research papers on questionnaire

Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire

Taherdoost, H. (2022). Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire, Asian Journal of Managerial Science, 11(1): 8-16. DOI: https://doi.org/10.51983/ajms-2022.11.1.3087

Posted: 5 Dec 2022

Hamed Taherdoost

Hamta Group

Date Written: August 1, 2022

A questionnaire is an important instrument in a research study to help the researcher collect relevant data regarding the research topic. It is significant to ensure that the design of the questionnaire is arranged to minimize errors. However, researchers commonly face challenges in designing an effective questionnaire including its content, appearance and usage that leads to inappropriate and biased findings in a study. This paper aims to review the main steps to design a questionnaire introducing the process that starts with defining the information required for a study, then continues with the identification of the type of survey and types of questions, writing questions and building the construct of the questionnaire. It also develops the demand to pre-test the questionnaire and finalizing the questionnaire to conduct the survey.

Keywords: Questionnaire, Academic Survey, Questionnaire Design, Research Methodology

Suggested Citation: Suggested Citation

Hamed Taherdoost (Contact Author)

Hamta group ( email ).

Vancouver Canada

Do you have a job opening that you would like to promote on SSRN?

Paper statistics, related ejournals, social sciences education ejournal.

Subscribe to this fee journal for more curated articles on this topic

Libraries & Media eJournal

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire

A questionnaire is an important instrument in a research study to help the researcher collect relevant data regarding the research topic. It is significant to ensure that the design of the questionnaire is arranged to minimize errors. However, researchers commonly face challenges in designing an effective questionnaire including its content, appearance and usage that leads to inappropriate and biased findings in a study. This paper aims to review the main steps to design a questionnaire introducing the process that starts with defining the information required for a study, then continues with the identification of the type of survey and types of questions, writing questions and building the construct of the questionnaire. It also develops the demand to pre-test the questionnaire and finalizing the questionnaire to conduct the survey.

Related Papers

Innovations in Measuring and Evaluating Scientific Information

Rayees Farooq

Indian Journal of Anaesthesia

Narayana Yaddanapudi

Edrine Wanyama

Questionnaire construction has overtime evolved with consistency and rarely, it has been skipped in the world’s researches. Questionnaires form the basis for which most pieces of information can be obtained. In the very light, response rates to questions and accuracy of data findings are possible through the use of questionnaire usage. Where a questionnaire is poorly constructed, one faces the risk of missing out vital information which could be forming the basis for research. This paper discusses the relevance and importance of questionnaire construction in data collection and research. An attempt is made to show questionnaire usage in social research and other research processes. Ultimately, questionnaire construction is considered just as important as any other research process used while collecting data. Some key recommendations that could make questionnaire usage in research better are also briefly considered.

Trisha Greenhalgh

Abla BENBELLAL

International Dental & Medical Journal of Advanced Research - VOLUME 2015

Saumya Dubey

Ebenezer Consultan

International Journal of Market Research

Petra Lietz

Some consider responding to survey questions as a sophisticated cognitive process whereby respondents go through, often iterative, steps to process the information provided to them by questions and response options. Others focus more on the interplay between questions and answers as a complex communication process between researchers and respondents, their assumptions, expectations and perceptions. In this article, cognitive and communication research is reviewed that has tested the impact of different question and answer alternatives on the responses obtained. This leads to evidence-based recommendations for market researchers, who frequently have to make decisions regarding various aspects of questionnaire design such as question length and order, question wording, as well as the optimal number of response options and the desirability or otherwise of a ‘don't know’ option or a middle alternative.

Journal of Family Planning and Reproductive Health Care

Gill Wakley

Daniela Garcia

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

De Wet Schutte

Lyberg/Survey

Norbert Schwarz

International Statistical Review

massimo borelli

Health Information & Libraries Journal

Andrew Booth

Nursing Times Research

michael kirk-smith

Petra Boynton

Market Research Society. Journal.

Zenodo (CERN European Organization for Nuclear Research)

Mohamad Adam Bujang

Medical Teacher

Anthony Artino

Jiayi Zhang

Sallie Newell

Health technology assessment (Winchester, England)

Lois Thomas , Claire Bamford , E. McColl

Burcu Akhun

International Journal of Assessment Tools in Education

Betty Adams

Jason Harlacher

Clinical Nurse Specialist

Sandra Siedlecki

Otolaryngology–Head and Neck Surgery

Randal Paniello

Nipuni Rangika

André Pereira

Biometrics & Biostatistics International Journal

Prof. Dr. İlker Etikan

International Journal of Management, Technology, and Social Sciences (IJMTS)

Srinivas Publication , Sreeramana Aithal

Zurina Saaya

Amanda Hunn

Anco Hundepool

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• How it works

Qualitative Research Questionnaire – Types & Examples

Published by Alvin Nicolas at August 19th, 2024 , Revised On August 20, 2024

Before you start your research, the first thing you need to identify is the research method . Depending on different factors, you will either choose a quantitative or qualitative study.

Qualitative research is a great tool that helps understand the depth and richness of human opinions and experiences. Unlike quantitative research, which focuses on numerical data , qualitative research allows exploring and interpreting the experiences of the subject. Questionnaires, although mostly associated with quantitative research, can also be a valuable instrument in qualitative studies. Let’s explore what qualitative research questionnaires are and how you can create one.

What Is A Qualitative Research Questionnaire

Qualitative research questionnaires are a structured or semi-structured set of questions designed to gather detailed, open-ended participant responses. It allows you to uncover underlying reasons and opinions and provides insights into a particular phenomenon.

While quantitative questionnaires often have closed-ended questions and numerical responses, a qualitative questionnaire encourages participants to express themselves freely. Before you design your questionnaire, you should know exactly what you need so you can keep your questions specific enough for the participants to understand.

For example:

• Describe your experience using our product.
• How has technology impacted your work-life balance?

Types of Qualitative Research Questions With Examples

Now that you are familiar with what qualitative research questions are, let’s look at the different types of questions you can use in your survey .

Descriptive Questions

These are used to explore and describe a phenomenon in detail. It helps answer the “what” part of the research, and the questions are mostly foundational.

Example: How do students experience online learning?

Comparative Questions

This type allows you to compare and contrast different groups or situations. You can explore the differences and similarities to highlight the impact of specific variables.

Example: How do the study habits of first-year and fourth-year university students differ?

Interpretive Questions

These questions help you understand the meanings people attach to experiences or phenomena by answering the “how” and “why”.

Example: What does “success” mean to entrepreneurs?

Evaluative Questions

You can use these to assess the quality or value of something. These allow you to understand the outcomes of various situations.

Example: How effective is the new customer service training program?

Process-Oriented Questions

To understand how something happens or develops over time, researchers often use process-oriented questions.

Example: How do individuals develop their career goals?

