difference between empirical research definition

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Empirical Research: Definition, Methods, Types and Examples

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Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

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You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

• Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
• Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

• Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

• Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

• Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

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For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

• Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

• Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

• Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

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Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

LEARN ABOUT: Qualitative Interview

• Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

• Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

• One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

• Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

• Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

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Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

• Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
• Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
• Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
• Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
• Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

LEARN MORE: Population vs Sample

There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

• It is used to authenticate traditional research through various experiments and observations.
• This research methodology makes the research being conducted more competent and authentic.
• It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
• The level of control in such a research is high so the researcher can control multiple variables.
• It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

• Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
• Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
• There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
• Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

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Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

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With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

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Empirical Research: Defining, Identifying, & Finding

Defining empirical research, what is empirical research, quantitative or qualitative.

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Calfee & Chambliss (2005)  (UofM login required) describe empirical research as a "systematic approach for answering certain types of questions."  Those questions are answered "[t]hrough the collection of evidence under carefully defined and replicable conditions" (p. 43). 

The evidence collected during empirical research is often referred to as "data." 

Characteristics of Empirical Research

Emerald Publishing's guide to conducting empirical research identifies a number of common elements to empirical research: 

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample [emphasis added]: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalize  from the findings to a larger sample and to other situations.

If you see these elements in a research article, you can feel confident that you have found empirical research. Emerald's guide goes into more detail on each element. 

Empirical research methodologies can be described as quantitative, qualitative, or a mix of both (usually called mixed-methods).

Ruane (2016)  (UofM login required) gets at the basic differences in approach between quantitative and qualitative research:

• Quantitative research  -- an approach to documenting reality that relies heavily on numbers both for the measurement of variables and for data analysis (p. 33).
• Qualitative research  -- an approach to documenting reality that relies on words and images as the primary data source (p. 33).

Both quantitative and qualitative methods are empirical . If you can recognize that a research study is quantitative or qualitative study, then you have also recognized that it is empirical study. 

Below are information on the characteristics of quantitative and qualitative research. This video from Scribbr also offers a good overall introduction to the two approaches to research methodology: 

Characteristics of Quantitative Research 

Researchers test hypotheses, or theories, based in assumptions about causality, i.e. we expect variable X to cause variable Y. Variables have to be controlled as much as possible to ensure validity. The results explain the relationship between the variables. Measures are based in pre-defined instruments.

Examples: experimental or quasi-experimental design, pretest & post-test, survey or questionnaire with closed-ended questions. Studies that identify factors that influence an outcomes, the utility of an intervention, or understanding predictors of outcomes. 

Characteristics of Qualitative Research

Researchers explore “meaning individuals or groups ascribe to social or human problems (Creswell & Creswell, 2018, p3).” Questions and procedures emerge rather than being prescribed. Complexity, nuance, and individual meaning are valued. Research is both inductive and deductive. Data sources are multiple and varied, i.e. interviews, observations, documents, photographs, etc. The researcher is a key instrument and must be reflective of their background, culture, and experiences as influential of the research.

Examples: open question interviews and surveys, focus groups, case studies, grounded theory, ethnography, discourse analysis, narrative, phenomenology, participatory action research.

Calfee, R. C. & Chambliss, M. (2005). The design of empirical research. In J. Flood, D. Lapp, J. R. Squire, & J. Jensen (Eds.),  Methods of research on teaching the English language arts: The methodology chapters from the handbook of research on teaching the English language arts (pp. 43-78). Routledge.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=125955&site=eds-live&scope=site .

Creswell, J. W., & Creswell, J. D. (2018).  Research design: Qualitative, quantitative, and mixed methods approaches  (5th ed.). Thousand Oaks: Sage.

How to... conduct empirical research . (n.d.). Emerald Publishing.  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research .

Scribbr. (2019). Quantitative vs. qualitative: The differences explained  [video]. YouTube.  https://www.youtube.com/watch?v=a-XtVF7Bofg .

Ruane, J. M. (2016).  Introducing social research methods : Essentials for getting the edge . Wiley-Blackwell.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1107215&site=eds-live&scope=site .  

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Penn State University Libraries

Empirical research in the social sciences and education.

• What is Empirical Research and How to Read It
• Finding Empirical Research in Library Databases
• Designing Empirical Research
• Ethics, Cultural Responsiveness, and Anti-Racism in Research
• Citing, Writing, and Presenting Your Work

Contact the Librarian at your campus for more help!

Introduction: What is Empirical Research?

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behavior, or   phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools used in the present study
• Results : sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Reading and Evaluating Scholarly Materials

Reading research can be a challenge. However, the tutorials and videos below can help. They explain what scholarly articles look like, how to read them, and how to evaluate them:

• CRAAP Checklist A frequently-used checklist that helps you examine the currency, relevance, authority, accuracy, and purpose of an information source.
• IF I APPLY A newer model of evaluating sources which encourages you to think about your own biases as a reader, as well as concerns about the item you are reading.
• Credo Video: How to Read Scholarly Materials (4 min.)
• Credo Tutorial: How to Read Scholarly Materials
• Credo Tutorial: Evaluating Information
• Credo Video: Evaluating Statistics (4 min.)
• Next: Finding Empirical Research in Library Databases >>
• Last Updated: Feb 18, 2024 8:33 PM
• URL: https://guides.libraries.psu.edu/emp

Difference between Theoretical and Empirical Research

The difference between theoretical and empirical research is fundamental to scientific, scholarly research, as it separates the development of ideas and models from their testing and validation.

These two approaches are used in many different fields of inquiry, including the natural sciences, social sciences, and humanities, and they serve different purposes and employ different methods.

Table of Contents

What is theoretical research.

Theoretical research involves the development of models, frameworks, and theories based on existing knowledge, logic, and intuition.

It aims to explain and predict phenomena, generate new ideas and insights, and provide a foundation for further research.

Theoretical research often takes place at the conceptual level and is typically based on existing knowledge, data, and assumptions.

What is Empirical Research?

In contrast, empirical research involves collecting and analysing data to test theories and models.

Empirical research is often conducted at the observational or experimental level and is based on direct or indirect observation of the world.

Empirical research involves testing theories and models, establishing cause-and-effect relationships, and refining or rejecting existing knowledge.

Theoretical vs Empirical Research

Theoretical research is often seen as the starting point for empirical research, providing the ideas and models that must be tested and validated.

Theoretical research can be qualitative or quantitative and involve mathematical models, simulations, and other computational methods.

Theoretical research is often conducted in isolation, without reference to primary data or observations.

On the other hand, empirical research is often seen as the final stage in the scientific process, as it provides evidence that supports or refutes theoretical models.

Empirical research can be qualitative or quantitative, involving surveys, experiments, observational studies, and other data collection methods.

Empirical research is often conducted in collaboration with others and is based on systematic data collection, analysis, and interpretation.

It is important to note that theoretical and empirical research are not mutually exclusive and can often complement each other.

For example, empirical data can inform the development of theories and models, and theoretical models can guide the design of empirical studies.

The most valuable research combines theoretical and empirical approaches in many fields, allowing for a comprehensive understanding of the studied phenomena.

It is important to note that this table is not meant to be exhaustive or prescriptive but rather to provide a general overview of the main difference between theoretical and empirical research.

The boundaries between these two approaches are not always clear, and in many cases, research may involve a combination of theoretical and empirical methods.

What are the Limitations of Theoretical Research?

Assumptions and simplifications may be made that do not accurately reflect the complexity of real-world phenomena, which is one of its limitations. Theoretical research relies heavily on logic and deductive reasoning, which can sometimes be biased or limited by the researcher’s assumptions and perspectives.

Furthermore, theoretical research may not be directly applicable to real-world situations without empirical validation. Applying theoretical ideas to practical situations is difficult if no empirical evidence supports or refutes them.

Furthermore, theoretical research may be limited by the availability of data and the researcher’s ability to access and interpret it, which can further limit the validity and applicability of theories.

What are the Limitations of Empirical Research?

There are many limitations to empirical research, including the limitations of the data available and the quality of the data that can be collected. Data collection can be limited by the resources available to collect the data, accessibility to populations or individuals of interest, or ethical constraints.

The researchers or participants may also introduce biases into empirical research, resulting in inaccurate or unreliable findings.

Lastly, due to confounding variables or other methodological limitations, empirical research may be limited by the inability to establish causal relationships between variables, even when statistical associations are identified.

What Methods Are Used In Theoretical Research?

In theoretical research, deductive reasoning, logical analysis, and conceptual frameworks generate new ideas and hypotheses. To identify gaps and inconsistencies in the present understanding of a phenomenon, theoretical research may involve analyzing existing literature and theories.

To test hypotheses and generate predictions, mathematical or computational models may also be developed.

Researchers may also use thought experiments or simulations to explore the implications of their ideas and hypotheses without collecting empirical data as part of theoretical research.

Theoretical research seeks to develop a conceptual framework for empirically testing and validating phenomena.

What Methods Are Used In Empirical Research?

Methods used in empirical research depend on the research questions, type of data collected, and study design. Surveys, experiments, observations, case studies, and interviews are common methods used in empirical research.

An empirical study tests hypotheses and generates new knowledge about phenomena by systematically collecting and analyzing data.

These methods may utilize standardized instruments or protocols for data collection consistency and reliability. Statistical analysis, content analysis, or qualitative analysis may be used for the data collection type.

As a result of empirical research, the findings can inform theories, models, and practical applications.

Conclusion: Theoretical vs Empirical Research

In conclusion, theoretical and empirical research are two distinct but interrelated approaches to scientific inquiry, and they serve different purposes and employ different methods.

Theoretical research involves the development of ideas and models, while empirical research involves testing and validating these ideas.

Both approaches are essential to research and can be combined to provide a more complete understanding of the world.

• Dictionary.com. “ Empirical vs Theoretical “.
• PennState University Libraries. “ Empirical Research in the Social Sciences and Education “.
• William M. Landes and Richard A. Posner. “ Legal Precedent: A Theoretical and Empirical Analysis “, The Journal of Law and Economics, 1976.

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 35min read

Ever wondered how we gather the facts, unveil hidden truths, and make informed decisions in a world filled with questions? Empirical research holds the key.

In this guide, we'll delve deep into the art and science of empirical research, unraveling its methods, mysteries, and manifold applications. From defining the core principles to mastering data analysis and reporting findings, we're here to equip you with the knowledge and tools to navigate the empirical landscape.

What is Empirical Research?

Empirical research is the cornerstone of scientific inquiry, providing a systematic and structured approach to investigating the world around us. It is the process of gathering and analyzing empirical or observable data to test hypotheses, answer research questions, or gain insights into various phenomena. This form of research relies on evidence derived from direct observation or experimentation, allowing researchers to draw conclusions based on real-world data rather than purely theoretical or speculative reasoning.

Characteristics of Empirical Research

Empirical research is characterized by several key features:

• Observation and Measurement : It involves the systematic observation or measurement of variables, events, or behaviors.
• Data Collection : Researchers collect data through various methods, such as surveys, experiments, observations, or interviews.
• Testable Hypotheses : Empirical research often starts with testable hypotheses that are evaluated using collected data.
• Quantitative or Qualitative Data : Data can be quantitative (numerical) or qualitative (non-numerical), depending on the research design.
• Statistical Analysis : Quantitative data often undergo statistical analysis to determine patterns , relationships, or significance.
• Objectivity and Replicability : Empirical research strives for objectivity, minimizing researcher bias . It should be replicable, allowing other researchers to conduct the same study to verify results.
• Conclusions and Generalizations : Empirical research generates findings based on data and aims to make generalizations about larger populations or phenomena.

