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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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• v.9(8); 2019

Beyond exploratory: a tailored framework for designing and assessing qualitative health research

Katharine a rendle.

1 Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA

Corey M Abramson

2 School of Sociology, University of Arizona, Tucson, Arizona, USA

Sarah B Garrett

3 Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, California, USA

Meghan C Halley

4 Palo Alto Medical Foundation for Health Care Research and Education, Palo Alto, California, USA

Daniel Dohan

Associated data.

The objective of this commentary is to develop a framework for assessing the rigour of qualitative approaches that identifies and distinguishes between the diverse objectives of qualitative health research, guided by a narrative review of the published literature on qualitative guidelines and standards from peer-reviewed journals and national funding organisations that support health services research, patient-centered outcomes research and other applied health research fields. In this framework, we identify and distinguish three objectives of qualitative studies in applied health research: exploratory, descriptive and comparative. For each objective, we propose methodological standards that may be used to assess and improve rigour across all study phases—from design to reporting. Similar to hierarchies of quality of evidence within quantitative studies, we argue that standards for qualitative rigour differ, appropriately, for studies with different objectives and should be evaluated as such. Distinguishing between different objectives of qualitative health research improves the ability to appreciate variation in qualitative studies and to develop appropriate evaluations of the rigour and success of qualitative studies in meeting their stated objectives. Researchers, funders and journal editors should consider how further developing and adopting the framework for assessing qualitative rigour outlined here may advance the rigour and potential impact of this important mode of inquiry.

Article summary

• Qualitative research in health services research (HSR) and allied fields has maintained steady, yet unsettled, interest and value over recent decades.
• Qualitative methods are epistemologically and theoretically diverse, which is a strength. However, it also means that investigators do not necessarily approach qualitative research using a unified set of evidentiary rules. As such, assessing rigour and quality across studies can be challenging.
• To help address these challenges, we propose a framework for assessing the rigour of qualitative approaches that identifies and distinguishes between three diverse study objectives. For each type of study, we propose preliminary methodological considerations to help improve rigour across all study phases. As is the case for quantitative studies, we argue that standards for qualitative rigourdiffer, appropriately, for different kinds of studies.
• The objective of this commentary is not to resolve all potential conflicts between philosophical assumptions of different qualitative approaches, but rather help to advance a broader and richer understanding of qualitative rigour in relationship to other evidence hierarchies.

In recent decades, the role of qualitative research in health services research (HSR) and allied fields has maintained steady, yet unsettled, interest and value. Evidence of steady interest includes publication of qualitative reviews and guidelines by leading journals including Health Services Research , 1 2 Medical Care Research and Review 3–5 and BMJ , 6 7 and by funders including the Robert Wood Johnson Foundation, 8 National Institutes of Health 9 10 and National Science Foundation. 11 12 In fields such as Patient-Centered Outcomes Research (PCOR) and implementation science, qualitative research has been embraced with particular enthusiasm for its ability to capture, advance and address questions meaningful to patients, clinicians and other healthcare system stakeholders. 2 13 The majority (82%) of inaugural projects awarded by the Patient-Centered Outcomes Research Institute (PCORI) incorporated qualitative research methods. 13 More recently, reflective of the continued prevalence of these approaches in the field, PCORI incorporated qualitative methods into their methodological standards.

Yet, despite this sustained interest, the status of qualitative health research remains unsettled, as illustrated by the BMJ’s changing engagement with the method. After championing qualitative methods in 2008, 7 14–17 BMJ editors in 2016 noted that they tended to assign low priority to qualitative studies because such studies are ‘usually exploratory by their very nature’. 18 This statement came in response to an open letter from scholars arguing that BMJ should adopt formal policies and training for editorial staff on what distinguishes ‘good from poor qualitative research’ rather than de-emphasising the method in toto . 19 In sum, despite sustained interest from the HSR community, the status of qualitative research remains contested. This status reflects debate over the purpose of qualitative research—is it a valuable tool to advance the field or a low-priority exercise in exploration? —and an ongoing desire for guidance on how best to distinguish high-quality from low-quality qualitative research.

Assessing rigour and quality in qualitative research is challenging because qualitative methods are epistemologically diverse. 20–22 This diversity is a strength because it allows for the theoretical and methodological flexibility necessary to fully understand a specific topic from multiple perspectives. 16 However, it also means that investigators do not necessarily approach qualitative research using a unified set of evidentiary rules. 22 Thus, scholars may measure the quality of studies using different or even incompatible yardsticks.

The challenge of diverse epistemologies has become more acute as qualitative health research has expanded beyond its historical roots in phenomenological or grounded theory studies. Contemporary researchers may use qualitative data and methods to improve the descriptive accuracy of health-related phenomena that have already been characterised by exploratory work or are difficult to capture using other approaches. 23 Researchers also use larger scale, comparative qualitative studies in ways that resemble quantitative efforts to identify explanatory pathways. 24 Therefore, assessing the rigour of a specific qualitative study benefits from first identifying the analytic goals and objectives of the study—that is, identifying which yardstick investigators themselves have adopted—and then using this yardstick to examine how the study measures up.