Exploratory Questions

These allow you to discover new perspectives on a topic. However, you have to be careful that there must be no preconceived notions or research biases to it.

Example: What are the emerging trends in the mobile gaming industry?

How To Write Qualitative Research Questions?

For your study to be successful, it is important to consider designing a questionnaire for qualitative research critically, as it will shape your research and data collection. Here is an easy guide to writing your qualitative research questions perfectly.

Tip 1: Understand Your Research Goals

Many students start their research without clear goals, and they have to make substantial changes to their study in the middle of the research. This wastes time and resources.

Before you start crafting your questions, it is important to know your research objectives. You should know what you aim to discover through your research, or what specific knowledge gaps you are going to fill. With the help of a well-defined research focus, you can develop relevant and meaningful information.

Tip 2: Choose The Structure For Research Questions

There are mostly open-ended questionnaires in qualitative research. They begin with words like “how,” “what,” and “why.” However, the structure of your research questions depends on your research design . You have to consider using broad, overarching questions to explore the main research focus, and then add some specific probes to further research the particular aspects of the topic.

Tip 3: Use Clear Language

The more clear and concise your research questions are, the more effective and free from ambiguity they will be. Do not use complex terminology that might confuse participants. Try using simple and direct language that accurately conveys your intended meaning.

Here is a table to explain the wrong and right ways of writing your qualitative research questions.

Tip 4: Check Relevance With Research Goals

Once you have developed some questions, check if they align with your research objectives. You must ensure that each question contributes to your overall research questions. After this, you can eliminate any questions that do not serve a clear purpose in your study.

Tip 5: Concentrate On A Single Theme

While it is tempting to cover multiple aspects of a topic in one question, it is best to focus on a single theme per question. This helps to elicit focused responses from participants. Moreover, you have to avoid combining unrelated concepts into a single question.

If your main research question is complicated, you can create sub-questions with a “ladder structure”. These allow you to understand the attributes, consequences, and core values of your research. For example, let’s say your main broad research question is:

• How do you feel about your overall experience with our company?

The intermediate questions may be:

• What aspects of your experience were positive?
• What aspects of your experience were negative?
• How likely are you to recommend our company to a friend or colleague?

Types Of Survey Questionnaires In Qualitative Research

It is important to consider your research objectives, target population, resources and needed depth of research when selecting a survey method. The main types of qualitative surveys are discussed below.

Face To Face Surveys

Face-to-face surveys involve direct interaction between the researcher and the participant. This method allows observers to capture non-verbal cues, body language, and facial expressions, and helps adapt questions based on participant responses. They also let you clarify any misunderstandings. Moreover, there is a higher response rate because of personal interaction.

Example: A researcher conducting a study on consumer experiences with a new product might visit participants’ homes to conduct a detailed interview.

Telephone Surveys

These type of qualitative research survey questionnaires provide a less intrusive method for collecting qualitative data. The benefits of telephone surveys include, that it allows you to collect data from a wider population. Moreover, it is generally less expensive than face-to-face interviews and interviews can be conducted efficiently.

Example: A market research firm might conduct telephone surveys to understand customer satisfaction with a telecommunication service.

Online Surveys

Online survey questionnaires are a convenient and cost-effective way to gather qualitative data. You can reach a wide audience quickly, and participants may feel more comfortable sharing sensitive information because of anonymity. Additionally, there are no travel or printing expenses.

Example: A university might use online surveys to explore students’ perceptions of online learning experiences.

Strengths & Limitations Of Questionnaires In Qualitative Research

Questionnaires are undoubtedly a great data collection tool. However, it comes with its fair share of advantages and disadvantages. Let’s discuss the benefits of questionnaires in qualitative research and their cons as well.

Qualitative Research Questionnaire Example

Here is a concise qualitative research questionnaire sample for research papers to give you a better idea of its format and how it is presented.

Thank you for participating in our survey. We value your feedback on our new mobile app. Your responses will help us improve the applications and better meet your needs.

Demographic Information

• Occupation:
• How long have you been using smartphones:
• How would you describe your overall experience with the new mobile app?
• What do you like most about the app?
• What do you dislike most about the app?
• Are there any specific features you find particularly useful or helpful? Please explain.
• Are there any features you think are missing or could be improved? Please elaborate.
• How easy is the app to navigate? Please explain any difficulties you encountered.
• How does this app compare to other similar apps you have used?
• What are your expectations for future updates or improvements to the app?
• Is there anything else you would like to share about your experience with the app?

Are questionnaires quantitative or qualitative research?

A survey research questionnaire can have both qualitative and quantitative questions. The qualitative questions are mostly open-ended, and quantitative questions take the form of yes/no, or Likert scale rating. 

Can we use questionnaires in qualitative research?

Yes, survey questionnaires can be used in qualitative research for data collection. However, instead of a Likert scale or rating, you can post open-ended questions to your respondents. The participants can provide detailed responses to the questions asked.

Why are questionnaires good for qualitative research?

In qualitative research, questionnaires allow you to collect qualitative data. The open-ended and unstructured questions help respondents present their ideas freely and provide insights. 

You May Also Like

Baffled by the concept of reliability and validity? Reliability refers to the consistency of measurement. Validity refers to the accuracy of measurement.

In historical research, a researcher collects and analyse the data, and explain the events that occurred in the past to test the truthfulness of observations.

This post provides the key disadvantages of secondary research so you know the limitations of secondary research before making a decision.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

• Privacy Policy

Home » Questionnaire – Definition, Types, and Examples

Questionnaire – Definition, Types, and Examples

Table of Contents

Questionnaire

Definition:

A Questionnaire is a research tool or survey instrument that consists of a set of questions or prompts designed to gather information from individuals or groups of people.

It is a standardized way of collecting data from a large number of people by asking them a series of questions related to a specific topic or research objective. The questions may be open-ended or closed-ended, and the responses can be quantitative or qualitative. Questionnaires are widely used in research, marketing, social sciences, healthcare, and many other fields to collect data and insights from a target population.

History of Questionnaire

The history of questionnaires can be traced back to the ancient Greeks, who used questionnaires as a means of assessing public opinion. However, the modern history of questionnaires began in the late 19th century with the rise of social surveys.

The first social survey was conducted in the United States in 1874 by Francis A. Walker, who used a questionnaire to collect data on labor conditions. In the early 20th century, questionnaires became a popular tool for conducting social research, particularly in the fields of sociology and psychology.

One of the most influential figures in the development of the questionnaire was the psychologist Raymond Cattell, who in the 1940s and 1950s developed the personality questionnaire, a standardized instrument for measuring personality traits. Cattell’s work helped establish the questionnaire as a key tool in personality research.

In the 1960s and 1970s, the use of questionnaires expanded into other fields, including market research, public opinion polling, and health surveys. With the rise of computer technology, questionnaires became easier and more cost-effective to administer, leading to their widespread use in research and business settings.

