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Exploratory Research – Types, Methods and Examples

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Exploratory Research

Definition:

Exploratory research is a type of research design that is used to investigate a research question when the researcher has limited knowledge or understanding of the topic or phenomenon under study.

The primary objective of exploratory research is to gain insights and gather preliminary information that can help the researcher better define the research problem and develop hypotheses or research questions for further investigation.

Exploratory Research Methods

There are several types of exploratory research, including:

Literature Review

This involves conducting a comprehensive review of existing published research, scholarly articles, and other relevant literature on the research topic or problem. It helps to identify the gaps in the existing knowledge and to develop new research questions or hypotheses.

Pilot Study

A pilot study is a small-scale preliminary study that helps the researcher to test research procedures, instruments, and data collection methods. This type of research can be useful in identifying any potential problems or issues with the research design and refining the research procedures for a larger-scale study.

This involves an in-depth analysis of a particular case or situation to gain insights into the underlying causes, processes, and dynamics of the issue under investigation. It can be used to develop a more comprehensive understanding of a complex problem, and to identify potential research questions or hypotheses.

Focus Groups

Focus groups involve a group discussion that is conducted to gather opinions, attitudes, and perceptions from a small group of individuals about a particular topic. This type of research can be useful in exploring the range of opinions and attitudes towards a topic, identifying common themes or patterns, and generating ideas for further research.

Expert Opinion

This involves consulting with experts or professionals in the field to gain their insights, expertise, and opinions on the research topic. This type of research can be useful in identifying the key issues and concerns related to the topic, and in generating ideas for further research.

Observational Research

Observational research involves gathering data by observing people, events, or phenomena in their natural settings to gain insights into behavior and interactions. This type of research can be useful in identifying patterns of behavior and interactions, and in generating hypotheses or research questions for further investigation.

Open-ended Surveys

Open-ended surveys allow respondents to provide detailed and unrestricted responses to questions, providing valuable insights into their attitudes, opinions, and perceptions. This type of research can be useful in identifying common themes or patterns, and in generating ideas for further research.

Data Analysis Methods

Exploratory Research Data Analysis Methods are as follows:

Content Analysis

This method involves analyzing text or other forms of data to identify common themes, patterns, and trends. It can be useful in identifying patterns in the data and developing hypotheses or research questions. For example, if the researcher is analyzing social media posts related to a particular topic, content analysis can help identify the most frequently used words, hashtags, and topics.

Thematic Analysis

This method involves identifying and analyzing patterns or themes in qualitative data such as interviews or focus groups. The researcher identifies recurring themes or patterns in the data and then categorizes them into different themes. This can be helpful in identifying common patterns or themes in the data and developing hypotheses or research questions. For example, a thematic analysis of interviews with healthcare professionals about patient care may identify themes related to communication, patient satisfaction, and quality of care.

Cluster Analysis

This method involves grouping data points into clusters based on their similarities or differences. It can be useful in identifying patterns in large datasets and grouping similar data points together. For example, if the researcher is analyzing customer data to identify different customer segments, cluster analysis can be used to group similar customers together based on their demographic, purchasing behavior, or preferences.

Network Analysis

This method involves analyzing the relationships and connections between data points. It can be useful in identifying patterns in complex datasets with many interrelated variables. For example, if the researcher is analyzing social network data, network analysis can help identify the most influential users and their connections to other users.

Grounded Theory

This method involves developing a theory or explanation based on the data collected during the exploratory research process. The researcher develops a theory or explanation that is grounded in the data, rather than relying on pre-existing theories or assumptions. This can be helpful in developing new theories or explanations that are supported by the data.

Applications of Exploratory Research

Exploratory research has many practical applications across various fields. Here are a few examples:

• Marketing Research : In marketing research, exploratory research can be used to identify consumer needs, preferences, and behavior. It can also help businesses understand market trends and identify new market opportunities.
• Product Development: In product development, exploratory research can be used to identify customer needs and preferences, as well as potential design flaws or issues. This can help companies improve their product offerings and develop new products that better meet customer needs.
• Social Science Research: In social science research, exploratory research can be used to identify new areas of study, as well as develop new theories and hypotheses. It can also be used to identify potential research methods and approaches.
• Healthcare Research : In healthcare research, exploratory research can be used to identify new treatments, therapies, and interventions. It can also be used to identify potential risk factors or causes of health problems.
• Education Research: In education research, exploratory research can be used to identify new teaching methods and approaches, as well as identify potential areas of study for further research. It can also be used to identify potential barriers to learning or achievement.

Examples of Exploratory Research

Here are some more examples of exploratory research from different fields:

• Social Science : A researcher wants to study the experience of being a refugee, but there is limited existing research on this topic. The researcher conducts exploratory research by conducting in-depth interviews with refugees to better understand their experiences, challenges, and needs.
• Healthcare : A medical researcher wants to identify potential risk factors for a rare disease but there is limited information available. The researcher conducts exploratory research by reviewing medical records and interviewing patients and their families to identify potential risk factors.
• Education : A teacher wants to develop a new teaching method to improve student engagement, but there is limited information on effective teaching methods. The teacher conducts exploratory research by reviewing existing literature and interviewing other teachers to identify potential approaches.
• Technology : A software developer wants to develop a new app, but is unsure about the features that users would find most useful. The developer conducts exploratory research by conducting surveys and focus groups to identify user preferences and needs.
• Environmental Science : An environmental scientist wants to study the impact of a new industrial plant on the surrounding environment, but there is limited existing research. The scientist conducts exploratory research by collecting and analyzing soil and water samples, and conducting interviews with residents to better understand the impact of the plant on the environment and the community.

How to Conduct Exploratory Research

Here are the general steps to conduct exploratory research:

• Define the research problem: Identify the research problem or question that you want to explore. Be clear about the objective and scope of the research.
• Review existing literature: Conduct a review of existing literature and research on the topic to identify what is already known and where gaps in knowledge exist.
• Determine the research design : Decide on the appropriate research design, which will depend on the nature of the research problem and the available resources. Common exploratory research designs include case studies, focus groups, interviews, and surveys.
• Collect data: Collect data using the chosen research design. This may involve conducting interviews, surveys, or observations, or collecting data from existing sources such as archives or databases.
• Analyze data: Analyze the data collected using appropriate qualitative or quantitative techniques. This may include coding and categorizing qualitative data, or running descriptive statistics on quantitative data.
• I nterpret and report findings: Interpret the findings of the analysis and report them in a way that is clear and understandable. The report should summarize the findings, discuss their implications, and make recommendations for further research or action.
• Iterate : If necessary, refine the research question and repeat the process of data collection and analysis to further explore the topic.

When to use Exploratory Research

Exploratory research is appropriate in situations where there is limited existing knowledge or understanding of a topic, and where the goal is to generate insights and ideas that can guide further research. Here are some specific situations where exploratory research may be particularly useful:

• New product development: When developing a new product, exploratory research can be used to identify consumer needs and preferences, as well as potential design flaws or issues.
• Emerging technologies: When exploring emerging technologies, exploratory research can be used to identify potential uses and applications, as well as potential challenges or limitations.
• Developing research hypotheses: When developing research hypotheses, exploratory research can be used to identify potential relationships or patterns that can be further explored through more rigorous research methods.
• Understanding complex phenomena: When trying to understand complex phenomena, such as human behavior or societal trends, exploratory research can be used to identify underlying patterns or factors that may be influencing the phenomenon.
• Developing research methods : When developing new research methods, exploratory research can be used to identify potential issues or limitations with existing methods, and to develop new methods that better capture the phenomena of interest.

Purpose of Exploratory Research

The purpose of exploratory research is to gain insights and understanding of a research problem or question where there is limited existing knowledge or understanding. The objective is to explore and generate ideas that can guide further research, rather than to test specific hypotheses or make definitive conclusions.

Exploratory research can be used to:

• Identify new research questions: Exploratory research can help to identify new research questions and areas of inquiry, by providing initial insights and understanding of a topic.
• Develop hypotheses: Exploratory research can help to develop hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Identify patterns and trends : Exploratory research can help to identify patterns and trends in data, which can be used to guide further research or decision-making.
• Understand complex phenomena: Exploratory research can help to provide a deeper understanding of complex phenomena, such as human behavior or societal trends, by identifying underlying patterns or factors that may be influencing the phenomena.
• Generate ideas: Exploratory research can help to generate new ideas and insights that can be used to guide further research, innovation, or decision-making.

Characteristics of Exploratory Research

The following are the main characteristics of exploratory research:

• Flexible and open-ended : Exploratory research is characterized by its flexible and open-ended nature, which allows researchers to explore a wide range of ideas and perspectives without being constrained by specific research questions or hypotheses.
• Qualitative in nature : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, or observation, to gather rich and detailed data on the research problem.
• Limited scope: Exploratory research is generally limited in scope, focusing on a specific research problem or question, rather than attempting to provide a comprehensive analysis of a broader phenomenon.
• Preliminary in nature : Exploratory research is preliminary in nature, providing initial insights and understanding of a research problem, rather than testing specific hypotheses or making definitive conclusions.
• I terative process : Exploratory research is often an iterative process, where the research design and methods may be refined and adjusted as new insights and understanding are gained.
• I nductive approach : Exploratory research typically takes an inductive approach to data analysis, seeking to identify patterns and relationships in the data that can guide further research or hypothesis development.