Importance of Empirical Research

Empirical research plays a pivotal role in advancing knowledge across various disciplines. Its importance extends to academia, industry, and society as a whole. Here are several reasons why empirical research is essential:

• Evidence-Based Knowledge : Empirical research provides a solid foundation of evidence-based knowledge. It enables us to test hypotheses, confirm or refute theories, and build a robust understanding of the world.
• Scientific Progress : In the scientific community, empirical research fuels progress by expanding the boundaries of existing knowledge. It contributes to the development of theories and the formulation of new research questions.
• Problem Solving : Empirical research is instrumental in addressing real-world problems and challenges. It offers insights and data-driven solutions to complex issues in fields like healthcare, economics, and environmental science.
• Informed Decision-Making : In policymaking, business, and healthcare, empirical research informs decision-makers by providing data-driven insights. It guides strategies, investments, and policies for optimal outcomes.
• Quality Assurance : Empirical research is essential for quality assurance and validation in various industries, including pharmaceuticals, manufacturing, and technology. It ensures that products and processes meet established standards.
• Continuous Improvement : Businesses and organizations use empirical research to evaluate performance, customer satisfaction, and product effectiveness. This data-driven approach fosters continuous improvement and innovation.
• Human Advancement : Empirical research in fields like medicine and psychology contributes to the betterment of human health and well-being. It leads to medical breakthroughs, improved therapies, and enhanced psychological interventions.
• Critical Thinking and Problem Solving : Engaging in empirical research fosters critical thinking skills, problem-solving abilities, and a deep appreciation for evidence-based decision-making.

Empirical research empowers us to explore, understand, and improve the world around us. It forms the bedrock of scientific inquiry and drives progress in countless domains, shaping our understanding of both the natural and social sciences.

How to Conduct Empirical Research?

So, you've decided to dive into the world of empirical research. Let's begin by exploring the crucial steps involved in getting started with your research project.

1. Select a Research Topic

Selecting the right research topic is the cornerstone of a successful empirical study. It's essential to choose a topic that not only piques your interest but also aligns with your research goals and objectives. Here's how to go about it:

• Identify Your Interests : Start by reflecting on your passions and interests. What topics fascinate you the most? Your enthusiasm will be your driving force throughout the research process.
• Brainstorm Ideas : Engage in brainstorming sessions to generate potential research topics. Consider the questions you've always wanted to answer or the issues that intrigue you.
• Relevance and Significance : Assess the relevance and significance of your chosen topic. Does it contribute to existing knowledge? Is it a pressing issue in your field of study or the broader community?
• Feasibility : Evaluate the feasibility of your research topic. Do you have access to the necessary resources, data, and participants (if applicable)?

2. Formulate Research Questions

Once you've narrowed down your research topic, the next step is to formulate clear and precise research questions . These questions will guide your entire research process and shape your study's direction. To create effective research questions:

• Specificity : Ensure that your research questions are specific and focused. Vague or overly broad questions can lead to inconclusive results.
• Relevance : Your research questions should directly relate to your chosen topic. They should address gaps in knowledge or contribute to solving a particular problem.
• Testability : Ensure that your questions are testable through empirical methods. You should be able to gather data and analyze it to answer these questions.
• Avoid Bias : Craft your questions in a way that avoids leading or biased language. Maintain neutrality to uphold the integrity of your research.

3. Review Existing Literature

Before you embark on your empirical research journey, it's essential to immerse yourself in the existing body of literature related to your chosen topic. This step, often referred to as a literature review, serves several purposes:

• Contextualization : Understand the historical context and current state of research in your field. What have previous studies found, and what questions remain unanswered?
• Identifying Gaps : Identify gaps or areas where existing research falls short. These gaps will help you formulate meaningful research questions and hypotheses.
• Theory Development : If your study is theoretical, consider how existing theories apply to your topic. If it's empirical, understand how previous studies have approached data collection and analysis.
• Methodological Insights : Learn from the methodologies employed in previous research. What methods were successful, and what challenges did researchers face?

4. Define Variables

Variables are fundamental components of empirical research. They are the factors or characteristics that can change or be manipulated during your study. Properly defining and categorizing variables is crucial for the clarity and validity of your research. Here's what you need to know:

• Independent Variables : These are the variables that you, as the researcher, manipulate or control. They are the "cause" in cause-and-effect relationships.
• Dependent Variables : Dependent variables are the outcomes or responses that you measure or observe. They are the "effect" influenced by changes in independent variables.
• Operational Definitions : To ensure consistency and clarity, provide operational definitions for your variables. Specify how you will measure or manipulate each variable.
• Control Variables : In some studies, controlling for other variables that may influence your dependent variable is essential. These are known as control variables.

Understanding these foundational aspects of empirical research will set a solid foundation for the rest of your journey. Now that you've grasped the essentials of getting started, let's delve deeper into the intricacies of research design.

Empirical Research Design

Now that you've selected your research topic, formulated research questions, and defined your variables, it's time to delve into the heart of your empirical research journey – research design . This pivotal step determines how you will collect data and what methods you'll employ to answer your research questions. Let's explore the various facets of research design in detail.

Types of Empirical Research

Empirical research can take on several forms, each with its own unique approach and methodologies. Understanding the different types of empirical research will help you choose the most suitable design for your study. Here are some common types:

• Experimental Research : In this type, researchers manipulate one or more independent variables to observe their impact on dependent variables. It's highly controlled and often conducted in a laboratory setting.
• Observational Research : Observational research involves the systematic observation of subjects or phenomena without intervention. Researchers are passive observers, documenting behaviors, events, or patterns.
• Survey Research : Surveys are used to collect data through structured questionnaires or interviews. This method is efficient for gathering information from a large number of participants.
• Case Study Research : Case studies focus on in-depth exploration of one or a few cases. Researchers gather detailed information through various sources such as interviews, documents, and observations.
• Qualitative Research : Qualitative research aims to understand behaviors, experiences, and opinions in depth. It often involves open-ended questions, interviews, and thematic analysis.
• Quantitative Research : Quantitative research collects numerical data and relies on statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys.

Your choice of research type should align with your research questions and objectives. Experimental research, for example, is ideal for testing cause-and-effect relationships, while qualitative research is more suitable for exploring complex phenomena.

Experimental Design

Experimental research is a systematic approach to studying causal relationships. It's characterized by the manipulation of one or more independent variables while controlling for other factors. Here are some key aspects of experimental design:

• Control and Experimental Groups : Participants are randomly assigned to either a control group or an experimental group. The independent variable is manipulated for the experimental group but not for the control group.
• Randomization : Randomization is crucial to eliminate bias in group assignment. It ensures that each participant has an equal chance of being in either group.
• Hypothesis Testing : Experimental research often involves hypothesis testing. Researchers formulate hypotheses about the expected effects of the independent variable and use statistical analysis to test these hypotheses.

Observational Design

Observational research entails careful and systematic observation of subjects or phenomena. It's advantageous when you want to understand natural behaviors or events. Key aspects of observational design include:

• Participant Observation : Researchers immerse themselves in the environment they are studying. They become part of the group being observed, allowing for a deep understanding of behaviors.
• Non-Participant Observation : In non-participant observation, researchers remain separate from the subjects. They observe and document behaviors without direct involvement.
• Data Collection Methods : Observational research can involve various data collection methods, such as field notes, video recordings, photographs, or coding of observed behaviors.

Survey Design

Surveys are a popular choice for collecting data from a large number of participants. Effective survey design is essential to ensure the validity and reliability of your data. Consider the following:

• Questionnaire Design : Create clear and concise questions that are easy for participants to understand. Avoid leading or biased questions.
• Sampling Methods : Decide on the appropriate sampling method for your study, whether it's random, stratified, or convenience sampling.
• Data Collection Tools : Choose the right tools for data collection, whether it's paper surveys, online questionnaires, or face-to-face interviews.

Case Study Design

Case studies are an in-depth exploration of one or a few cases to gain a deep understanding of a particular phenomenon. Key aspects of case study design include:

• Single Case vs. Multiple Case Studies : Decide whether you'll focus on a single case or multiple cases. Single case studies are intensive and allow for detailed examination, while multiple case studies provide comparative insights.
• Data Collection Methods : Gather data through interviews, observations, document analysis, or a combination of these methods.

Qualitative vs. Quantitative Research

In empirical research, you'll often encounter the distinction between qualitative and quantitative research . Here's a closer look at these two approaches:

• Qualitative Research : Qualitative research seeks an in-depth understanding of human behavior, experiences, and perspectives. It involves open-ended questions, interviews, and the analysis of textual or narrative data. Qualitative research is exploratory and often used when the research question is complex and requires a nuanced understanding.
• Quantitative Research : Quantitative research collects numerical data and employs statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys. Quantitative research is ideal for testing hypotheses and establishing cause-and-effect relationships.

Understanding the various research design options is crucial in determining the most appropriate approach for your study. Your choice should align with your research questions, objectives, and the nature of the phenomenon you're investigating.

Data Collection for Empirical Research

Now that you've established your research design, it's time to roll up your sleeves and collect the data that will fuel your empirical research. Effective data collection is essential for obtaining accurate and reliable results.

Sampling Methods

Sampling methods are critical in empirical research, as they determine the subset of individuals or elements from your target population that you will study. Here are some standard sampling methods:

• Random Sampling : Random sampling ensures that every member of the population has an equal chance of being selected. It minimizes bias and is often used in quantitative research.
• Stratified Sampling : Stratified sampling involves dividing the population into subgroups or strata based on specific characteristics (e.g., age, gender, location). Samples are then randomly selected from each stratum, ensuring representation of all subgroups.
• Convenience Sampling : Convenience sampling involves selecting participants who are readily available or easily accessible. While it's convenient, it may introduce bias and limit the generalizability of results.
• Snowball Sampling : Snowball sampling is instrumental when studying hard-to-reach or hidden populations. One participant leads you to another, creating a "snowball" effect. This method is common in qualitative research.
• Purposive Sampling : In purposive sampling, researchers deliberately select participants who meet specific criteria relevant to their research questions. It's often used in qualitative studies to gather in-depth information.

The choice of sampling method depends on the nature of your research, available resources, and the degree of precision required. It's crucial to carefully consider your sampling strategy to ensure that your sample accurately represents your target population.

Data Collection Instruments

Data collection instruments are the tools you use to gather information from your participants or sources. These instruments should be designed to capture the data you need accurately. Here are some popular data collection instruments:

• Questionnaires : Questionnaires consist of structured questions with predefined response options. When designing questionnaires, consider the clarity of questions, the order of questions, and the response format (e.g., Likert scale, multiple-choice).
• Interviews : Interviews involve direct communication between the researcher and participants. They can be structured (with predetermined questions) or unstructured (open-ended). Effective interviews require active listening and probing for deeper insights.
• Observations : Observations entail systematically and objectively recording behaviors, events, or phenomena. Researchers must establish clear criteria for what to observe, how to record observations, and when to observe.
• Surveys : Surveys are a common data collection instrument for quantitative research. They can be administered through various means, including online surveys, paper surveys, and telephone surveys.
• Documents and Archives : In some cases, data may be collected from existing documents, records, or archives. Ensure that the sources are reliable, relevant, and properly documented.

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Data Collection Procedures

Data collection procedures outline the step-by-step process for gathering data. These procedures should be meticulously planned and executed to maintain the integrity of your research.

• Training : If you have a research team, ensure that they are trained in data collection methods and protocols. Consistency in data collection is crucial.
• Pilot Testing : Before launching your data collection, conduct a pilot test with a small group to identify any potential problems with your instruments or procedures. Make necessary adjustments based on feedback.
• Data Recording : Establish a systematic method for recording data. This may include timestamps, codes, or identifiers for each data point.
• Data Security : Safeguard the confidentiality and security of collected data. Ensure that only authorized individuals have access to the data.
• Data Storage : Properly organize and store your data in a secure location, whether in physical or digital form. Back up data to prevent loss.