Today, questionnaires are used in a wide range of settings, including academic research, business, healthcare, and government. They continue to evolve as a research tool, with advances in computer technology and data analysis techniques making it easier to collect and analyze data from large numbers of participants.

Types of Questionnaire

Types of Questionnaires are as follows:

Structured Questionnaire

This type of questionnaire has a fixed format with predetermined questions that the respondent must answer. The questions are usually closed-ended, which means that the respondent must select a response from a list of options.

Unstructured Questionnaire

An unstructured questionnaire does not have a fixed format or predetermined questions. Instead, the interviewer or researcher can ask open-ended questions to the respondent and let them provide their own answers.

Open-ended Questionnaire

An open-ended questionnaire allows the respondent to answer the question in their own words, without any pre-determined response options. The questions usually start with phrases like “how,” “why,” or “what,” and encourage the respondent to provide more detailed and personalized answers.

Close-ended Questionnaire

In a closed-ended questionnaire, the respondent is given a set of predetermined response options to choose from. This type of questionnaire is easier to analyze and summarize, but may not provide as much insight into the respondent’s opinions or attitudes.

Mixed Questionnaire

A mixed questionnaire is a combination of open-ended and closed-ended questions. This type of questionnaire allows for more flexibility in terms of the questions that can be asked, and can provide both quantitative and qualitative data.

Pictorial Questionnaire:

In a pictorial questionnaire, instead of using words to ask questions, the questions are presented in the form of pictures, diagrams or images. This can be particularly useful for respondents who have low literacy skills, or for situations where language barriers exist. Pictorial questionnaires can also be useful in cross-cultural research where respondents may come from different language backgrounds.

Types of Questions in Questionnaire

The types of Questions in Questionnaire are as follows:

Multiple Choice Questions

These questions have several options for participants to choose from. They are useful for getting quantitative data and can be used to collect demographic information.

• a. Red b . Blue c. Green d . Yellow

Rating Scale Questions

These questions ask participants to rate something on a scale (e.g. from 1 to 10). They are useful for measuring attitudes and opinions.

• On a scale of 1 to 10, how likely are you to recommend this product to a friend?

Open-Ended Questions

These questions allow participants to answer in their own words and provide more in-depth and detailed responses. They are useful for getting qualitative data.

• What do you think are the biggest challenges facing your community?

Likert Scale Questions

These questions ask participants to rate how much they agree or disagree with a statement. They are useful for measuring attitudes and opinions.

How strongly do you agree or disagree with the following statement:

“I enjoy exercising regularly.”

• a . Strongly Agree
• c . Neither Agree nor Disagree
• d . Disagree
• e . Strongly Disagree

Demographic Questions

These questions ask about the participant’s personal information such as age, gender, ethnicity, education level, etc. They are useful for segmenting the data and analyzing results by demographic groups.

• What is your age?

Yes/No Questions

These questions only have two options: Yes or No. They are useful for getting simple, straightforward answers to a specific question.

Have you ever traveled outside of your home country?

Ranking Questions

These questions ask participants to rank several items in order of preference or importance. They are useful for measuring priorities or preferences.

Please rank the following factors in order of importance when choosing a restaurant:

• a. Quality of Food
• c. Ambiance
• d. Location

Matrix Questions

These questions present a matrix or grid of options that participants can choose from. They are useful for getting data on multiple variables at once.

Dichotomous Questions

These questions present two options that are opposite or contradictory. They are useful for measuring binary or polarized attitudes.

Do you support the death penalty?

How to Make a Questionnaire

Step-by-Step Guide for Making a Questionnaire:

• Define your research objectives: Before you start creating questions, you need to define the purpose of your questionnaire and what you hope to achieve from the data you collect.
• Choose the appropriate question types: Based on your research objectives, choose the appropriate question types to collect the data you need. Refer to the types of questions mentioned earlier for guidance.
• Develop questions: Develop clear and concise questions that are easy for participants to understand. Avoid leading or biased questions that might influence the responses.
• Organize questions: Organize questions in a logical and coherent order, starting with demographic questions followed by general questions, and ending with specific or sensitive questions.
• Pilot the questionnaire : Test your questionnaire on a small group of participants to identify any flaws or issues with the questions or the format.
• Refine the questionnaire : Based on feedback from the pilot, refine and revise the questionnaire as necessary to ensure that it is valid and reliable.
• Distribute the questionnaire: Distribute the questionnaire to your target audience using a method that is appropriate for your research objectives, such as online surveys, email, or paper surveys.
• Collect and analyze data: Collect the completed questionnaires and analyze the data using appropriate statistical methods. Draw conclusions from the data and use them to inform decision-making or further research.
• Report findings: Present your findings in a clear and concise report, including a summary of the research objectives, methodology, key findings, and recommendations.

Questionnaire Administration Modes

There are several modes of questionnaire administration. The choice of mode depends on the research objectives, sample size, and available resources. Some common modes of administration include:

• Self-administered paper questionnaires: Participants complete the questionnaire on paper, either in person or by mail. This mode is relatively low cost and easy to administer, but it may result in lower response rates and greater potential for errors in data entry.
• Online questionnaires: Participants complete the questionnaire on a website or through email. This mode is convenient for both researchers and participants, as it allows for fast and easy data collection. However, it may be subject to issues such as low response rates, lack of internet access, and potential for fraudulent responses.
• Telephone surveys: Trained interviewers administer the questionnaire over the phone. This mode allows for a large sample size and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Face-to-face interviews : Trained interviewers administer the questionnaire in person. This mode allows for a high degree of control over the survey environment and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Mixed-mode surveys: Researchers use a combination of two or more modes to administer the questionnaire, such as using online questionnaires for initial screening and following up with telephone interviews for more detailed information. This mode can help overcome some of the limitations of individual modes, but it requires careful planning and coordination.

Example of Questionnaire

Title of the Survey: Customer Satisfaction Survey

Introduction:

We appreciate your business and would like to ensure that we are meeting your needs. Please take a few minutes to complete this survey so that we can better understand your experience with our products and services. Your feedback is important to us and will help us improve our offerings.

Instructions:

Please read each question carefully and select the response that best reflects your experience. If you have any additional comments or suggestions, please feel free to include them in the space provided at the end of the survey.

1. How satisfied are you with our product quality?

• Very satisfied
• Somewhat satisfied
• Somewhat dissatisfied
• Very dissatisfied

2. How satisfied are you with our customer service?

3. How satisfied are you with the price of our products?

4. How likely are you to recommend our products to others?

• Very likely
• Somewhat likely
• Somewhat unlikely
• Very unlikely

5. How easy was it to find the information you were looking for on our website?

• Somewhat easy
• Somewhat difficult
• Very difficult

6. How satisfied are you with the overall experience of using our products and services?

7. Is there anything that you would like to see us improve upon or change in the future?

…………………………………………………………………………………………………………………………..

