empirical research results

Skip to main content
Skip to primary sidebar
Skip to footer
QuestionPro

Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case AskWhy Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Empirical Research: Definition, Methods, Types and Examples

Content Index

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.

LEARN ABOUT: Behavioral Research

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.

LEARN ABOUT: Level of Analysis

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.

LEARN ABOUT: Action Research

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?

Learn More: Data Collection Methods: Types & Examples

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.

LEARN ABOUT: Best Data Collection Tools

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.

LEARN ABOUT: Social Communication Questionnaire

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.

LEARN ABOUT: 12 Best Tools for Researchers

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.

Create a single source of real data with a built-for-insights platform. Store past data, add nuggets of insights, and import research data from various sources into a CRM for insights. Build on ever-growing research with a real-time dashboard in a unified research management platform to turn insights into knowledge.

LEARN MORE FREE TRIAL

MORE LIKE THIS

Experimental vs Observational Studies: Differences & Examples

Sep 5, 2024

Interactive Forms: Key Features, Benefits, Uses + Design Tips

Sep 4, 2024

Closed-Loop Management: The Key to Customer Centricity

Sep 3, 2024

Net Trust Score: Tool for Measuring Trust in Organization

Sep 2, 2024

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.)
Credo Tutorial: Evaluating for Diverse Points of View
Next: Finding Empirical Research in Library Databases >>
Last Updated: Aug 13, 2024 3:16 PM
URL: https://guides.libraries.psu.edu/emp

Identifying Empirical Research Articles

Identifying empirical articles.

Searching for Empirical Research Articles

What is Empirical Research?

An empirical research article reports the results of a study that uses data derived from actual observation or experimentation. Empirical research articles are examples of primary research. To learn more about the differences between primary and secondary research, see our related guide:

Primary and Secondary Sources

By the end of this guide, you will be able to:

Identify common elements of an empirical article
Use a variety of search strategies to search for empirical articles within the library collection

Look for the IMRaD layout in the article to help identify empirical research. Sometimes the sections will be labeled differently, but the content will be similar.

I ntroduction: why the article was written, research question or questions, hypothesis, literature review
M ethods: the overall research design and implementation, description of sample, instruments used, how the authors measured their experiment
R esults: output of the author's measurements, usually includes statistics of the author's findings
D iscussion: the author's interpretation and conclusions about the results, limitations of study, suggestions for further research

Parts of an Empirical Research Article

Parts of an empirical article.

The screenshots below identify the basic IMRaD structure of an empirical research article.

Introduction

The introduction contains a literature review and the study's research hypothesis.

The method section outlines the research design, participants, and measures used.

Results

The results section contains statistical data (charts, graphs, tables, etc.) and research participant quotes.

The discussion section includes impacts, limitations, future considerations, and research.

Learn the IMRaD Layout: How to Identify an Empirical Article

This short video overviews the IMRaD method for identifying empirical research.

Next: Searching for Empirical Research Articles >>
Last Updated: Nov 16, 2023 8:24 AM

CityU Home - CityU Catalog

Ask a Librarian

Research: Overview & Approaches

Getting Started with Undergraduate Research
Planning & Getting Started
Building Your Knowledge Base
Locating Sources
Reading Scholarly Articles
Creating a Literature Review
Productivity & Organizing Research
Scholarly and Professional Relationships

Introduction to Empirical Research

Databases for finding empirical research, guided search, google scholar, examples of empirical research, sources and further reading.

Interpretive Research
Action-Based Research
Creative & Experimental Approaches

Your Librarian

Introductory Video This video covers what empirical research is, what kinds of questions and methods empirical researchers use, and some tips for finding empirical research articles in your discipline.

Guided Search: Finding Empirical Research Articles This is a hands-on tutorial that will allow you to use your own search terms to find resources.

Study on radiation transfer in human skin for cosmetics
Long-Term Mobile Phone Use and the Risk of Vestibular Schwannoma: A Danish Nationwide Cohort Study
Emissions Impacts and Benefits of Plug-In Hybrid Electric Vehicles and Vehicle-to-Grid Services
Review of design considerations and technological challenges for successful development and deployment of plug-in hybrid electric vehicles
Endocrine disrupters and human health: could oestrogenic chemicals in body care cosmetics adversely affect breast cancer incidence in women?

<< Previous: Scholarly and Professional Relationships
Next: Interpretive Research >>
Last Updated: Aug 13, 2024 12:18 PM
URL: https://guides.lib.purdue.edu/research_approaches

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.

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

Empirical Research: A Comprehensive Guide for Academics

Empirical research relies on gathering and studying real, observable data. The term ’empirical’ comes from the Greek word ’empeirikos,’ meaning ‘experienced’ or ‘based on experience.’ So, what is empirical research? Instead of using theories or opinions, empirical research depends on real data obtained through direct observation or experimentation.

Why Empirical Research?

Empirical research plays a key role in checking or improving current theories, providing a systematic way to grow knowledge across different areas. By focusing on objectivity, it makes research findings more trustworthy, which is critical in research fields like medicine, psychology, economics, and public policy. In the end, the strengths of empirical research lie in deepening our awareness of the world and improving our capacity to tackle problems wisely. 1,2

Qualitative and Quantitative Methods

There are two main types of empirical research methods – qualitative and quantitative. 3,4 Qualitative research delves into intricate phenomena using non-numerical data, such as interviews or observations, to offer in-depth insights into human experiences. In contrast, quantitative research analyzes numerical data to spot patterns and relationships, aiming for objectivity and the ability to apply findings to a wider context.

Steps for Conducting Empirical Research

When it comes to conducting research, there are some simple steps that researchers can follow. 5,6

Create Research Hypothesis: Clearly state the specific question you want to answer or the hypothesis you want to explore in your study.
Examine Existing Research: Read and study existing research on your topic. Understand what’s already known, identify existing gaps in knowledge, and create a framework for your own study based on what you learn.
Plan Your Study: Decide how you’ll conduct your research—whether through qualitative methods, quantitative methods, or a mix of both. Choose suitable techniques like surveys, experiments, interviews, or observations based on your research question.
Develop Research Instruments: Create reliable research collection tools, such as surveys or questionnaires, to help you collate data. Ensure these tools are well-designed and effective.
Collect Data: Systematically gather the information you need for your research according to your study design and protocols using the chosen research methods.
Data Analysis: Analyze the collected data using suitable statistical or qualitative methods that align with your research question and objectives.
Interpret Results: Understand and explain the significance of your analysis results in the context of your research question or hypothesis.
Draw Conclusions: Summarize your findings and draw conclusions based on the evidence. Acknowledge any study limitations and propose areas for future research.

Advantages of Empirical Research

Empirical research is valuable because it stays objective by relying on observable data, lessening the impact of personal biases. This objectivity boosts the trustworthiness of research findings. Also, using precise quantitative methods helps in accurate measurement and statistical analysis. This precision ensures researchers can draw reliable conclusions from numerical data, strengthening our understanding of the studied phenomena. 4

Disadvantages of Empirical Research

While empirical research has notable strengths, researchers must also be aware of its limitations when deciding on the right research method for their study.4 One significant drawback of empirical research is the risk of oversimplifying complex phenomena, especially when relying solely on quantitative methods. These methods may struggle to capture the richness and nuances present in certain social, cultural, or psychological contexts. Another challenge is the potential for confounding variables or biases during data collection, impacting result accuracy.

Tips for Empirical Writing

In empirical research, the writing is usually done in research papers, articles, or reports. The empirical writing follows a set structure, and each section has a specific role. Here are some tips for your empirical writing. 7

Define Your Objectives: When you write about your research, start by making your goals clear. Explain what you want to find out or prove in a simple and direct way. This helps guide your research and lets others know what you have set out to achieve.
Be Specific in Your Literature Review: In the part where you talk about what others have studied before you, focus on research that directly relates to your research question. Keep it short and pick studies that help explain why your research is important. This part sets the stage for your work.
Explain Your Methods Clearly : When you talk about how you did your research (Methods), explain it in detail. Be clear about your research plan, who took part, and what you did; this helps others understand and trust your study. Also, be honest about any rules you follow to make sure your study is ethical and reproducible.
Share Your Results Clearly : After doing your empirical research, share what you found in a simple way. Use tables or graphs to make it easier for your audience to understand your research. Also, talk about any numbers you found and clearly state if they are important or not. Ensure that others can see why your research findings matter.
Talk About What Your Findings Mean: In the part where you discuss your research results, explain what they mean. Discuss why your findings are important and if they connect to what others have found before. Be honest about any problems with your study and suggest ideas for more research in the future.
Wrap It Up Clearly: Finally, end your empirical research paper by summarizing what you found and why it’s important. Remind everyone why your study matters. Keep your writing clear and fix any mistakes before you share it. Ask someone you trust to read it and give you feedback before you finish.