Ethical Considerations

Ethical considerations are paramount in empirical research, as they ensure the well-being and rights of participants are protected.

• Informed Consent : Obtain informed consent from participants, providing clear information about the research purpose, procedures, risks, and their right to withdraw at any time.
• Privacy and Confidentiality : Protect the privacy and confidentiality of participants. Ensure that data is anonymized and sensitive information is kept confidential.
• Beneficence : Ensure that your research benefits participants and society while minimizing harm. Consider the potential risks and benefits of your study.
• Honesty and Integrity : Conduct research with honesty and integrity. Report findings accurately and transparently, even if they are not what you expected.
• Respect for Participants : Treat participants with respect, dignity, and sensitivity to cultural differences. Avoid any form of coercion or manipulation.
• Institutional Review Board (IRB) : If required, seek approval from an IRB or ethics committee before conducting your research, particularly when working with human participants.

Adhering to ethical guidelines is not only essential for the ethical conduct of research but also crucial for the credibility and validity of your study. Ethical research practices build trust between researchers and participants and contribute to the advancement of knowledge with integrity.

With a solid understanding of data collection, including sampling methods, instruments, procedures, and ethical considerations, you are now well-equipped to gather the data needed to answer your research questions.

Empirical Research Data Analysis

Now comes the exciting phase of data analysis, where the raw data you've diligently collected starts to yield insights and answers to your research questions. We will explore the various aspects of data analysis, from preparing your data to drawing meaningful conclusions through statistics and visualization.

Data Preparation

Data preparation is the crucial first step in data analysis. It involves cleaning, organizing, and transforming your raw data into a format that is ready for analysis. Effective data preparation ensures the accuracy and reliability of your results.

• Data Cleaning : Identify and rectify errors, missing values, and inconsistencies in your dataset. This may involve correcting typos, removing outliers, and imputing missing data.
• Data Coding : Assign numerical values or codes to categorical variables to make them suitable for statistical analysis. For example, converting "Yes" and "No" to 1 and 0.
• Data Transformation : Transform variables as needed to meet the assumptions of the statistical tests you plan to use. Common transformations include logarithmic or square root transformations.
• Data Integration : If your data comes from multiple sources, integrate it into a unified dataset, ensuring that variables match and align.
• Data Documentation : Maintain clear documentation of all data preparation steps, as well as the rationale behind each decision. This transparency is essential for replicability.

Effective data preparation lays the foundation for accurate and meaningful analysis. It allows you to trust the results that will follow in the subsequent stages.

Descriptive Statistics

Descriptive statistics help you summarize and make sense of your data by providing a clear overview of its key characteristics. These statistics are essential for understanding the central tendencies, variability, and distribution of your variables. Descriptive statistics include:

• Measures of Central Tendency : These include the mean (average), median (middle value), and mode (most frequent value). They help you understand the typical or central value of your data.
• Measures of Dispersion : Measures like the range, variance, and standard deviation provide insights into the spread or variability of your data points.
• Frequency Distributions : Creating frequency distributions or histograms allows you to visualize the distribution of your data across different values or categories.

Descriptive statistics provide the initial insights needed to understand your data's basic characteristics, which can inform further analysis.

Inferential Statistics

Inferential statistics take your analysis to the next level by allowing you to make inferences or predictions about a larger population based on your sample data. These methods help you test hypotheses and draw meaningful conclusions. Key concepts in inferential statistics include:

• Hypothesis Testing : Hypothesis tests (e.g., t-tests, chi-squared tests) help you determine whether observed differences or associations in your data are statistically significant or occurred by chance.
• Confidence Intervals : Confidence intervals provide a range within which population parameters (e.g., population mean) are likely to fall based on your sample data.
• Regression Analysis : Regression models (linear, logistic, etc.) help you explore relationships between variables and make predictions.
• Analysis of Variance (ANOVA) : ANOVA tests are used to compare means between multiple groups, allowing you to assess whether differences are statistically significant.

Inferential statistics are powerful tools for drawing conclusions from your data and assessing the generalizability of your findings to the broader population.

Qualitative Data Analysis

Qualitative data analysis is employed when working with non-numerical data, such as text, interviews, or open-ended survey responses. It focuses on understanding the underlying themes, patterns, and meanings within qualitative data. Qualitative analysis techniques include:

• Thematic Analysis : Identifying and analyzing recurring themes or patterns within textual data.
• Content Analysis : Categorizing and coding qualitative data to extract meaningful insights.
• Grounded Theory : Developing theories or frameworks based on emergent themes from the data.
• Narrative Analysis : Examining the structure and content of narratives to uncover meaning.

Qualitative data analysis provides a rich and nuanced understanding of complex phenomena and human experiences.

Data Visualization

Data visualization is the art of representing data graphically to make complex information more understandable and accessible. Effective data visualization can reveal patterns, trends, and outliers in your data. Common types of data visualization include:

• Bar Charts and Histograms : Used to display the distribution of categorical or discrete data.
• Line Charts : Ideal for showing trends and changes in data over time.
• Scatter Plots : Visualize relationships and correlations between two variables.
• Pie Charts : Display the composition of a whole in terms of its parts.
• Heatmaps : Depict patterns and relationships in multidimensional data through color-coding.
• Box Plots : Provide a summary of the data distribution, including outliers.
• Interactive Dashboards : Create dynamic visualizations that allow users to explore data interactively.

Data visualization not only enhances your understanding of the data but also serves as a powerful communication tool to convey your findings to others.

As you embark on the data analysis phase of your empirical research, remember that the specific methods and techniques you choose will depend on your research questions, data type, and objectives. Effective data analysis transforms raw data into valuable insights, bringing you closer to the answers you seek.

How to Report Empirical Research Results?

At this stage, you get to share your empirical research findings with the world. Effective reporting and presentation of your results are crucial for communicating your research's impact and insights.

1. Write the Research Paper

Writing a research paper is the culmination of your empirical research journey. It's where you synthesize your findings, provide context, and contribute to the body of knowledge in your field.

• Title and Abstract : Craft a clear and concise title that reflects your research's essence. The abstract should provide a brief summary of your research objectives, methods, findings, and implications.
• Introduction : In the introduction, introduce your research topic, state your research questions or hypotheses, and explain the significance of your study. Provide context by discussing relevant literature.
• Methods : Describe your research design, data collection methods, and sampling procedures. Be precise and transparent, allowing readers to understand how you conducted your study.
• Results : Present your findings in a clear and organized manner. Use tables, graphs, and statistical analyses to support your results. Avoid interpreting your findings in this section; focus on the presentation of raw data.
• Discussion : Interpret your findings and discuss their implications. Relate your results to your research questions and the existing literature. Address any limitations of your study and suggest avenues for future research.
• Conclusion : Summarize the key points of your research and its significance. Restate your main findings and their implications.
• References : Cite all sources used in your research following a specific citation style (e.g., APA, MLA, Chicago). Ensure accuracy and consistency in your citations.
• Appendices : Include any supplementary material, such as questionnaires, data coding sheets, or additional analyses, in the appendices.

Writing a research paper is a skill that improves with practice. Ensure clarity, coherence, and conciseness in your writing to make your research accessible to a broader audience.

2. Create Visuals and Tables

Visuals and tables are powerful tools for presenting complex data in an accessible and understandable manner.

• Clarity : Ensure that your visuals and tables are clear and easy to interpret. Use descriptive titles and labels.
• Consistency : Maintain consistency in formatting, such as font size and style, across all visuals and tables.
• Appropriateness : Choose the most suitable visual representation for your data. Bar charts, line graphs, and scatter plots work well for different types of data.
• Simplicity : Avoid clutter and unnecessary details. Focus on conveying the main points.
• Accessibility : Make sure your visuals and tables are accessible to a broad audience, including those with visual impairments.
• Captions : Include informative captions that explain the significance of each visual or table.

Compelling visuals and tables enhance the reader's understanding of your research and can be the key to conveying complex information efficiently.

3. Interpret Findings

Interpreting your findings is where you bridge the gap between data and meaning. It's your opportunity to provide context, discuss implications, and offer insights. When interpreting your findings:

• Relate to Research Questions : Discuss how your findings directly address your research questions or hypotheses.
• Compare with Literature : Analyze how your results align with or deviate from previous research in your field. What insights can you draw from these comparisons?
• Discuss Limitations : Be transparent about the limitations of your study. Address any constraints, biases, or potential sources of error.
• Practical Implications : Explore the real-world implications of your findings. How can they be applied or inform decision-making?
• Future Research Directions : Suggest areas for future research based on the gaps or unanswered questions that emerged from your study.

Interpreting findings goes beyond simply presenting data; it's about weaving a narrative that helps readers grasp the significance of your research in the broader context.

With your research paper written, structured, and enriched with visuals, and your findings expertly interpreted, you are now prepared to communicate your research effectively. Sharing your insights and contributing to the body of knowledge in your field is a significant accomplishment in empirical research.

Examples of Empirical Research

To solidify your understanding of empirical research, let's delve into some real-world examples across different fields. These examples will illustrate how empirical research is applied to gather data, analyze findings, and draw conclusions.

Social Sciences

In the realm of social sciences, consider a sociological study exploring the impact of socioeconomic status on educational attainment. Researchers gather data from a diverse group of individuals, including their family backgrounds, income levels, and academic achievements.

Through statistical analysis, they can identify correlations and trends, revealing whether individuals from lower socioeconomic backgrounds are less likely to attain higher levels of education. This empirical research helps shed light on societal inequalities and informs policymakers on potential interventions to address disparities in educational access.

Environmental Science

Environmental scientists often employ empirical research to assess the effects of environmental changes. For instance, researchers studying the impact of climate change on wildlife might collect data on animal populations, weather patterns, and habitat conditions over an extended period.

By analyzing this empirical data, they can identify correlations between climate fluctuations and changes in wildlife behavior, migration patterns, or population sizes. This empirical research is crucial for understanding the ecological consequences of climate change and informing conservation efforts.

Business and Economics

In the business world, empirical research is essential for making data-driven decisions. Consider a market research study conducted by a business seeking to launch a new product. They collect data through surveys, focus groups, and consumer behavior analysis.

By examining this empirical data, the company can gauge consumer preferences, demand, and potential market size. Empirical research in business helps guide product development, pricing strategies, and marketing campaigns, increasing the likelihood of a successful product launch.

Psychological studies frequently rely on empirical research to understand human behavior and cognition. For instance, a psychologist interested in examining the impact of stress on memory might design an experiment. Participants are exposed to stress-inducing situations, and their memory performance is assessed through various tasks.

By analyzing the data collected, the psychologist can determine whether stress has a significant effect on memory recall. This empirical research contributes to our understanding of the complex interplay between psychological factors and cognitive processes.

These examples highlight the versatility and applicability of empirical research across diverse fields. Whether in medicine, social sciences, environmental science, business, or psychology, empirical research serves as a fundamental tool for gaining insights, testing hypotheses, and driving advancements in knowledge and practice.

Conclusion for Empirical Research

Empirical research is a powerful tool for gaining insights, testing hypotheses, and making informed decisions. By following the steps outlined in this guide, you've learned how to select research topics, collect data, analyze findings, and effectively communicate your research to the world. Remember, empirical research is a journey of discovery, and each step you take brings you closer to a deeper understanding of the world around you. Whether you're a scientist, a student, or someone curious about the process, the principles of empirical research empower you to explore, learn, and contribute to the ever-expanding realm of knowledge.

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What is Field Research? Definition, Types, Methods, Examples

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Bibliography

Bhattacherjee, A. (2012). Social science research: Principles, methods, and practices. Textbooks Collection . Book 3.

Google Scholar  

Comte, A., & Bridges, J. H. (Tr.) (1865). A general view of positivism . Trubner and Co. (reissued by Cambridge University Press, 2009).