Conclusion:

Thank you for taking the time to complete this survey. Your feedback is valuable to us and will help us improve our products and services. If you have any further comments or concerns, please do not hesitate to contact us.

Applications of Questionnaire

Some common applications of questionnaires include:

• Research : Questionnaires are commonly used in research to gather information from participants about their attitudes, opinions, behaviors, and experiences. This information can then be analyzed and used to draw conclusions and make inferences.
• Healthcare : In healthcare, questionnaires can be used to gather information about patients’ medical history, symptoms, and lifestyle habits. This information can help healthcare professionals diagnose and treat medical conditions more effectively.
• Marketing : Questionnaires are commonly used in marketing to gather information about consumers’ preferences, buying habits, and opinions on products and services. This information can help businesses develop and market products more effectively.
• Human Resources: Questionnaires are used in human resources to gather information from job applicants, employees, and managers about job satisfaction, performance, and workplace culture. This information can help organizations improve their hiring practices, employee retention, and organizational culture.
• Education : Questionnaires are used in education to gather information from students, teachers, and parents about their perceptions of the educational experience. This information can help educators identify areas for improvement and develop more effective teaching strategies.

Purpose of Questionnaire

Some common purposes of questionnaires include:

• To collect information on attitudes, opinions, and beliefs: Questionnaires can be used to gather information on people’s attitudes, opinions, and beliefs on a particular topic. For example, a questionnaire can be used to gather information on people’s opinions about a particular political issue.
• To collect demographic information: Questionnaires can be used to collect demographic information such as age, gender, income, education level, and occupation. This information can be used to analyze trends and patterns in the data.
• To measure behaviors or experiences: Questionnaires can be used to gather information on behaviors or experiences such as health-related behaviors or experiences, job satisfaction, or customer satisfaction.
• To evaluate programs or interventions: Questionnaires can be used to evaluate the effectiveness of programs or interventions by gathering information on participants’ experiences, opinions, and behaviors.
• To gather information for research: Questionnaires can be used to gather data for research purposes on a variety of topics.

When to use Questionnaire

Here are some situations when questionnaires might be used:

• When you want to collect data from a large number of people: Questionnaires are useful when you want to collect data from a large number of people. They can be distributed to a wide audience and can be completed at the respondent’s convenience.
• When you want to collect data on specific topics: Questionnaires are useful when you want to collect data on specific topics or research questions. They can be designed to ask specific questions and can be used to gather quantitative data that can be analyzed statistically.
• When you want to compare responses across groups: Questionnaires are useful when you want to compare responses across different groups of people. For example, you might want to compare responses from men and women, or from people of different ages or educational backgrounds.
• When you want to collect data anonymously: Questionnaires can be useful when you want to collect data anonymously. Respondents can complete the questionnaire without fear of judgment or repercussions, which can lead to more honest and accurate responses.
• When you want to save time and resources: Questionnaires can be more efficient and cost-effective than other methods of data collection such as interviews or focus groups. They can be completed quickly and easily, and can be analyzed using software to save time and resources.

Characteristics of Questionnaire

Here are some of the characteristics of questionnaires:

• Standardization : Questionnaires are standardized tools that ask the same questions in the same order to all respondents. This ensures that all respondents are answering the same questions and that the responses can be compared and analyzed.
• Objectivity : Questionnaires are designed to be objective, meaning that they do not contain leading questions or bias that could influence the respondent’s answers.
• Predefined responses: Questionnaires typically provide predefined response options for the respondents to choose from, which helps to standardize the responses and make them easier to analyze.
• Quantitative data: Questionnaires are designed to collect quantitative data, meaning that they provide numerical or categorical data that can be analyzed using statistical methods.
• Convenience : Questionnaires are convenient for both the researcher and the respondents. They can be distributed and completed at the respondent’s convenience and can be easily administered to a large number of people.
• Anonymity : Questionnaires can be anonymous, which can encourage respondents to answer more honestly and provide more accurate data.
• Reliability : Questionnaires are designed to be reliable, meaning that they produce consistent results when administered multiple times to the same group of people.
• Validity : Questionnaires are designed to be valid, meaning that they measure what they are intended to measure and are not influenced by other factors.

Advantage of Questionnaire

Some Advantage of Questionnaire are as follows:

• Standardization: Questionnaires allow researchers to ask the same questions to all participants in a standardized manner. This helps ensure consistency in the data collected and eliminates potential bias that might arise if questions were asked differently to different participants.
• Efficiency: Questionnaires can be administered to a large number of people at once, making them an efficient way to collect data from a large sample.
• Anonymity: Participants can remain anonymous when completing a questionnaire, which may make them more likely to answer honestly and openly.
• Cost-effective: Questionnaires can be relatively inexpensive to administer compared to other research methods, such as interviews or focus groups.
• Objectivity: Because questionnaires are typically designed to collect quantitative data, they can be analyzed objectively without the influence of the researcher’s subjective interpretation.
• Flexibility: Questionnaires can be adapted to a wide range of research questions and can be used in various settings, including online surveys, mail surveys, or in-person interviews.

Limitations of Questionnaire

Limitations of Questionnaire are as follows:

• Limited depth: Questionnaires are typically designed to collect quantitative data, which may not provide a complete understanding of the topic being studied. Questionnaires may miss important details and nuances that could be captured through other research methods, such as interviews or observations.
• R esponse bias: Participants may not always answer questions truthfully or accurately, either because they do not remember or because they want to present themselves in a particular way. This can lead to response bias, which can affect the validity and reliability of the data collected.
• Limited flexibility: While questionnaires can be adapted to a wide range of research questions, they may not be suitable for all types of research. For example, they may not be appropriate for studying complex phenomena or for exploring participants’ experiences and perceptions in-depth.
• Limited context: Questionnaires typically do not provide a rich contextual understanding of the topic being studied. They may not capture the broader social, cultural, or historical factors that may influence participants’ responses.
• Limited control : Researchers may not have control over how participants complete the questionnaire, which can lead to variations in response quality or consistency.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Ethnographic Research -Types, Methods and Guide

Quasi-Experimental Research Design – Types...