References:

Empirical Research in the Social Sciences and Education, Penn State University Libraries. Available online at https://guides.libraries.psu.edu/emp
How to conduct empirical research, Emerald Publishing. Available online at https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research
Empirical Research: Quantitative & Qualitative, Arrendale Library, Piedmont University. Available online at https://library.piedmont.edu/empirical-research
Bouchrika, I. What Is Empirical Research? Definition, Types & Samples in 2024. Research.com, January 2024. Available online at https://research.com/research/what-is-empirical-research
Quantitative and Empirical Research vs. Other Types of Research. California State University, April 2023. Available online at https://libguides.csusb.edu/quantitative
Empirical Research, Definitions, Methods, Types and Examples, Studocu.com website. Available online at https://www.studocu.com/row/document/uganda-christian-university/it-research-methods/emperical-research-definitions-methods-types-and-examples/55333816
Writing an Empirical Paper in APA Style. Psychology Writing Center, University of Washington. Available online at https://psych.uw.edu/storage/writing_center/APApaper.pdf

Paperpal is an AI writing assistant that help academics write better, faster with real-time suggestions for in-depth language and grammar correction. Trained on millions of research manuscripts enhanced by professional academic editors, Paperpal delivers human precision at machine speed.

Try it for free or upgrade to  Paperpal Prime , which unlocks unlimited access to premium features like academic translation, paraphrasing, contextual synonyms, consistency checks and more. It’s like always having a professional academic editor by your side! Go beyond limitations and experience the future of academic writing.  Get Paperpal Prime now at just US$19 a month!

Ethics in Science: Importance, Principles & Guidelines

Presenting research data effectively through tables and figures, you may also like, academic integrity vs academic dishonesty: types & examples, dissertation printing and binding | types & comparison , what is a dissertation preface definition and examples , the ai revolution: authors’ role in upholding academic..., the future of academia: how ai tools are..., how to write a research proposal: (with examples..., how to write your research paper in apa..., how to choose a dissertation topic, how to write a phd research proposal, how to write an academic paragraph (step-by-step guide).

What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 36min 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.

To streamline your process and gather insights with precision and efficiency, consider leveraging innovative tools like Appinio . With Appinio's intuitive platform, you can harness the power of real-time consumer data to inform your research decisions effectively. Whether you're conducting surveys, interviews, or observations, Appinio empowers you to define your target audience, collect data from diverse demographics, and analyze results seamlessly.

By incorporating Appinio into your data collection toolkit, you can unlock a world of possibilities and elevate the impact of your empirical research. Ready to revolutionize your approach to data collection?

Book a Demo

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.

Chi-Square Calculator :

t-Test Calculator :

One-way ANOVA Calculator :

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 data 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.

How to Collect Data for Empirical Research?

Introducing Appinio , the real-time market research platform revolutionizing how companies gather consumer insights for their empirical research endeavors. With Appinio, you can conduct your own market research in minutes, gaining valuable data to fuel your data-driven decisions.

Appinio is more than just a market research platform; it's a catalyst for transforming the way you approach empirical research, making it exciting, intuitive, and seamlessly integrated into your decision-making process.

Here's why Appinio is the go-to solution for empirical research:

From Questions to Insights in Minutes : With Appinio's streamlined process, you can go from formulating your research questions to obtaining actionable insights in a matter of minutes, saving you time and effort.
Intuitive Platform for Everyone : No need for a PhD in research; Appinio's platform is designed to be intuitive and user-friendly, ensuring that anyone can navigate and utilize it effectively.
Rapid Response Times : With an average field time of under 23 minutes for 1,000 respondents, Appinio delivers rapid results, allowing you to gather data swiftly and efficiently.
Global Reach with Targeted Precision : With access to over 90 countries and the ability to define target groups based on 1200+ characteristics, Appinio empowers you to reach your desired audience with precision and ease.

Get free access to the platform!

Join the loop 💌

Be the first to hear about new updates, product news, and data insights. We'll send it all straight to your inbox.

Get the latest market research news straight to your inbox! 💌

Wait, there's more

03.09.2024 | 3min read

Get your brand Holiday Ready: 4 Essential Steps to Smash your Q4

Beyond Demographics: Psychographic Power in target group identification

03.09.2024 | 8min read

Beyond Demographics: Psychographics power in target group identification

29.08.2024 | 32min read

What is Convenience Sampling? Definition, Method, Examples

Empirical evidence: A definition

Empirical evidence is information that is acquired by observation or experimentation.

The scientific method

Types of empirical research, identifying empirical evidence, empirical law vs. scientific law, empirical, anecdotal and logical evidence, additional resources and reading, bibliography.

Empirical evidence is information acquired by observation or experimentation. Scientists record and analyze this data. The process is a central part of the scientific method , leading to the proving or disproving of a hypothesis and our better understanding of the world as a result.

Empirical evidence might be obtained through experiments that seek to provide a measurable or observable reaction, trials that repeat an experiment to test its efficacy (such as a drug trial, for instance) or other forms of data gathering against which a hypothesis can be tested and reliably measured.

"If a statement is about something that is itself observable, then the empirical testing can be direct. We just have a look to see if it is true. For example, the statement, 'The litmus paper is pink', is subject to direct empirical testing," wrote Peter Kosso in " A Summary of Scientific Method " (Springer, 2011).

"Science is most interesting and most useful to us when it is describing the unobservable things like atoms , germs , black holes , gravity , the process of evolution as it happened in the past, and so on," wrote Kosso. Scientific theories , meaning theories about nature that are unobservable, cannot be proven by direct empirical testing, but they can be tested indirectly, according to Kosso. "The nature of this indirect evidence, and the logical relation between evidence and theory, are the crux of scientific method," wrote Kosso.

The scientific method begins with scientists forming questions, or hypotheses , and then acquiring the knowledge through observations and experiments to either support or disprove a specific theory. "Empirical" means "based on observation or experience," according to the Merriam-Webster Dictionary . Empirical research is the process of finding empirical evidence. Empirical data is the information that comes from the research.

Before any pieces of empirical data are collected, scientists carefully design their research methods to ensure the accuracy, quality and integrity of the data. If there are flaws in the way that empirical data is collected, the research will not be considered valid.

The scientific method often involves lab experiments that are repeated over and over, and these experiments result in quantitative data in the form of numbers and statistics. However, that is not the only process used for gathering information to support or refute a theory.

This methodology mostly applies to the natural sciences. "The role of empirical experimentation and observation is negligible in mathematics compared to natural sciences such as psychology, biology or physics," wrote Mark Chang, an adjunct professor at Boston University, in " Principles of Scientific Methods " (Chapman and Hall, 2017).

"Empirical evidence includes measurements or data collected through direct observation or experimentation," said Jaime Tanner, a professor of biology at Marlboro College in Vermont. There are two research methods used to gather empirical measurements and data: qualitative and quantitative.

Qualitative research, often used in the social sciences, examines the reasons behind human behavior, according to the National Center for Biotechnology Information (NCBI) . It involves data that can be found using the human senses . This type of research is often done in the beginning of an experiment. "When combined with quantitative measures, qualitative study can give a better understanding of health related issues," wrote Dr. Sanjay Kalra for NCBI.

Quantitative research involves methods that are used to collect numerical data and analyze it using statistical methods, ."Quantitative research methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques," according to the LeTourneau University . This type of research is often used at the end of an experiment to refine and test the previous research.

Identifying empirical evidence in another researcher's experiments can sometimes be difficult. According to the Pennsylvania State University Libraries , there are some things one can look for when determining if evidence is empirical:

Can the experiment be recreated and tested?
Does the experiment have a statement about the methodology, tools and controls used?
Is there a definition of the group or phenomena being studied?