Dilworth, C. B. (1982). Empirical research in the literature class. English Journal, 71 (3), 95–97.

Article   Google Scholar  

Heisenberg, W. (1971). Positivism, metaphysics and religion. In R. N. Nanshen (Ed.), Werner Heisenberg – Physics and beyond – Encounters and conversations , World Perspectives. 42. Translator: Arnold J. Pomerans. New York: Harper and Row.

Hossain, F. M. A. (2014). A critical analysis of empiricism. Open Journal of Philosophy, 2014 (4), 225–230.

Kant, I. (1783). Prolegomena to any future metaphysic (trans: Bennett, J.). Early Modern Texts. www.earlymoderntexts.com

Koch, S. (1992). Psychology’s Bridgman vs. Bridgman’s Bridgman: An essay in reconstruction. Theory and Psychology, 2 (3), 261–290.

Matin, A. (1968). An outline of philosophy . Dhaka: Mullick Brothers.

Mcleod, S. (2008). Psychology as science. http://www.simplypsychology.org/science-psychology.html

Popper, K. (1963). Conjectures and refutations: The growth of scientific knowledge . London: Routledge.

Simmel, G. (1908). The problem areas of sociology in Kurt H. Wolf: The sociology of Georg Simmel . London: The Free Press.

Weber, M. (1991). The nature of social action. In W. G. Runciman (Ed.), Weber: Selections in translation . Cambridge: Cambridge University Press.

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Empirical Research: What is Empirical Research?

• What is Empirical Research?
• Finding Empirical Research in Library Databases
• Designing Empirical Research

Introduction

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology." Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behavior, or phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format (Introduction – Method – Results – and – Discussion), to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology : sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools
• Results : sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Empirical research  is published in books and in  scholarly, peer-reviewed journals .

Make sure to select the  peer-review box  within each database!

• Next: Finding Empirical Research in Library Databases >>
• Last Updated: Nov 21, 2022 8:55 AM
• URL: https://libguides.lahc.edu/empirical

Quantitative and Empirical Research vs. Other Types of Research: Quantitative Research

• Quantitative Research
• Other Types of Research
• What are Scholarly Journals?

     P rofessors often want you to use scholarly journal articles for your assignments.

     Sometimes, they will require you to use scholarly journal articles that contain quantitative research .

DEFINITIONS

QUANTITATIVE

     Quantitative research looks at factors that can actually be measured in some way, in other words, quantified . It produces numerical results that can be analyzed statistically.

     Quantitative research commonly involves experimentation, surveys, or questionnaires in the context of a large, randomly selected group.

     The term  empirical research  is often used as a synonym for quantitative research, but strictly speaking, empirical research is simply any form of research based upon direct observation. It might also be quantitative, but it might not.

PLEASE NOTE: Some professors use these two terms interchangeably.  When this occurs, they are usually referring to articles that fit the quantitative description above.

HINT: Don't use the words "quantitative" or "empirical" in your keyword searches.  They usually do not appear in article titles, abstracts, or subject words.  Instead, check the articles you find to see if some sort of numerical measuring and statistical analysis is present along with the characteristics listed on the right.

CHARACTERISTICS OF QUANTITATIVE RESEARCH

      W atch for these features when determining if an article has quantitative research. They may appear in the abstract, or you may need to skim the text of the article to find them.

• Introduction : a statement of background or purpose (what was being studied and why). May review prior studies on the same topic.
• Description of the design and/or method of the study (the experimental group or sample , control, variables, number of test subjects, test conditions, etc.)
• Results , or report of the findings (in numeric form as tables, charts, or graphs, etc., often with statistical analysis)
• Conclusions that can be drawn from the results (may be labeled  discussion or significance )
• Footnotes and/or a bibliography
• Author credentials (degrees earned, where they work, etc.)  

SAMPLE QUANTITATIVE RESEARCH ARTICLES

• Relations Between Trait Impulsivity, Behavioral Impulsivity, Physiological Arousal, and Risky Sexual Behavior Among Young Men
• Nocturnal Heart Rate Variability in Patients Treated with Cognitive–Behavioral Therapy for Insomnia.
• Characterisation of Mainstream and Passive Vapors Emitted by Selected Electronic Cigarettes

• Next: Other Types of Research >>
• Last Updated: Apr 6, 2023 8:16 AM
• URL: https://libguides.csusb.edu/quantitative

• Connelly Library

Qualitative and Quantitative Research

What is "empirical research".

• empirical research
• Locating Articles in Cinahl and PsycInfo
• Locating Articles in PubMed
• Getting the Articles

Empirical research  is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions  to be answered
• Definition of the  population, behavior, or   phenomena  being studied
• Description of the  process  used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology:  sometimes called "research design" --  how to recreate the study -- usually describes the population, research process, and analytical tools
• Results : sometimes called "findings"  --  what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies
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Library Subject Support

News, tips and features from the Library.

Finding empirical and methodological research articles

When it comes to research methods or research methodologies, there can be a lot of unfamiliar terms and concepts to get to grips with. One question we’re often asked by masters business students is how to find empirical and methodological research articles. It’s a good question as it can be quite tricky to locate articles on these topics, so here’s some advice on how you can go about searching for them in Library Search and the databases that we subscribe to.

What is the difference between empirical and methodological research?

Let’s start by defining our key terms, so we know what to look out for:

Empirical research

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief.

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research methodology . Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behaviour, or phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the “IMRaD” format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called “literature review” — what is currently known about the topic — usually includes a theoretical framework and/or discussion of previous studies
• Methodology : sometimes called “research design” — how to recreate the study — usually describes the population, research process, and analytical tools
• Results : sometimes called “findings” — what was learned through the study — usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called “conclusion” or “implications” — why the study is important — usually describes how the research results influence professional practices or future studies

Thank you to Penn State University for their description of empirical research: https://guides.libraries.psu.edu/emp

Methodological research / study

According to Mbaugbaw et al., a methodological study will:

“…evaluate the design, analysis or reporting of other research-related reports […] They help to highlight issues in the conduct of research with the aim of improving […] research methodology, and ultimately reducing research waste (2020, p.1).

In simple terms, it’s research on research!

• Will have the term ‘methodological research’ or ‘methodological study’ in the title or abstract.
• Has more of a focus on the method(s) employed to do the research (e.g. interviews, questionnaires) rather than the findings of the research.
• Evaluates how research was done and how the methodology could be improved.

How to find empirical and methodological research articles in Library Search and databases

Finding these research articles isn’t always easy, but it can be done! While they are indexed in most databases, it can sometimes be tricky to find them because of the wide variety of names used for these type of studies (methodological research can also be known as research-on-research, meta-research, meta-epidemiological studies etc.).

First, watch this short video that goes through how to find empirical and methodological research articles:

Here’s our top tips for finding empirical and methodological research articles:

Searching via journal titles

The easiest way to find these journal articles is to target journals that are focused on research methods, then search or browse within those titles.

Here’s some examples of such journal titles to help you find methodological studies:

• International Journal of Social Research Methodology
• Organizational Research Methods
• The International Journal of Qualitative Methods
• Journal of Mixed Methods Research
• Methodology
• Qualitative Research

I recommend that you search for these titles in Library Search under ‘Everything except articles’ filter:

Within these titles I recommend searching for “methodological study” in the abstract:

To find empirical research articles , you would go to top, peer-reviewed, research journals in your field of study (the list is endless!) and search within these using relevant keywords.

Here are some key journal titles in the field of business:

• The International Journal of Human Resource Management
• Journal of International Business Studies
• Work, Employment and Society
• Organization Studies
• Academy of Management Journal

You then need to search within these journal titles , ideally within the abstract, for keywords relating to the research design / method ( i.e. how the researcher collected their empirical research) So you might search for terms such as interview*, survey*, questionnaire*, “focus group*” or “mixed method*” :

Searching via keyword in Library Search and databases

If you aren’t finding enough when searching within journal titles, broaden your search by looking within Library Search and other suitable databases.

The Advanced Search within Library Search is a good place to start. Again, try to search for keywords such as “methodological study”, or by method, e.g., interview*, survey*, questionnaire*, “focus group*” or “mixed method*” , along with your subject topic. Remember to use the filters if you need to find research within a particular time frame, such as the last 10 years and to change the drop down to search “everything”.

If you are looking within Scopus or subject specialist databases, such as Business Source Complete, the process is exactly the same. If your search isn’t working, try different keywords, but persevere as the research is there, it just might be hiding:

Searching with controlled vocabulary / subject headings

Some of our databases use controll e d vocabulary (a thesaurus), this allows you to identify the preferred terms used in a particular database for your topic of interest, making it easier to find relevant articles. Here is a worked example using controlled vocabulary in Business Source Complete:

I tried a search for “empirical research”, and found it is a preferred term within this database:

Clicking on this preferred term allows you to explore any related or narrower terms, which you can choose to add to your search to improve the quality of your results:

I decided to add Empirical research and the related term Quantitative research to my search, clicking add to include them in my search string:

I can then add subject related terms to my search:

Many of the social sciences databases have a thesaurus that you can search within.

SAGE Research Methods

For further help on topic of research methods and methodologies, check out SAGE Research Methods . This is a database containing thousands of resources, dedicated to the subject area of Research Methods. It supports all stages of the research process including:  writing a research question, conducting a literature review, choosing the best research methods, analysing data,  to  writing up  your results and thinking about publication. It contains information suited to all levels of researchers, from undergraduates starting your first project to research associates. Within the resource, you can access dictionary and encyclopaedia entries, book chapters, full books, journal articles, case studies, some datasets and video. There are many uses for the resources you will find in SAGE Research Methods:

• get a quick explanation of a term or concept in a dictionary or encyclopaedia entry
• access a full overview of a qualitative and quantitative methods, theory or approach in a specialist book
• use an e-book chapter that covers a specific method in more detail for your methodology chapter or when choosing how to approach your research
• access a journal article that illustrates the real world application of the methods in research

Access the  SAGE Research Methods User Guide  for an overview of the resource, and use the tabs below to access videos and training materials to get started. 

To access SAGE Research Methods, either:

• find it on  Library Search (Links to an external site.)
• visit the the journals and databases section of your  Subject Guide

I hope you have found this useful. I’m sorry there isn’t an easy way for finding such articles, however, a thorough and systematic search within journal titles, Library Search and databases will allow you to find some relevant and good quality articles that you can use in your research.

If you need further help with this topic or something similar, please make an appointment with your Liaison Librarian .

Mbuagbaw, L., Lawson, D. O., Puljak, L., Allison, D. B. and Thabane, L. (2020) ‘A tutorial on methodological studies: the what, when, how and why’, BMC Medical Research Methodology, 20(1). Available at: https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-020-01107-7 (Accessed: 15 June 2022).

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Empirical Research: Quantitative & Qualitative

• Empirical Research

Introduction: What is Empirical Research?

Quantitative methods, qualitative methods.

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Empirical research  is based on phenomena that can be observed and measured. Empirical research derives knowledge from actual experience rather than from theory or belief. 

Key characteristics of empirical research include:

• Specific research questions to be answered;
• Definitions of the population, behavior, or phenomena being studied;
• Description of the methodology or research design used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys);
• Two basic research processes or methods in empirical research: quantitative methods and qualitative methods (see the rest of the guide for more about these methods).

(based on the original from the Connelly LIbrary of LaSalle University)

Empirical Research: Qualitative vs. Quantitative

Learn about common types of journal articles that use APA Style, including empirical studies; meta-analyses; literature reviews; and replication, theoretical, and methodological articles.

Academic Writer

© 2024 American Psychological Association.

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Quantitative Research

A quantitative research project is characterized by having a population about which the researcher wants to draw conclusions, but it is not possible to collect data on the entire population.

