francis: Abingdon, UK, 2014. [ Google Scholar ]
  • Nižetić, S.; Šolić, P.; Gonzalez-De, D.L.-I.; Patrono, L. Internet of Things (IoT): Opportunities, Issues and Challenges towards a Smart and Sustainable Future. J. Clean. Prod. 2020 , 274 , 122877. [ Google Scholar ] [ CrossRef ]
  • Denicolai, S.; Zucchella, A.; Magnani, G. Internationalization, Digitalization, and Sustainability: Are SMEs Ready? A Survey on Synergies and Substituting Effects among Growth Paths. Technol. Forecast. Soc. Change 2021 , 166 , 120650. [ Google Scholar ] [ CrossRef ]
  • Al-Jaroodi, J.; Mohamed, N. Industrial Applications of Blockchain. In Proceedings of the 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), IEEE, Las Vegas, NV, USA, 7–9 January 2019; pp. 550–555. [ Google Scholar ]
  • Okechukwu, N.; Agbai, E.P.; PCE, H.N.D. EXPLORING THE ROLE OF VALUE ORIENTATION IN SMALL AND MEDIUM-SIZED ENTERPRISE (SME) AND ENTREPRENEURIAL DEVELOPMENT IN NIGERIA. Disseminating Sch. Res. Across Globe 2024 , 1 , 5. [ Google Scholar ]
  • Riano Cruz, J.D. Investigating Formation of Social Capital Benefits for Value Creation and Strategy Enhancement: The Case of SMEs in the UK’s Construction Industry. Ph.D. Thesis, Newcastle University, Newcastle upon Tyne, UK, 2022. [ Google Scholar ]

Click here to enlarge figure

Demographic CharacteristicsN (305)(%)
Male23878.0
Female6722.0
Total305100
20–30 years 8126.6
31–40 years 10233.4
41–50 years 5317.4
51–60 years 5518.0
61 years and above144.60
Total305100
Never attended school4615.1
Primary3411.1
Secondary11638.0
Tenth Grade4013.0
Twelfth Grade3310.8
Graduation154.90
Graduation and higher216.90
Total305100
Sukkur16453.8
Larkana9531.1
Jacobabad1705.6
Khairpur2909.5
Total305100
Manufacturing6019.7
Retail9129.8
Wholesale3210.5
Agriculture3912.8
Livestock216.90
Poultry247.90
Services185.90
Other206.60
Total305100
ConstructsFactor LoadingCRAVEA
AI-Enabled Application (AEA)0.890.950.770.91
0.91
0.87
0.86
Blockchain Application (BCA)0.750.880.640.82
0.78
0.86
0.82
Big Data Analysis (BDA)0.860.920.740.88
0.86
0.85
0.86
Economic Value (ECV)0.810.900.630.86
0.77
0.77
0.87
0.77
IoT Application (IoA)0.820.880.650.82
0.78
0.86
0.76
Social Media Application (SMA)0.820.880.650.82
0.83
0.83
0.76
SME Performance (SMP)0.770.870.690.77
0.87
0.84
Social Value (SOV)0.770.880.590.82
0.81
0.83
0.73
0.68
ConstructsAEABCABDAECVIoTSMASMPSOV
AEA
BCA0.07
BDA0.050.12
ECV0.080.830.20
IoA0.050.700.150.78
SMA0.070.600.070.710.78
SMP0.070.640.120.780.750.63
SOV0.070.960.200.840.820.710.78
ConstructsAEABCABDAECVIoTSMASMPSOV
AEA
BCA0.06
BDA−0.030.10
ECV0.020.700.17
IoA0.020.580.130.66
SMA−0.050.490.040.600.65
SMP0.010.510.100.630.600.50
SOV0.050.800.180.710.670.590.61
VariablesR Adjusted R Remarks
Economic Value (ECV)0.620.61Substantial
SME Performance (SMP)0.450.44Moderate
Social Value (SOV)0.730.72Substantial
Hypothesesβt-ValueDecision
H1a = SMAs → ECV0.448.72Supported
H1b = SMAsSOV0.498.50Supported
H2a = AEAsECV0.010.17Unsupported
H2b = AEAsSOV0.020.65Unsupported
H3a = BDAECV0.224.23Supported
H3b = BDASOV0.163.07Supported
H4a = IoAsECV0.254.07Supported
H4b = IoAsSOV0.224.14Supported
H5a = BCAsECV0.092.23Supported
H5b = BCAsSOV0.082.26Supported
H6 = ECVSMP0.405.34Supported
H7 = SOVSMP0.324.01Supported
TrainingTesting
NSSERMSENSSERMSETotal Samples
27179.4181.84723407.9320.4830503
27788.7781.76632811.0260.6275503
27886.8331.78922710.1700.6137503
27183.9051.7971348.6020.5030503
26580.2031.81774011.3500.5327503
27583.1021.81913012.7650.6523503
26679.5191.82893912.5620.5675503
27479.6741.85443117.0140.7408503
27183.8131.79813407.2800.4627503
27787.0661.78362804.0420.3799503
27179.4181.84723407.9320.4830503
27788.7781.76632811.0260.6275503
Mean83.2311.8102Mean10.2740.5563
SD3.30750.0268SD3.38650.1001
Neural Network (NN)BCABDAIoASMA
NN (i)0.150.561.000.52
NN (ii)0.030.951.000.97
NN (iii)0.250.441.000.39
NN (iv)0.040.701.000.59
NN (v)0.170.401.000.52
NN (vi)0.100.951.000.83
NN (vii)0.100.111.000.23
NN (viii)0.220.641.000.56
NN (ix)0.080.351.000.48
NN (x)0.190.771.000.63
Average importance0.580.520.720.36
Normalized importance (%)19%77%100%63%
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.