Advantages of Exploratory Research

The following are some advantages of exploratory research:

• Provides initial insights: Exploratory research is useful for providing initial insights and understanding of a research problem or question where there is limited existing knowledge or understanding. It can help to identify patterns, relationships, and potential hypotheses that can guide further research.
• Flexible and adaptable : Exploratory research is flexible and adaptable, allowing researchers to adjust their methods and approach as they gain new insights and understanding of the research problem.
• Qualitative methods : Exploratory research typically relies on qualitative methods, such as in-depth interviews, focus groups, and observation, which can provide rich and detailed data that is useful for gaining insights into complex phenomena.
• Cost-effective : Exploratory research is often less costly than other research methods, such as large-scale surveys or experiments. It is typically conducted on a smaller scale, using fewer resources and participants.
• Useful for hypothesis generation : Exploratory research can be useful for generating hypotheses and testable propositions that can be further explored through more rigorous research methods.
• Provides a foundation for further research: Exploratory research can provide a foundation for further research by identifying potential research questions and areas of inquiry, as well as providing initial insights and understanding of the research problem.

Limitations of Exploratory Research

The following are some limitations of exploratory research:

• Limited generalizability: Exploratory research is typically conducted on a small scale and uses non-random sampling techniques, which limits the generalizability of the findings to a broader population.
• Subjective nature: Exploratory research relies on qualitative methods and is therefore subject to researcher bias and interpretation. The findings may be influenced by the researcher’s own perceptions, beliefs, and assumptions.
• Lack of rigor: Exploratory research is often less rigorous than other research methods, such as experimental research, which can limit the validity and reliability of the findings.
• Limited ability to test hypotheses: Exploratory research is not designed to test specific hypotheses, but rather to generate initial insights and understanding of a research problem. It may not be suitable for testing well-defined research questions or hypotheses.
• Time-consuming : Exploratory research can be time-consuming and resource-intensive, particularly if the researcher needs to gather data from multiple sources or conduct multiple rounds of data collection.
• Difficulty in interpretation: The open-ended nature of exploratory research can make it difficult to interpret the findings, particularly if the researcher is unable to identify clear patterns or relationships in the data.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Organizing an Exploratory Essay

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Exploratory essays are very different from argumentative essays. In fact, an exploratory essay is likely different from any other essay you’ve written. Instead of writing to convince an audience of the validity of a thesis, you will be writing to find out about a problem and perhaps to form some preliminary conclusions about how it might be solved.

But there is another aspect the exploratory genre that is equally important. An exploratory essay is, in essence, a retrospective of your writing and thinking process as you work through a problem. It describes when, how, and why you completed certain types of research. This kind of writing is about how you work through problems that require writing and research. You will have to be introspective and think about your thinking process in order for your essay to turn out well.

Very roughly, then, your exploratory essay may follow this sort of structure:

Introduction

The introduction should outline the problem you explored and why it’s important. In addition, you should briefly discuss 1) some of the problem’s possible causes; 2) the institutions and people involved with the problem; 3) some of the possible solutions to the problem. A brief overview of the types of sources you researched during your inquiry.

Body Paragraphs

Body paragraphs should discuss the inquiry process you followed to research your problem. These paragraphs should include the following:

• Introduction of source (title, author, type of media, publisher, publication date, etc.) and why you chose to use it in your exploration
• Important information you found in the source regarding your problem
• Why the information is important and dependable in relation to the problem
• Some personal introspection on how the source helped you, allowed you to think differently about the problem, or even fell short of your expectations and led you in a new direction in your research, which forms a transition into your next source.

The conclusion should restate the problem you explored, outline some of its possible causes, review the institutions and people involved, and highlight some possible solutions. If you still have any questions about the problem (and it’s ok to have some), you will discuss them here. Talk about why you think you still have questions regarding the problem you explored, where you might look to answer these questions, and what other forms of research you would have to do.

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How to write an exploratory essay [Updated 2023]

Unlike other types of essays, the exploratory essay does not present a specific argument or support a claim with evidence. Instead, an exploratory essay allows a writer to "explore" a topic and consider tentative conclusions about it. This article covers what you need to know to write a successful exploratory essay.

What is an exploratory essay?

An exploratory essay considers a topic or problem and explores possible solutions. This type of paper also sometimes includes background about how you have approached the topic, as well as information about your research process.

Whereas other types of essays take a concrete stance on an issue and offer extensive support for that stance, the exploratory essay covers how you arrived at an idea and what research materials and methods you used to explore it.

For example, an argumentative essay on expanding public transportation might argue that increasing public transit options improves citizens' quality of life. However, an exploratory essay would provide context for the issue and discuss what data and research you gathered to consider the problem.

What to include in an exploratory essay

Importantly, an exploratory essay does not reach a specific conclusion about a topic. Rather, it explores multiple conclusions and possibilities. So, for the above example, your exploratory essay might include several viewpoints about public transit, including research from urban planners, transportation advocates, and other experts.

Finally, an exploratory essay will include some reflection on your own research and writing process. You might be asked to draw some conclusions about how you could tackle your topic in an argumentative essay or you might reflect on what sources or pieces of evidence were most helpful as you were exploring the topic.

Ultimately, the primary goal of an exploratory essay is to make an inquiry about a topic or problem, investigate the context, and address possible solutions.

What to expect in an exploratory essay assignment

This section discusses what you can expect in an exploratory essay assignment, in terms of length, style, and sources. Instructors may also provide you with an exploratory essay example or an assignment rubric to help you determine if your essay meets the appropriate guidelines .

The expected length of an exploratory essay varies depending on the topic, course subject, and course level. For instance, an exploratory essay assigned in an upper-level sociology course will likely be longer than a similar assignment in an introductory course.

Like other essay types, exploratory essays typically include at least five paragraphs, but most range from a few pages to the length of a full research paper .

While exploratory essays will generally follow academic style guidelines, they differ from other essays because they tend to utilize a more reflective, personal tone. This doesn't mean that you can cast off academic style rules, however.

Rather, think of an exploratory essay as a venue for presenting your topic and methods to a sympathetic and intelligent audience of fellow researchers. Most importantly, make sure that your writing is clear, correct, and concise.

As an exploration of your approach to a topic, an exploratory essay will necessarily incorporate research material. As a result, you should expect to include a bibliography or references page with your essay. This page will list both the sources that you cite in your essay, as well as any sources that you may have consulted during your research process.

The citation style of your essay's bibliography will vary based on the subject of the course. For example, an exploratory essay for a sociology class will probably adhere to APA style , while an essay in a history class might use Chicago style .

Exploratory essay outline and format

An exploratory essay utilizes the same basic structure that you'll find in other essays. It includes an introduction, body paragraphs, and a conclusion. The introduction sets up the context for your topic, addresses why that topic is worthy of study, and states your primary research question(s).

The body paragraphs cover the research that you've conducted and often include overviews of the sources that you've consulted. The conclusion returns to your research question and considers possible solutions.

• Introduction

The introduction of an exploratory essay functions as an overview. In this section, you should provide context for your topic, explain why the topic is important, and state your research question:

• Context includes general information about the topic. This part of the introduction may also outline, or signpost, what the rest of the paper will cover.
• Topic importance helps readers "buy in" to your research. A few sentences that address the question, "so what?" will enable you to situate your research within an ongoing debate.
• The last part of of your introduction should clearly state your research question. It's okay to have more than one, depending on the assignment.

If you were writing an exploratory essay on public transportation, you might start by briefly introducing the recent history of public transit debates. Next, you could explain that public transportation research is important because it has a concrete impact on our daily lives. Finally, you might end your introduction by articulating your primary research questions.

While some individuals may choose not to utilize public transportation, decisions to expand or alter public transit systems affect the lives of all. As a result of my preliminary research, I became interested in exploring whether public transportation systems improve citizens' quality of life. In particular, does public transit only improve conditions for those who regularly use these systems? Or, do improvements in public transportation positively impact the quality of life for all individuals within a given city or region? The remainder of this essay explores the research around these questions and considers some possible conclusions.

Body paragraphs

The body paragraphs of an exploratory essay discuss the research process that you used to explore your topic. This section highlights the sources that you found most useful and explains why they are important to the debate.

You might also use the body paragraphs to address how individual resources changed your thinking about your topic. Most exploratory essays will have several body paragraphs.

One source that was especially useful to my research was a 2016 study by Richard J. Lee and Ipek N. Sener that considers the intersections between transportation planning and quality of life . They argue that, while planners have consistently addressed physical health and well-being in transportation plans, they have not necessarily factored in how mental and social health contributes to quality of life. Put differently, transportation planning has traditionally utilized a limited definition of quality of life and this has necessarily impacted data on the relationship between public transit and quality of life. This resource helped me to broaden my conception of quality of life to include all aspects of human health. It also enabled me to better understand the stakeholders involved in transportation decisions.

Your conclusion should return to the research question stated in your introduction. What are some possible solutions to your questions, based on the sources that you highlighted in your essay? While you shouldn't include new information in your conclusion, you can discuss additional questions that arose as you were conducting your research.

In my introduction, I asked whether public transit improves quality of life for all, not simply for users of public transportation. My research demonstrates that there are strong connections between public transportation and quality of life, but that researchers differ as to how quality of life is defined. Many conclude that public transit improves citizens' lives, but it is still not clear how public transit decisions affect non-users, since few studies have focused on this distinct group. As a result, I believe that more research is needed to answer the research questions that I posed above.

Frequently Asked Questions about exploratory essays

You should begin an exploratory essay by introducing the context for your topic, explaining the topic's importance, and outlining your original research question.