• For an observational study, it is necessary to select a proper, statistical random sample and to use methods of statistical inference to draw conclusions about the population. 
• For an experimental study, it is necessary to have a random assignment of subjects to experimental and control groups in order to use methods of statistical inference.

Statistical methods are used in all three stages of a quantitative research project.

For observational studies, the data are collected using statistical sampling theory. Then, the sample data are analyzed using descriptive statistical analysis. Finally, generalizations are made from the sample data to the entire population using statistical inference.

For experimental studies, the subjects are allocated to experimental and control group using randomizing methods. Then, the experimental data are analyzed using descriptive statistical analysis. Finally, just as for observational data, generalizations are made to a larger population.

Iversen, G. (2004). Quantitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.), Encyclopedia of social science research methods . (pp. 897-898). Thousand Oaks, CA: SAGE Publications, Inc.

Qualitative Research

What makes a work deserving of the label qualitative research is the demonstrable effort to produce richly and relevantly detailed descriptions and particularized interpretations of people and the social, linguistic, material, and other practices and events that shape and are shaped by them.

Qualitative research typically includes, but is not limited to, discerning the perspectives of these people, or what is often referred to as the actor’s point of view. Although both philosophically and methodologically a highly diverse entity, qualitative research is marked by certain defining imperatives that include its case (as opposed to its variable) orientation, sensitivity to cultural and historical context, and reflexivity. 

In its many guises, qualitative research is a form of empirical inquiry that typically entails some form of purposive sampling for information-rich cases; in-depth interviews and open-ended interviews, lengthy participant/field observations, and/or document or artifact study; and techniques for analysis and interpretation of data that move beyond the data generated and their surface appearances. 

Sandelowski, M. (2004).  Qualitative research . In M. Lewis-Beck, A. Bryman, & T. Liao (Eds.),  Encyclopedia of social science research methods . (pp. 893-894). Thousand Oaks, CA: SAGE Publications, Inc.

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1.2: Theory and Empirical Research

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• Jenkins-Smith et al.
• University of Oklahoma via University of Oklahoma Libraries

This book is concerned with the connection between theoretical claims and empirical data. It is about using statistical modeling; in particular, the tool of regression analysis, which is used to develop and refine theories. We define theory broadly as a set of interrelated propositions that seek to explain and, in some cases, predict an observed phenomenon.

Theory: A set of interrelated propositions that seek to explain and predict an observed phenomenon.

Theories contain three important characteristics that we discuss in detail below.

Characteristics of Good Theories Coherent and internally consistent Causal in nature Generate testable hypotheses

1.2.1 Coherent and Internally Consistent

The set of interrelated propositions that constitute a well-structured theory are based on concepts . In well-developed theories, the expected relationships among these concepts are both coherent and internally consistent. Coherence means the identification of concepts and the specified relationships among them are logical, ordered, and integrated. An internally consistent theory will explain relationships with respect to a set of common underlying causes and conditions, providing for consistency in expected relationships (and avoidance of contradictions). For systematic quantitative research, the relevant theoretical concepts are defined such that they can be measured and quantified. Some concepts are relatively easy to quantify, such as the number of votes cast for the winning Presidential candidate in a specified year or the frequency of arrests for gang-related crimes in a particular region and time period. Others are more difficult, such as the concepts of democratization, political ideology or presidential approval. Concepts that are more difficult to measure must be carefully operationalized , which is a process of relating a concept to an observation that can be measured using a defined procedure. For example, political ideology is often operationalized through public opinion surveys that ask respondents to place themselves on a Likert-type scale of ideological categories.

Concepts and Variables

A concept is a commonality across observed individual events or cases. It is a regularity that we find in a complex world. Concepts are our building blocks to understanding the world and to developing theory that explains the world. Once we have identified concepts we seek to explain them by developing theories based on them. Once we have explained a concept we need to define it. We do so in two steps. First, we give it a dictionary-like definition, called a nominal definition. Then, we develop an operational definition that identifies how we can measure and quantify it.

Once a concept has been quantified, it is employed in modeling as a variable . In statistical modeling, variables are thought of as either dependent or independent variables. A dependent variable , Y, is the outcome variable; this is the concept we are trying to explain and/or predict. The independent variable(s) , X, is the variable(s) that is used to predict or explain the dependent variable. The expected relationships between (and among) the variables are specified by the theory.

Measurement

When measuring concepts, the indicators that are used in building and testing theories should be both valid and reliable . Validity refers to how well the measurement captures the concept. Face validity, for example, refers to the plausibility and general acceptance of the measure, while the domain validity of the measure concerns the degree to which it captures all relevant aspects of the concept. Reliability, by contrast, refers to how consistent the measure is with repeated applications. A measure is reliable if, when applied to the repeated observations in similar settings, the outcomes are consistent.

Assessing the Quality of a Measure

Measurement is the process of assigning numbers to the phenomenon or concept that you are interested in. Measurement is straight-forward when we can directly observe the phenomenon. One agrees on a metric, such as inches or pounds, and then figures out how many of those units are present for the case in question. Measurement becomes more challenging when you cannot directly observe the concept of interest. In political science and public policy, some of the things we want to measure are directly observable: how many dollars were spent on a project or how many votes the incumbent receives, but many of our concepts are not observable: is issue X on the public’s agenda, how successful is a program, or how much do citizens trust the president. When the concept is not directly observable the operational definition is especially important. The operational definition explains exactly what the researcher will do to assign a number for each subject/case.

In reality, there is always some possibility that the number assigned does not reflect the true value for that case, i.e., there may be some error involved. Error can come about for any number of reasons, including mistakes in coding, the need for subjective judgments, or a measuring instrument that lacks precision. These kinds of error will generally produce inconsistent results; that is, they reduce reliability. We can assess the reliability of an indicator using one of two general approaches. One approach is a test-retest method where the same subjects are measured at two different points in time. If the measure is reliable the correlation between the two observations should be high. We can also assess reliability by using multiple indicators of the same concept and determining if there is a strong inter-correlation among them using statistical formulas such as Cronbach’s alpha or Kuder-Richardson Formula 20 (KR-20).

We can also have error when our measure is not valid. Valid indicators measure the concept we think they are measuring. The indicator should both converge with the concept and discriminate between the concept and similar yet different concepts. Unfortunately, there is no failsafe way to determine whether an indicator is valid. There are, however, a few things you can do to gain confidence in the validity of the indicator. First, you can simply look at it from a logical perspective and ask if it seems like it is valid. Does it have face validity? Second, you can see if it correlates well with other indicators that are considered valid, and in ways that are consistent with theory. This is called construct validity. Third, you can determine if it works in the way expected, which is referred to as predictive validity. Finally, we have more confidence if other researchers using the same concept agree that the indicator is considered valid. This consensual validity at least ensures that different researchers are talking about the same thing.

Measurement of Different Kinds of Concepts

Measurement can be applied to different kinds of concepts, which causes measures of different concepts to vary. There are three primary levels of measurement ; ordinal, interval, and nominal. Ordinal level measures indicate relative differences, such as more or less, but do not provide equal distances between intervals on the measurement scale. Therefore, ordinal measures cannot tell us how much more or less one observation is than another. Imagine a survey question asking respondents to identify their annual income. Respondents are given a choice of five different income levels: $0-20,000, $20,000-50,000, $50,000-$100,000, and $100,000+. This measure gives us an idea of the rank order of respondents’ income, but it is impossible for us to identify consistent differences between these responses. With an interval level measure, the variable is ordered and the differences between values are consistent. Sticking with the example of income, survey respondents are now asked to provide their annual income to the nearest ten thousand dollar mark (e.g., $10,000, $20,000, $30,000, etc.). This measurement technique produces an interval level variable because we have both a rank ordering and equal spacing between values. Ratio scales are interval measures with the special characteristic that the value of zero (0) indicates the absence of some property. A value of zero (0) income in our example may indicate a person does not have a job. Another example of a ratio scale is the Kelvin temperature scale because zero (0) degrees Kelvin indicates the complete absence of heat. Finally, a nominal level measure identifies categorical differences among observations. Numerical values assigned to nominal variables have no inherent meaning, but only differentiate one type" (e.g., gender, race, religion) from another.

1.2.2 Theories and Causality

Theories should be causal in nature, meaning that an independent variable is thought to have a causal influence on the dependent variable. In other words, a change in the independent variable causes a change in the dependent variable. Causality can be thought of as the motor" that drives the model and provides the basis for explanation and (possibly) prediction.

The Basis of Causality in Theories

• Time Ordering: The cause precedes the effect, X→Y
• Co-Variation: Changes in X are associated with changes in Y
• Non-Spuriousness: There is not a variable Z that causes both X and Y

To establish causality we want to demonstrate that a change in the independent variable is a necessary and sufficient condition for a change in the dependent variable (though more complex, interdependent relationships can also be quantitatively modeled). We can think of the independent variable as a treatment, τ, and we speculate that τ causes a change in our dependent variable, Y. The gold standard’’ for causal inference is an experiment where a) the level of ττ is controlled by the researcher and b) subjects are randomly assigned to a treatment or control group. The group that receives the treatment has outcome Y 1 and the control group has outcome Y 0 ; the treatment effect can be defined as τ=Y 1 -Y 0 . Causality is inferred because the treatment was only given to one group, and since these groups were randomly assigned other influences should wash out. Thus the difference τ=Y 1 -Y0 can be attributed to the treatment.

Given the nature of social science and public policy theorizing, we often can’t control the treatment of interest. For example, our case study in this text concerns the effect of political ideology on views about the environment. For this type of relationship, we cannot randomly assign ideology in an experimental sense. Instead, we employ statistical controls to account for the possible influences of confounding factors, such as age and gender. Using multiple regression we control for other factors that might influence the dependent variable. 1

1.2.3 Generation of Testable Hypothesis

Theory building is accomplished through the testing of hypotheses derived from theory. In simple form, a theory implies (sets of) relationships among concepts. These concepts are then operationalized. Finally, models are developed to examine how the measures are related. Properly specified hypotheses can be tested with empirical data, which are derived from the application of valid and reliable measures to relevant observations. The testing and re-testing of hypotheses develops levels of confidence that we can have for the core propositions that constitute the theory. In short, empirically grounded theories must be able to posit clear hypotheses that are testable. In this text, we discuss hypotheses and test them using relevant models and data.

As noted above, this text uses the concepts of political ideology and views about the environment as a case study in order to generate and test hypotheses about the relationships between these variables. For example, based on popular media accounts, it is plausible to expect that political conservatives are less likely to be concerned about the environment than political moderates or liberals. Therefore, we can pose the working hypothesis that measures of political ideology will be systematically related to measures of concern for the environment – with conservatives showing less concern for the environment. In classical hypothesis testing, the working hypothesis is tested against a null hypothesis . A null hypothesis is an implicit hypothesis that posits the independent variable has no effect (i.e., null effect) on the dependent variable. In our example, the null hypothesis states ideology has no effect on environmental concern.

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Identifying Empirical Research: Home

What is empirical research.

Empirical research is research that is based on observation or experimentation. Typically empirical research is published in peer-reviewed articles by the individuals who conducted the research. Watch the video below to learn about the characteristics of empirical research! 

Identifying Empirical Research

But how do you identify empirical research? Empirical research is typically published in scholarly journals. But not everything in scholarly journals is necessarily empirical research - you still need to carefully evaluate the methods of the article to determine if it is empirical research. 

1. Carefully evaluate the article's Methods and Results sections.  Empirical articles will a) include these sections and b) explicitly state their methodologies and share their results. Evaluate the methodology - are the methods based on observation, a survey, experimentation, etc? Look for charts, data, and other representations in the results section. 