Share and Cite

Soomro, R.B.; Memon, S.G.; Dahri, N.A.; Al-Rahmi, W.M.; Aldriwish, K.; A. Salameh, A.; Al-Adwan, A.S.; Saleem, A. The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach. Sustainability 2024 , 16 , 7351. https://doi.org/10.3390/su16177351

Soomro RB, Memon SG, Dahri NA, Al-Rahmi WM, Aldriwish K, A. Salameh A, Al-Adwan AS, Saleem A. The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach. Sustainability . 2024; 16(17):7351. https://doi.org/10.3390/su16177351

Soomro, Raheem Bux, Sanam Gul Memon, Nisar Ahmed Dahri, Waleed Mugahed Al-Rahmi, Khalid Aldriwish, Anas A. Salameh, Ahmad Samed Al-Adwan, and Atif Saleem. 2024. "The Adoption of Digital Technologies by Small and Medium-Sized Enterprises for Sustainability and Value Creation in Pakistan: The Application of a Two-Staged Hybrid SEM-ANN Approach" Sustainability 16, no. 17: 7351. https://doi.org/10.3390/su16177351

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IMAGES

  1. How To Do Case Study Analysis?

    analysis and hypothesis in case study

  2. 13 Different Types of Hypothesis (2024)

    analysis and hypothesis in case study

  3. Research Hypothesis: Definition, Types, Examples and Quick Tips (2022)

    analysis and hypothesis in case study

  4. Case Analysis Guide

    analysis and hypothesis in case study

  5. Hypothesis Testing with One Sample Case Study (Unit 7)

    analysis and hypothesis in case study

  6. Theoretical Hypothesis Case Study Help by PhD Experts

    analysis and hypothesis in case study

VIDEO

  1. Concept of Hypothesis

  2. Sahulat

  3. Sahulat

  4. Sahulat

  5. Sahulat

  6. [統計學] 第八講、Hypothesis Testing (1)

COMMENTS

  1. Writing a Case Analysis Paper

    Case study is unbounded and relies on gathering external information; case analysis is a self-contained subject of analysis. The scope of a case study chosen as a method of research is bounded. However, the researcher is free to gather whatever information and data is necessary to investigate its relevance to understanding the research problem.

  2. Case Study Method: A Step-by-Step Guide for Business Researchers

    Case study protocol is a formal document capturing the entire set of procedures involved in the collection of empirical material . It extends direction to researchers for gathering evidences, empirical material analysis, and case study reporting . This section includes a step-by-step guide that is used for the execution of the actual study.

  3. Case Study Methods and Examples

    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 ...

  4. Writing a Case Study Analysis

    Identify the key problems and issues in the case study. Formulate and include a thesis statement, summarizing the outcome of your analysis in 1-2 sentences. Background. Set the scene: background information, relevant facts, and the most important issues. Demonstrate that you have researched the problems in this case study. Evaluation of the Case

  5. Case Study

    Defnition: 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.

  6. How to Write a Strong Hypothesis

    4. Refine your hypothesis. You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain: The relevant variables; The specific group being studied; The predicted outcome of the experiment or analysis; 5.

  7. Writing a Case Study

    In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the ...

  8. What Is a Case Study?

    Revised on November 20, 2023. A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. A case study research design usually involves qualitative methods, but quantitative methods are ...

  9. How to Write a Strong Hypothesis

    Step 5: Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.

  10. Case Studies: Types, Designs, and Logics of Inference

    tion of case study analysis with a qualitative approach is a "methodological affinity, not a definitional entailment." Typology of Case Studies Most typologies of case studies reflect some variation of Lijphart's (1971:691) categories of atheoretical, interpretive, hypothesis-generating, theory-confirming, theory-informing, and

  11. Case Study Methodology of Qualitative Research: Key Attributes and

    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 ...

  12. Toward Developing a Framework for Conducting Case Study Research

    Data Analysis in of Case Study Research-Practice oriented- Theory oriented (Dul & Hak, 2008)- Exploration- Theory building- Theory testing ... Research phase which entails defining the type of case study based on the propositions and hypothesis (single case study or comparative case study) and selecting cases, data collection, and data analysis

  13. A Practical Guide to Writing Quantitative and Qualitative Research

    INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...