Like other types of essays, the exploratory essay has three primary parts:

Although an exploratory essay does not make a specific argument, your research question technically serves as your thesis.

Yes, you can use "I" throughout your paper. An exploratory essay is meant to explore your own research process, so a first-person perspective is appropriate.

You should end your exploratory essay with a succinct conclusion that returns to your research question and considers possible answers. You can also end by highlighting further questions you may have about your research.

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• USC Libraries
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Organizing Your Social Sciences Research Paper

• Types of Research Designs
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• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
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• Academic Writing Style
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• Scholarly vs. Popular Publications
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• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE : Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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Drafting an exploratory essay

Exploratory papers are NOT argument papers. An exploratory assignment is usually given so that students find ways to branch out in a specific topic without taking a stance. Exploratory papers can range from a full research paper to a short essay.

Introduction

The introduction should do several things for the reader:

Set context – this is where the author can begin to give general background information and set up a “map” of what the paper will discuss.

State importance – the introduction should also explain why the topic is important, it should compel the audience to read further and create interest in the topic.

State the question or topic of exploration – this can be one or several sentences or questions that states what the author is interested in finding out, why, and how they intend to do it.

An acceptable general structure for exploratory papers is given below:

Each paragraph or section should explain what source was used, say why it was chosen, include information found using the source, explain why the information is important, and reflect on the source and its information.

This format is meant as a basic outline and does not need to be repeated exactly the same way for every source.

The conclusion is very similar to the introduction in that it gives a general overview of what has been discussed. This section also ties up any loose ends not confronted in the body of the paper. Many times, the question is restated in the conclusion for reinforcement.

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Exploratory Research: Types & Characteristics

Consider a scenario where a juice bar owner feels that increasing the variety of juices will enable an increase in customers. However, he is not sure and needs more information. The owner intends to conduct exploratory research to find out; hence, he decides to do exploratory research to find out if expanding their juices selection will enable him to get more customers or if there is a better idea.

Another example of exploratory research is a podcast survey template that can be used to collect feedback about the podcast consumption metrics both from existing listeners as well as other podcast listeners that are currently not subscribed to this channel. This helps the author of the podcast create curated content that will gain a larger audience. Let’s explore this topic.

LEARN ABOUT: Research Process Steps

Content Index

Exploratory research: Definition

Primary research methods, secondary research methods, exploratory research: steps to conduct a research, characteristics of exploratory research, advantages of exploratory research, disadvantages of exploratory research, importance of exploratory research.

Exploratory research is defined as a research used to investigate a problem which is not clearly defined. It is conducted to have a better understanding of the existing research problem , but will not provide conclusive results. For such a research, a researcher starts with a general idea and uses this research as a medium to identify issues, that can be the focus for future research. An important aspect here is that the researcher should be willing to change his/her direction subject to the revelation of new data or insight. Such a research is usually carried out when the problem is at a preliminary stage. It is often referred to as grounded theory approach or interpretive research as it used to answer questions like what, why and how.

Types and methodologies of Exploratory research

While it may sound difficult to research something that has very little information about it, there are several methods which can help a researcher figure out the best research design, data collection methods and choice of subjects. There are two ways in which research can be conducted namely primary and secondary.. Under these two types, there are multiple methods which can used by a researcher. The data gathered from these research can be qualitative or quantitative . Some of the most widely used research designs include the following:

LEARN ABOUT: Best Data Collection Tools

Primary research is information gathered directly from the subject.  It can be through a group of people or even an individual. Such a research can be carried out directly by the researcher himself or can employ a third party to conduct it on their behalf. Primary research is specifically carried out to explore a certain problem which requires an in-depth study.

• Surveys/polls : Surveys /polls are used to gather information from a predefined group of respondents. It is one of the most important quantitative method. Various types of surveys  or polls can be used to explore opinions, trends, etc. With the advancement in technology, surveys can now be sent online and can be very easy to access. For instance, use of a survey app through tablets, laptops or even mobile phones. This information is also available to the researcher in real time as well. Nowadays, most organizations offer short length surveys and rewards to respondents, in order to achieve higher response rates.

LEARN ABOUT: Live polls for Classroom Experience

For example: A survey is sent to a given set of audience to understand their opinions about the size of mobile phones when they purchase one. Based on such information organization can dig deeper into the topic and make business related decision.

• Interviews: While you may get a lot of information from public sources, but sometimes an in person interview can give in-depth information on the subject being studied. Such a research is a qualitative research method . An interview with a subject matter expert can give you meaningful insights that a generalized public source won’t be able to provide. Interviews are carried out in person or on telephone which have open-ended questions to get meaningful information about the topic.

For example: An interview with an employee can give you more insights to find out the degree of job satisfaction, or an interview with a subject matter expert of quantum theory can give you in-depth information on that topic.

• Focus groups: Focus group is yet another widely used method in exploratory research. In such a method a group of people is chosen and are allowed to express their insights on the topic that is being studied. Although, it is important to make sure that while choosing the individuals in a focus group they should have a common background and have comparable experiences.

For example: A focus group helps a research identify the opinions of consumers if they were to buy a phone. Such a research can help the researcher understand what the consumer value while buying a phone. It may be screen size, brand value or even the dimensions. Based on which the organization can understand what are consumer buying attitudes, consumer opinions, etc.

• Observations: Observational research can be qualitative observation or quantitative observation . Such a research is done to observe a person and draw the finding from their reaction to certain parameters. In such a research, there is no direct interaction with the subject.

For example: An FMCG company wants to know how it’s consumer react to the new shape of their product. The researcher observes the customers first reaction and collects the data, which is then used to draw inferences from the collective information.

LEARN ABOUT: Causal Research

Secondary research is gathering information from previously published primary research. In such a research you gather information from sources likes case studies, magazines, newspapers, books, etc.

• Online research: In today’s world, this is one of the fastest way to gather information on any topic. A lot of data is readily available on the internet and the researcher can download it whenever he needs it. An important aspect to be noted for such a research is the genuineness and authenticity of the source websites that the researcher is gathering the information from.

For example: A researcher needs to find out what is the percentage of people that prefer a specific brand phone. The researcher just enters the information he needs in a search engine and gets multiple links with related information and statistics.

• Literature research : Literature research is one of the most inexpensive method used for discovering a hypothesis. There is tremendous amount of information available in libraries, online sources, or even commercial databases. Sources can include newspapers, magazines, books from library, documents from government agencies, specific topic related articles, literature, Annual reports, published statistics from research organizations and so on.

However, a few things have to be kept in mind while researching from these sources. Government agencies have authentic information but sometimes may come with a nominal cost. Also, research from educational institutions is generally overlooked, but in fact educational institutions carry out more number of research than any other entities.

Furthermore, commercial sources provide information on major topics like political agendas, demographics, financial information, market trends and information, etc.

For example: A company has low sales. It can be easily explored from available statistics and market literature if the problem is market related or organization related or if the topic being studied is regarding financial situation of the country, then research data can be accessed through government documents or commercial sources.

• Case study research: Case study research can help a researcher with finding more information through carefully analyzing existing cases which have gone through a similar problem. Such exploratory data analysis are very important and critical especially in today’s business world. The researcher just needs to make sure he analyses the case carefully in regards to all the variables present in the previous case against his own case. It is very commonly used by business organizations or social sciences sector or even in the health sector.

LEARN ABOUT: Level of Analysis

For example: A particular orthopedic surgeon has the highest success rate for performing knee surgeries. A lot of other hospitals or doctors have taken up this case to understand and benchmark the method in which this surgeon does the procedure to increase their success rate.

• Identify the problem : A researcher identifies the subject of research and the problem is addressed by carrying out multiple methods to answer the questions.
• Create the hypothesis : When the researcher has found out that there are no prior studies and the problem is not precisely resolved, the researcher will create a hypothesis based on the questions obtained while identifying the problem.
• Further research : Once the data has been obtained, the researcher will continue his study through descriptive investigation. Qualitative methods are used to further study the subject in detail and find out if the information is true or not.

LEARN ABOUT: Descriptive Analysis

• They are not structured studies
• It is usually low cost, interactive and open ended.
• It will enable a researcher answer questions like what is the problem? What is the purpose of the study? And what topics could be studied?
• To carry out exploratory research, generally there is no prior research done or the existing ones do not answer the problem precisely enough.
• It is a time consuming research and it needs patience and has risks associated with it.
• The researcher will have to go through all the information available for the particular study he is doing.
• There are no set of rules to carry out the research per se, as they are flexible, broad and scattered.
• The research needs to have importance or value. If the problem is not important in the industry the research carried out is ineffective.
• The research should also have a few theories which can support its findings as that will make it easier for the researcher to assess it and move ahead in his study
• Such a research usually produces qualitative data , however in certain cases quantitative data can be generalized for a larger sample through use of surveys and experiments.

LEARN ABOUT: Action Research

• The researcher has a lot of flexibility and can adapt to changes as the research progresses.
• It is usually low cost.
• It helps lay the foundation of a research, which can lead to further research.
• It enables the researcher understand at an early stage, if the topic is worth investing the time and resources  and if it is worth pursuing.
• It can assist other researchers to find out possible causes for the problem, which can be further studied in detail to find out, which of them is the most likely cause for the problem.
• Even though it can point you in the right direction towards what is the answer, it is usually inconclusive.
• The main disadvantage of exploratory research is that they provide qualitative data. Interpretation of such information can be judgmental and biased.
• Most of the times, exploratory research involves a smaller sample , hence the results cannot be accurately interpreted for a generalized population.
• Many a times, if the data is being collected through secondary research, then there is a chance of that data being old and is not updated.