2. Look out for types of articles that are NOT empirical.  Meta-analyses, literature reviews (with no other study components), editorials/letters, book reviews, case studies, opinions. 

3. In some databases, such as PsycINFO, you can limit to empirical research under Methodology in the "Advanced Search" section. Or limit to evidence-based practice" in CINAHL. 

4. In other databases, try using keywords such as empirical research, quantitative method, qualitative method, survey, ethnography, fieldwork or other type of empirical research method.

• Last Updated: Sep 12, 2019 2:43 PM
• URL: https://libguides.usu.edu/empirical_research

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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• What is empirical research: Methods, types & examples

Defne Çobanoğlu

Having opinions on matters based on observation is okay sometimes. Same as having theories on the subject you want to solve. However, some theories need to be tested. Just like Robert Oppenheimer says, “Theory will take you only so far .” 

In that case, when you have your research question ready and you want to make sure it is correct, the next step would be experimentation. Because only then you can test your ideas and collect tangible information. Now, let us start with the empirical research definition:

• What is empirical research?

Empirical research is a research type where the aim of the study is based on finding concrete and provable evidence . The researcher using this method to draw conclusions can use both quantitative and qualitative methods. Different than theoretical research, empirical research uses scientific experimentation and investigation. 

Using experimentation makes sense when you need to have tangible evidence to act on whatever you are planning to do. As the researcher, you can be a marketer who is planning on creating a new ad for the target audience, or you can be an educator who wants the best for the students. No matter how big or small, data gathered from the real world using this research helps break down the question at hand. 

• When to use empirical research?

Empirical research methods are used when the researcher needs to gather data analysis on direct, observable, and measurable data. Research findings are a great way to make grounded ideas. Here are some situations when one may need to do empirical research:

1. When quantitative or qualitative data is needed

There are times when a researcher, marketer, or producer needs to gather data on specific research questions to make an informed decision. And the concrete data gathered in the research process gives a good starting point.

2. When you need to test a hypothesis

When you have a hypothesis on a subject, you can test the hypothesis through observation or experiment. Making a planned study is a great way to collect information and test whether or not your hypothesis is correct.

3. When you want to establish causality

Experimental research is a good way to explore whether or not there is any correlation between two variables. Researchers usually establish causality by changing a variable and observing if the independent variable changes accordingly.

• Types of empirical research

The aim of empirical research is to collect information about a subject from the people by doing experimentation and other data collection methods. However, the methods and data collected are divided into two groups: one collects numerical data, and the other one collects opinion-like data. Let us see the difference between these two types:

Quantitative research

Quantitative research methods are used to collect data in a numerical way. Therefore, the results gathered by these methods will be numbers, statistics, charts, etc. The results can be used to quantify behaviors, opinions, and other variables. Quantitative research methods are surveys, questionnaires, and experimental research.

Qualitiative research

Qualitative research methods are not used to collect numerical answers, instead, they are used to collect the participants’ reasons, opinions, and other meaningful aspects. Qualitative research methods include case studies, observations, interviews, focus groups, and text analysis.

• 5 steps to conduct empirical research

Necessary steps for empirical research

When you want to collect direct and concrete data on a subject, empirical research is a great way to go. And, just like every other project and research, it is best to have a clear structure in mind. This is even more important in studies that may take a long time, such as experiments that take years. Let us look at a clear plan on how to do empirical research:

1. Define the research question

The very first step of every study is to have the question you will explore ready. Because you do not want to change your mind in the middle of the study after investing and spending time on the experimentation.

2. Go through relevant literature

This is the step where you sit down and do a desk research where you gather relevant data and see if other researchers have tried to explore similar research questions. If so, you can see how well they were able to answer the question or what kind of difficulties they faced during the research process.

3. Decide on the methodology

Once you are done going through the relevant literature, you can decide on which method or methods you can use. The appropriate methods are observation, experimentation, surveys, interviews, focus groups, etc.

4. Do data analysis

When you get to this step, it means you have successfully gathered enough data to make a data analysis. Now, all you need to do is look at the data you collected and make an informed analysis.

5. Conclusion

This is the last step, where you are finished with the experimentation and data analysis process. Now, it is time to decide what to do with this information. You can publish a paper and make informed decisions about whatever your goal is.

• Empirical research methodologies

Some essential methodologies to conduct empirical research

The aim of this type of research is to explore brand-new evidence and facts. Therefore, the methods should be primary and gathered in real life, directly from the people. There is more than one method for this goal, and it is up to the researcher to use which one(s). Let us see the methods of empirical research: 

• Observation

The method of observation is a great way to collect information on people without the effect of interference. The researcher can choose the appropriate area, time, or situation and observe the people and their interactions with one another. The researcher can be just an outside observer or can be a participant as an observer or a full participant.

• Experimentation

The experimentation process can be done in the real world by intervening in some elements to unify the environment for all participants. This method can also be done in a laboratory environment. The experimentation process is good for being able to change the variables according to the aim of the study.

The case study method is done by making an in-depth analysis of already existing cases. When the parameters and variables are similar to the research question at hand, it is wise to go through what was researched before.

• Focus groups

The case study method is done by using a group of individuals or multiple groups and using their opinions, characteristics, and responses. The scientists gather the data from this group and generalize it to the whole population.

Surveys are an effective way to gather data directly from people. It is a systematic approach to collecting information. If it is done in an online setting as an online survey , it would be even easier to reach out to people and ask their opinions in open-ended or close-ended questions.

Interviews are similar to surveys as you are using questions to collect information and opinions of the people. Unlike a survey, this process is done face-to-face, as a phone call, or as a video call.

• Advantages of empirical research

Empirical research is effective for many reasons, and helps researchers from numerous fields. Here are some advantages of empirical research to have in mind for your next research:

• Empirical research improves the internal validity of the study.
• Empirical evidence gathered from the study is used to authenticate the research question.
• Collecting provable evidence is important for the success of the study.
• The researcher is able to make informed decisions based on the data collected using empirical research.
• Disadvantages of empirical research

After learning about the positive aspects of empirical research, it is time to mention the negative aspects. Because this type may not be suitable for everyone and the researcher should be mindful of the disadvantages of empirical research. Here are the disadvantages of empirical research:

• As it is similar to other research types, a case study where experimentation is included will be time-consuming no matter what. It has more steps and variables than concluding a secondary research.
• There are a lot of variables that need to be controlled and considered. Therefore, it may be a challenging task to be mindful of all the details.
• Doing evidence-based research can be expensive if you need to complete it on a large scale.
• When you are conducting an experiment, you may need some waivers and permissions.
• Frequently asked questions about empirical research

Empirical research is one of the many research types, and there may be some questions in mind about its similarities and differences to other research types.

Is empirical research qualitative or quantitative?

The data collected by empirical research can be qualitative, quantitative, or a mix of both. It is up to the aim of researcher to what kind of data is needed and searched for.

Is empirical research the same as quantitative research?

As quantitative research heavily relies on data collection methods of observation and experimentation, it is, in nature, an empirical study. Some professors may even use the terms interchangeably. However, that does not mean that empirical research is only a quantitative one.

What is the difference between theoretical and empirical research?

Empirical studies are based on data collection to prove theories or answer questions, and it is done by using methods such as observation and experimentation. Therefore, empirical research relies on finding evidence that backs up theories. On the other hand, theoretical research relies on theorizing on empirical research data and trying to make connections and correlations.

What is the difference between conceptual and empirical research?

Conceptual research is about thoughts and ideas and does not involve any kind of experimentation. Empirical research, on the other hand, works with provable data and hard evidence.

What is the difference between empirical vs applied research?

Some scientists may use these two terms interchangeably however, there is a difference between them. Applied research involves applying theories to solve real-life problems. On the other hand, empirical research involves the obtaining and analysis of data to test hypotheses and theories.

• Final words

Empirical research is a good means when the goal of your study is to find concrete data to go with. You may need to do empirical research when you need to test a theory, establish causality, or need qualitative/quantitative data. For example, you are a scientist and want to know if certain colors have an effect on people’s moods, or you are a marketer and want to test your theory on ad places on websites. 

In both scenarios, you can collect information by using empirical research methods and make informed decisions afterward. These are just the two of empirical research examples. This research type can be applied to many areas of work life and social sciences. Lastly, for all your research needs, you can visit forms.app to use its many useful features and over 1000 form and survey templates!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

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Home » Education » Difference Between Conceptual and Empirical Research

Difference Between Conceptual and Empirical Research

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts, whereas empirical research involves research based on observation, experiments and verifiable evidence.

Conceptual research and empirical research are two ways of doing scientific research. These are two opposing types of research frameworks since conceptual research doesn’t involve any experiments and empirical research does.

Key Areas Covered

1. What is Empirical Research     – Definition, Characteristics, Uses 2. What is Empirical Research     – Definition, Characteristics, Uses 3. What is the Difference Between Conceptual and Empirical Research     – Comparison of Key Differences

Conceptual Research, Empirical Research, Research

What is Conceptual Research?

Conceptual research is a type of research that is generally related to abstract ideas or concepts. It doesn’t particularly involve any practical experimentation. However, this type of research typically involves observing and analyzing information already present on a given topic. Philosophical research is a generally good example for conceptual research.

Conceptual research can be used to solve real-world problems. Conceptual frameworks, which are analytical tools researchers use in their studies, are based on conceptual research. Furthermore, these frameworks help to make conceptual distinctions and organize ideas researchers need for research purposes.

Figure 2: Conceptual Framework

In simple words, a conceptual framework is the researcher’s synthesis of the literature (previous research studies) on how to explain a particular phenomenon. It explains the actions required in the course of the study based on the researcher’s observations on the subject of research as well as the knowledge gathered from previous studies.

What is Empirical Research?

Empirical research is basically a research that uses empirical evidence. Empirical evidence refers to evidence verifiable by observation or experience rather than theory or pure logic. Thus, empirical research is research studies with conclusions based on empirical evidence. Moreover, empirical research studies are observable and measurable.

Empirical evidence can be gathered through qualitative research studies or quantitative research studies . Qualitative research methods gather non-numerical or non-statistical data. Thus, this type of studies helps to understand the underlying reasons, opinions, and motivations behind something as well as to uncover trends in thought and opinions. Quantitative research studies, on the other hand, gather statistical data. These have the ability to quantify behaviours, opinions, or other defined variables. Moreover, a researcher can even use a combination of quantitative and qualitative methods to find answers to his research questions .

Figure 2: Empirical Research Cycle

A.D. de Groot, a famous psychologist, came up with a cycle (figure 2) to explain the process of the empirical research process. Moreover, this cycle has five steps, each as important as the other. These steps include observation, induction, deduction, testing and evaluation.

Conceptual research is a type of research that is generally related to abstract ideas or concepts whereas empirical research is any research study where conclusions of the study are drawn from evidence verifiable by observation or experience rather than theory or pure logic.

Conceptual research involves abstract idea and concepts; however, it doesn’t involve any practical experiments. Empirical research, on the other hand, involves phenomena that are observable and measurable.

Type of Studies

Philosophical research studies are examples of conceptual research studies, whereas empirical research includes both quantitative and qualitative studies.

The main difference between conceptual and empirical research is that conceptual research involves abstract ideas and concepts whereas empirical research involves research based on observation, experiments and verifiable evidence.

1.“Empirical Research: Definition, Methods, Types and Examples.” QuestionPro, 14 Dec. 2018, Available here . 2. “Empirical Research.” Wikipedia, Wikimedia Foundation, 15 Sept. 2019, Available here . 3.“Conceptual Research: Definition, Framework, Example and Advantages.” QuestionPro, 18 Sept. 2018, Available here. 4. Patrick. “Conceptual Framework: A Step-by-Step Guide on How to Make One.” SimplyEducate.Me, 4 Dec. 2018, Available here .