  14. PDF Hypothesis Testing

    23.1 How Hypothesis Tests Are Reported in the News 1. Determine the null hypothesis and the alternative hypothesis. 2. Collect and summarize the data into a test statistic. 3. Use the test statistic to determine the p-value. 4. The result is statistically significant if the p-value is less than or equal to the level of significance.

  15. Hypothesis Testing

    The Case Study was used to understand the overview of the hypothesis testing for data analysis on two independent samples. I feel the case study approach can help cement your understanding of hypothesis testing theory and look at real-life problems. As a disclaimer, I would like to highlight that this was purely an academic project and the ...

  16. What is a Case Study? Definition & Examples

    A case study is an in-depth investigation of a single person, group, event, or community. This research method involves intensively analyzing a subject to understand its complexity and context. The richness of a case study comes from its ability to capture detailed, qualitative data that can offer insights into a process or subject matter that ...

  17. Hypothesis Testing

    Step 5: Present your findings. The results of hypothesis testing will be presented in the results and discussion sections of your research paper, dissertation or thesis.. In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p-value).

  18. The case study approach

    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 ...

  19. Case Study Analysis: Examples + How-to Guide & Writing Tips

    Briefly introduce the problems and issues found in the case study. Discuss the theory you will be using in the analysis; Present the key points of the study and present any assumptions made during the analysis. Findings. This is where you present in more detail the specific problems you discovered in the case study.

  20. The Basics of a Case Study

    The thesis differs from the hypothesis in that the thesis is the statement that is proven true with the case study. The hypothesis is the question or idea that the researcher had going into the study. It is possible the hypothesis and thesis are the same. However, it is also possible that once all the research has been completed, the thesis ...

  21. A Necessary Dialogue: Theory in Case Study Research

    Abstract. This article is premised on the understanding that there are multiple dimensions of the case-theory relation and examines four of these: theory of the case, theory for the case, theory from the case, and a dialogical relation between theory and case. This fourth dimension is the article's key contribution to theorizing case study.

  22. Methodologic and Data-Analysis Triangulation in Case Studies: A Scoping

    Within-case analysis . In 7 studies, a within-case analysis was performed. 15-20,22 Six studies used qualitative data for the within-case analysis, and 1 study employed qualitative and quantitative data. Data were analyzed separately, consecutively, or in parallel. The themes generated from qualitative data were compared and then summarized.

  23. What Is A Hypothesis?

    Hypothesis Definition. In the context of a consulting interview, a hypothesis definition is "a testable statement that needs further data for verification". In other words, the meaning of a hypothesis is that it's an educated guess that you think could be the answer to your client's problem. A hypothesis is therefore not always true.

  24. Quantum DNA Encoder: A Case-Study in gRNA Analysis

    Quantum computing, with its potential to expedite specific tasks, requires a more precise definition of its benefits in early research. This paper introduces the Quantum DNA Encoder (QDE), a novel approach for encoding genetic information efficiently and effectively. Utilizing a simple circuit suitable for a 4-qubit system, QDE surpasses One-Hot Encoding (OHE) in creating better class ...

  25. Writing a Case Study

    A case study paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or among more than two subjects. ... In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been ...

  26. Towards a Computational Theory of the Brain: The Simplest Neural Models

    Obtaining a computational understanding of the brain is one of the most important problems in basic science. However, the brain is an incredibly complex organ, and neurobiological research has uncovered enormous amounts of detail at almost every level of analysis (the synapse, the neuron, other brain cells, brain circuits, areas, and so on); it is unclear which of these details are ...

  27. Navigating Total-factor Carbon Emission Efficiency in ...

    First, this study verifies the spatial nexus between the key independent and dependent variables through spatial autocorrelation tests. Fig. 2 illustrates the global Moran index results. The l n T C E E and l n D T I are positively significant at the 1% level for all periods. This indicates a significant spatial dependence characteristic of the clustering of TCEE and digital technology ...

  28. Sustainable Development of Digital Cultural Heritage: A Hybrid Analysis

    Cultural heritage crowdsourcing has emerged as a promising approach to address the challenges of digitizing and preserving cultural heritage, contributing to the sustainable development goals of cultural preservation and digital inclusivity. However, the long-term sustainability of these projects faces numerous obstacles. This study explores the key configurational determinants and dynamic ...

  29. [PDF] Analysis of Multimodal Metaphor and Values Representation in

    Children's picture books, as a form of text interwoven with vision and language, carry rich cultural information and educational functions. The purpose of this article is to explore the phenomenon of multimodal metaphor in children's picture books and reveal its influence on ideological construction. Firstly, the article compiles the research background and puts forward the research value ...

  30. Sustainability

    Digital technologies have revolutionized the business field, offering significant opportunities for small and medium-sized enterprises (SMEs) to enhance sustainability and value creation. This study investigates the impact of digital technology adoption on economic and social value creation, as well as SME performance. Specifically, it examines how social media applications, big data analytics ...