LEARN ABOUT: Projective Techniques & Conformity Bias

Exploratory research is carried out when a topic needs to be understood in depth, especially if it hasn’t been done before. The goal of such a research is to explore the problem and around it and not actually derive a conclusion from it. Such kind of research will enable a researcher to  set a strong foundation for exploring his ideas, choosing the right research design and finding variables that actually are important for the in-depth analysis . Most importantly, such a research can help organizations or researchers save up a lot of time and resources, as it will enable the researcher to know if it worth pursuing.

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• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on 6 May 2022 by Tegan George . Revised on 20 January 2023.

Exploratory research is a methodology approach that investigates topics and research questions that have not previously been studied in depth.

Exploratory research is often qualitative in nature. However, a study with a large sample conducted in an exploratory manner can be quantitative as well. It is also often referred to as interpretive research or a grounded theory approach due to its flexible and open-ended nature.

Table of contents

When to use exploratory research, exploratory research questions, exploratory research data collection, step-by-step example of exploratory research, exploratory vs explanatory research, advantages and disadvantages of exploratory research, frequently asked questions about exploratory research.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use this type of research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

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Exploratory research questions are designed to help you understand more about a particular topic of interest. They can help you connect ideas to understand the groundwork of your analysis without adding any preconceived notions or assumptions yet.

Here are some examples:

• What effect does using a digital notebook have on the attention span of primary schoolers?
• What factors influence mental health in undergraduates?
• What outcomes are associated with an authoritative parenting style?
• In what ways does the presence of a non-native accent affect intelligibility?
• How can the use of a grocery delivery service reduce food waste in single-person households?

Collecting information on a previously unexplored topic can be challenging. Exploratory research can help you narrow down your topic and formulate a clear hypothesis , as well as giving you the ‘lay of the land’ on your topic.

Data collection using exploratory research is often divided into primary and secondary research methods, with data analysis following the same model.

Primary research

In primary research, your data is collected directly from primary sources : your participants. There is a variety of ways to collect primary data.

Some examples include:

• Survey methodology: Sending a survey out to the student body asking them if they would eat vegan meals
• Focus groups: Compiling groups of 8–10 students and discussing what they think of vegan options for dining hall food
• Interviews: Interviewing students entering and exiting the dining hall, asking if they would eat vegan meals

Secondary research

In secondary research, your data is collected from preexisting primary research, such as experiments or surveys.

Some other examples include:

• Case studies : Health of an all-vegan diet
• Literature reviews : Preexisting research about students’ eating habits and how they have changed over time
• Online polls, surveys, blog posts, or interviews; social media: Have other universities done something similar?

For some subjects, it’s possible to use large- n government data, such as the decennial census or yearly American Community Survey (ACS) open-source data.

How you proceed with your exploratory research design depends on the research method you choose to collect your data. In most cases, you will follow five steps.

We’ll walk you through the steps using the following example.

Therefore, you would like to focus on improving intelligibility instead of reducing the learner’s accent.

Step 1: Identify your problem

The first step in conducting exploratory research is identifying what the problem is and whether this type of research is the right avenue for you to pursue. Remember that exploratory research is most advantageous when you are investigating a previously unexplored problem.

Step 2: Hypothesise a solution

The next step is to come up with a solution to the problem you’re investigating. Formulate a hypothetical statement to guide your research.

Step 3. Design your methodology

Next, conceptualise your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyse data

Next, you proceed with collecting and analysing your data so you can determine whether your preliminary results are in line with your hypothesis.

In most types of research, you should formulate your hypotheses a priori and refrain from changing them due to the increased risk of Type I errors and data integrity issues. However, in exploratory research, you are allowed to change your hypothesis based on your findings, since you are exploring a previously unexplained phenomenon that could have many explanations.

Step 5: Avenues for future research

Decide if you would like to continue studying your topic. If so, it is likely that you will need to change to another type of research. As exploratory research is often qualitative in nature, you may need to conduct quantitative research with a larger sample size to achieve more generalisable results.

It can be easy to confuse exploratory research with explanatory research. To understand the relationship, it can help to remember that exploratory research lays the groundwork for later explanatory research.

Exploratory research investigates research questions that have not been studied in depth. The preliminary results often lay the groundwork for future analysis.

Explanatory research questions tend to start with ‘why’ or ‘how’, and the goal is to explain why or how a previously studied phenomenon takes place.

Like any other research design , exploratory research has its trade-offs: it provides a unique set of benefits but also comes with downsides.

• It can be very helpful in narrowing down a challenging or nebulous problem that has not been previously studied.
• It can serve as a great guide for future research, whether your own or another researcher’s. With new and challenging research problems, adding to the body of research in the early stages can be very fulfilling.
• It is very flexible, cost-effective, and open-ended. You are free to proceed however you think is best.

Disadvantages

• It usually lacks conclusive results, and results can be biased or subjective due to a lack of preexisting knowledge on your topic.
• It’s typically not externally valid and generalisable, and it suffers from many of the challenges of qualitative research .
• Since you are not operating within an existing research paradigm, this type of research can be very labour-intensive.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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Other students also liked, qualitative vs quantitative research | examples & methods, descriptive research design | definition, methods & examples, case study | definition, examples & methods.

Exploratory Research

Exploratory research, as the name implies, intends merely to explore the research questions and does not intend to offer final and conclusive solutions to existing problems. This type of research is usually conducted to study a problem that has not been clearly defined yet. Conducted in order to determine the nature of the problem, exploratory research is not intended to provide conclusive evidence, but helps us to have a better understanding of the problem.

When conducting exploratory research, the researcher ought to be willing to change his/her direction as a result of revelation of new data and new insights. [1] Accordingly, exploratory studies are often conducted using interpretive research methods and they answer to questions such as what, why and how.

Exploratory research design does not aim to provide the final and conclusive answers to the research questions, but merely explores the research topic with varying levels of depth. It has been noted that “exploratory research is the initial research, which forms the basis of more conclusive research. It can even help in determining the research design, sampling methodology and data collection method” [2] . Exploratory research “tends to tackle new problems on which little or no previous research has been done” [3] .

Unstructured interviews are the most popular primary data collection method with exploratory studies. Additionally, surveys , focus groups and observation methods can be used to collect primary data for this type of studies.

Examples of Exploratory Research Design

The following are some examples for studies with exploratory research design in business studies:

• A study into the role of social networking sites as an effective marketing communication channel
• An investigation into the ways of improvement of quality of customer services within hospitality sector in London
• An assessment of the role of corporate social responsibility on consumer behaviour in pharmaceutical industry in the USA

Differences between Exploratory and Conclusive Research

The difference between exploratory and conclusive research is drawn by Sandhursen (2000) [4] in a way that exploratory studies result in a range of causes and alternative options for a solution of a specific problem, whereas, conclusive studies identify the final information that is the only solution to an existing research problem.

In other words, exploratory research design simply explores the research questions, leaving room for further researches, whereas conclusive research design is aimed to provide final findings for the research.

Moreover, it has been stated that “an exploratory study may not have as rigorous as methodology as it is used in conclusive studies, and sample sizes may be smaller. But it helps to do the exploratory study as methodically as possible, if it is going to be used for major decisions about the way we are going to conduct our next study” [5] (Nargundkar, 2003, p.41).

Exploratory studies usually create scope for future research and the future research may have a conclusive design. For example, ‘a study into the implications of COVID-19 pandemic into the global economy’ is an exploratory research. COVID-19 pandemic is a recent phenomenon and the study can generate an initial knowledge about economic implications of the phenomenon.

A follow-up study, building on the findings of this research ‘a study into the effects of COVID-19 pandemic on tourism revenues in Morocco’ is a causal conclusive research. The second research can produce research findings that can be of a practical use for decision making.

Advantages of Exploratory Research

• Lower costs of conducting the study
• Flexibility and adaptability to change
• Exploratory research is effective in laying the groundwork that will lead to future studies.
• Exploratory studies can potentially save time by determining at the earlier stages the types of research that are worth pursuing

Disadvantages of Exploratory Research

• Inclusive nature of research findings
• Exploratory studies generate qualitative information and interpretation of such type of information is subject to bias
• These types of studies usually make use of a modest number of samples that may not adequately represent the target population. Accordingly, findings of exploratory research cannot be generalized to a wider population.
• Findings of such type of studies are not usually useful in decision making in a practical level.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research designs. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Source: Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[2] Singh, K. (2007) “Quantitative Social Research Methods” SAGE Publications, p.64

[3] Brown, R.B. (2006) “Doing Your Dissertation in Business and Management: The Reality of Research and Writing” Sage Publications, p.43

[4] Sandhusen, R.L. (2000) “Marketing” Barrons

[5] Nargundkar, R. (2008) “Marketing Research: Text and Cases” 3 rd edition, p.38

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Exploratory Research: Purpose And Process

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Bernd Reiter

Confirmatory, deductive research cannot produce absolute truths, according Karl POPPER (2002). If we accept this premise, then it is worth giving inductive and explorative research another chance. Exploration can produce valid and insightful findings in the social sciences, if conducted in a transparent and self-reflexive way. It can also profit from applying dialectical thinking. This article proposes a rationale for exploration in the social sciences and it elaborates the criteria on which such research must stand.