The objective of science is that all empirical data that has been gathered through observation, experience and experimentation is without bias. The strength of any scientific research depends on the ability to gather and analyze empirical data in the most unbiased and controlled fashion possible.

However, in the 1960s, scientific historian and philosopher Thomas Kuhn promoted the idea that scientists can be influenced by prior beliefs and experiences, according to the Center for the Study of Language and Information .

— Amazing Black scientists

— Marie Curie: Facts and biography

— What is multiverse theory?

"Missing observations or incomplete data can also cause bias in data analysis, especially when the missing mechanism is not random," wrote Chang.

Because scientists are human and prone to error, empirical data is often gathered by multiple scientists who independently replicate experiments. This also guards against scientists who unconsciously, or in rare cases consciously, veer from the prescribed research parameters, which could skew the results.

The recording of empirical data is also crucial to the scientific method, as science can only be advanced if data is shared and analyzed. Peer review of empirical data is essential to protect against bad science, according to the University of California .

Empirical laws and scientific laws are often the same thing. "Laws are descriptions — often mathematical descriptions — of natural phenomenon," Peter Coppinger, associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology, told Live Science.

Empirical laws are scientific laws that can be proven or disproved using observations or experiments, according to the Merriam-Webster Dictionary . So, as long as a scientific law can be tested using experiments or observations, it is considered an empirical law.

Empirical, anecdotal and logical evidence should not be confused. They are separate types of evidence that can be used to try to prove or disprove and idea or claim.

Logical evidence is used proven or disprove an idea using logic. Deductive reasoning may be used to come to a conclusion to provide logical evidence. For example, "All men are mortal. Harold is a man. Therefore, Harold is mortal."

Anecdotal evidence consists of stories that have been experienced by a person that are told to prove or disprove a point. For example, many people have told stories about their alien abductions to prove that aliens exist. Often, a person's anecdotal evidence cannot be proven or disproven.

There are some things in nature that science is still working to build evidence for, such as the hunt to explain consciousness .

Meanwhile, in other scientific fields, efforts are still being made to improve research methods, such as the plan by some psychologists to fix the science of psychology .

" A Summary of Scientific Method " by Peter Kosso (Springer, 2011)

"Empirical" Merriam-Webster Dictionary

" Principles of Scientific Methods " by Mark Chang (Chapman and Hall, 2017)

"Qualitative research" by Dr. Sanjay Kalra National Center for Biotechnology Information (NCBI)

"Quantitative Research and Analysis: Quantitative Methods Overview" LeTourneau University

"Empirical Research in the Social Sciences and Education" Pennsylvania State University Libraries

"Thomas Kuhn" Center for the Study of Language and Information

"Misconceptions about science" University of California

Sign up for the Live Science daily newsletter now

Get the world’s most fascinating discoveries delivered straight to your inbox.

Live Science x HowTheLightGetsIn — Get discounted tickets to the world’s largest ideas and music festival

Do opposites really attract in relationships?

Scientists make lab-grown black hole jets

Empirical & Non-Empirical Research

Empirical Research

Introduction: What is Empirical Research?

Quantitative methods, qualitative methods.

Quantitative vs. Qualitative
Reference Works for Social Sciences Research
What is Non-Empirical Research?
Contact Us!

Call us at 706-776-0111

Chat with a Librarian

Send Us Email

Library Hours

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

More about Academic Writer ...

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.

Next: Quantitative vs. Qualitative >>
Last Updated: Jul 24, 2024 12:04 PM
URL: https://library.piedmont.edu/empirical-research
Ebooks & Online Video
New Materials
Renew Checkouts
Faculty Resources
Library Friends
Library Services
Our Mission
Library History
Ask a Librarian!
Making Citations
Working Online

Arrendale Library Piedmont University 706-776-0111

Empirical Research: What is empirical research?

What is empirical research.

How do I find empirical research in databases?
What does empirical research look like?
How is empirical research conducted?
What is Empirical Research?
How do I Find Empirical Research in Databases?
How is Empirical Research Conducted?

Ask a Librarian

Contact the reference desk.

	[email protected]

	(603) 556-8883
	(603) 641-7306

Reference Desk Hours

Sunday	CLOSED
Monday	11AM - 10PM
Tuesday	11AM - 10PM
Wednesday	11AM - 5PM
Thursday	11AM - 5PM
Friday	11AM - 3PM
Saturday	12PM - 5PM

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

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

What about when research is not empirical?

Many humanities scholars do not use empirical methods. if you are looking for empirical articles in one of these subject areas, try including keywords like:.

quantitative
qualitative

Also, look for opportunities to narrow your search to scholarly, academic, or peer-reviewed journals articles in the database.

Adapted from " Research Methods: Finding Empirical Articles " by Jill Anderson at Georgia State University Library.

See the complete A-Z databases list for more resources

The primary content of this guide was originally created by Ellysa Cahoy at Penn State Libraries .

Next: How do I find empirical research in databases? >>
Last Updated: Aug 26, 2024 10:45 AM
URL: https://geiselguides.anselm.edu/Empirical-Research

Sociology Research Guide: Identifying & Finding Empirical Articles

Evaluating Your Sources
Types of Publications
Identifying & Finding Empirical Articles
Known Item Searching
EndNote Web

How to Recognize Empirical Journal Articles

Definition of an empirical study: An empirical research article reports the results of a study that uses data derived from actual observation or experimentation. Empirical research articles are examples of primary research.

Parts of a standard empirical research article: (articles will not necessary use the exact terms listed below.)

Abstract ... A paragraph length description of what the study includes.
Introduction ...Includes a statement of the hypotheses for the research and a review of other research on the topic.
Method ...A description of how the research was conducted, such as: ◊ Who are participants ◊ Design of the study ◊ What the participants did ◊ What measures were used
Results ...Describes the outcomes of the measures of the study.
Discussion...C ontains the interpretations and implications of the study.
References...C ontains citation information on the material cited in the report. (also called bibliography or works cited)

Characteristics of an Empirical Article:

Empirical articles will include charts, graphs, or statistical analysis.
Empirical research articles are usually substantial, maybe from 8-30 pages long.
There is always a bibliography found at the end of the article.

Type of publications that publish empirical studies:

Empirical research articles are published in scholarly or academic journals These journals are also called “peer-reviewed,” or “refereed” publications.
Examples of such publications include: ◊ American Journal of Sociology ◊ Sociological Quarterly ◊ Sociological Methods and Research

Databases that contain empirical research: (selected list only)

Academic Search Premier add these words to your search terms: method* or research or research design or survey* or data or result*
PsycINFO limit your searches by Form/Content Type to Empirical Study
ERIC limit to Pub. Type to Reports - Research/Technical Change one dropdown box to Record. This finds REPORTS--RESEARCH.
Sociological Abstracts 1963 - present.
Sports Discus Change search limit to Level = Advanced for original scientific research

Empirical Articles - Sample Research Tips

Empirical articles detail original research/studies that have been done.

Some of the major components of empirical articles include the following: Abstract , Introduction , Method , Results , Discussion , References

Locating Empirical Articles in APA PsycINFO

Use the "Methodology" limiter to select: EMPIRICAL STUDY

Locating Empirical Articles in ERIC

Use the "Publication Type" limiter to select: Reports - Research

Locating Empirical Articles in Other Databases

Use terms such as: study , research , empirical , methods , methodology , research design , survey , data , results

Please remember to use OR between your combination of terms. For example, you may enter the following in one search box:

study OR research OR empirical

research OR methods OR data OR results

<< Previous: Articles
Next: Known Item Searching >>
Last Updated: Aug 28, 2024 10:22 AM
URL: https://libraryguides.fullerton.edu/sociology

This site is maintained by Pollak Library .

Web Accessibility

CSUF is committed to ensuring equal accessibility to our users. Let us know about any accessibility problems you encounter using this website. We'll do our best to improve things and get you the information you need.