Applied Research – Types, Methods and Examples

Experimental Design – Types, Methods, Guide

Focus Groups – Steps, Examples and Guide

Mixed Methods Research – Types & Analysis

• PRO Courses Guides New Tech Help Pro Expert Videos About wikiHow Pro Upgrade Sign In
• EDIT Edit this Article
• EXPLORE Tech Help Pro About Us Random Article Quizzes Request a New Article Community Dashboard This Or That Game Happiness Hub Popular Categories Arts and Entertainment Artwork Books Movies Computers and Electronics Computers Phone Skills Technology Hacks Health Men's Health Mental Health Women's Health Relationships Dating Love Relationship Issues Hobbies and Crafts Crafts Drawing Games Education & Communication Communication Skills Personal Development Studying Personal Care and Style Fashion Hair Care Personal Hygiene Youth Personal Care School Stuff Dating All Categories Arts and Entertainment Finance and Business Home and Garden Relationship Quizzes Cars & Other Vehicles Food and Entertaining Personal Care and Style Sports and Fitness Computers and Electronics Health Pets and Animals Travel Education & Communication Hobbies and Crafts Philosophy and Religion Work World Family Life Holidays and Traditions Relationships Youth
• Browse Articles
• Learn Something New
• Quizzes Hot
• Happiness Hub
• This Or That Game
• Train Your Brain
• Explore More
• Support wikiHow
• About wikiHow
• Log in / Sign up
• Education and Communications

How to Develop a Questionnaire for Research

Last Updated: July 21, 2024 Fact Checked

This article was co-authored by Alexander Ruiz, M.Ed. . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. There are 12 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 593,712 times.

A questionnaire is a technique for collecting data in which a respondent provides answers to a series of questions. [1] X Research source To develop a questionnaire that will collect the data you want takes effort and time. However, by taking a step-by-step approach to questionnaire development, you can come up with an effective means to collect data that will answer your unique research question.

Designing Your Questionnaire

• Come up with a research question. It can be one question or several, but this should be the focal point of your questionnaire.
• Develop one or several hypotheses that you want to test. The questions that you include on your questionnaire should be aimed at systematically testing these hypotheses.

• Dichotomous question: this is a question that will generally be a “yes/no” question, but may also be an “agree/disagree” question. It is the quickest and simplest question to analyze, but is not a highly sensitive measure.
• Open-ended questions: these questions allow the respondent to respond in their own words. They can be useful for gaining insight into the feelings of the respondent, but can be a challenge when it comes to analysis of data. It is recommended to use open-ended questions to address the issue of “why.” [2] X Research source
• Multiple choice questions: these questions consist of three or more mutually-exclusive categories and ask for a single answer or several answers. [3] X Research source Multiple choice questions allow for easy analysis of results, but may not give the respondent the answer they want.
• Rank-order (or ordinal) scale questions: this type of question asks your respondent to rank items or choose items in a particular order from a set. For example, it might ask your respondents to order five things from least to most important. These types of questions forces discrimination among alternatives, but does not address the issue of why the respondent made these discriminations. [4] X Research source
• Rating scale questions: these questions allow the respondent to assess a particular issue based on a given dimension. You can provide a scale that gives an equal number of positive and negative choices, for example, ranging from “strongly agree” to “strongly disagree.” [5] X Research source These questions are very flexible, but also do not answer the question “why.”

• Write questions that are succinct and simple. You should not be writing complex statements or using technical jargon, as it will only confuse your respondents and lead to incorrect responses.
• Ask only one question at a time. This will help avoid confusion
• Asking questions such as these usually require you to anonymize or encrypt the demographic data you collect.
• Determine if you will include an answer such as “I don’t know” or “Not applicable to me.” While these can give your respondents a way of not answering certain questions, providing these options can also lead to missing data, which can be problematic during data analysis.
• Put the most important questions at the beginning of your questionnaire. This can help you gather important data even if you sense that your respondents may be becoming distracted by the end of the questionnaire.

• Only include questions that are directly useful to your research question. [8] X Trustworthy Source Food and Agricultural Organization of the United Nations Specialized agency of the United Nations responsible for leading international efforts to end world hunger and improve nutrition Go to source A questionnaire is not an opportunity to collect all kinds of information about your respondents.
• Avoid asking redundant questions. This will frustrate those who are taking your questionnaire.

• Consider if you want your questionnaire to collect information from both men and women. Some studies will only survey one sex.
• Consider including a range of ages in your target demographic. For example, you can consider young adult to be 18-29 years old, adults to be 30-54 years old, and mature adults to be 55+. Providing the an age range will help you get more respondents than limiting yourself to a specific age.
• Consider what else would make a person a target for your questionnaire. Do they need to drive a car? Do they need to have health insurance? Do they need to have a child under 3? Make sure you are very clear about this before you distribute your questionnaire.

• Consider an anonymous questionnaire. You may not want to ask for names on your questionnaire. This is one step you can take to prevent privacy, however it is often possible to figure out a respondent’s identity using other demographic information (such as age, physical features, or zipcode).
• Consider de-identifying the identity of your respondents. Give each questionnaire (and thus, each respondent) a unique number or word, and only refer to them using that new identifier. Shred any personal information that can be used to determine identity.
• Remember that you do not need to collect much demographic information to be able to identify someone. People may be wary to provide this information, so you may get more respondents by asking less demographic questions (if it is possible for your questionnaire).
• Make sure you destroy all identifying information after your study is complete.

Writing your questionnaire

• My name is Jack Smith and I am one of the creators of this questionnaire. I am part of the Department of Psychology at the University of Michigan, where I am focusing in developing cognition in infants.
• I’m Kelly Smith, a 3rd year undergraduate student at the University of New Mexico. This questionnaire is part of my final exam in statistics.
• My name is Steve Johnson, and I’m a marketing analyst for The Best Company. I’ve been working on questionnaire development to determine attitudes surrounding drug use in Canada for several years.

• I am collecting data regarding the attitudes surrounding gun control. This information is being collected for my Anthropology 101 class at the University of Maryland.
• This questionnaire will ask you 15 questions about your eating and exercise habits. We are attempting to make a correlation between healthy eating, frequency of exercise, and incidence of cancer in mature adults.
• This questionnaire will ask you about your recent experiences with international air travel. There will be three sections of questions that will ask you to recount your recent trips and your feelings surrounding these trips, as well as your travel plans for the future. We are looking to understand how a person’s feelings surrounding air travel impact their future plans.

• Beware that if you are collecting information for a university or for publication, you may need to check in with your institution’s Institutional Review Board (IRB) for permission before beginning. Most research universities have a dedicated IRB staff, and their information can usually be found on the school’s website.
• Remember that transparency is best. It is important to be honest about what will happen with the data you collect.
• Include an informed consent for if necessary. Note that you cannot guarantee confidentiality, but you will make all reasonable attempts to ensure that you protect their information. [11] X Research source

• Time yourself taking the survey. Then consider that it will take some people longer than you, and some people less time than you.
• Provide a time range instead of a specific time. For example, it’s better to say that a survey will take between 15 and 30 minutes than to say it will take 15 minutes and have some respondents quit halfway through.
• Use this as a reason to keep your survey concise! You will feel much better asking people to take a 20 minute survey than you will asking them to take a 3 hour one.