Saima Jafri , Dr Shumaila Memon

The current paper aims to examine Exploratory Practice as a form of practitioner research. It highlights the usefulness of EP for practitioner as well as learners. Adopting an explanatory approach the research discusses the main concepts and methods employed in EP. Informed by literature review the paper attempts to suggest ways in which EP could be conducted as a well established methodology for investigating phenomenon related with teaching and learning. From the statement and identification of puzzle to monitoring and data collection a step by step analysis, the paper studies the various stages of EP and studies their implications. Introduction Today when English has become a global medium of communication and access to information, English Language teaching is considered a field worth exploring. This paper aims to discuss Exploratory Practice (EP), which is a kind of practitioner research. Developments in EP have mainly taken place over the past 15 years .It is a kind of practitioner research aimed at enhancing the worth of language education within the classrooms. Basically EP started as a reaction to both academics oriented research and Action, first as a general framework of rules and regulations not as a set of actual classroom practices. Since principles have a global bearing ,whereas classroom practices are essentially local in their nature ,so the principles were coming g from years of experience and expertise of professionals of the field of education and were discussed with a global perspective.

Yuanita Damayanti

Daniel Peusca

Corey M. Abramson

IJRASET Publication

The term Research means a systematic way to investigate new facts or analyse the existing information to update the knowledge. Research methodology refers to the Science of Understanding how the solution to research problem can be obtained systematically. It can also be termed as the specific methods used to conduct the research. This paper presents the detail overview of different research methods. The research methods and methodology differ from problem to problem. In order to conduct a research, it is important for a researcher to not only have a good knowledge on Research methods but also on the research methodology. Researchers need to develop a Research design which acts like a blue print for conducting the research. This paper provides the analysis of different research methods and how to choose the research method based on the application Index Terms-Methodology, Research Process, Pure Research, Qualitative methods, and Quantitative methods I. INTRODUCTION Research is very important in order to progress. The term research is a combination of two words "Re-again, Search-find out". It an art of finding solution to the problem. According to the Oxford Advanced American Dictionary research is defined as "A careful study of a subject, especially in order to discover new facts or information about it" [1]P.M. Cook referred as "Research is an honest, exhaustive, intelligent searching for facts and their meanings or implications with reference to a given problem. The product or findings of a given piece of research should be an authentic, verifiable contribution to knowledge in the field studied." [2] Methodology refers to the organized, theoretical investigation of the methods used in the research. It includes the analysis of the research methods along with the ideologies related to the area of investigation. Technically it includes paradigm, research model, and the research techniques. [3] Research Methodology is art of studying how research is done systematically. It aims to explain on how to conduct a research, what are the problems that need to be answered and what are the pitfalls while conducting a research.

Satyajit Behera

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• Pilot Feasibility Stud

Exploratory studies to decide whether and how to proceed with full-scale evaluations of public health interventions: a systematic review of guidance

Britt hallingberg.

1 Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), Cardiff University, Cardiff, Wales UK

Ruth Turley

4 Specialist Unit for Review Evidence, Cardiff University, Cardiff, Wales UK

Jeremy Segrott

2 Centre for Trials Research, Cardiff University, Cardiff, Wales UK

Daniel Wight

3 MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow, UK

Peter Craig

Laurence moore, simon murphy, michael robling, sharon anne simpson, graham moore, associated data.

The datasets generated and/or analysed during the current study are not publicly available due to copyright infringement.

Evaluations of complex interventions in public health are frequently undermined by problems that can be identified before the effectiveness study stage. Exploratory studies, often termed pilot and feasibility studies, are a key step in assessing the feasibility and value of progressing to an effectiveness study. Such studies can provide vital information to support more robust evaluations, thereby reducing costs and minimising potential harms of the intervention. This systematic review forms the first phase of a wider project to address the need for stand-alone guidance for public health researchers on designing and conducting exploratory studies. The review objectives were to identify and examine existing recommendations concerning when such studies should be undertaken, questions they should answer, suitable methods, criteria for deciding whether to progress to an effectiveness study and appropriate reporting.

We searched for published and unpublished guidance reported between January 2000 and November 2016 via bibliographic databases, websites, citation tracking and expert recommendations. Included papers were thematically synthesized.

The search retrieved 4095 unique records. Thirty papers were included, representing 25 unique sources of guidance/recommendations. Eight themes were identified: pre-requisites for conducting an exploratory study, nomenclature, guidance for intervention assessment, guidance surrounding any future evaluation study design, flexible versus fixed design, progression criteria to a future evaluation study, stakeholder involvement and reporting of exploratory studies. Exploratory studies were described as being concerned with the intervention content, the future evaluation design or both. However, the nomenclature and endorsed methods underpinning these aims were inconsistent across papers. There was little guidance on what should precede or follow an exploratory study and decision-making surrounding this.

Conclusions

Existing recommendations are inconsistent concerning the aims, designs and conduct of exploratory studies, and guidance is lacking on the evidence needed to inform when to proceed to an effectiveness study.

Trial registration

PROSPERO 2016, CRD42016047843

Electronic supplementary material

The online version of this article (10.1186/s40814-018-0290-8) contains supplementary material, which is available to authorized users.

Improving public health and disrupting complex problems such as smoking, obesity and mental health requires complex, often multilevel, interventions. Such interventions are often costly and may cause unanticipated harms and therefore require evaluation using the most robust methods available. However, pressure to identify effective interventions can lead to premature commissioning of large effectiveness studies of poorly developed interventions, wasting finite research resources [ 1 – 3 ]. In the development of pharmaceutical drugs over 80% fail to reach ‘Phase III’ effectiveness trials, even after considerable investment [ 4 ]. With public health interventions, the historical tendency to rush to full evaluation has in some cases led to evaluation failures due to issues which could have been identified at an earlier stage, such as difficulties recruiting sufficient participants [ 5 ]. There is growing consensus that improving the effectiveness of public health interventions relies on attention to their design and feasibility [ 3 , 6 ]. However, what constitutes good practice when deciding when a full evaluation is warranted, what uncertainties should be addressed to inform this decision and how, is unclear. This systematic review aims to synthesize existing sources of guidance for ‘exploratory studies’ which we broadly define as studies intended to generate evidence needed to decide whether and how to proceed with a full-scale effectiveness study. They do this by optimising or assessing the feasibility of the intervention and/or evaluation design that the effectiveness study would use. Hence, our definition includes studies variously referred to throughout the literature as ‘pilot studies’, ‘feasibility studies’ or ‘exploratory trials’. Our definition is consistent with previous work conducted by Eldridge et al. [ 7 , 8 ], who define feasibility as an overarching concept [ 8 ] which assesses; ‘… whether the future trial can be done, should be done, and, if so, how’ (p. 2) [ 7 ]. However, our definition also includes exploratory studies to inform non-randomised evaluations, rather than a sole focus on trials.

The importance of thoroughly establishing the feasibility of intervention and evaluation plans prior to embarking on an expensive, fully powered evaluation was indicated in the Medical Research Council’s (MRC) framework for the development and evaluation of complex interventions to improve health [ 9 , 10 ]. This has triggered shifts in the practice of researchers and funders toward seeking and granting funding for an ever growing number of studies to address feasibility issues. Such studies are however in themselves often expensive [ 11 , 12 ]. While there is a compelling case for such studies, the extent to which this substantial investment in exploratory studies has to date improved the effectiveness and cost-effectiveness of evidence production remains to be firmly established. Where exploratory studies are conducted poorly, this investment may simply lead to expenditure of large amounts of additional public money, and several years’ delay in getting evidence into the hands of decision-makers, without necessarily increasing the likelihood that a future evaluation will provide useful evidence.

The 2000 MRC guidance used the term ‘exploratory trial’ for work conducted prior to a ‘definitive trial’, indicating that it should primarily address issues concerning the optimisation, acceptability and delivery of the intervention [ 13 ]. This included adaptation of the intervention, consideration of variants of the intervention, testing and refinement of delivery method or content, assessment of learning curves and implementation strategies and determining the counterfactual. Other possible purposes of exploratory trials included preliminary assessment of effect size in order to calculate the sample size for the main trial and other trial design parameters, including methods of recruitment, randomisation and follow-up. Updated MRC guidance in 2008 moved away from the sole focus on RCTs (randomised controlled trials) of its predecessor reflecting recognition that not all interventions can be tested using an RCT and that the next most robust methods may sometimes be the best available option [ 10 , 14 ]. Guidance for exploratory studies prior to a full evaluation have, however, often been framed as relevant only where the main evaluation is to be an RCT [ 13 , 15 ].

However, the goals of exploratory studies advocated by research funders have to date varied substantially. For instance, the National Institute for Health Research Evaluation Trials and Studies Coordinating Centre (NETSCC) definitions of feasibility and pilot studies do not include examination of intervention design, delivery or acceptability and do not suggest that modifications to the intervention prior to full-scale evaluation will arise from these phases. However, the NIHR (National Institute of Health Research) portfolio of funded studies indicates various uses of terms such as ‘feasibility trial’, ‘pilot trial’ and ‘exploratory trial’ to describe studies with similar aims, while it is rare for such studies not to include a focus on intervention parameters [ 16 – 18 ]. Within the research literature, there is considerable divergence over what exploratory studies should be called, what they should achieve, what they should entail, whether and how they should determine progression to future studies and how they should be reported [ 7 , 8 , 19 – 21 ].