Adobe Reader
Microsoft Viewers
Report An ATI Issue
Accessible @ CSUF

Empirical Research

First Online: 08 May 2024

Cite this chapter

Claes Wohlin 7 ,
Per Runeson 8 ,
Martin Höst 9 ,
Magnus C. Ohlsson 10 ,
Björn Regnell 8 &
Anders Wesslén 11

This chapter presents a decision-making structure for determining an appropriate research design for a specific study. A selection of research approaches is introduced to help illustrate the decision-making structure. The research approaches are described briefly to provide a basic understanding of different options. Moreover, the chapter discusses how different research approaches may be used in a research project or when, for example, pursuing PhD studies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save.

Get 10 units per month
Download Article/Chapter or eBook
1 Unit = 1 Article or 1 Chapter
Cancel anytime
Available as PDF
Read on any device
Instant download
Own it forever
Available as EPUB and PDF
Compact, lightweight edition
Dispatched in 3 to 5 business days
Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

The term “investigation” is used as a more general term than a specific study.

It is sometimes also referred to as a review or a code review, if reviewing code. However, we have chosen to use the term “inspection” to avoid mixing it up with a systematic literature review.

Latin for “in the glass” and refers to chemical experiments in a test tube.

Latin for “in life” and refers to experiments in a real environment.

Ali, N.B., Petersen, K., Wohlin, C.: A systematic literature review on the industrial use of software process simulation. J. Syst. Software 97 , 65–85 (2014). https://doi.org/10.1016/j.jss.2014.06.059

Article Google Scholar

Anastas, J.W.: Research Design for the Social Work and the Human Services, 2nd edn. Columbia University Press, New York (2000). https://doi.org/10.7312/anas11890

Anthony, R.N.: Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business Administration, Boston (1965)

Google Scholar

Arisholm, E., Gallis, H., Dybå, T., Sjøberg, D.I.K.: Evaluating pair programming with respect to system complexity and programmer expertise. IEEE Trans. Software Eng. 33 (2), 65–86 (2007). https://doi.org/10.1109/TSE.2007.17

Ayala, C., Turhan, B., Franch, X., Juristo, N.: Use and misuse of the term ‘experiment’ in mining software repositories research. IEEE Trans. Software Eng. 48 (11), 4229–4248 (2022). https://doi.org/10.1109/TSE.2021.3113558

Babbie, E.R.: Survey Research Methods. Wadsworth, Belmont (1998)

Baskerville, R.: What design science is not. Eur. J. Inf. Syst. 17 (5), 441–443 (2008). https://doi.org/10.1057/ejis.2008.45

Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3 (2), 77–101 (2006). https://doi.org/10.1191/1478088706qp063oa

Collis, J., Hussey, R.: Business Research: A Practical Guide for Undergraduate and Postgraduate Students. Bloomsbury Publishing, London (2021)

Creswell, J.W., Creswell, J.D.: Research Design: Qualitative, Quantitative, and Mixed methods Approaches. Sage publications, Thousand Oaks (2017)

Drisko, J.W., Maschi, T.: Content Analysis. Oxford University Press, Oxford (2016)

Easterbrook, S., Singer, J., Storey, M.A., Damian, D.: Selecting empirical methods for software engineering research. In: Shull, F., Singer, J., Sjøberg, D.I.K. (eds.) Guide to Advanced Empirical Software Engineering. Springer, London (2008). https://doi.org/10.1007/978-1-84800-044-5_11

Emerson, R.M., Fretz, R.I., Shaw, L.L.: Participant observation and fieldnotes. In: Stanley, L. (ed.) Handbook of Ethnography, pp. 352–368. SAGE Publications Ltd., Thousand Oaks (2001)

Chapter Google Scholar

Engström, E., Storey, M.A., Runeson, P., Höst, M., Baldassarre, M.T.: How software engineering research aligns with design science: a review. Empirical Software Eng. 25 , 2630–2660 (2020). https://doi.org/10.1007/s10664-020-09818-7

Felderer, M., Travassos, G.H.: Contemporary Empirical Methods in Software Engineering. Springer, Cham (2020)

Book Google Scholar

Glaser, B., Strauss, A.: Discovery of Grounded Theory: Strategies for Qualitative Research. Routledge, Milton Park (2017). https://doi.org/10.4324/9780203793206

Hannay, J.E., Dybå, T., Arisholm, E., Sjøberg, D.I.K.: The effectiveness of pair programming: a meta-analysis. Inf. Software Technol. 51 (7), 1110–1122 (2009). https://doi.org/10.1016/j.infsof.2009.02.001

Harwood, T.G., Garry, T.: An overview of content analysis. Mark. Rev. 3 (4), 479–498 (2003). https://doi.org/10.1362/146934703771910080

Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28 (1), 75–105 (2004). https://doi.org/10.2307/25148625

Hoda, R.: Socio-technical grounded theory for software engineering. IEEE Trans. Software Eng. 48 (10), 3808–3832 (2022). https://doi.org/10.1109/TSE.2021.3106280

Jiménez, M., Piattini, M.: Problems and solutions in distributed software development: a systematic review. In: Proceedings of the Software Engineering Approaches for Offshore and Outsourced Development, pp. 107–125 (2009). https://doi.org/10.1007/978-3-642-01856-5_8

Karahasanović, A., Anda, B., Arisholm, E., Hove, S.E., Jørgensen, M., Sjøberg, D.I.K., Welland, R.: Collecting feedback during software engineering experiments. Empirical Software Eng. 10 (2), 113–147 (2005). https://doi.org/10.1007/s10664-004-6189-4

Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering (version 2.3). Techncial Report. EBSE Technical Report EBSE-2007-01, Keele University and Durham University (2007)

Kitchenham, B.A., Pfleeger, S.L.: Principles of survey research part 2: designing a survey. ACM SIGSOFT Software Eng. Notes 27 (1), 18–20 (2002). https://doi.org/10.1145/566493.566495

Kitchenham, B., Pickard, L., Pfleeger, S.L.: Case studies for method and tool evaluation. IEEE Software, 52–62 (1995). https://doi.org/10.1109/52.391832

Kitchenham, B.A., Budgen, D., Brereton, P.: Evidence-Based Software Engineering and Systematic Reviews, vol. 4. CRC Press, Boca Raton (2015)

Kitchenham, B., Madeyski, L., Budgen, D.: SEGRESS: software engineering guidelines for reporting secondary studies. IEEE Trans. Software Eng. 49 (3), 1273–1298 (2023). https://doi.org/10.1109/TSE.2022.3174092

Klein, H.K., Myers, M.D.: A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Q., 67–93 (1999). https://doi.org/10.2307/249410

Kontio, J., Bragge, J., Lehtola, L.: The focus group method as an empirical tool in software engineering. In: Guide to Advanced Empirical Software Engineering, pp. 93–116. Springer, London (2008). https://doi.org/10.1007/978-1-84800-044-5_4

Krishnaiah, V., Narsimha, G., Chandra, N.S.: Survey of classification techniques in data mining. Int. J. Comput. Sci. Eng. 2 (9), 65–74 (2014)

Law, A.M., Kelton, W.D.: Simulation Modeling and Analysis, vol. 3. Mcgraw-Hill, New York (2007)

Linkman, S., Rombach, H.D.: Experimentation as a vehicle for software technology transfer – a family of software reading techniques. Inf. Software Technol. 39 (11), 777–780 (1997). https://doi.org/10.1016/S0950-5849(97)00029-3

Moe, N.B., Aurum, A., Dybå, T.: Challenges of shared decision-making: a multiple case study of agile software development. Inf. Software Technol. 54 (8), 853–865 (2012). https://doi.org/10.1016/j.infsof.2011.11.006

Müller, M., Pfahl, D.: Simulation methods. In: Shull, F., Singer, J., Sjøberg, D.I.K. (eds.) Guide to Advanced Empirical Software Engineering, pp. 117–152. Springer, London (2008). https://doi.org/10.1007/978-1-84800-044-5_5

Petersen, K., Wohlin, C.: Context in industrial software engineering research. In: Proceedings of the International Symposium on Empirical Software Engineering and Measurement, pp. 401–404 (2009). https://doi.org/10.1109/ESEM.2009.5316010

Pfleeger, S.L.: Experimental design and analysis in software engineering. Ann. Software Eng. 1 , 219–253 (1995)

Pinsonneault, A., Kraemer, K.: Survey research methodology in management information systems: an assessment. J. Manage. Inf. Syst., 75–105 (1993). https://doi.org/10.1080/07421222.1993.11518001