To address these challenges, we propose a tailored framework for designing and informing assessments of different types of qualitative health research common within HSR. The framework recognises that qualitative investigators have different objectives and yardsticks in mind when undertaking studies and that rigour should be assessed accordingly. We distinguish three central types of qualitative study objectives common in applied health research: exploratory, descriptive and comparative. For each objective, we propose preliminary methodological considerations to help improve rigour across all study phases—from design to reporting. As is the case for quantitative studies, we argue that standards for qualitative rigour differ, appropriately, for different kinds of studies. The objective of this commentary is not to resolve all potential conflicts between philosophical assumptions of different qualitative approaches, but rather help to advance a broader and richer understanding of qualitative rigour in relationship to other evidence hierarchies. The proposed framework offers a nuanced set of categories by which to conduct and recognise high-quality qualitative research. The framework also supports efforts to shift debates over the value of qualitative research to discussions on how we can promote rigour across different types of valuable qualitative studies, and underscore how qualitative methods can advance clinical and applied health research.

Designing a tailored framework: methods and results

Our framework is based on a team-based review of published guidelines and standards discussing the scientific conduct of qualitative health research. Guided by expert consensus and a targeted literature scan, we identified and reviewed 17 peer-reviewed articles and expert reports published by journals widely read by the HSR community and by major funders or sponsors of qualitative health research (1–12, 21, 33–36). In contrast to previous reviews, 25 we did not seek to synthesise these guidelines. Rather we drew on them to develop a conceptual framework for designing and informing formal assessments of rigorous qualitative research.

Range of approaches in qualitative research

Qualitative research incorporates a range of methods including in-depth interviews, focus groups, ethnography and many others. 26 Even within a single method, accepted approaches and standards for rigour vary depending on disciplinary and theoretical orientations. Correspondingly, qualitative research cannot be defined by a single theoretical approach or data collection procedure. Rather many, often debated, approaches exist with distinct implications for appropriate standards for data collection, analysis and interpretation.

On one end of the spectrum, qualitative researchers guided by realism subscribe to the assumption that rigorous scientific research can provide an accurate and objective representation of reality, and that objectivity should be a primary goal of all scientific inquiries, including qualitative research. 27 These qualitative researchers generally consider standards such as validity, reliability, reproducibility and generalisability as similarly legitimate yardsticks for qualitative research as they are in quantitative research. 28 On the other end of the spectrum, relativist philosophical approaches to qualitative research typically argue that all research is inherently subjective and/or political, 29 and some relativists criticise the scientific approach specifically because it claims to be objective. 30 31 Much of applied qualitative health research falls somewhere between the two ends of the spectrum. For example, Mays and Pope consider themselves ‘subtle realists’. 6 They acknowledge that all research involves subjectivity and includes political dimensions, but they also contend that qualitative research should, nevertheless, be assessed by a similar set of quality criteria as quantitative studies. Although we recognise the value strictly relativist approaches provide, the framework and design considerations we propose are largely guided by a realist (or subtle realist) orientation. However, in addition to resonating with those who operate under similar orientations, we hope this framework will serve to advance discussions of how best to communicate and assess qualitative research using different theoretical and epistemological standpoints.

Tailored framework for qualitative health research

Given the diversity of approaches, a foundational step to improving the assessment of rigour in qualitative research is to abandon the attempt to develop a single standard for the best practices regardless of study orientation and objective. Instead, standards must begin with an assessment of epistemological assumptions and corresponding study objectives, an approach that is similar to standards for quantitative PCOR research 32 and mixed-methods research. 33 In this vein, we identified and defined three general types of study objectives broadly used in applied qualitative health research (see figure 1 ). These three types reflect differences in primary study objectives and existing knowledge within a topic area.

Three broad types of qualitative health research.

In table 1 , we provide preliminary distinctions on how exploratory, descriptive and comparative studies compare across a range of standards and guidelines that have been proposed for qualitative research (see table 1 ). Regardless of study type, researchers should report study details in clear, comprehensive ways, using standardised reporting guidelines whenever possible. 34 35

Framework for designing different types of applied qualitative health research and developing evaluative instruments to assess their rigour

Compared with descriptive or comparative studies, exploratory studies approach the topic of study primarily in an inductive fashion to investigate the areas of potential research interest that remain mostly or wholly unexamined by the scientific community. Investigators undertaking exploratory studies typically have few expectations for what they might find, and their research design and approach may shift dramatically as they learn more about the phenomena of interest. An example of an exploratory study is a study that uses convenience sampling and unstructured interviews to explore what patients think about a new treatment in a single healthcare setting.

At the opposite end of this spectrum, investigators conducting comparative studies aim to use a primarily deductive approach designed to compare and document how well-defined qualitative phenomena are represented in different settings or populations. The qualitative methods employed in a comparative study are typically defined in advance, sampling should be systematic and structured by aims, and investigators enter the field with hypothesised ideas of what findings they may uncover and how to interpret those findings in light of previous research. An example of a comparative study is a multisite ethnography that seeks to compare how patient-provider communication varies by location, and uses random sampling of patient-provider interactions to collect data.

Descriptive studies occupy a middle position, building on previously conducted exploratory work so researchers will be able to proceed with more-focused inquiry. This should include well-defined procedures including sampling protocols and analytical plans, and investigators should usually articulate expected findings prior to beginning the study. However, as researchers investigate phenomena in new settings or patient populations, it is reasonable to expect descriptive studies to generate surprises. Thus, descriptive studies also feature inductive elements to detect unexpected findings, and must be flexible enough in design to accommodate shifts in research focus and methods based on empirical findings. An example of a descriptive study is a longitudinal study of patients with ovarian cancer that employs semistructured interviews and directed content analysis to examine decision-making across patients in a novel setting.