Image Courtesy:

1. “APM Conceptual Framework” By LarryDragich – Created for a Technical Management Counsel meeting Previously published: First published in APM Digest in March (CC BY-SA 3.0) via Commons Wikimedia 2. “Empirical Cycle” By Empirical_Cycle.png: TesseUndDaanderivative work: Beao (talk) – Empirical_Cycle.png (CC BY 3.0) via Commons Wikimedia

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BY 499 - Senior Seminar

• Library Catalog(s)
• Searching Tips and Source Evaluation
• Article Databases
• Writing Style - APA
• Empirical v. Non-Empirical Research
• Poster Design
• How Did We Do?

Subject Guide

Biology Articles

Primary Databases

Featuring thousands of full-text journals, this collection of scholarly trade and popular articles offers information on a broad range of important areas including: anthropology, biology, chemistry, ethnic & multicultural studies, law, mathematics, music, psychology, women's studies, and many other fields. Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

ProQuest Research Library™ provides access to more than 5,060 titles —over 3,600 in full text— on a wide range of popular academic subjects. The database features a diversified mix of scholarly journals, trade publications, magazines, and newspapers.  Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

The National Science Digital Library (NSDL) was created by the National Science Foundation to provide organized access to high quality resources and tools that support innovations in teaching and learning at all levels of science, technology, engineering, and mathematics education. Part of the database offerings in GALILEO, Georgia's virtual library.

This database contains more than 820 leading full-text journals covering relevant aspects of the scientific and technical community. In addition to full text, Science & Technology Collection™ offers indexing and abstracts for more than 1,750 journals. Topics include aeronautics, astrophysics, biology, chemistry, computer technology, geology, aviation, physics, archaeology, marine sciences and materials science. Part of the Database Offerings in GALILEO, Georgia’s Virtual Library

A leading full-text scientific database covering the life and health sciences.

How to Make a Poster

• Designing Conference Posters & Poster Templates

Empirical Versus Non-empirical Research

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief.

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology." Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behavior, or   phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)
• Author(s) present a new set of findings from original research after conducting an original experiment
• Firsthand collection of data

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction : sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population or variables to be researched, research process, and analytical tools
• Results : sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion : sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Here are some common characteristics of review articles:

• Author(s) analyze and summarize existing research
• Author(s) did NOT do original research. They are summarizing work of others.
• Often focus on a general topic (such as breast cancer treatment) and bring together all relevant, useful articles on that topic in one review article.
• Do not contain sections such as Methods (and Materials), Results because they did not do any original research!

Fermentation and quality of yellow pigments from golden brown rice solid culture by a selected Monascus mutant.

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Conceptual Research vs. Empirical Research

What's the difference.

Conceptual research and empirical research are two distinct approaches to conducting research. Conceptual research focuses on exploring and developing theories, concepts, and ideas. It involves analyzing existing literature, theories, and concepts to gain a deeper understanding of a particular topic. Conceptual research is often used in the early stages of research to generate hypotheses and develop a theoretical framework. On the other hand, empirical research involves collecting and analyzing data to test hypotheses and answer research questions. It relies on observation, measurement, and experimentation to gather evidence and draw conclusions. Empirical research is more focused on obtaining concrete and measurable results, often through surveys, experiments, or observations. Both approaches are valuable in research, with conceptual research providing a foundation for empirical research and empirical research validating or refuting conceptual theories.

Further Detail

Introduction.

Research is a fundamental aspect of any field of study, providing a systematic approach to acquiring knowledge and understanding. In the realm of research, two primary methodologies are commonly employed: conceptual research and empirical research. While both approaches aim to contribute to the body of knowledge, they differ significantly in their attributes, methodologies, and outcomes. This article aims to explore and compare the attributes of conceptual research and empirical research, shedding light on their unique characteristics and applications.

Conceptual Research

Conceptual research, also known as theoretical research, focuses on the exploration and development of theories, concepts, and ideas. It is primarily concerned with abstract and hypothetical constructs, aiming to enhance understanding and generate new insights. Conceptual research often involves a comprehensive review of existing literature, analyzing and synthesizing various theories and concepts to propose new frameworks or models.

One of the key attributes of conceptual research is its reliance on deductive reasoning. Researchers start with a set of existing theories or concepts and use logical reasoning to derive new hypotheses or frameworks. This deductive approach allows researchers to build upon existing knowledge and propose innovative ideas. Conceptual research is often exploratory in nature, seeking to expand the boundaries of knowledge and provide a foundation for further empirical investigations.

Conceptual research is particularly valuable in fields where empirical data may be limited or difficult to obtain. It allows researchers to explore complex phenomena, develop theoretical frameworks, and generate hypotheses that can later be tested through empirical research. By focusing on abstract concepts and theories, conceptual research provides a theoretical foundation for empirical investigations, guiding researchers in their quest for empirical evidence.

Furthermore, conceptual research plays a crucial role in the development of new disciplines or interdisciplinary fields. It helps establish a common language and theoretical framework, facilitating communication and collaboration among researchers from different backgrounds. By synthesizing existing knowledge and proposing new concepts, conceptual research lays the groundwork for empirical studies and contributes to the overall advancement of knowledge.

Empirical Research

Empirical research, in contrast to conceptual research, is concerned with the collection and analysis of observable data. It aims to test hypotheses, validate theories, and provide evidence-based conclusions. Empirical research relies on the systematic collection of data through various methods, such as surveys, experiments, observations, or interviews. The data collected is then analyzed using statistical or qualitative techniques to draw meaningful conclusions.

One of the primary attributes of empirical research is its inductive reasoning approach. Researchers start with specific observations or data and use them to develop general theories or conclusions. This inductive approach allows researchers to derive broader implications from specific instances, providing a basis for generalization. Empirical research is often hypothesis-driven, seeking to test and validate theories or hypotheses through the collection and analysis of data.

Empirical research is highly valued for its ability to provide concrete evidence and support or refute existing theories. It allows researchers to investigate real-world phenomena, understand cause-and-effect relationships, and make informed decisions based on empirical evidence. By relying on observable data, empirical research enhances the credibility and reliability of research findings, contributing to the overall body of knowledge in a field.

Moreover, empirical research is particularly useful in applied fields, where practical implications and real-world applications are of utmost importance. It allows researchers to evaluate the effectiveness of interventions, assess the impact of policies, or measure the outcomes of specific actions. Empirical research provides valuable insights that can inform decision-making processes, guide policy development, and drive evidence-based practices.

Comparing Conceptual Research and Empirical Research

While conceptual research and empirical research differ in their methodologies and approaches, they are both essential components of the research process. Conceptual research focuses on the development of theories and concepts, providing a theoretical foundation for empirical investigations. Empirical research, on the other hand, relies on the collection and analysis of observable data to test and validate theories.

Conceptual research is often exploratory and aims to expand the boundaries of knowledge. It is valuable in fields where empirical data may be limited or difficult to obtain. By synthesizing existing theories and proposing new frameworks, conceptual research provides a theoretical basis for empirical studies. It helps researchers develop hypotheses and guides their quest for empirical evidence.

Empirical research, on the other hand, is hypothesis-driven and seeks to provide concrete evidence and support or refute existing theories. It allows researchers to investigate real-world phenomena, understand cause-and-effect relationships, and make informed decisions based on empirical evidence. Empirical research is particularly useful in applied fields, where practical implications and real-world applications are of utmost importance.

Despite their differences, conceptual research and empirical research are not mutually exclusive. In fact, they often complement each other in the research process. Conceptual research provides the theoretical foundation and guidance for empirical investigations, while empirical research validates and refines existing theories or concepts. The iterative nature of research often involves a continuous cycle of conceptual and empirical research, with each informing and influencing the other.

Both conceptual research and empirical research contribute to the advancement of knowledge in their respective fields. Conceptual research expands theoretical frameworks, proposes new concepts, and lays the groundwork for empirical investigations. Empirical research, on the other hand, provides concrete evidence, validates theories, and informs practical applications. Together, they form a symbiotic relationship, driving progress and innovation in various disciplines.

Conceptual research and empirical research are two distinct methodologies employed in the pursuit of knowledge and understanding. While conceptual research focuses on the development of theories and concepts, empirical research relies on the collection and analysis of observable data. Both approaches have their unique attributes, methodologies, and applications.

Conceptual research plays a crucial role in expanding theoretical frameworks, proposing new concepts, and providing a foundation for empirical investigations. It is particularly valuable in fields where empirical data may be limited or difficult to obtain. On the other hand, empirical research provides concrete evidence, validates theories, and informs practical applications. It is highly valued in applied fields, where evidence-based decision-making is essential.

Despite their differences, conceptual research and empirical research are not mutually exclusive. They often work in tandem, with conceptual research guiding the development of hypotheses and theoretical frameworks, and empirical research validating and refining these theories through the collection and analysis of data. Together, they contribute to the overall advancement of knowledge and understanding in various disciplines.

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12 Interpretive research

Chapter 11 introduced interpretive research—or more specifically, interpretive case research. This chapter will explore other kinds of interpretive research. Recall that positivist or deductive methods—such as laboratory experiments and survey research—are those that are specifically intended for theory (or hypotheses) testing. Interpretive or inductive methods—such as action research and ethnography—one the other hand, are intended for theory building. Unlike a positivist method, where the researcher tests existing theoretical postulates using empirical data, in interpretive methods, the researcher tries to derive a theory about the phenomenon of interest from the existing observed data.

The term ‘interpretive research’ is often used loosely and synonymously with ‘qualitative research’, although the two concepts are quite different. Interpretive research is a research paradigm (see Chapter 3) that is based on the assumption that social reality is not singular or objective. Rather, it is shaped by human experiences and social contexts (ontology), and is therefore best studied within its sociohistoric context by reconciling the subjective interpretations of its various participants (epistemology). Because interpretive researchers view social reality as being embedded within—and therefore impossible to abstract from—their social settings, they ‘interpret’ the reality though a ‘sense-making’ process rather than a hypothesis testing process. This is in contrast to the positivist or functionalist paradigm that assumes that the reality is relatively independent of the context, can be abstracted from their contexts, and studied in a decomposable functional manner using objective techniques such as standardised measures. Whether a researcher should pursue interpretive or positivist research depends on paradigmatic considerations about the nature of the phenomenon under consideration and the best way to study it.

However, qualitative versus quantitative research refers to empirical or data-oriented considerations about the type of data to collect and how to analyse it. Qualitative research relies mostly on non-numeric data, such as interviews and observations, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures such as regression analysis, but is coded using techniques like content analysis. Sometimes, coded qualitative data is tabulated quantitatively as frequencies of codes, but this data is not statistically analysed. Many puritan interpretive researchers reject this coding approach as a futile effort to seek consensus or objectivity in a social phenomenon which is essentially subjective.

Although interpretive research tends to rely heavily on qualitative data, quantitative data may add more precision and clearer understanding of the phenomenon of interest than qualitative data. For example, Eisenhardt (1989), [1] in her interpretive study of decision-making in high-velocity firms (discussed in the previous chapter on case research), collected numeric data on how long it took each firm to make certain strategic decisions—which ranged from approximately six weeks to 18 months—how many decision alternatives were considered for each decision, and surveyed her respondents to capture their perceptions of organisational conflict. Such numeric data helped her clearly distinguish the high-speed decision-making firms from the low-speed decision-makers without relying on respondents’ subjective perceptions, which then allowed her to examine the number of decision alternatives considered by and the extent of conflict in high-speed versus low-speed firms. Interpretive research should attempt to collect both qualitative and quantitative data pertaining to the phenomenon of interest, and so should positivist research as well. Joint use of qualitative and quantitative data—often called ‘mixed-mode design’—may lead to unique insights, and is therefore highly prized in the scientific community.