Rainer, A.: The longitudinal, chronological case study research strategy: a definition, and an example from IBM Hursley Park. Inf. Software Technol. 53 (7), 730–746 (2011). https://doi.org/10.1016/j.infsof.2011.01.003

Robson, C.: Small-Scale Evaluation: Principles and Practice. Sage Publications Ltd., Thousand Oaks (2017)

Robson, C., McCartan, K.: Real World Research: A Resource for Users of Social Research Methods in Applied Settings, 4th edn. Wiley, Hoboken (2016)

Runeson, P., Höst, M.: Guidelines for conducting and reporting case study research in software engineering. Empirical Software Eng. 14 , 131–164 (2009). https://doi.org/10.1007/s10664-008-9102-8

Runeson, P., Skoglund, M.: Reference-based search strategies in systematic reviews. In: Proceedings of the International Conference on Empirical Assessment & Evaluation in Software Engineering (2009). https://doi.org/10.14236/ewic/EASE2009.4

Runeson, P., Höst, M., Rainer, A., Regnell, B.: Case Study Research in Software Engineering. Guidelines and Examples. John Wiley & Sons, Hoboken (2012)

Runeson, P., Engström, E., Storey, M.A.: The design science paradigm as a frame for empirical software engineering. In: Felderer, M., Travassos, G.H. (eds.) Contemporary Empirical Methods in Software Engineering, pp. 127–147. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-32489-6_5

Seaman, C.B.: Qualitative methods in empirical studies of software engineering. IEEE Trans. Software Eng. 25 (4), 557–572 (1999). https://doi.org/10.1109/32.799955

Shull, F.J., Carver, J.C., Vegas, S., Juristo, N.: The role of replications in empirical software engineering. Empirical Software Eng. 13 , 211–218 (2008). https://doi.org/10.1007/s10664-008-9060-1

Sjøberg, D.I.K., Dybå, T., Jørgensen, M.: The future of empirical methods in software engineering research. In: Proceedings of the Future of Software Engineering, pp. 358–378 (2007). https://doi.org/10.1109/FOSE.2007.30

Staron, M.: Action Research in Software Engineering. Springer International Publishing, Berlin (2020)

Staron, M., Kuzniarz, L., Wohlin, C.: Empirical assessment of using stereotypes to improve comprehension of UML models: a set of experiments. J. Syst. Software 79 (5), 727–742 (2006). https://doi.org/10.1016/j.jss.2005.09.014

Stol, K.J., Ralph, P., Fitzgerald, B.: Grounded theory in software engineering research: a critical review and guidelines. In: Proceedings of the International Conference on Software Engineering, pp. 120–131 (2016). https://doi.org/10.1145/2884781.2884833

Usman, M., bin Ali, N., Wohlin, C.: A quality assessment instrument for systematic literature reviews in software engineering. e-Inform. Software Eng. J. 17 (1), 230105 (2023). https://doi.org/10.37190/e-Inf230105

Verner, J.M., Sampson, J., Tosic, V., Abu Bakar, N.A., Kitchenham, B.A.: Guidelines for industrially-based multiple case studies in software engineering. In: Proceedings of the International Conference on Research Challenges in Information Science, pp. 313–324 (2009). https://doi.org/10.1109/RCIS.2009.5089295

Wieringa, R.J.: Design Science Methodology for Information Systems and Software Engineering. Springer, Berlin (2014). https://doi.org/10.1007/978-3-662-43839-8

Williams, L.A., Kessler, R.R.: Experiments with industry’s “pair-programming” model in the computer science classroom. Comput. Sci. Educ. 11 (1), 7–20 (2001). https://doi.org/10.1076/csed.11.1.7.3846

Wohlin, C.: Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (2014). https://doi.org/10.1145/2601248.2601268

Wohlin, C.: Case study research in software engineering—it is a case, and it is a study, but is it a case study? Inf. Software Technol. 133 , 106514 (2021). https://doi.org/10.1016/j.infsof.2021.106514

Wohlin, C., Aurum, A.: Towards a decision-making structure for selecting a research design in empirical software engineering. Empirical Software Eng. 20 (6), 1427–1455 (2015). https://doi.org/10.1007/s10664-014-9319-7

Wohlin, C., Rainer, A.: Is it a case study?–a critical analysis and guidance. J. Syst. Software 192 , 111395 (2022). https://doi.org/10.1016/j.jss.2022.111395

Wohlin, C., Runeson, P.: Guiding the selection of research methodology in industry–academia collaboration in software engineering. Inf. Software Technol. 140 , 106678 (2021). https://doi.org/10.1016/j.infsof.2021.106678

Wohlin, C., Gustavsson, A., Höst, M., Mattsson, C.: A framework for technology introduction in software organizations. In: Proceedings of the Conference on Software Process Improvement, pp. 167–176 (1996)

Zannier, C., Melnik, G., Maurer, F.: On the success of empirical studies in the international conference on software engineering. In: Proceedings of the International Conference on Software Engineering, pp. 341–350 (2006). https://doi.org/10.1145/1134285.1134333

Download references

Author information

Authors and affiliations.

Blekinge Institute of Technology, Karlskrona, Sweden

Claes Wohlin

Department of Computer Science, Lund University, Lund, Sweden

Per Runeson & Björn Regnell

Faculty of Technology and Society, Malmö University, Malmö, Sweden

Martin Höst

System Verification Sweden AB, Malmö, Sweden

Magnus C. Ohlsson

Ericsson AB, Lund, Sweden

Anders Wesslén

You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

About this chapter

Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., Wesslén, A. (2024). Empirical Research. In: Experimentation in Software Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-69306-3_2

Download citation

DOI : https://doi.org/10.1007/978-3-662-69306-3_2

Published : 08 May 2024

Publisher Name : Springer, Berlin, Heidelberg

Print ISBN : 978-3-662-69305-6

Online ISBN : 978-3-662-69306-3

eBook Packages : Computer Science Computer Science (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Publish with us

Policies and ethics

Find a journal
Track your research

La Salle University

Connelly library, library main menu.

Course Reserves
Interlibrary Loan (ILL)
Study Room Use & Reservations
Technology & Printing
Citation Guides
Reserve Library Space
Request Instruction
Copyright Information
Guides for Faculty

Special Collections

University Archives
Historical & Cultural Collections
Rare Bibles & Prayer Books
Historical Research Guides
Information & Guidelines
Staff Directory
Meet with a Librarian
Directions & Building Maps

Research Hub

Research Tools
Research Guides

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.

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
<< Previous: Home
Next: Locating Articles in Cinahl and PsycInfo >>

Chat Assistance

University of Memphis Libraries
Research Guides
Empirical Research: Defining, Identifying, & Finding

Introduction

Image attribution.

Defining Empirical Research
Database Tools
Search Terms
Image Descriptions

Get Help at McWherter Library

Ned R. McWherter Library 3785 Norriswood Ave., Memphis, TN 38152

Ask a Librarian

Hours / Events

Sometimes you may be asked to find and use empirical research. If you aren't sure what is and is not empirical research, this might seem scary. We are here to help.

Note: while this guide is designed to help you understand and find empirical research, you should always default to your instructor's definition if they provide one and direct any specific questions about whether a source fits that definition to your instructor.

Guide Overview

In this guide, you will learn:

The definition and characteristics of empirical research.
How to identify the characteristics of empirical research quickly when reading an article.
Ways to search more quickly for empirical research.

Photo by Pixabay from Pexels

Next: Defining Empirical Research >>
Last Updated: Apr 2, 2024 11:25 AM
URL: https://libguides.memphis.edu/empirical-research

Information

Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

Active Journals
Find a Journal
Proceedings Series
For Authors
For Reviewers
For Editors
For Librarians
For Publishers
For Societies
For Conference Organizers
Open Access Policy
Institutional Open Access Program
Special Issues Guidelines
Editorial Process
Research and Publication Ethics
Article Processing Charges
Testimonials
Preprints.org
SciProfiles
Encyclopedia

Article Menu

Subscribe SciFeed
Recommended Articles
Google Scholar
on Google Scholar
Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

How do the representatives of small and micro restaurants perceive food waste in their own restaurant empirical evidence from the netherlands.