Our review identified a number of qualitative standards and guidelines that have been published. The conceptual framework we present here draws on those extant guidelines through the recognition that qualitative health research includes studies of diverse theoretical and epistemological orientations, each of which has distinct understandings of scientific quality and rigour. Given this intellectual diversity, it is inappropriate to use a single yardstick for all qualitative research. Rather, assessments of qualitative quality must begin with an assessment of a study’s theoretical orientations and research objectives to ensure that rigour is assessed on a study’s own terms. This framework and suggested approaches may help to advance evaluations of qualitative rigour that acknowledge and differentiate between the studies that report exploratory, descriptive or comparative study objectives.

Existing standards for conducting health research and grading evidence, such as Grading of Recommendations Assessment, Development and Evaluation (GRADE), 36 do not capture the diversity of qualitative studies—often designating all qualitative studies as providing weak levels of evidence. PCORI’s own methodological standards have been largely silent regarding qualitative methods until recently, 32 leaving applicants without clear direction on how to conduct rigorous qualitative research. Incorporation of tailored qualitative standards could help to clarify and improve the rigour of proposal design, review and completion. The establishment and integration of such standards could also guide journal editors in developing transparent standards for deciding priorities for publication. For example, editors may decide against publication of exploratory or descriptive studies, but prioritise well-executed comparative studies that advance the field in ways quantitative studies could not.

In addition to these immediate applications, implementing standards that incorporate the diversity of objectives within applied qualitative research has the potential to address broader challenges facing qualitative health research. These include: (1) the need to educate broader audiences about the many goals of qualitative research, including but not limited to exploration; (2) the need to create rigorous standards for conducting and reporting various types of qualitative studies to help audiences, editors and funders evaluate studies on their own merits and (3) the challenges of publishing qualitative research in prestigious and high-impact journals that will reach a wide range of practitioners, researchers and lay audiences. We contend that these challenges can be reframed as opportunities to advance the science of qualitative research, and its potential for improving outcomes for patients, providers and communities.

Supplementary Material

Acknowledgments.

Portions of this work were presented at the 2016 Academy Health Annual Research Meeting and 2017 Society of Behavioral Medicine Annual Meeting. The authors thank Katherine Gillespie and members of our Stakeholder Advisory Board for their invaluable contributions to the project.

Presented in: Earlier version presented at the 2016 Academy Health Annual Research Meeting in Boston, MA, USA.

Contributors: All authors (KAR, CMA, SBG, MCH and DD) helped to design and conceptualise this work including reviewing guidelines and conceptualising the proposed framework. KAR drafted the manuscript, and CMA, SBG, MCH and DD provided substantial review and writing to revisions.

Funding: This work was funded by the Patient-Centered Outcomes Research Institute (PCORI) Award (ME-1409-22996).

Disclaimer: The views presented in this article are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee. Funders had no role in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit the paper for publication.

Competing interests: None declared.

Patient consent for publication: Not required.

Provenance and peer review: Not commissioned; externally peer reviewed.

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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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Exploratory Research Design: A Guide for Students

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Exploratory Research refers to the research methodology used when researchers have a limited understanding of the topic at hand and want to gain a broader perspective or more insights into the subject.

This type of research is conducted in the initial stages of a study when there is a lack of clarity about the problem. It may lead to subsequent studies that attempt to generate greater clarity on the findings generated in the initial, exploratory, phase, or to test hypotheses that the exploratory phase generated.

Definition of Exploratory Research

If you’re writing a research proposal, methodology, or essay in which you need to discuss exploratory research design , I recommend providing a scholarly definition of the topic.

Here are three solid scholarly definitions you could use:

• “… research used to investigate an issue that is new, a problem which is not clearly defined, a topic on which there is little data” (Gozdziak & Chantavanich, 2022)
• “… initial research conducted to clarify and define the nature of the problem. It is done to help diagnose the situation, allow for screening of alternatives, and discover new ideas.” (Hutchison, Allen & Macy, 2012)
• “… the initial research into a hypothetical or theoretical idea. This is where the researcher has an idea and wishes to research a topic seeking to understand it more deeply. An exploratory research study is an attempt to lay the groundwork that could of will lead to future studies.” (Blecher, 2018)

Objectives of Exploratory Research

Exploratory research is generally conducted in order to generate initial data on a relatively unknown topic (Hammond & Wellington, 2013).

We could divide this up into a range of more specific objectives that you could state for your research project, including:

• Descriptive Data : Exploratory research often aims to provide a better understanding of a relatively unknown problem, phenomenon, or behavior by generating descriptive data (Cargan, 2007). This helps in establishing a clearer understanding of a topic and, consequently, gives subsequent projects the chance to dig deeper now that they have some baseline data.
• Generation of New Ideas : Through exploratory research, new ideas and perspectives can emerge that were not initially considered (Swedberg, 2020). An exploratory study often begins with an open mind, ready to reveal surprising, remarkable, and unexpected new ideas and insights. For example, researchers may conclude the study with a hypothesis for future research to examine.
• Determining the Most Appropriate Research Method : After getting a clearer idea of the topic, researchers can determine which research methods (e.g., qualitative, quantitative) would be most suitable for a subsequent, more detailed, conclusive research study.
• Clarifying Concepts : In generating descriptive datasets, an exploratory study can help in defining and refining ambiguous or unclear concepts, which can help to start to build foundational definitions and conceptual frameworks for the emerging body of literature on a novel topic (Tan, 2022).
• Establishing Importance: An exploratory study could also serve the purpose of demonstrating that a topic is worthy of larger-scale studies. So, researchers might conduct their exploratory study, and use its results to approach funding bodies. With the exploratory study complete, they will be armed with more data about the topic and informed evidence about the best way to approach it.
• Establishing Priorities for Future Research : By identifying key issues and questions, researchers can prioritize areas that need deeper investigation. Conclusions of exploratory studies usually provide recommendations for future studies, including by proposing hypotheses and prioritizing future projects.