This paper presents a systematic review of the existing recommendations and guidance on exploratory studies relevant to public health, conducted as the first stage of a project to develop new MRC guidance on exploratory studies. This review aims to produce a synthesis of current guidance/recommendations in relation to the definition, purpose and content of exploratory studies, and what is seen as ‘good’ and ‘bad’ practice as presented by the authors. It will provide an overview of key gaps and areas in which there is inconsistency within and between documents. The rationale for guidance and recommendations are presented, as well as the theoretical perspectives informing them. In particular, we examine how far the existing recommendations answer the following questions:

• When is it appropriate to conduct an exploratory study?
• What questions should such studies address?
• What are the key methodological considerations in answering these questions?
• What criteria should inform a decision on whether to progress to an effectiveness study?
• How should exploratory studies be reported?

This review is reported in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement [ 22 ] as evidenced in the PRISMA checklist (see Additional file  1 : Table S1). The review protocol is registered on PROSPERO (registration number: CRD42016047843; www.crd.york.ac.uk/prospero ).

Literature search

A comprehensive search (see Additional file  2 : Appendix) was designed and completed during August to November 2016 to identify published and grey literature reported between January 2000 and November 2016 that contained guidance and recommendations on exploratory studies that could have potential relevance to public health. Bibliographic databases were CINAHL, Embase, MEDLINE, MEDLINE-In-process, PsycINFO, Web of Science and PubMed. Supplementary searches included key websites (see Additional file  2 : Appendix) and forward and backward citation tracking of included papers, as well as contacting experts in the field. The first MRC guidance on developing and evaluating complex interventions in health was published in 2000; we therefore excluded guidance published before this year.

Selection of included papers

Search results were exported into reference management software Endnote and clearly irrelevant or duplicate records removed by an information specialist. Eligibility criteria were applied to abstracts and potentially relevant full-text papers by two reviewers working independently in duplicate (BH, JS). Discrepancies were agreed by consensus or by a third reviewer if necessary. Full criteria are shown in Table  1 . During screening of eligible studies, it became evident that determining whether or not guidance was applicable to public health was not always clear. The criteria in Table  1 were agreed by the team after a list of potentially eligible publications were identified.

Eligibility criteria for selecting papers

Quality assessment of included papers

Given the nature of publications included (expert guidance or methodological discussion papers) quality assessment was not applicable.

Data extraction and thematic synthesis

A thematic synthesis of guidance within included documents was performed [ 23 ]. This involved the use of an a priori coding framework (based on the projects aims and objectives), developed by RT, JS and DW ([ 24 ], see Additional file  2 : Appendix). Data were extracted using this schema in qualitative analytic software NVivo by one reviewer (BH). A 10% sample of coded papers was checked by a second reviewer (JS). Data were then conceptualised into final themes by agreement (BH, JS, DW, RT).

Review statistics

Four thousand ninety-five unique records were identified of which 93 were reviewed in full text (see Fig.  1 ). In total, 30 documents were included in the systematic review representing 25 unique sets of guidance. Most sources of guidance did not explicitly identify an intended audience and guidance varied in its relevance to public health. Table  2 presents an overview of all sources of guidance included in the review with sources of guidance more or less relevant to public health identified as well as those which specifically applied to exploratory studies with a randomised design.

Flow diagram

Summary of included guidance

a Guidance with greater relevance to public health included those where public health audiences was clearly among intended users of the guidance (authors are from Public Health departments, cites literature from public health journals, provides public health examples or uses the term ‘public health’ or variants of this, e.g. ‘prevention science’, ‘health improvement’). Guidance with less relevance was not specific about the intended audience but was of plausible relevance to public health (might, for example, include either an author from a public health research department or a citation to a public health journal).

b Authors make distinctions between the terms “pilot study” and “feasibility study”. c Aims of exploratory studies presented in the table map onto aims presented in themes 3 ( Guidance for intervention assessment ) and 4 ( Guidance surrounding the future evaluation design )

Findings from guidance

The included guidance reported a wide range of recommendations on the process of conducting and reporting exploratory studies. We categorised these into eight themes that capture: pre-requisites for conducting an exploratory study, nomenclature, guidance for intervention assessment, guidance surrounding the future evaluation study design, adaptive vs rigid designs, progression criteria for exploratory studies, stakeholder involvement and reporting.

Narrative description of themes

Theme 1: pre-requisites for conducting an exploratory study.

Where mentioned, pre-requisite activities included determining the evidence base, establishing the theoretical basis for the intervention, identifying the intervention components as well as modelling of the intervention in order to understand how intervention components interact and impact on final outcomes [ 9 , 25 – 27 ]. These were often discussed within the context of the MRC’s intervention development-evaluation cycle [ 6 , 9 , 10 , 13 , 25 – 28 ]. Understanding how intervention components interact with various contextual settings [ 6 , 27 , 29 ] and identifying unintended harms [ 6 , 29 ] as well as potential implementation issues [ 6 , 9 , 10 , 30 ] were also highlighted. There was an absence of detail in judging when these above conditions were met sufficiently for moving onto an exploratory study.

Theme 2: nomenclature

A wide range of terms were used, sometimes interchangeably, to describe exploratory studies with the most common being pilot trial/study. Table  3 shows the frequency of the terms used in guidance including other terms endorsed.

Frequency of nomenclature used

Note: terms are not mutually exclusive

Different terminology did not appear to be consistently associated with specific study purposes (see theme 3), as illustrated in Table  2 . ‘Pilot’ and ‘feasibility’ studies were sometimes used interchangeably [ 10 , 20 , 25 – 28 , 31 ] while others made distinctions between the two according to design features or particular aims [ 7 , 8 , 19 , 29 , 32 – 34 ]. For example, some described pilot studies as a smaller version of a future RCT to run in miniature [ 7 , 8 , 19 , 29 , 32 – 34 ] and was sometimes associated with a randomised design [ 32 , 34 ], but not always [ 7 , 8 ]. In contrast, feasibility studies were used as an umbrella term by Eldridge et al. with pilot studies representing a subset of feasibility studies [ 7 , 8 ]: ‘We suggest that researchers view feasibility as an overarching concept, with all studies done in preparation for a main study open to being called feasibility studies, and with pilot studies as a subset of feasibility studies.’ (p. 18) [ 8 ].

Feasibility studies could focus on particular intervention and trial design elements [ 29 , 32 ] which may not include randomisation [ 32 , 34 ]. Internal pilot studies were primarily viewed as part of the full trial [ 8 , 32 , 35 – 38 ] and are therefore not depicted under nomenclature in Table  3 .

While no sources explicitly stated that an exploratory study should focus on one area and not the other, aims and associated methods of exploratory studies diverged into two separate themes. They pertained to either examining the intervention itself or the future evaluation design, and are detailed below in themes 3 and 4.

Theme 3: guidance for intervention assessment

Sources of guidance endorsed exploratory studies having formative purposes (i.e. refining the intervention and addressing uncertainties related to intervention implementation [ 13 , 15 , 29 , 31 , 39 ]) as well as summative goals (i.e. assessing the potential impact of an intervention or its promise [ 6 , 13 , 39 ]).

Refining the intervention and underlying theory

Some guidance suggested that changes could be made within exploratory studies to refine the intervention and underlying theory [ 15 , 29 , 31 ] and adapt intervention content to a new setting [ 39 ]. However, guidance was not clear on what constituted minor vs. major changes and implications for progression criteria (see theme 6). When making changes to the intervention or underlying theory, some guidance recommended this take place during the course of the exploratory study (see theme 5). Others highlighted the role of using a multi-arm design to select the contents of the intervention before a full evaluation [ 13 ] and to assess potential mechanisms of multiple different interventions or intervention components [ 29 ]. Several sources highlighted the role of qualitative research in optimising or refining an intervention, particularly for understanding the components of the logic model [ 29 ] and surfacing hidden aspects of the intervention important for delivering outcomes [ 15 ].

Intervention implementation

There was agreement across a wide range of guidance that exploratory studies could explore key uncertainties related to intervention implementation, such as acceptability, feasibility or practicality. Notably these terms were often ill-defined and used interchangeably. Acceptability was considered in terms of recipients’ reactions [ 7 , 8 , 29 , 32 , 39 ] while others were also attentive to feasibility from the perspective of intervention providers, deliverers and health professionals [ 6 , 9 , 29 , 30 , 34 , 39 ]. Implementation, feasibility, fidelity and ‘practicality’ explored the likelihood of being able to deliver in practice what was intended [ 25 – 27 , 30 , 39 ]. These were sometimes referred to as aims within an embedded process evaluation that took place alongside an exploratory study, although the term process evaluation was never defined [ 7 , 10 , 15 , 29 , 40 ].

Qualitative research was encouraged for assessment of intervention acceptability [ 21 ] or for implementation (e.g. via non-participant observation [ 15 ]). Caution was recommended with regards to focus groups where there is a risk of masking divergent views [ 15 ]. Others recommended quantitative surveys to examine retention rates and reasons for dropout [ 7 , 30 ]. Furthermore, several sources emphasised the importance of testing implementation in a range of contexts [ 15 , 29 , 39 , 41 ]—especially in less socioeconomically advantaged groups, to examine the risk of widening health inequalities [ 29 , 39 ].

One source of guidance considered whether randomisation was required for assessing intervention acceptability, believing this to be unnecessary but also suggesting it could ‘potentially depend on preference among interventions offered in the main trial’ ([ 21 ]; p. 9). Thus, issues of intervention acceptability, particularly within multi-arm trials, may relate to clinical equipoise and acceptability of randomisation procedures among participants [ 30 ].