• Incentives can attract the wrong kind of respondent. You don’t want to incorporate responses from people who rush through your questionnaire just to get the reward at the end. This is a danger of offering an incentive. [12] X Research source
• Incentives can encourage people to respond to your survey who might not have responded without a reward. This is a situation in which incentives can help you reach your target number of respondents. [13] X Research source
• Consider the strategy used by SurveyMonkey. Instead of directly paying respondents to take their surveys, they offer 50 cents to the charity of their choice when a respondent fills out a survey. They feel that this lessens the chances that a respondent will fill out a questionnaire out of pure self-interest. [14] X Research source
• Consider entering each respondent in to a drawing for a prize if they complete the questionnaire. You can offer a 25$ gift card to a restaurant, or a new iPod, or a ticket to a movie. This makes it less tempting just to respond to your questionnaire for the incentive alone, but still offers the chance of a pleasant reward.

• Always proof read. Check for spelling, grammar, and punctuation errors.
• Include a title. This is a good way for your respondents to understand the focus of the survey as quickly as possible.
• Thank your respondents. Thank them for taking the time and effort to complete your survey.

Distributing Your Questionnaire

• Was the questionnaire easy to understand? Were there any questions that confused you?
• Was the questionnaire easy to access? (Especially important if your questionnaire is online).
• Do you feel the questionnaire was worth your time?
• Were you comfortable answering the questions asked?
• Are there any improvements you would make to the questionnaire?

• Use an online site, such as SurveyMonkey.com. This site allows you to write your own questionnaire with their survey builder, and provides additional options such as the option to buy a target audience and use their analytics to analyze your data. [18] X Research source
• Consider using the mail. If you mail your survey, always make sure you include a self-addressed stamped envelope so that the respondent can easily mail their responses back. Make sure that your questionnaire will fit inside a standard business envelope.
• Conduct face-to-face interviews. This can be a good way to ensure that you are reaching your target demographic and can reduce missing information in your questionnaires, as it is more difficult for a respondent to avoid answering a question when you ask it directly.
• Try using the telephone. While this can be a more time-effective way to collect your data, it can be difficult to get people to respond to telephone questionnaires.

• Make your deadline reasonable. Giving respondents up to 2 weeks to answer should be more than sufficient. Anything longer and you risk your respondents forgetting about your questionnaire.
• Consider providing a reminder. A week before the deadline is a good time to provide a gentle reminder about returning the questionnaire. Include a replacement of the questionnaire in case it has been misplaced by your respondent.

Community Q&A

You Might Also Like

• ↑ https://www.questionpro.com/blog/what-is-a-questionnaire/
• ↑ https://www.hotjar.com/blog/open-ended-questions/
• ↑ https://www.questionpro.com/a/showArticle.do?articleID=survey-questions
• ↑ https://surveysparrow.com/blog/ranking-questions-examples/
• ↑ https://www.lumoa.me/blog/rating-scale/
• ↑ http://www.sciencebuddies.org/science-fair-projects/project_ideas/Soc_survey.shtml
• ↑ http://www.fao.org/docrep/W3241E/w3241e05.htm
• ↑ http://managementhelp.org/businessresearch/questionaires.htm
• ↑ https://www.surveymonkey.com/mp/survey-rewards/
• ↑ http://www.ideafit.com/fitness-library/how-to-develop-a-questionnaire
• ↑ https://www.surveymonkey.com/mp/take-a-tour/?ut_source=header

About This Article

To develop a questionnaire for research, identify the main objective of your research to act as the focal point for the questionnaire. Then, choose the type of questions that you want to include, and come up with succinct, straightforward questions to gather the information that you need to answer your questions. Keep your questionnaire as short as possible, and identify a target demographic who you would like to answer the questions. Remember to make the questionnaires as anonymous as possible to protect the integrity of the person answering the questions! For tips on writing out your questions and distributing the questionnaire, keep reading! Did this summary help you? Yes No

• Send fan mail to authors

Reader Success Stories

Abdul Bari Khan

Nov 11, 2020

Did this article help you?

Jul 25, 2023

Iman Ilhusadi

Nov 26, 2016

Jaydeepa Das

Aug 21, 2018

Atefeh Abdollahi

Jan 3, 2017

Featured Articles

Trending Articles

Watch Articles

• Terms of Use
• Privacy Policy
• Do Not Sell or Share My Info
• Not Selling Info

Don’t miss out! Sign up for

wikiHow’s newsletter

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on 6 May 2022 by Pritha Bhandari . Revised on 10 October 2022.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs surveys, questionnaire methods, open-ended vs closed-ended questions, question wording, question order, step-by-step guide to design, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyse data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives, placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleaning and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalise your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimising these will help you avoid sampling bias .

Prevent plagiarism, run a free check.

Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

• Cost-effective
• Easy to administer for small and large groups
• Anonymous and suitable for sensitive topics

But they may also be:

• Unsuitable for people with limited literacy or verbal skills
• Susceptible to a nonreponse bias (most people invited may not complete the questionnaire)
• Biased towards people who volunteer because impersonal survey requests often go ignored

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents.

Researcher-administered questionnaires can:

• Help you ensure the respondents are representative of your target audience
• Allow clarifications of ambiguous or unclear questions and answers
• Have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

• Costly and time-consuming to perform
• More difficult to analyse if you have qualitative responses
• Likely to contain experimenter bias or demand characteristics
• Likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions, or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalisable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert-type questions collect ordinal data using rating scales with five or seven points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio data, you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer ‘multiracial’ for the question on race rather than selecting from a restricted list.

• How do you feel about open science?
• How would you describe your personality?
• In your opinion, what is the biggest obstacle to productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarising responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorise answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counterargument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

• The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favour flexible work-from-home policies even after it’s safe to return to offices?
• Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barrelled questions. Double-barrelled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organise the questions logically, with a clear progression from simple to complex. Alternatively, you can randomise the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioural or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

• How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
• Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
• Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimise order effects because they can be a source of systematic error or bias in your study.

Randomisation

Randomisation involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomisation, order effects will be minimised in your dataset. But a randomised order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Follow this step-by-step guide to design your questionnaire.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

• What topics or experiences are you studying?
• What specifically do you want to find out?
• Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalise your variables of interest into questionnaire items. Operationalising concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

• Are the respondents familiar with the language and terms used in your questions?
• Would any of the questions insult, confuse, or embarrass them?
• Do the response items for any closed-ended questions capture all possible answers?
• Are the response items mutually exclusive?
• Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivised or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomise questions. Randomising questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis.

You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Bhandari, P. (2022, October 10). Questionnaire Design | Methods, Question Types & Examples. Scribbr. Retrieved 9 September 2024, from https://www.scribbr.co.uk/research-methods/questionnaire-design/

Is this article helpful?

Pritha Bhandari

Other students also liked, doing survey research | a step-by-step guide & examples, what is a likert scale | guide & examples, reliability vs validity in research | differences, types & examples.

Publications by Topics

Explore science topics to find research in your field such as publications, questions, research projects, and methods.