Common Methods for Exploratory Research Designs

There is no one clear set of methods that must be used in exploratory design. A researcher should select the methodologies that would be most effective in meeting your research questions.

However, commonly, exploratory studies are shaped as small-scale qualitative designs. Qualitative research allows researchers to delve deep into a topic to generate high-quality, contextualized, and nuanced descriptive data. Qualitative data generally cannot create generalizable results, but it does help to create hypotheses that can be looked at with larger-scale quantitative studies.

Examples of exploratory research designs can include:

• Expert Interviews : When exploring a relatively new phenomenon, researchers can speak to professionals or experts in the field to gain their perspectives. This perspective-taking, often taking the form of a delphi method focus group , can help researchers to better understand the key factors within a topic that will inform subsequent study designs (Raley et al., 2016).
• Case Studies : Oftentimes, exploratory research looks at novel and rare phenomena. To begin to understand them, researchers need to look at them in depth. To do this, they may employ a case study design, which allows researchers to take a very in-depth examination of one instance (Lee & Saunders, 2017). This will, in turn, inform future studies that may look at a wider corpus that can create statistically relevant results.
• Observational Studies : This involves observing and noting the behavior or situation of interest. There are multiple types of observational research , ranging from non-intrusive ‘fly on the wall’ observations to participant observations such as ethnographic studies .
• Cross-Sectional Research : This is an example of a qualitative exploratory research design. Imagine researchers want to study an emerging health condition among a population. As it’s emergent, there’s no data yet, but researchers need to know how big a problem this is. To do so, they may conduct an initial cross-sectional study , which gathers statistically relevant descriptive data about how prevalent the condition is. This exploratory study won’t be able to determine cause-and-effect between variables, but it could from the basis and justification for subsequent studies.

A Hypothetical Example

Study Title: The relationship between urban green spaces and mental well-being

Explanation: In an exploratory study examining the relationship between urban green spaces and mental well-being, researchers could survey residents from various neighborhoods about their frequency of visiting local parks and their perceived stress levels.

Design: Since, hypothetically, little prior research exists on this specific topic, the team could employ open-ended interviews, allowing participants to share detailed experiences and insights. Preliminary data might indicate a potential positive correlation between regular park visits and lower stress levels. To gain a deeper understanding, focus groups could be conducted next, where participants discuss the therapeutic effects of nature, setting the stage for more structured, quantitative studies in the future.

Recommendations: Exploratory research usually provides recommendations for more focused subsequent studies. The researchers in this study might recommend exploring the supposed positive correlation between park visits and lower stress through a statistical analysis.

See More Exploratory Research Examples

Benefits and Limitations of Exploratory Research Design

Exploratory research design is very useful for providing initial insights into a topic, describing phenomena in detail, and exploring a topic without the predetermined constraints of mere hypothesis testing.

But it’s not the best research design in all situations. For example, it might not be ideal if you were seeking to achieve clarity on well-worn topics, generate generalizable results that add to existing literature, or contribute to a specific set of existing scholarly discourse on a topic.

Below are some strengths and weaknesses of this research design:

Blecher, M. (2018). Israeli Settlements: Land Politics Beyond the Geneva Convention . Hamilton Books.

Cargan, L. (2007). Doing Social Research . Rowman & Littlefield Publishers.

Gozdziak, E. M., & Chantavanich, S. (2022). Africans in Thailand. In Gozdziak, E. M., & Chantavanich, S. (Eds.). African Migration to Thailand: Race, Mobility, and Integration. Taylor & Francis.

Hammond, M., & Wellington, J. J. (2013).  Research Methods: The Key Concepts . Routledge.

Hutchison, T., Allen, P., & Macy, A. (2012).  Record Label Marketing . Taylor & Francis.

Lee, B., & Saunders, M. N. K. (2017).  Conducting Case Study Research for Business and Management Students.  SAGE Publications.

Morrison, A. M. (2022).  Tourism Marketing: In the Age of the Consumer . Taylor & Francis.

Raley, M. E., Ragona, M., Sijtsema, S. J., Fischer, A. R., & Frewer, L. J. (2016). Barriers to using consumer science information in food technology innovations: An exploratory study using Delphi methodology.  International Journal of Food Studies ,  5 (1). ( Source )

Swedberg, R. (2020). Exploratory Research. In Elman C, Gerring J, & Mahoney J. (Eds.)  The Production of Knowledge: Enhancing Progress in Social Science.  Cambridge: Cambridge University Press.

Tan, W. C. K. (2022).  Research Methods: A Practical Guide For Students And Researchers  (Second Edition). World Scientific Publishing Company.

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Home » Exploratory Research – Types, Methods and Examples

Exploratory Research – Types, Methods and Examples

Table of Contents

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.

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• Types of Research Designs

TRIO McNair Undergraduate Research Guide: Types of Research Designs

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Ethics of Research
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Expanding the Timeliness of a Topic Idea
• Writing a Research Proposal
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• The Abstract
• Background Information
• The Research Problem/The Question
• Theoretical Framework
• Citation Mining
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• Scholarly v. Popular Sources
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Preparing Your Poster
• Dealing with Nervousness
• Using Visual Aids
• Peer Review Process
• Informed Consent
• Writing Field Notes

Introduction

Before beginning your paper, you will need to design the study. 