1. Introduction

2. materials and methods, 2.1. food waste at restaurants: literature review, 2.2. bridge from theory to practice, 2.3. fieldwork, 2.4. collected data, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

Available online: https://www.un.org/sustainabledevelopment/sustainable-development-goals (accessed on 1 December 2023).
Available online: https://www.unep.org (accessed on 1 December 2023).
Bhajan, C.; Neetoo, H.; Hardowar, S.; Boodia, N.; Driver, M.F.; Chooneea, M.; Ramasawmy, B.; Goburdhun, D.; Ruggoo, A. Food waste generated by the Mauritian hotel industry. Tour. Crit. Theory Pract. 2022 , 3 , 120–137. [ Google Scholar ] [ CrossRef ]
Dhir, A.; Talwar, S.; Kaur, P.; Malibari, A. Food waste in hospitality and food services: A systematic literature review and framework development approach. J. Clean. Prod. 2020 , 270 , 122861. [ Google Scholar ] [ CrossRef ]
Afzal, N.; Basit, A.; Daniel, A.; Ilyas, N.; Imran, A.; Awan, Z.A.; Papargyropoulou, E.; Stringer, L.C.; Hashem, M.; Alamri, S.; et al. Quantifying food waste in the hospitality sector and exploring its underlying reasons—A case study of Lahore, Pakistan. Sustainability 2022 , 14 , 6914. [ Google Scholar ] [ CrossRef ]
Coşkun, A.; Filimonau, V. ‘I waste food but this is not my fault!’: Exploring the drivers of plate waste in food services of Turkey through the prism of neutralization theory. J. Clean. Prod. 2021 , 329 , 129695. [ Google Scholar ] [ CrossRef ]
Dolnicar, S.; Juvan, E.; Grün, B. Reducing the plate waste of families at hotel buffets: A quasi-experimental field study. Tour. Manag. 2020 , 80 , 1040134. [ Google Scholar ] [ CrossRef ]
Eckert Matzembacher, D.; Brancoli, P.; Moltene Maia, L.; Eriksson, M. Consumer’s food waste in different restaurants configuration: A comparison between different levels of incentive and interaction. Waste Manag. 2020 , 114 , 263–273. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Matyakubov, U.; Allonazarov, O.; Ermolaev, V.A. Food waste and its management in restaurants of a transition economy: An exploratory story of Uzbekistan. Sustain. Prod. Consum. 2022 , 29 , 25–35. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Matute, J.; Kubal-Czerwińska, M.; Krzesiwo, K.; Mika, M. The determinants of consumer engagement in restaurant food waste mitigation in Poland: An exploratory study. J. Clean. Prod. 2020 , 247 , 119105. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Ermolaev, V.A. A sleeping giant? Food waste in the foodservice sector of Russia. J. Clean. Prod. 2021 , 297 , 126705. [ Google Scholar ] [ CrossRef ]
van Herpen, E.; De Hooge, I.E.; de Visser-Amundson, A.; Kleijnen, M.H.P. Take it or leave it: How an opt-out strategy for doggy bags affects consumer food waste behavior and restaurant evaluations. J. Clean. Prod. 2021 , 325 , 129199. [ Google Scholar ] [ CrossRef ]
de Oliveira Pontes, T.; da Silva César, A.; Conejero, M.A.; Deliberado, L.R.; Batalha, M.O. Food waste measurement in a chain of industrial restaurants in Brazil. J. Clean. Prod. 2022 , 369 , 133351. [ Google Scholar ] [ CrossRef ]
Talwar, S.; Kaur, P.; Okumus, B.; Ahmed, U.; Dhir, A. Food waste reduction and taking away leftovers: Interplay of food-ordering routine, planning routine, and motives. Int. J. Hosp. Manag. 2021 , 98 , 103033. [ Google Scholar ] [ CrossRef ]
Zhang, H.; Li, S.; Wei, D.; He, J.; Chen, J.; Sun, C.; Vuppaladadiyam, A.K.; Duan, H. Characteristics, environmental impact, and reduction strategies of food waste generated by young adults: Case study on university canteens in Wuhan, China. J. Clean. Prod. 2021 , 321 , 12877. [ Google Scholar ] [ CrossRef ]
Olavarria-Key, N.; Ding, A.; Legendre, T.S.; Min, J. Communication of food waste messages: The effects of communication modality, presentation order, and mindfulness on food waste reduction intention. Int. J. Hosp. Manag. 2021 , 96 , 102962. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; De Coteau, D.A. Food waste management in hospitality operations: Critical review. Tour. Manag. 2019 , 71 , 234–245. [ Google Scholar ] [ CrossRef ]
Chalak, A.; Hassan, H.F.; Aoun, P.; Abiad, M.G. Drivers and determinants of food waste generation in restaurants serving Mediterranean Mezze-type cuisine. Sustainability 2021 , 13 , 6358. [ Google Scholar ] [ CrossRef ]
Filimononau, V.; Nghiem, V.N.; Wang, L. Food waste management in ethnic food restaurants. Int. J. Hosp. Manag. 2020 , 92 , 102731. [ Google Scholar ] [ CrossRef ]
Greggio, N.; Serafini, A.; Balugani, E.; Carlini, C.; Contin, A.; Marazza, D. Quantification and mapping of fish waste in retail trade and restaurant sector: Experience in Emilia-Romagna, Italy. Waste Manag. 2021 , 135 , 256–266. [ Google Scholar ] [ CrossRef ]
Liang, Y.; Song, Q.; Liui, G.; Li, G.L. Uncovering residents and restaurants’ attitude and willingness toward effective food waste management: A case of Macau. Waste Manag. 2021 , 130 , 107–116. [ Google Scholar ] [ CrossRef ]
Vizzoto, F.; Testa, F.; Iraldo, F. Strategies to reduce food waste in the foodservices sector: A systematic review. Int. J. Hosp. Manag. 2021 , 95 , 102933. [ Google Scholar ] [ CrossRef ]
Vidal-Mones, B.; Diaz-Ruiz, R.; Gil, J.M. From evaluation to action: Testing nudging strategies to prevent food waste in school canteens. Waste Manag. 2022 , 140 , 90–99. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Visschers, V.H.M.; Gundlach, D.; Beretta, C. Smaller servings vs. Information provision: Results of two interventions to reduce plate waste in two university canteens. Waste Manag. 2020 , 103 , 322–333. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Camilleri, M.A. Sustainable production and consumption of food. Mise-en-place circular economy policies and waste management practices in tourism cities. Sustainability 2021 , 13 , 9986. [ Google Scholar ] [ CrossRef ]
Sharma, R.; Dhir, A.; Talwar, S.; Kaur, P. Over-ordering and food waste: The use of food delivery apps during a pandemic. Int. J. Hosp. Manag. 2021 , 96 , 102977. [ Google Scholar ] [ CrossRef ]
Patel, S.; Dora, M.; Hahladakis, J.N.; Iacovidou, E. Opportunities, challenges and trade-offs with decreasing avoidable food waste in the UK. Waste Manag. Res. 2021 , 39 , 473–488. [ Google Scholar ] [ CrossRef ]
Goossens, Y.; Leverenz, D.; Kuntscher, M. Waste-tracking tools: A business case for more sustainable and resource efficient food services. Resour. Conserv. Recycl. Adv. 2022 , 15 , 200112. [ Google Scholar ] [ CrossRef ]
Igeta, J.; Nakamura, H. Business Incentive to Reduce Food Losses in Japan. Sustainability 2022 , 14 , 2266. [ Google Scholar ] [ CrossRef ]
De Almeida Oroski, F.; da Silva, J.M. Understanding food waste-reducing platforms: A mini-review. J. Waste Manag. 2023 , 41 , 816–827. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Faezirad, M.; Pooya, A.; Naji-Azimi, Z.; Amir Haeri, M. Preventing food waste in subsidy-based university dining systems: An artificial neural network-aided model under uncertainty. Waste Manag. Res. 2021 , 39 , 1027–1038. [ Google Scholar ] [ CrossRef ]
Beretta, C.; Hellweg, S. Potential environmental benefits from food waste prevention in the food service sector. J. Clean. Prod. 2019 , 147 , 169–178. [ Google Scholar ] [ CrossRef ]
Katajajuuri, J.M.; Silvennoinen, K.; Hartikainen, H.; Heikkilä, L.; Reinikainen, A. Food waste in the Finnish food chain. J. Clean. Prod. 2014 , 73 , 322–329. [ Google Scholar ] [ CrossRef ]
Silvennoinen, K.; Nisonen, S.; Pietiläinen, O. Food waste case study and monitoring developing in Finnish food services. Waste Manag. 2019 , 97 , 97–104. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Carletto, F.C.; Ferriani, L.O.; Silva, D.A. Sustainability in food service: A systematic review. Waste Manag. Res. 2023 , 41 , 285–302. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Vizzotto, F.; Tessitore, S.; Iraldo, F.; Testa, F. Passively concerned: Horeca managers’ recognition of the importance of food wste hardly 3elads to the adoption of more strategies to reduce it. Waste Manag. 2020 , 107 , 266–275. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Uddin, R. Food waste management in chain-affiliated and independent consumers’ places: A preliminary and exploratory study. J. Clean. Prod. 2021 , 319 , 128721. [ Google Scholar ] [ CrossRef ]
Okumus, B.; Taheri, B.; Giritlioglu, I.; Gannon, M.J. Tackling food waste in all-inclusive resort hotels. Int. J. Hosp. Manag. 2020 , 88 , 102543. [ Google Scholar ] [ CrossRef ]
Lévesque, J.; Perreault, V.; Bazinet, L.; Mikhaylin, S. Food waste in a hotel foodservice: A case study identifying hot spots and strategies to prioritize towards a reduction. Int. J. Gastron. Food. Sci. 2022 , 30 , 100600. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Zhang, H.; Wang, L. Food waste management in Shanghai full service restaurants: A senior managers’ perspective. J. Clean. Prod. 2020 , 258 , 120975. [ Google Scholar ] [ CrossRef ]
Filimonau, V.; Todorova, E.; Mzembe, A.; Sauer, L.; Yankholmes, A. A comparative study of food waste management in full service restaurants of the United Kingdom and the Netherlands. J. Clean. Prod. 2020 , 258 , 120775. [ Google Scholar ] [ CrossRef ]
Martin-Rios, C.; Hofmann, A.; Mackenzie, N. Sustainability-Oriented Innovations in Food Waste Management Technology. Sustainability 2020 , 13 , 210. [ Google Scholar ] [ CrossRef ]
Moghawemi, S.; Mohd Salleh, N.A.; Standing, C. Entrepreneurs Adoption of Information System Innovation: The Impact of Individual Perception and Exogenous Factors on Entrepreneurs Behavior. Internet Res. 2016 , 26 , 1181–1208. [ Google Scholar ] [ CrossRef ]
Available online: https://www.cbs.nl (accessed on 1 December 2023).
Available online: https://www.rvo.nl (accessed on 1 December 2023).
Frese, M.; Krauss, S.I.; Keith, N.; Escher, S.; Grabarkiewicz, R.; Luneng, S.T.; Heers, C.; Unger, J.; Friedrich, C. Business Owners’ Action Planning and Its Relationship to Business Success in Three African Countries. J. Appl. Psychol. 2007 , 92 , 1481–1498. [ Google Scholar ] [ CrossRef ] [ PubMed ]