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Research Questionnaire

Questionnaire generator.

When a researcher creates a research paper using the scientific method they will need to use a gathering method that is adjacent to the research topic. This means that the researcher will use a quantitative research method for a quantitive topic and a qualitative method for a qualitative  one.  The research questionnaire is one of the quantitative data-gathering methods a researcher can use in their research paper.

1. Market Research Questionnaire Template Example

• Google Docs
• Apple Pages

Size: 38 KB

2. Market Research Questionnaire Example

Size: 94 KB

3. Research Questionnaire Example

4. Sample Market Research Questionnaire

Size: 35 KB

5. Research Survey Questionnaire

Size: 42 KB

6. Research Survey Questionnaire Construction

Size: 80 KB

7. Research Questionnaire Survey of Consumers

Size: 39 KB

8. Guide to the Design of Research Questionnaires

Size: 77 KB

9. Planning Survey Research Questionnaires

Size: 85 KB

10. Climate Change Survey Questionnaires

Size: 41 KB

11. Survey Questionnaire Design

Size: 96 KB

12. Developing Questionnaires for Educational Research

Size: 81 KB

13. Graudate Research Student Questionnaires

14. Sample Research Survey Questionnaires

Size: 46 KB

15. Market Research Questionnaire Example

16. Research Survey Questionnaire Example

17. Product X Research Study Questionnaire Example

What Is a Research Questionnaire?

A research questionnaire is a physical or digital questionnaire that researchers use to obtain quantitative data. The research questionnaire is a more in-depth version of a survey   as its questions often delve deeper than survey questions .

How to Write a Research Questionnaire

A well-made research questionnaire can effectively and efficiently gather data from the population. Creating a good research questionnaire does not require that many writing skills , soft skills , or hard skills , it just requires the person to properly understand the data set they are looking for.

Step 1: Select a Topic or Theme for the Research Questionnaire

Begin by choosing a topic or theme   for the research questionnaire as this will provide much-needed context for the research questionnaire. Not only that but the topic will also dictate the tone of the questions in the questionnaire.

Step 2: Obtain or Use a Research Questionnaire Outline

You may opt to use a research questionnaire outline or outline format for your research questionnaire. This outline will provide you with a structure you can use to easily make your research questionnaire.

Step 3: Create your Research Questionnaire

Start by creating questions that will help provide you with the necessary data to prove or disprove your research question. You may conduct brainstorming sessions to formulate the questions for your research questionnaire.

Step 4: Edit and Have Someone Proofread the Questionnaire

After you have created and completed the research questionnaire, you must edit the contents of the questionnaire. Not only that but it is wise to have someone proofread the contents of your questionnaire before deploying the questionnaire. 

How does a research questionnaire help businesses?

A successful business or company utilizes research questionnaires to not only obtain data from their customers but also to gather data about the performance and quality of the employees in the business. The research questionnaire provides the business or company with actionable data, which they can use to improve the product, service, or commodity to obtain more customers.

Do I need to provide a consent form when I ask someone to answer the research questionnaire?

Yes, consent is very important as without this the data you have gathered from your questionnaires or surveys are useless. Therefore it is important to provide a consent form with your research questionnaire when you are asking a participant to answer the document.

What type of answers are allowed in the research questionnaire?

Research questionnaires can host a multitude of types of questions each with its specific way of answering.  A questionnaire can use multiple-choice questions, open-ended questions, and closed questions. Just be sure to properly pace the questions as having too many different types of answering styles can demotivate or distract the target audience, which might lead to errors.

A research questionnaire is a data-gathering document people can use to obtain information and data from a specific group of people. Well-made and crafted research questionnaires will provide much-needed information one can use to answer a specific research question.

Text prompt

• Instructive
• Professional

Create a fun quiz to find out which historical figure you're most like in your study habits

Design a survey to discover students' favorite school subjects and why they love them.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• Survey Research | Definition, Examples & Methods

Survey Research | Definition, Examples & Methods

Published on August 20, 2019 by Shona McCombes . Revised on June 22, 2023.

Survey research means collecting information about a group of people by asking them questions and analyzing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyze the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyze the survey results, step 6: write up the survey results, other interesting articles, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research : investigating the experiences and characteristics of different social groups
• Market research : finding out what customers think about products, services, and companies
• Health research : collecting data from patients about symptoms and treatments
• Politics : measuring public opinion about parties and policies
• Psychology : researching personality traits, preferences and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and in longitudinal studies , where you survey the same sample several times over an extended period.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• US college students
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18-24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalized to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

Several common research biases can arise if your survey is not generalizable, particularly sampling bias and selection bias . The presence of these biases have serious repercussions for the validity of your results.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every college student in the US. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalize to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions. Again, beware of various types of sampling bias as you design your sample, particularly self-selection bias , nonresponse bias , undercoverage bias , and survivorship bias .

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by mail, online or in person, and respondents fill it out themselves.
• An interview , where the researcher asks a set of questions by phone or in person and records the responses.

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by mail is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g. residents of a specific region).
• The response rate is often low, and at risk for biases like self-selection bias .

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyze.
• The anonymity and accessibility of online surveys mean you have less control over who responds, which can lead to biases like self-selection bias .

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping mall or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g. the opinions of a store’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations and is at risk for sampling bias .

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data: the researcher records each response as a category or rating and statistically analyzes the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analyzed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g. yes/no or agree/disagree )
• A scale (e.g. a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g. age categories)
• A list of options with multiple answers possible (e.g. leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analyzed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an “other” field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic. Avoid jargon or industry-specific terminology.

Survey questions are at risk for biases like social desirability bias , the Hawthorne effect , or demand characteristics . It’s critical to use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no indication that you’d prefer a particular answer or emotion.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by mail, online, or in person.

There are many methods of analyzing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also clean the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organizing them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analyzing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analyzed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyze it. In the results section, you summarize the key results from your analysis.

In the discussion and conclusion , you give your explanations and interpretations of these results, answer your research question, and reflect on the implications and limitations of the research.

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

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your sampling methods or criteria for selecting subjects
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, June 22). Survey Research | Definition, Examples & Methods. Scribbr. Retrieved September 9, 2024, from https://www.scribbr.com/methodology/survey-research/

Is this article helpful?

Shona McCombes

Other students also liked, qualitative vs. quantitative research | differences, examples & methods, questionnaire design | methods, question types & examples, what is a likert scale | guide & examples, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 13 September 2024

From the lab to a career in defence research

• Teresa Schubert 1  

Nature Reviews Psychology ( 2024 ) Cite this article

1 Altmetric

Metrics details

• Scientific community

Nature Reviews Psychology is interviewing individuals with doctoral degrees in psychology who pursued non-academic careers. We spoke with Mike Tombu about his journey from a postdoctoral fellow to a defence scientist.