The research design refers to the overall strategy that you choose to integrate the different components of the study in a coherent and logical way, thereby, ensuring you will effectively address the research problem; it constitutes the blueprint for the collection, measurement, and analysis of data. Note that your research problem determines the type of design you can use, not the other way around! 

• General Structure & Writing Style

Action Research Design

Case study design.

• Causal Design

Cohort Design

Cross-sectional design, descriptive design, experimental design, exploratory design, historical design, longitudinal design, observational design, philosophical design, sequential design.

Kirshenblatt-Gimblett, Barbara. Part 1, What Is Research Design? The Context of Design. Performance Studies Methods Course syllabus. New York University, Spring 2006; 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 as unambiguously as possible. In social sciences research, obtaining evidence relevant to the research problem generally entails specifying the type of evidence needed to test a theory, to evaluate a program, or to accurately describe a phenomenon. However, researchers can often begin their investigations far too early, before they have thought critically about what information is required to answer the study's research questions. Without attending to these design issues beforehand, the conclusions drawn risk being weak and unconvincing and, consequently, will fail to adequately address the overall research problem. 

 Given this, the length and complexity of research designs can vary considerably, but any sound design will do the following things: 

Identify the research problem clearly and justify its selection, 

Review previously published literature associated with the problem area, 

Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem selected, 

Effectively describe the data which will be necessary for an adequate test of the hypotheses and explain how such data will be obtained, and 

Describe the methods of analysis which will be applied to the data in determining whether or not the hypotheses are true or false. 

Kirshenblatt-Gimblett, Barbara. Part 1, What Is Research Design? The Context of Design. Performance Studies Methods Course syllabus. New York University, Spring 2006.

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 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 the cyclic process repeats, continuing until a sufficient understanding of (or implement able 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? 

A collaborative and adaptive research design that lends itself to use in work or community situations. 

Design focuses on pragmatic and solution-driven research 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 also be regarded as a learning cycle. 

Action search studies often have direct and obvious relevance to practice. 

There are no hidden controls or preemption of direction by the researcher. 

What do these studies not tell you? 

It is harder to do than conducting conventional studies because the researcher takes on responsibilities for encouraging change as well as for research. 

Action research is much harder to write because you probably can’t use a standard format to report your findings effectively. 

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. 

Gall, Meredith.  Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In  Handbook of Qualitative Research . Norman Denzin and Yvonna S. Locoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605.; Reason, Peter and Hilary Bradbury.  Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey. 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 a 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 extension of methods. 

The design can provide detailed descriptions of specific and rare cases. 

What do these studies not tell you?  

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. 

The intense exposure to study of the 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 criterion 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. 

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; 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.

Casual 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 help researchers understand why the world works the way it does through the process of proving a causal link between variables and 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 casual! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxsutawney 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. 

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; 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.

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 on 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. 

Because of the lack of randomization 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;  Levin, Kate Ann. Study Design IV: Cohort Studies.  Evidence-Based Dentistry  7 (2003): 51–52;  Study Design 101 . Himmelfarb Health Sciences Library. George Washington University, November 2011;  Cohort Study . Wikipedia.

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 change. As such, researchers using this design can only employ a relative passive approach to making causal inferences based on findings. 

Cross-sectional studies provide a 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time. 

Unlike the 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 contexts. 

Studies cannot be utilized to establish cause and effect relationships. 

Provide only a snapshot of analysis so there is always the possibility that a study could have differing results if another timeframe had been chosen. 

There is no follow up to the findings. 

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 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. 

Descriptive research is often used as a pre-cursor to more quantitatively research designs, 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. 

Approach collects a large amount of data for detailed analysis. 

The results from 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;  McNabb, Connie.  Descriptive Research Methodologies . Powerpoint Presentation; Shuttleworth, Martyn.  Descriptive Research Design , September 26, 2008. Explorable.com website.

A blueprint of the procedure 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 subject behaviors or responses. 

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 experimental designed research 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; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Trochim, William M.K.  Experimental Design . Research Methods Knowledge Base. 2006; Rasool, Shafqat.  Experimental Research . Slideshare presentation.

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to. The focus is on gaining insights and familiarity for later investigation or undertaken when problems are in a preliminary stage of investigation. 

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 assumption, 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. 

Exploratory studies help establish research priorities. 

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. 

The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value in decision-making. 

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; 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.

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute your hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, logs, 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 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 is 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. 

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. 

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.

A longitudinal study follows the same sample over time and makes repeated observations. With longitudinal surveys, for example, 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 and is sometimes referred to as a panel study. 

Longitudinal data allow the analysis of 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 to explain fluctuations in the data. 

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 representativeness. 

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; 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; 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.

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 a depth of 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 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 of determining "cause and effect" relationships since nothing is manipulated. 

Sources or subjects may not all be equally credible. 

Any group that is studied is altered to some degree by the very presence of the researcher, therefore, skewing to some degree any data collected (the Heisenberg Uncertainty Principle). 

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; Rosenbaum, Paul R.  Design of Observational Studies . New York: Springer, 2010.

Definition and Purpose  

Understood more as a 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, on what 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. 

Chapter 4, Research Methodology and Design . Unisa Institutional Repository (UnisaIR), University of South Africa;  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, D.C.: Falmer Press, 1994;  Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential research is that which is carried out in a deliberate, staged approach [i.e., serially] where one stage will be completed, followed by another, then another, and so on, with the aim that each stage will build upon the previous one until enough data is gathered over an interval of time to test your hypothesis. The sample size is not predetermined. After each sample is analyzed, the researcher can accept the null hypothesis, accept the alternative hypothesis, or select another pool of subjects and conduct the study once again. This means the researcher can obtain a limitless number of subjects before finally making a decision whether to accept the null or alternative hypothesis. Using a quantitative framework, a sequential study generally utilizes sampling techniques to gather data and apply statistical methods to analyze the data. Using a qualitative framework, sequential studies generally utilize samples of individuals or groups of individuals [cohorts] and use qualitative methods, such as interviews or observations, to gather information from each sample. 