	Number of Respondents	%
Gender
Female	107	53.5
Male	93	46.5
All	200	100
Education
Higher education	107	55.7
Lower education	85	44.3
All	192	100
Role within the restaurant
Owner–managers	97	49.5
Directors/managers	65	32.5
Restaurant chefs	36	18.0
All	198	100

	Number of Respondents	%
Type of restaurant
Casual dining	112	56.0
Fine dining	51	25.5
Fast food	37	18.5
All	200	100
Location
Amsterdam	105	52.5
Elsewhere in the western Netherlands	95	47.5
All	200	100

Percentage Food Waste	Number of Respondents	%
0–10%	93	49.7
10–20%	40	21.4
20–30%	43	23.0
30–40%	8	4.3
40–50%	2	1.1
60–70%	1	0.5
All	187	100

	Average Score	Standard Deviation	Minimum Score	Maximum Score
General problem	3.1	1.1	1	5
Financial problem	2.6	1.0	1	5
Social problem	2.7	1.1	1	5
Environmental problem	3.3	1.1	1	5

Variable	Beta	T Value	Significance
Constant	2.670	13.660	<0.001 ***
Respondent
Age (years)	−0.306	−2.329	0.021 **
Gender (female = 0; male = 1)	0.53	0.460	0.646
Education (low = 0; high = 1)	−0.088	−0.768	0.443
Function (active owners = 0; others = 1)	0.327	2.768	0.006 **
Restaurant
Location (Amsterdam = 0; elsewhere = 1)	0.160	1.315	0.190
Type (casual dining = 0; other = 1)	0.167	1.380	0.169
Employees (number)	0.014	2.068	0.04 **
Age (years)	−0.001	−0.130	0.897
Actual percentage of food waste	0.273	4.688	<0.001 ***

	Average Score	Standard Deviation	Minimum Score	Maximum Score
The respondent does not know how to combat food waste.	2.30	0.97	1	5
The employees do not know how to combat food waste.	2.41	0.90	1	5
The business environment does not know how to combat food waste.	2.54	0.92	1	5

Variable	Beta	T Value	Significance
Constant	2.164	12.627	<0.001
Respondent
Age (years)	−0.130	−1.131	0.260
Gender (female = 0; male = 1)	0.016	0.156	0.876
Education (low = 0; high = 1)	−0.008	−0.079	0.937
Function (active owner = 0; Other = 1)	0.081	0.782	0.435
Restaurant
Location (Amsterdam = 0; elsewhere = 1)	0.140	1.318	0.189
Type (casual dining = 0; other = 1)	0.122	1.147	0.253
Employees (number)	0.001	0.193	0.847
Age (years)	−0.002	−0.307	0.760
Actual percentage of food waste	0.251	4.909	<0.001 ***

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

Masurel, E.; van Montfort, K.; Nederhorst, A. How Do the Representatives of Small and Micro Restaurants Perceive Food Waste in Their Own Restaurant? Empirical Evidence from The Netherlands. Sustainability 2024 , 16 , 7820. https://doi.org/10.3390/su16177820

Masurel E, van Montfort K, Nederhorst A. How Do the Representatives of Small and Micro Restaurants Perceive Food Waste in Their Own Restaurant? Empirical Evidence from The Netherlands. Sustainability . 2024; 16(17):7820. https://doi.org/10.3390/su16177820

Masurel, Enno, Kees van Montfort, and Anne Nederhorst. 2024. "How Do the Representatives of Small and Micro Restaurants Perceive Food Waste in Their Own Restaurant? Empirical Evidence from The Netherlands" Sustainability 16, no. 17: 7820. https://doi.org/10.3390/su16177820

Article Metrics

Further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Empirical results (generation and value) from a unique Fixed Multi-Azimuth (Carousel) Solar Photovoltaic infrastructure based in the Arctic

Description.

The dataset consists of the solar photovoltaic (PV) energy generation information from a unique fixed multiple-azimuth research infrastructure equipped with solar PV panels in the four cardinal and four intercardinal directions at two distinct tilt angles, 40° and 90°. The dataset is of high importance mainly due to the location of the research infrastructure, which lies in the Arctic region that experiences unique weather conditions across all four seasons in a year. Secondly, the lack of empirical information on solar PV generation patterns in the area and scepticism surrounding the accuracy of solar modelling tools and satellite data in simulation make the dataset vital by validating and addressing gaps in the simulated tools and results. The dataset consists of two years of data, from September 2021 until August 2023. It features two main parameters from the study: the solar PV energy generation, which was collected at an interval of 15 minutes for two consecutive years, and the value of electricity at an hourly interval, generated by the panels facing the eight compass points derived with a combination of hourly day-ahead prices in Finland over the two selected years. The dataset further consists of "energy generated" and "value" of electricity generated by each panel, additionally divided into morning, afternoon, and evening hours to provide a detailed understanding of the energy and cost-efficient generation patterns across the eight compass points (four cardinal and four intercardinal directions). The abbreviations used in the datasets are as follows: South-S, Southwest-SW, West-W, Northwest-NW, North-N, Northeast-NE, East-E and Southeast-SE. These abbreviations are accompanied by 40 or 90, indicating the panel's tilt angles at 40° and 90°, respectively.