Interpretive research came into existence in the early nineteenth century—long before positivist techniques were developed—and has its roots in anthropology, sociology, psychology, linguistics, and semiotics. Many positivist researchers view interpretive research as erroneous and biased, given the subjective nature of the qualitative data collection and interpretation process employed in such research. However, since the 1970s, many positivist techniques’ failure to generate interesting insights or new knowledge has resulted in a resurgence of interest in interpretive research—albeit with exacting methods and stringent criteria to ensure the reliability and validity of interpretive inferences.

Distinctions from positivist research

In addition to the fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organisations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling —or a variation of this technique—in which cases are chosen randomly from a population for the purpose of generalisability. Hence, convenience samples and small samples are considered acceptable in interpretive research—as long as they fit the nature and purpose of the study—but not in positivist research.

Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and their specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a ’neutral’ or unbiased stance during the data collection and analysis processes, and ensure that their personal biases or preconceptions do not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context, and is not presumed to bias the data collection and analytic procedures.

Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches to data collection and analysis, rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change their original research question if they realise that their original research questions are unlikely to generate new or useful insights. This is a valuable—but often understated—benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and challenges of interpretive research

Interpretive research has several unique advantages. First, it is well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes—such as inter-firm relationships or inter-office politics—where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, it is often helpful for theory construction in areas with no or insufficient a priori theory. Third, it is also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, interpretive research can also help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, interpretive research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than positivist research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, interpretive research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants, and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas which may lead to misleading or false impressions. Inadequate trust between the researcher and participants may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the interpretive researcher to ‘see through the smoke’ (i.e., hidden or biased agendas) and understand the true nature of the problem. Fourth, given the heavily contextualised nature of inferences drawn from interpretive research, such inferences do not lend themselves well to replicability or generalisability. Finally, interpretive research may sometimes fail to answer the research questions of interest or predict future behaviours.

Characteristics of interpretive research

All interpretive research must adhere to a common set of principles, as described below.

Naturalistic inquiry: Social phenomena must be studied within their natural setting.

Because interpretive research assumes that social phenomena are situated within—and cannot be isolated from—their social context, interpretations of such phenomena must be grounded within their sociohistorical context. This implies that contextual variables should be observed and considered in seeking explanations of a phenomenon of interest, even though context sensitivity may limit the generalisability of inferences.

Researcher as instrument: Researchers are often embedded within the social context that they are studying, and are considered part of the data collection instrument in that they must use their observational skills, their trust with the participants, and their ability to extract the correct information. Further, their personal insights, knowledge, and experiences of the social context are critical to accurately interpreting the phenomenon of interest. At the same time, researchers must be fully aware of their personal biases and preconceptions, and not let such biases interfere with their ability to present a fair and accurate portrayal of the phenomenon.

Interpretive analysis: Observations must be interpreted through the eyes of the participants embedded in the social context. Interpretation must occur at two levels. The first level involves viewing or experiencing the phenomenon from the subjective perspectives of the social participants. The second level is to understand the meaning of the participants’ experiences in order to provide a ‘thick description’ or a rich narrative story of the phenomenon of interest that can communicate why participants acted the way they did.

Use of expressive language: Documenting the verbal and non-verbal language of participants and the analysis of such language are integral components of interpretive analysis. The study must ensure that the story is viewed through the eyes of a person, and not a machine, and must depict the emotions and experiences of that person, so that readers can understand and relate to that person. Use of imageries, metaphors, sarcasm, and other figures of speech are very common in interpretive analysis.

Temporal nature: Interpretive research is often not concerned with searching for specific answers, but with understanding or ‘making sense of’ a dynamic social process as it unfolds over time. Hence, such research requires the researcher to immerse themself in the study site for an extended period of time in order to capture the entire evolution of the phenomenon of interest.

Hermeneutic circle: Interpretive interpretation is an iterative process of moving back and forth from pieces of observations (text), to the entirety of the social phenomenon (context), to reconcile their apparent discord, and to construct a theory that is consistent with the diverse subjective viewpoints and experiences of the embedded participants. Such iterations between the understanding/meaning of a phenomenon and observations must continue until ‘theoretical saturation’ is reached, whereby any additional iteration does not yield any more insight into the phenomenon of interest.

Interpretive data collection

Data is collected in interpretive research using a variety of techniques. The most frequently used technique is interviews (face-to-face, telephone, or focus groups). Interview types and strategies are discussed in detail in Chapter 9. A second technique is observation . Observational techniques include direct observation , where the researcher is a neutral and passive external observer, and is not involved in the phenomenon of interest (as in case research), and participant observation , where the researcher is an active participant in the phenomenon, and their input or mere presence influence the phenomenon being studied (as in action research). A third technique is documentation , where external and internal documents—such as memos, emails, annual reports, financial statements, newspaper articles, or websites—may be used to cast further insight into the phenomenon of interest or to corroborate other forms of evidence.

Interpretive research designs

Case research . As discussed in the previous chapter, case research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualised inferences, and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories, or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting, rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Action research . Action research is a qualitative but positivist research design aimed at theory testing rather than theory building. This is an interactive design that assumes that complex social phenomena are best understood by introducing changes, interventions, or ‘actions’ into those phenomena, and observing the outcomes of such actions on the phenomena of interest. In this method, the researcher is usually a consultant or an organisational member embedded into a social context —such as an organisation—who initiates an action in response to a social problem, and examines how their action influences the phenomenon, while also learning and generating insights about the relationship between the action and the phenomenon. Examples of actions may include organisational change programs—such as the introduction of new organisational processes, procedures, people, or technology or the replacement of old ones—initiated with the goal of improving an organisation’s performance or profitability. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may bring forth the desired social change. The theory is validated by the extent to which the chosen action is successful in remedying the targeted problem. Simultaneous problem-solving and insight generation are the central feature that distinguishes action research from other research methods (which may not involve problem solving), and from consulting (which may not involve insight generation). Hence, action research is an excellent method for bridging research and practice.

There are several variations of the action research method. The most popular of these methods is participatory action research , designed by Susman and Evered (1978). [2] This method follows an action research cycle consisting of five phases: diagnosing, action-planning, action-taking, evaluating, and learning (see Figure 12.1). Diagnosing involves identifying and defining a problem in its social context. Action-planning involves identifying and evaluating alternative solutions to the problem, and deciding on a future course of action based on theoretical rationale. Action-taking is the implementation of the planned course of action. The evaluation stage examines the extent to which the initiated action is successful in resolving the original problem—i.e., whether theorised effects are indeed realised in practice. In the learning phase, the experiences and feedback from action evaluation are used to generate insights about the problem and suggest future modifications or improvements to the action. Based on action evaluation and learning, the action may be modified or adjusted to address the problem better, and the action research cycle is repeated with the modified action sequence. It is suggested that the entire action research cycle be traversed at least twice so that learning from the first cycle can be implemented in the second cycle. The primary mode of data collection is participant observation, although other techniques such as interviews and documentary evidence may be used to corroborate the researcher’s observations.

Ethnography . The ethnographic research method—derived largely from the field of anthropology—emphasises studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time—usually eight months to two years—and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a ‘sense-making’ approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the transsituational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviours. While living with chimpanzees in their natural habitat at Gombe National Park in Tanzania, she observed their behaviours, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialise with each other, their communication patterns, their mating behaviours, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996) [3] study of decision-making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and healthcare providers to document their lived experience.

Phenomenology. Phenomenology is a research method that emphasises the study of conscious experiences as a way of understanding the reality around us. It is based on the ideas of early twentieth century German philosopher, Edmund Husserl, who believed that human experience is the source of all knowledge. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences such as human judgment, perceptions, and actions. Its goal is (appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and understanding the symbolic meanings (‘deep structure’) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathise with the participant’s situation, and tune into existential dimensions of that situation so that they can fully understand the deep structures that drive the conscious thinking, feeling, and behaviour of the studied participants.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) [4] developed an existential phenomenological research method to guide studies in this area. This method, illustrated in Figure 12.2, can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation. Examples of questions that may be asked include ‘Can you describe a typical day?’ or ‘Can you describe that particular incident in more detail?’. These interviews are recorded and transcribed for further analysis. During data analysis , the researcher reads the transcripts to: get a sense of the whole, and establish ‘units of significance’ that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as ‘felt-space’ and ‘felt-time’, which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (‘felt-space’)? Did they feel that their experience was pressured, slow, or discontinuous (‘felt-time’)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose his/herself in an imaginary sense into the participant’s situation (i.e., temporarily live the participant’s life). The participants’ lived experience is described in the form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Rigor in interpretive research

While positivist research employs a ‘reductionist’ approach by simplifying social reality into parsimonious theories and laws, interpretive research attempts to interpret social reality through the subjective viewpoints of the embedded participants within the context where the reality is situated. These interpretations are heavily contextualised, and are naturally less generalisable to other contexts. However, because interpretive analysis is subjective and sensitive to the experiences and insight of the embedded researcher, it is often considered less rigorous by many positivist (functionalist) researchers. Because interpretive research is based on a different set of ontological and epistemological assumptions about social phenomena than positivist research, the positivist notions of rigor—such as reliability, internal validity, and generalisability—do not apply in a similar manner. However, Lincoln and Guba (1985) [5] provide an alternative set of criteria that can be used to judge the rigor of interpretive research.

Dependability. Interpretive research can be viewed as dependable or authentic if two researchers assessing the same phenomenon, using the same set of evidence, independently arrive at the same conclusions, or the same researcher, observing the same or a similar phenomenon at different times arrives at similar conclusions. This concept is similar to that of reliability in positivist research, with agreement between two independent researchers being similar to the notion of inter-rater reliability, and agreement between two observations of the same phenomenon by the same researcher akin to test-retest reliability. To ensure dependability, interpretive researchers must provide adequate details about their phenomenon of interest and the social context in which it is embedded, so as to allow readers to independently authenticate their interpretive inferences.

Credibility. Interpretive research can be considered credible if readers find its inferences to be believable. This concept is akin to that of internal validity in functionalistic research. The credibility of interpretive research can be improved by providing evidence of the researcher’s extended engagement in the field, by demonstrating data triangulation across subjects or data collection techniques, and by maintaining meticulous data management and analytic procedures—such as verbatim transcription of interviews, accurate records of contacts and interviews—and clear notes on theoretical and methodological decisions, that can allow an independent audit of data collection and analysis if needed.

Confirmability. Confirmability refers to the extent to which the findings reported in interpretive research can be independently confirmed by others—typically, participants. This is similar to the notion of objectivity in functionalistic research. Since interpretive research rejects the notion of an objective reality, confirmability is demonstrated in terms of ‘intersubjectivity’—i.e., if the study’s participants agree with the inferences derived by the researcher. For instance, if a study’s participants generally agree with the inferences drawn by a researcher about a phenomenon of interest—based on a review of the research paper or report—then the findings can be viewed as confirmable.

Transferability. Transferability in interpretive research refers to the extent to which the findings can be generalised to other settings. This idea is similar to that of external validity in functionalistic research. The researcher must provide rich, detailed descriptions of the research context (‘thick description’) and thoroughly describe the structures, assumptions, and processes revealed from the data so that readers can independently assess whether and to what extent the reported findings are transferable to other settings.

• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Susman, G. I. and Evered, R. D. (1978) An assessment of the scientific merits of action research. Administrative Science Quarterly , 23, 582–603. ↵
• Bluebond-Langer, M. (1996). In the shadow of illness: Parents and siblings of the chronically ill child . Princeton, NJ: Princeton University Press. ↵
• Giorgi, A., & Giorgi, B. (2003). Phenomenology. In J. A. Smith (ed.), Qualitative psychology: A practical guide to research methods (pp. 25–50). London: Sage Publications ↵
• Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry . Beverly Hills: Sage Publications. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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