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 made during the initial parts of the study to correct and hone the research method. 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 extensive. 

Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. 

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 sample can be difficult. 

Because the sampling technique is not randomized, the design cannot be used to create conclusions and interpretations that pertain to an entire population. Generalizability from findings is limited. 

Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection. 

Rebecca Betensky, Harvard University,  Course Lecture Note slides ; 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; 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.

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Business Research Design: Exploratory, Descriptive and Causal Designs

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The objective of this chapter is to define and explain research design in detail. In this chapter, we discussed three major types of research designs, such as exploratory, descriptive and causal research designs. We also explained the mode of data used in each of these designs and the techniques to collect these data, which would ultimately helps the researcher to decide appropriate analysis technique. This chapter concludes with budgeting and scheduling of a business research project and elaborated the guidelines for writing a business research proposal. This chapter designed in such a way that the reader can appreciate these concepts by considering the examples and cartoon illustrations, which would better elicit and convince the concept understanding.

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The Use of Experiments in Business Research

Basic Research Methods

Writing about Research Design

By David Voreacos, Alex Nussbaum and Greg Farrel, Johnson and Johnson reaches a band-aid, Bloomberg Business week.

Due of lack of representativeness it is not possible to compare the results from different groups in a strict quantitative sense.

See Ref. Sudman ( 1980 ).

See Ref. Cook and Campbell ( 1979 ).

ASQ Statistics Division Newsletter (2000), vol 19(issue 2)

Google Scholar  

Beri GC (1989) Marketing research, 1st edn. Tata McGraw-Hill, New Delhi

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Sudman S (1980) Improving the quality of shopping centre sampling. J Mark Res 17:423–431

Zikmund WG (2003) Business research methods, 7th edn. Thomson South-Western, Singapore, p 281

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In an experimental design, the primary goal is to isolate and identify the effects produced by the…

Dependent variable

Extraneous variable

Independent variable

An experiment has high… if one has confidence that the experiential treatment has been the source of change in the dependent variable.

Internal validity

External validity

Internal and external validity

Internal and external reliability

Which of the following is a threat to internal validity of an experimental design

Interaction of setting and treatment

Interaction effects of pre-testing

Reactive effects of experimental design

Which of the following effect in internal validity occurs when test units with extreme scores move closer to the average score during the course of the experiment

Statistical Regression

Selection bias

Instrumentation

Which of the following statement is incorrect with respect to ‘An experimental design is a set of procedures specifying

How to test units (subjects) are divided into homogeneous sub samples

What independent variables or treatments are to be measured

What dependent variables are to be measured

How the extraneous variables are to be controlled

Randomization of test units is a part of…

A characteristic that distinguishes true experiments from weaker experimental designs is that true experiments include

Random assignment

Repeated measurements of the dependent variable

Random sampling

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Sreejesh, S., Mohapatra, S., Anusree, M.R. (2014). Business Research Design: Exploratory, Descriptive and Causal Designs. In: Business Research Methods. Springer, Cham. https://doi.org/10.1007/978-3-319-00539-3_3

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• Key Differences

Know the Differences & Comparisons

Difference Between Exploratory and Descriptive Research

The research design is defined as a framework for carrying out research activities in different fields of study. The research design is classified into two important categories i.e. exploratory and conclusive research. Conclusive research is further subdivided into descriptive and casual research. The people often juxtapose exploratory research and descriptive research, but the fact is that they are different.

Take a read of this article to understand the differences between exploratory and descriptive research.

Content: Exploratory Research Vs Descriptive Research

Comparison chart.

Definition of Exploratory Research

As the name implies, the primary objective of exploratory research is to explore a problem to provide insights into and comprehension for more precise investigation. It focuses on the discovery of ideas and thoughts. The exploratory research design is suitable for studies which are flexible enough to provide an opportunity for considering all the aspects of the problem.

At this point, the required information is loosely defined, and the research process is flexible and unstructured. It is used in the situation when you must define the problem correctly, identify alternative courses of actions, develop a hypothesis, gain additional insights before the development of an approach, set priorities for further examination. The following methods are used for conducting exploratory research

• Survey of concerning literature
• Experience survey
• Analysis of insights stimulating

Definition of Descriptive Research

By the term descriptive research, we mean a type of conclusive research study which is concerned with describing the characteristics of a particular individual or group. It includes research related to specific predictions, features or functions of person or group, the narration of facts, etc.

The descriptive research aims at obtaining complete and accurate information for the study, the method adopted must be carefully planned. The researcher should precisely define what he wants to measure? How does he want to measure? He should clearly define the population under study. It uses methods like quantitative analysis of secondary data, surveys, panels, observations, interviews, questionnaires, etc.

Descriptive Research concentrates on formulating the research objective, designing methods for the collection of data, selection of the sample, data collection, processing, and analysis, reporting the results.