Institutions

Kvantum-instituutti, Oulun Yliopisto

IMAGES

Empirical Research: Definition, Methods, Types and Examples
What Is Empirical Research? Definition, Types & Samples in 2024
Empirical Evidence
What is empirical analysis and how does it work?
Definition, Types and Examples of Empirical Research
What Is Empirical Research? Definition, Types & Samples

VIDEO

The Empirical Reserch Article Screencast
Empirical Research with example
Empirical research methods
05 2015 How to do empirical research in Economics
TLDR: Keynote, Frequent Batch Auctions
Research-i Review

COMMENTS

Empirical Research: Definition, Methods, Types and Examples
Empirical Research: Definition, Methods, Types and ...
Empirical research
Empirical research
Results
The Results section provides the outcomes of the research process detailed in the Methods section. What Criteria to Look For. The Results section is where the authors talk about the primary data that has been collected and analyzed.Most articles will not have the complete, unanalyzed primary data, but instead have data that has already gone through some analysis for patterns, trends, and cause ...
Empirical Research: Defining, Identifying, & Finding
Empirical Research: Defining, Identifying, & Finding
Empirical Research in the Social Sciences and Education
Empirical Research in the Social Sciences and Education
Identifying Empirical Research Articles
An empirical research article reports the results of a study that uses data derived from actual observation or experimentation. Empirical research articles are examples of primary research. To learn more about the differences between primary and secondary research, see our related guide:
Empirical Research
This book introduces readers to methods and strategies for research and provides them with enough knowledge to become discerning, confident consumers of research in writing. Topics covered include: library research, empirical methodology, quantitative research, experimental research, surveys, focus groups, ethnographies, and much more.
How to Write a Methodology and Results Section for Empirical Research
when developing a dataset, results, and conclusions in an empirical research study. Therefore, the methodology section should contain four key elements: 1) the data collection procedures, 2) study ...
Empirical Research
The term "empirical" entails gathered data based on experience, observations, or experimentation. In empirical research, knowledge is developed from factual experience as opposed to theoretical assumption and usually involved the use of data sources like datasets or fieldwork, but can also be based on observations within a laboratory setting.
Empirical Research: What is Empirical Research?
Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather ... 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 ...
Empirical Research: A Comprehensive Guide for Academics
Tips for Empirical Writing. In empirical research, the writing is usually done in research papers, articles, or reports. The empirical writing follows a set structure, and each section has a specific role. Here are some tips for your empirical writing. 7. Define Your Objectives: When you write about your research, start by making your goals clear.
PDF Results/Findings Sections for Empirical Research Papers
Results/Findings Sections for Empirical Research Papers
What is Empirical Research? Definition, Methods, Examples
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.
Empirical evidence: A definition
Empirical research is the process of finding empirical evidence. Empirical data is the information that comes from the research. ... which could skew the results. The recording of empirical data ...
Empirical Research
Empirical & Non-Empirical Research
What Is Empirical Research? Definition, Types & Samples in 2024
What Is Empirical Research? Definition, Types & Samples ...
Identifying Empirical Research
Many scholarly, peer-reviewed journal articles, especially empirical articles, are structured according to the IMRaD layout. IMRaD stands for "Introduction, Methods, Results, and Discussion." These are the major sections of the article, and each part has an important role: Introduction: explains the research project and why it is needed.
PDF Empirical Research Papers
Empirical researchers observe, measure, record, and analyze data with the goal of generating knowledge. Empirical research may explore, describe, or explain behaviors or phenomena in humans, animals, or the natural world. It may use any number of quantitative or qualitative methods, ranging from laboratory experiments to surveys to artifact ...
The Empirical Research Paper: A Guide
Then compare your results to the literature that you referenced in your introduction section and to other research that has been conducted. In this section you will also want to address the generalizability and potential limitations of your study. Finally it is often recommended that a section on future research directions be included in your ...
Empirical Research: What is empirical research?
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 ...
Identifying & Finding Empirical Articles
Definition of an empirical study: An empirical research article reports the results of a study that uses data derived from actual observation or experimentation. Empirical research articles are examples of primary research. Parts of a standard empirical research article: (articles will not necessary use the exact terms listed below.) Abstract...
Empirical Research
The overall objective of this chapter is to introduce empirical research. More specifically, the objectives are: (1) to introduce and discuss a decision-making structure for selecting an appropriate research approach, (2) to compare a selection of the introduced research methodologies and methods, and (3) to discuss how different research methodologies and research methods can be used in ...
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. ... sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies << Previous: Home; Next: ...
Empirical Research: Defining, Identifying, & Finding
If you aren't sure what is and is not empirical research, this might seem scary. We are here to help. Note: while this guide is designed to help you understand and find empirical research, you should always default to your instructor's definition if they provide one and direct any specific questions about whether a source fits that definition ...
The Need for Localized, Socio-economic Policy Measures for Controlling
A pertinent research question relates to the debate of whether a localized lockdown could have partially averted the adverse economic outcomes of a national lockdown. ... Our article consolidates all the earlier findings into a robust empirical framework. We also introduce some new variables related to socio-economic behaviours (e.g., access to ...
Sustainability
The dispersion in results was also caused by the period of research (going back even as far as to 2014); the use of studies from different continents, focusing on different institutions; the use of different measurement methods; and the use of different terminologies.
Empirical results (generation and value) from a unique Fixed Multi
The dataset consists of the solar photovoltaic (PV) energy generation information from a unique fixed multiple-azimuth research infrastructure equipped with solar PV panels in the four cardinal and four intercardinal directions at two distinct tilt angles, 40° and 90°. The dataset is of high importance mainly due to the location of the research infrastructure, which lies in the Arctic region ...

Empirical Research: Definition, Methods, Types and Examples

Empirical research: Definition

Types and methodologies of empirical research

MORE LIKE THIS

Experimental vs Observational Studies: Differences & Examples

Interactive Forms: Key Features, Benefits, Uses + Design Tips

Closed-Loop Management: The Key to Customer Centricity

Net Trust Score: Tool for Measuring Trust in Organization

Other categories

Penn State University Libraries

Contact the Librarian at your campus for more help!

Introduction: What is Empirical Research?

Reading and Evaluating Scholarly Materials

Identifying Empirical Research Articles

What is Empirical Research?

Parts of an Empirical Research Article

Introduction

Results

Learn the IMRaD Layout: How to Identify an Empirical Article

Research: Overview & Approaches

Introduction to Empirical Research

Your Librarian

Empirical Research: What is Empirical Research?

Introduction

Empirical Research: A Comprehensive Guide for Academics

Why Empirical Research?

Qualitative and Quantitative Methods

Steps for Conducting Empirical Research

Advantages of Empirical Research

Disadvantages of Empirical Research

Tips for Empirical Writing

Related Reads:

Ethics in Science: Importance, Principles & Guidelines

What is Empirical Research? Definition, Methods, Examples

What is Empirical Research?

Characteristics of Empirical Research

Importance of Empirical Research

How to Conduct Empirical Research?

1. Select a Research Topic

2. Formulate Research Questions

3. Review Existing Literature

4. Define Variables

Empirical Research Design

Types of Empirical Research

Experimental Design

Observational Design

Survey Design

Case Study Design

Qualitative vs. Quantitative Research

Data Collection for Empirical Research

Sampling Methods

Data Collection Instruments

Data Collection Procedures

Ethical Considerations

Empirical Research Data Analysis

Data Preparation

Descriptive Statistics

Inferential Statistics

Qualitative Data Analysis

Data Visualization

How to Report Empirical Research Results?

1. Write the Research Paper

2. Create Visuals and Tables

3. Interpret Findings

Examples of Empirical Research

Social Sciences

Environmental Science

Business and Economics

Conclusion for Empirical Research

How to Collect Data for Empirical Research?

Wait, there's more

Empirical evidence: A definition

The scientific method

Sign up for the Live Science daily newsletter now

Most Popular

Empirical & Non-Empirical Research

Introduction: What is Empirical Research?

Quantitative Research

Qualitative Research

Empirical Research: What is empirical research?