Appropriateness of assessing intervention impact

Several sources of guidance discussed the need to understand the impact of the intervention, including harms, benefits or unintended consequences [ 6 , 7 , 15 , 29 , 39 ]. Much of the guidance focused on statistical tests of effectiveness with disagreement on the soundness of this aim, although qualitative methods were also recommended [ 15 , 42 ]. Some condemned statistically testing for effectiveness [ 7 , 20 , 29 , 32 , 41 ], as such studies are often underpowered, hence leading to imprecise and potentially misleading estimates of effect sizes [ 7 , 20 ]. Others argued that an estimate of likely effect size could evidence the intervention was working as intended and not having serious unintended harms [ 6 ] and thus be used to calculate the power for the full trial [ 13 ]. Later guidance from the MRC is more ambiguous than earlier guidance, stating that estimates should be interpreted with caution, while simultaneously stating ‘safe’ assumptions of effect sizes as a pre-requisite before continuing to a full evaluation [ 10 ]. NIHR guidance, which distinguished between pilot and feasibility studies, supported the assessment of a primary outcome in pilot studies, although it is unclear whether this is suggesting that a pilot should involve an initial test of changes in the primary outcome, or simply that the primary outcome should be measured in the same way as it would be in a full evaluation. By contrast, for ‘feasibility studies’, it indicated that an aim may include designing an outcome measure to be used in a full evaluation.

Others made the case for identifying evidence of potential effectiveness, including use of interim or surrogate endpoints [ 7 , 41 ], defined as ‘…variables on the causal pathway of what might eventually be the primary outcome in the future definitive RCT, or outcomes at early time points, in order to assess the potential for the intervention to affect likely outcomes in the future definitive RCT…’ [ 7 ] (p. 14).

Randomisation was implied as a design feature of exploratory studies when estimating an effect size estimate of the intervention as it maximised the likelihood that observed differences are due to intervention [ 9 , 39 ], with guidance mostly written from a starting assumption that full evaluation will take the form of an RCT and guidance focused less on exploratory studies for quasi-experimental or other designs. For studies that aim to assess potential effectiveness using a surrogate or interim outcome, using a standard sample size calculation was recommended to ensure adequate power, although it was noted that this aim is rare in exploratory studies [ 7 ].

Theme 4: guidance surrounding the future evaluation design

Sources consistently advocated assessing the feasibility of study procedures or estimating parameters of the future evaluation. Recommendations are detailed below.

Assessing feasibility of the future evaluation design

Assessing feasibility of future evaluation procedures was commonly recommended [ 6 , 7 , 10 , 15 , 30 , 32 – 34 , 37 , 41 ] to avert problems that could undermine the conduct or acceptability of future evaluation [ 6 , 15 , 30 ]. A wide range of procedures were suggested as requiring assessments of feasibility including data collection [ 20 , 30 , 34 , 36 , 41 ], participant retention strategies [ 13 ], randomisation [ 7 , 13 , 20 , 30 , 34 , 36 , 38 , 41 ], recruitment methods [ 13 , 30 , 32 , 34 , 35 , 38 , 41 ], running the full trial protocol [ 20 , 30 , 36 ], the willingness of participants to be randomised [ 30 , 32 ] and issues of contamination [ 30 ]. There was disagreement concerning the appropriateness of assessing blinding in exploratory studies [ 7 , 30 , 34 ], with one source noting double blinding is difficult when participants are assisted in changing their behaviour; although assessing single blinding may be possible [ 30 ].

Qualitative [ 15 , 30 , 34 ], quantitative [ 34 ] and mixed methods [ 7 ] were endorsed for assessing these processes. Reflecting the tendency for guidance of exploratory studies to be limited to studies in preparation for RCTs, discussion of the role of randomisation at the exploratory study stage featured heavily in guidance. Randomisation within an exploratory study was considered necessary for examining feasibility of recruitment, consent to randomisation, retention, contamination or maintenance of blinding in the control and intervention groups, randomisation procedures and whether all the components of a protocol can work together, although randomisation was not deemed necessary to assess outcome burden and participant eligibility [ 21 , 30 , 34 ]. While there was consensus about what issues could be assessed through randomisation, sources disagreed on whether randomisation should always precede a future evaluation study, even if that future study is to be an RCT. Contention seemed to be linked to variation in nomenclature and associated aims. For example, some defined pilot study as a study run in miniature to test how all its components work together, thereby dictating a randomised design [ 32 , 34 ]. Yet for feasibility studies, randomisation was only necessary if it reduced the uncertainties in estimating parameters for the future evaluation [ 32 , 34 ]. Similarly, other guidance highlighted an exploratory study (irrespective of nomenclature) should address the main uncertainties, and thus may not depend on randomisation [ 8 , 15 ].

Estimating parameters of the future evaluation design

A number of sources recommended exploratory studies should inform the parameters of the future evaluation design. Areas for investigation included estimating sample sizes required for the future evaluation (e.g. measuring outcomes [ 32 , 35 ]; power calculations [ 13 ]; derive effect size estimates [ 6 , 7 , 39 ]; estimating target differences [ 35 , 43 ]; deciding what outcomes to measure and how [ 9 , 20 , 30 , 36 ]; assessing quality of measures (e.g. for reliability/ validity/ feasibility/ sensitivity [ 7 , 20 , 30 ]; identification of control group [ 9 , 13 ]; recruitment, consent and retention rates [ 10 , 13 , 20 , 30 , 32 , 34 , 36 ]; and information on the cost of the future evaluation design [ 9 , 30 , 36 ].

While qualitative methods were deemed useful for selecting outcomes and their suitable measures [ 15 ], most guidance concentrated on quantitative methods for estimating future evaluation sample sizes. This was contentious due to the potential to over- or under-estimate sample sizes required in a future evaluation due to the lack of precision of estimates from a small pilot [ 20 , 30 , 41 ]. Estimating sample sizes from effect size estimates in an exploratory study was nevertheless argued by some to be useful if there was scant literature and the exploratory study used the same design and outcome as the future evaluation [ 30 , 39 ]. Cluster RCTs, which are common in public health interventions, were specifically earmarked as unsuitable for estimating parameters for sample size calculations (e.g. intra-cluster correlation coefficients) as well as recruitment and follow-up rates without additional information from other resources, because a large number of clusters and individual participants would be required [ 41 ]. Others referred to ‘rules of thumb’ when determining sample sizes in an exploratory study with numbers varying between 10 and 75 participants per trial arm in individually randomised studies [ 7 , 30 , 36 ]. Several also recommended the need to consider a desired meaningful difference in the health outcomes from a future evaluation and the appropriate sample size needed to detect this, rather than conducting sample size calculations using estimates of likely effect size from pilot data [ 30 , 35 , 38 , 43 ].

A randomised design was deemed unnecessary for estimating costs or selecting outcomes, although was valued for estimating recruitment and retention rates for intervention and control groups [ 21 , 34 ]. Where guidance indicated the estimation of an effect size appropriate to inform the sample size for a future evaluation, a randomised design was deemed necessary [ 9 , 39 ].

Theme 5: flexible vs. fixed design

Sources stated that exploratory studies could employ a rigid or flexible design. With the latter, the design can change during the course of the study, which is useful for making changes to the intervention, as well as the future evaluation design [ 6 , 13 , 15 , 31 ]. Here, qualitative data can be analysed as it is collected, shaping the exploratory study process, for instance sampling of subsequent data collection points [ 15 ], and clarifying implications for intervention effectiveness [ 31 ].

In contrast, fixed exploratory studies were encouraged when primarily investigating the future evaluation parameters and processes [ 13 ]. It may be that the nomenclature used in some guidance (e.g. pilot studies that are described as miniature versions of the evaluation) is suggesting a distinction between more flexible vs. more stringent designs. In some guidance, it was not mentioned whether changes should be made during the course of an exploratory study or afterwards, in order to get the best possible design for the future evaluation [ 6 , 7 , 21 ].

Theme 6: progression criteria to a future evaluation study

Little guidance was provided on what should be considered when formulating progression criteria for continuing onto a future evaluation study. Some focussed on the relevant uncertainties of feasibility [ 32 , 39 ], while others highlight specific items concerning cost-effectiveness [ 10 ], refining causal hypotheses to be tested in a future evaluation [ 29 ] and meeting recruitment targets [ 20 , 34 ]. As discussed in themes 3 and 4, statistically testing for effectiveness and using effect sizes for power calculations was cautioned by some, and so criteria based on effect sizes were not specified [ 38 ].

Greater discussion was devoted to how to weight evidence from an exploratory study that addressed multiple aims and used different methods. Some explicitly stated progression criteria should not be judged as strict thresholds but as guidelines using, for example, a traffic lights system with varying levels of acceptability [ 7 , 41 ]. Others highlighted a realist approach, moving away from binary indicators to focusing on ‘what is feasible and acceptable for whom and under what circumstances’ [ 29 ]. In light of the difficulties surrounding interpretation of effect estimates, several sources recommended qualitative findings from exploratory studies should be more influential than quantitative findings [ 15 , 38 ].

Interestingly, there was ambiguity regarding progression when exploratory findings indicated substantial changes to the intervention or evaluation design. Sources considering this issue suggested that if ‘extensive changes’ or ‘major modifications’ are made to either (note they did not specify what qualified as such), researchers should return to the exploratory [ 21 , 30 ] or intervention development phases [ 15 ].

‘Alternatively, at the feasibility phase, researchers may identify fundamental problems with the intervention or trial conduct and return to the development phase rather than proceed to a full trial.’ (p. 1) [ 15 ].