Key Differences Between Exploratory and Descriptive Research

The difference between exploratory and descriptive research can be drawn clearly on the following grounds:

• Research conducted for formulating a problem for more clear investigation is called exploratory research. Research that explore and explains an individual, group or a situation, is called descriptive research.
• The exploratory research aims at the discovery of ideas and thoughts whereas the primary purpose of descriptive research is to describe the characteristics and functions.
• The overall design of the exploratory research should be flexible enough so that it provides an opportunity to consider various aspects of the problem. On the contrary, in descriptive research, the overall design should be rigid which protects against bias and also maximise reliability.
• The research process is unstructured in exploratory research. However, it is structured in the case of descriptive research.
• Non-probability sampling i.e. judgment or purposive sampling design is used in exploratory research. As opposed to descriptive research where probability (random) sampling design is used.
• When it comes to statistical design, exploratory research has no pre-planned design for analysis. Unlike, descriptive research that has the pre-planned design for analysis.

Therefore exploratory research results in insights or hypothesis, regardless of the method adopted, the most important thing is that it should remain flexible so that all the facets of the problem can be studied, as and when they arise. Conversely, descriptive research is a comparative design which is prepared according to the study and resources available. Such study minimises bias and maximises reliability.

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• Knowledge Base

Methodology

• Exploratory Research | Definition, Guide, & Examples

Exploratory Research | Definition, Guide, & Examples

Published on December 6, 2021 by Tegan George . Revised on November 20, 2023.

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

Exploratory research is often qualitative and primary 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, other interesting articles, 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 middle 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 and problem statement , 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 schools 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: Hypothesize 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, conceptualize your data collection and data analysis methods and write them up in a research design.

Step 4: Collect and analyze data

Next, you proceed with collecting and analyzing 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 generalizable results.

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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 studies have their trade-offs: they provide a unique set of benefits but also come 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 generalizable, 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 labor-intensive.

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

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

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.

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

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Research design and its types: Exploratory, descriptive and causal

Table of Contents

Research designs in marketing research and their types: Exploratory, descriptive and causal

A common definition of research is gathering and analysing information systematically. After having set the objectives of research, next step is to decide the research design which best suits the research objectives. It is on the basis of the research design that the research methodology and sampling procedure are selected. Then lay out the structure and sequence of the overall research project. Finally, the research design is implemented and this implementation begins with the design of the data gathering instruments. After that follows, data collection, manipulation and analysis and at last the data is interpreted to know the results.

A research design is an important part of research that serves as a road map letting you know your position and where you will stand once you have completed the research. Researchers must keep their ultimate objectives in mind even if they have to take detours and change direction during the research process. The road map helps them reach their destination. Based on the research objectives a researcher can decide which is the best way to reach the destination and there are always more than one to go. There is not one research design which you can consider the best but you can select from several. The choice of research design is affected by several factors, small and large. From research objectives to search budget and time frame, there are several factors that can help you determine which research design suits your research the best. Much of the choice is still based on the objectives of the research which may be one of the following or something similar:

– Gain insight into a specific phenomenon and conduct a broad exploration of a topic to gain better knowledge in that field.

– Describing a phenomenon, population or event where we can establish numerical relationships or determine the extent to which two variables covary.

– Establish cause and effect relationships between two variables to understand how one changes when we vary the other.

These were the three broadly defined types of objectives on which names of types of research designs have been obtained respectively.

The three types of research designs are:

– Exploratory research

– Descriptive research

– Causal   research.

 Exploratory research

It is a lot like exploration or detective work fuelled by curiosity. Researchers should use their instincts to find clues and venture into new territories in search of information. Flexibility is important in exploratory research and it is bound to result in new ideas, revelations and insights.

These are some of the objectives that warrant the need for exploratory research:

– To define an ambiguous problem more precisely like why sales of a specific product are declining.

– To gain   a better understanding of an   issue.

– to generate new ideas like what one can do to improve customer relationships.

– develop hypotheses that can explain the occurrence of specific phenomena.

– for providing insights like what political changes in the international environmental are going to affect our business.

– to determine if some research would be practical and to set priorities for future like we must focus on these two product categories because as per research interest in other categories has waned and they are not profitable nay more.

Some tools used to conduct exploratory research:

1. Secondary information:

Most often the best point to start research from is to study the previous research conducted in this area. If you study what others have found out, it will help you generate ideas, hypotheses and gain insights. For example if you are trying to conduct research to create an instrument that helps you measure customer satisfaction from your product or services then studying others’ research will help you reach your objectives quicker. Literature reviews most often are a great tool to conduct exploratory research.

2. Personal interviews:

Personal interviews are a great tool of exploratory research and talking to people with expertise in the respective areas can help you achieve your objectives more easily. Moreover, it is important to be flexible because the sources from which you can gain the most valuable insights are always not obvious. Sometimes you may find the right information from your managers, sometimes from your customers and sometimes talking to your supply chain partners could help understand the issue better. However, while personal interviews are also used in descriptive research, the level of flexibility differs. In descriptive research you are somewhat bound by your questions and in exploratory research you have to be flexible and rather than sticking to your original questions, you must ask questions related to what you are hearing from people you are talking to.

3. Focus groups:

Focus group is also a highly popular technique used to conduct exploratory research. A group of 8 to 12 people works on addressing a topic introduced by the moderator and the researcher. Focus groups have proved to be of special importance in :

– Letting marketing managers see how consumers respond to the company’s efforts.

– Generating hypothesis that can be tested through the use of descriptive and causal research.

– Introducing a new product to the respondents to know their impression.

– Suggest the current market trends.

– Deriving real results from abstract data or finding how a survey response translates into real life reactions.

The popularity of focus groups is because of their effectiveness and efficiency as well as because researchers or decision makers can themselves attend them and observe the response of the participants live. However, a major disadvantage is that a group of just 8 to 12 people cannot be believed to be representative of the entire consumer group. Moreover one cannot conduct extra focus groups to convert findings of exploratory research into descriptive data.

4. Case Analysis:

Analysing select cases also helps achieve the objectives of exploratory research. By doing an in-depth analysis of elect cases related to the topic one can reach his objectives. This approach is suitable when there are complex variables at work and to understand these complexities one may need to conduct intensive study. For example you want to know the reason or traits related to his level performance among your sales managers. You compare the top performers and bottom performers to check out which traits are common to the best performing salespeople.

5. Projective techniques:

Projective techniques are useful where the researchers are exploring a topic on which the respondents do not speak directly and clearly. Sensitive topics involving people’s personal lives fall obviously in this category. Projective techniques can be used to find out these deep hidden psychological motives which people would otherwise not reveal. Using a variety of communication and observable methods researchers explore these deep psychological motivations which otherwise do not reveal themselves at the surface.

These methods include (types of projective techniques):

– Word association –

In word association, a series of words are used to associate responses and find out the relationship. The respondents are provided with a   series of words and they select the word that comes to mind first. The response, its frequency as well as the time taken to make the response helps establish the underlying motivations towards the topic. No response means a high level of emotional involvement blocking the response. 

– Sentence completion –

Sentence completion is like a game of filling the gaps and allows responders to complete the sentence by inserting the right word or phrases. The responses are then analysed to establish underlying motivations towards the topic.

– Story telling –

Respondents are provided with a scene or drawing related to the topic and asked to knit a story around it. This allows the researcher to see there respondent’s association with the topic and his psychological motivations. Suppose a workplace scene is provided to the respondents and the stories help understand how these people view a workplace. The picture works as a visual aid or stimulus to bring out the inner thoughts or deep motivations of the respondent.

– Role playing or the third person technique –

Respondents are asked to play particular roles or enter a third person’s shoes to explain why a person might act in a certain way in a given situation. Like asking people to play the role of a retail customer arriving at a retain store..

While these techniques can provide intriguing insights, it is best to leave the tasks to the experts. Apart from being skilled at structuring these approaches, it is essential that one is also experienced at interpreting these results. If properly applied, these techniques can help you generate hypotheses, clarify results and generate ideas. Often it is good to start a multistage research project with exploratory research. Then based upon the results of exploratory research one can frame a descriptive research questionnaire or set a causal research experiment. However, exploratory results do not have value alone and cannot be used till the real research has taken place. It is because the preliminary research alone is not sufficient to support your claims   and therefore exploratory research results  cannot be used alone. Descriptive research is important to reach your objectives and test the hypotheses generated by exploratory research and still exploratory research is like a stepping stone to start the process.

Descriptive research:

Descriptive research as the name suggests is used for description or to describe   phenomenon or idea. It is generally used in the following conditions:

1. to describe the traits of specific groups like our largest customers who account for more than 60 percent of our sales and based upon the results design future marketing efforts.

2. Covariance of two variables – like does consumption of our services vary by income range.

3. to estimate the size of consumer groups in a   population that act in a specific manner.   How often do newly married like to shop from our brand?

4. For specific predictions. Forecasting the number of companies switching to new CRM software.

Compared to exploratory research, descriptive research follows a very rigid approach. Its data collection methods are highly rigid as compared to the unstructured and flexible approach used in exploratory research. Exploratory research often forms the basis for descriptive research and the knowledge acquires through exploratory research is used to select respondents, setting priority issues, framing and asking questions as well as setting the time and place for the respondents like when and where to ask questions. While exploratory research can provide the hypotheses, you need to conduct descriptive research to prove the hypotheses. Exploratory research will answer the basic questions related to who, where, what when, why and how if descriptive research but then descriptive research will answer the final questions related to the market. The main difference between exploratory and descriptive research is that the first does not follow standardized methods but the second does.

So, descriptive research does the task of putting the picture created by exploratory research into the frame. Two basic types of descriptive research studies for collecting data are cross sectional and longitudinal studies.

Cross sectional studies:

Cross sectional designs are the most used and popular descriptive research design. It involves sampling the population at a given point of time. also referred to as sample surveys, it follows a high degree of structure in both data collection process and instrument.

Longitudinal studies:

While cross sectional studies sample the population at a point of time, longitudinal studies sample it over a period of time. The difference is just like that between a still photo and video film. The main objective of longitudinal studies is to observe behavioural changes occurring over   period of time. Also known as true panels, these studies provide the same information at various specific points of time. This information can be combined with other information to know if some specific behaviour change was triggered by a particular act like brand switching was caused due to exposure to a particular advertisement.

Causal research:

Casual research is effective in terms of identifying covariation between variables but when it comes to identifying causality. Causal research helps identify if there is a causal relationship between two or more variables. It is highly structured like descriptive research and is also known for use of control procedures used during experimental designs related to tests of causal relationships. In most of such cases the researcher is concerned with knowing the impact the independent variable has on the dependent variable. Following are the main things that we are concerned with when using causal research:

Manipulation:

manipulation of the independent variable like price

Measurement:

Measuring the dependent variable like profit.

Controlling the variable that affects the dependent variable

Good marketing decisions and great strategy are always based upon useful market intelligence and such information can be obtained through research. Organisational problems can be carefully translated into research problems to find a solution.   R esearch design is an essential and important component of research that helps you reach your destination and arrive at great decisions by getting actionable information. Research design includes one or more of the above categories. It is the research objectives that help us establish that   whether one or more of the research designs must be used.

The Marketing Research Guide By Robert E. Stevens