As described previously, however, the threshold at which changes are determined to be ‘major’ remained ambiguous. While updated MRC guidance [ 10 ] moved to a more iterative model, accepting that movement back between feasibility/piloting and intervention development may sometimes be needed, there was no guidance on under what conditions movement between these two stages should take place.

Theme 7: stakeholder involvement

Several sources recommended a range of stakeholders (e.g. intervention providers, intervention recipients, public representatives as well as practitioners who might use the evidence produced by the full trial) be involved in the planning and running of the exploratory study to ensure exploratory studies reflect the realities of intervention setting [ 15 , 28 , 31 , 32 , 39 , 40 ]. In particular, community-based participatory approaches were recommended [ 15 , 39 ]. While many highlighted the value of stakeholders on Trial Steering Committees and other similar study groups [ 15 , 28 , 40 ], some warned about equipoise between researchers and stakeholders [ 15 , 40 ] and also cautioned against researchers conflating stakeholder involvement with qualitative research [ 15 ].

‘Although patient and public representatives on research teams can provide helpful feedback on the intervention, this does not constitute qualitative research and may not result in sufficiently robust data to inform the appropriate development of the intervention.’ (p. 8) [ 15 ].

Theme 8: reporting of exploratory studies

Detailed recommendations for reporting exploratory studies were recently provided in new Consolidated Standards of Reporting Trials (CONSORT) guidance by Eldridge et al. [ 7 ]. In addition to this, recurrent points were brought up by other sources of guidance. Most notably, it was recommended exploratory studies be published in peer-reviewed journals as this can provide useful information to other researchers on what has been done, what did not work and what might be most appropriate [ 15 , 30 ]. An exploratory study may also result in multiple publications, but should provide reference to other work carried out in the same exploratory study [ 7 , 15 ]. Several sources of guidance also highlight that exploratory studies should be appropriately labelled in the title/abstract to enable easy identification; however, the nomenclature suggested varied depending on guidance [ 7 , 8 , 15 ].

While exploratory studies—carried out to inform decisions about whether and how to proceed with an effectiveness study [ 7 , 8 ]—are increasingly recognised as important in the efficient evaluation of complex public health interventions, our findings suggest that this area remains in need of consistent standards to inform practice. At present, there are multiple definitions of exploratory studies, a lack of consensus on a number of key issues, and a paucity of detailed guidance on how to approach the main uncertainties such studies aim to address prior to proceeding to a full evaluation.

Existing guidance commonly focuses almost exclusively on testing methodological parameters [ 33 ], such as recruitment and retention, although in practice, it is unusual for such studies not to also focus on the feasibility of the intervention itself. Where intervention feasibility is discussed, there is limited guidance on when an intervention is ‘ready’ for an exploratory study and a lack of demarcation between intervention development and pre-evaluation work to understand feasibility. Some guidance recognised that an intervention continues to develop throughout an exploratory study, with distinctions made between ‘optimisation/refinement’ (i.e. minor refinements to the intervention) vs. ‘major changes’. However, the point at which changes become so substantial that movement back toward intervention development rather than forward to a full evaluation remains ambiguous. Consistent with past reviews which adopted a narrower focus on studies with randomised designs [ 21 ] or in preparation for a randomised trial [ 8 , 36 ] and limited searches of guidance in medical journals [ 19 , 36 ], terms to describe exploratory studies were inconsistent, with a distinction sometimes made between pilot and feasibility studies, though with others using these terms interchangeably.

The review identifies a number of key areas of disagreement or limited guidance in regards to the critical aims of exploratory studies and addressing uncertainties which might undermine a future evaluation, and how these aims should be achieved. There was much disagreement for example on whether exploratory studies should include a preliminary assessment of intervention effects to inform decisions on progression to a full evaluation, and the appropriateness of using estimates of effect from underpowered data (from non-representative samples and a study based on a not fully optimised version of the intervention) to power a future evaluation study. Most guidance focused purely on studies in preparation for RCTs; nevertheless, guidance varied on whether randomisation was a necessary feature of the exploratory study, even where a future evaluation study was an RCT. Guidance was often difficult to assess regarding its applicability to public health research, with many sources focusing on literature and practice primarily from clinical research, and limited consideration of the transferability of these problems and proposed solutions to complex social interventions, such as those in public health. Progression criteria were highlighted as important by some as a means of preventing biased post hoc cases for continuation. However, there was a lack of guidance on how to devise progression criteria and processes for assessing whether these had been sufficiently met. Where they had not been met, there was a lack of guidance on how to decide whether the exploratory study had generated sufficient insight about uncertainties that the expense of a further feasibility study would not be justified prior to large-scale evaluation.

Although our review included a broad focus on guidance of exploratory studies from published and grey literature and moved beyond a focus on studies conducted in preparation for an RCT specifically, a number of limitations should be noted. Guidance from other areas of social intervention research where challenges may be similar to those in public health (e.g. education, social work and business) may not have been captured by our search strategy. We found few worked examples of exploratory studies in public health that provided substantial information from learned experience and practice. Hence, the review drew largely on recommendations from funding organisations, or relatively abstract guidance from teams of researchers, with fewer clear examples of how these recommendations are grounded in experience from the conduct of such studies. As such, it should be acknowledged that these documents represent one element within a complex system of research production and may not necessarily fully reflect what is taking place in the conduct of exploratory studies. Finally, treating sources of guidance as independent from each other does not reflect how some recommendations developed over time (see for example [ 7 , 8 , 20 , 36 , 41 ]).

There is inconsistent guidance, and for some key issues a lack of guidance, for exploratory studies of complex public health interventions. As this lack of guidance for researchers in public health continues, the implications and consequences could be far reaching. It is unclear how researchers use existing guidance to shape decision-making in the conduct of exploratory studies, and in doing so, how they adjudicate between various conflicting perspectives. This systematic review has aimed largely to identify areas of agreement and disagreement as a starting point in bringing order to this somewhat chaotic field of work. Following this systematic review, our next step is to conduct an audit of published public health exploratory studies in peer-reviewed journals, to assess current practice and how this reflects the reviewed guidance. As part of a wider study, funded by the MRC/NIHR Methodology Research Programme to develop GUidance for Exploratory STudies of complex public health interventions (GUEST; Moore L, et al. Exploratory studies to inform full scale evaluations of complex public health interventions: the need for guidance, submitted), the review has informed a Delphi survey of researchers, funders and publishers of public health research. In turn, this will contribute to a consensus meeting which aims to reach greater unanimity on the aims of exploratory studies, and how these can most efficiently address uncertainties which may undermine a full-scale evaluation.

Additional files

Table S1. PRISMA checklist. (DOC 62 kb)

Appendix 1. Search strategies and websites. Appendix 2. Coding framework. (DOCX 28 kb)

Acknowledgements

We thank the Specialist Unit for Review Evidence (SURE) at Cardiff University, including Mala Mann, Helen Morgan, Alison Weightman and Lydia Searchfield, for their assistance with developing and conducting the literature search.

This study is supported by funding from the Methodology Research Panel (MR/N015843/1). LM, SS and DW are supported by the UK Medical Research Council (MC_UU_12017/14) and the Chief Scientist Office (SPHSU14). PC is supported by the UK Medical Research Council (MC_UU_12017/15) and the Chief Scientist Office (SPHSU15). The work was also undertaken with the support of The Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement (DECIPHer), a UKCRC Public Health Research Centre of Excellence. Joint funding (MR/KO232331/1) from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, the Welsh Government and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.

Availability of data and materials

Abbreviations, authors’ contributions.

LM, GM, PC, MR, JS, RT and SS were involved in the development of the study. RT, JS, DW and BH were responsible for the data collection, overseen by LM and GM. Data analysis was undertaken by BH guided by RT, JS, DW and GM. The manuscript was prepared by BH, RT, DW, JS and GM. All authors contributed to the final version of the manuscript. LM is the principal investigator with overall responsibility for the project. GM is Cardiff lead for the project. All authors read and approved the final manuscript.

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Not applicable.

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Inventors’ brokerages dynamic and exploratory innovation: the moderating role of knowledge diversity

• Published: 18 April 2024

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• Xueyun Rong 1 ,
• Zhongkai Yang 1 &
• Yutao Sun   ORCID: orcid.org/0000-0002-8198-5387 2  

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An inventor’s exploratory innovation is driven by an extensive external knowledge search. This paper contributes to this understanding by exploring how inventors’ brokerages dynamic influence exploratory innovation from the perspective of ego-network, and the moderating role of knowledge diversity is also explored. Specifically, we define an inventor’s direct partners (tier-1) as brokerages between the inventor and its indirect partners (tier-2) and discuss the effects of the inventor’s brokerage expansion, stability, and recession on its exploratory innovation. Our empirical research is based on 4198 inventors working in the artificial intelligence field during the period from 1991 to 2019, and we identify those inventors through the USPTO database. Our results indicate that the brokerage expansion of an inventor has an inverted U-shaped impact on exploratory innovation, the brokerage stability has a positive impact on exploratory innovation, and the brokerage recession has a negative impact on exploratory innovation. Furthermore, knowledge diversity strengthens the positive impact of brokerage expansion and stability on exploratory innovation and strengthens the negative impact of brokerage recession on exploratory innovation.

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Rong, X., Yang, Z. & Sun, Y. Inventors’ brokerages dynamic and exploratory innovation: the moderating role of knowledge diversity. Scientometrics (2024). https://doi.org/10.1007/s11192-024-04993-6

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