This is a preview of subscription content, access via your institution

Access options

Subscribe to this journal

Receive 12 digital issues and online access to articles

55,14 € per year

only 4,60 € per issue

Buy this article

• Purchase on SpringerLink
• Instant access to full article PDF

Prices may be subject to local taxes which are calculated during checkout

Author information

Authors and affiliations.

Nature Reviews Psychology https://www.nature.com/nrpsychol/

Teresa Schubert

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Teresa Schubert .

Ethics declarations

Competing interests.

T.S. is employed by Springer Nature, the publisher of Nature Reviews Psychology .

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Schubert, T. From the lab to a career in defence research. Nat Rev Psychol (2024). https://doi.org/10.1038/s44159-024-00366-1

Download citation

Published : 13 September 2024

DOI : https://doi.org/10.1038/s44159-024-00366-1

Share this article

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

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Ann R Coll Surg Engl
• v.95(1); 2013 Jan

A quick guide to survey research

1 University of Cambridge,, UK

2 Cambridge University Hospitals NHS Foundation Trust,, UK

Questionnaires are a very useful survey tool that allow large populations to be assessed with relative ease. Despite a widespread perception that surveys are easy to conduct, in order to yield meaningful results, a survey needs extensive planning, time and effort. In this article, we aim to cover the main aspects of designing, implementing and analysing a survey as well as focusing on techniques that would improve response rates.

Medical research questionnaires or surveys are vital tools used to gather information on individual perspectives in a large cohort. Within the medical realm, there are three main types of survey: epidemiological surveys, surveys on attitudes to a health service or intervention and questionnaires assessing knowledge on a particular issue or topic. 1

Despite a widespread perception that surveys are easy to conduct, in order to yield meaningful results, a survey needs extensive planning, time and effort. In this article, we aim to cover the main aspects of designing, implementing and analysing a survey as well as focusing on techniques that would improve response rates.

Clear research goal

The first and most important step in designing a survey is to have a clear idea of what you are looking for. It will always be tempting to take a blanket approach and ask as many questions as possible in the hope of getting as much information as possible. This type of approach does not work as asking too many irrelevant or incoherent questions reduces the response rate 2 and therefore reduces the power of the study. This is especially important when surveying physicians as they often have a lower response rate than the rest of the population. 3 Instead, you must carefully consider the important data you will be using and work on a ‘need to know’ rather than a ‘would be nice to know’ model. 4

After considering the question you are trying to answer, deciding whom you are going to ask is the next step. With small populations, attempting to survey them all is manageable but as your population gets bigger, a sample must be taken. The size of this sample is more important than you might expect. After lost questionnaires, non-responders and improper answers are taken into account, this sample must still be big enough to be representative of the entire population. If it is not big enough, the power of your statistics will drop and you may not get any meaningful answers at all. It is for this reason that getting a statistician involved in your study early on is absolutely crucial. Data should not be collected until you know what you are going to do with them.

Directed questions

After settling on your research goal and beginning to design a questionnaire, the main considerations are the method of data collection, the survey instrument and the type of question you are going to ask. Methods of data collection include personal interviews, telephone, postal or electronic ( Table 1 ).

Advantages and disadvantages of survey methods

Collected data are only useful if they convey information accurately and consistently about the topic in which you are interested. This is where a validated survey instrument comes in to the questionnaire design. Validated instruments are those that have been extensively tested and are correctly calibrated to their target. They can therefore be assumed to be accurate. 1 It may be possible to modify a previously validated instrument but you should seek specialist advice as this is likely to reduce its power. Examples of validated models are the Beck Hopelessness Scale 5 or the Addenbrooke’s Cognitive Examination. 6

The next step is choosing the type of question you are going to ask. The questionnaire should be designed to answer the question you want answered. Each question should be clear, concise and without bias. Normalising statements should be included and the language level targeted towards those at the lowest educational level in your cohort. 1 You should avoid open, double barrelled questions and those questions that include negative items and assign causality. 1 The questions you use may elicit either an open (free text answer) or closed response. Open responses are more flexible but require more time and effort to analyse, whereas closed responses require more initial input in order to exhaust all possible options but are easier to analyse and present.

Questionnaire

Two more aspects come into questionnaire design: aesthetics and question order. While this is not relevant to telephone or personal questionnaires, in self-administered surveys the aesthetics of the questionnaire are crucial. Having spent a large amount of time fine-tuning your questions, presenting them in such a way as to maximise response rates is pivotal to obtaining good results. Visual elements to think of include smooth, simple and symmetrical shapes, soft colours and repetition of visual elements. 7

Once you have attracted your subject’s attention and willingness with a well designed and attractive survey, the order in which you put your questions is critical. To do this you should focus on what you need to know; start by placing easier, important questions at the beginning, group common themes in the middle and keep questions on demographics to near the end. The questions should be arrayed in a logical order, questions on the same topic close together and with sensible sections if long enough to warrant them. Introductory and summary questions to mark the start and end of the survey are also helpful.

Pilot study

Once a completed survey has been compiled, it needs to be tested. The ideal next step should highlight spelling errors, ambiguous questions and anything else that impairs completion of the questionnaire. 8 A pilot study, in which you apply your work to a small sample of your target population in a controlled setting, may highlight areas in which work still needs to be done. Where possible, being present while the pilot is going on will allow a focus group-type atmosphere in which you can discuss aspects of the survey with those who are going to be filling it in. This step may seem non-essential but detecting previously unconsidered difficulties needs to happen as early as possible and it is important to use your participants’ time wisely as they are unlikely to give it again.

Distribution and collection

While it should be considered quite early on, we will now discuss routes of survey administration and ways to maximise results. Questionnaires can be self-administered electronically or by post, or administered by a researcher by telephone or in person. The advantages and disadvantages of each method are summarised in Table 1 . Telephone and personal surveys are very time and resource consuming whereas postal and electronic surveys suffer from low response rates and response bias. Your route should be chosen with care.

Methods for maximising response rates for self-administered surveys are listed in Table 2 , taken from a Cochrane review.2 The differences between methods of maximising responses to postal or e-surveys are considerable but common elements include keeping the questionnaire short and logical as well as including incentives.

Methods for improving response rates in postal and electronic questionnaires 2

• – Involve a statistician early on.
• – Run a pilot study to uncover problems.
• – Consider using a validated instrument.
• – Only ask what you ‘need to know’.
• – Consider guidelines on improving response rates.

The collected data will come in a number of forms depending on the method of collection. Data from telephone or personal interviews can be directly entered into a computer database whereas postal data can be entered at a later stage. Electronic questionnaires can allow responses to go directly into a computer database. Problems arise from errors in data entry and when questionnaires are returned with missing data fields. As mentioned earlier, it is essential to have a statistician involved from the beginning for help with data analysis. He or she will have helped to determine the sample size required to ensure your study has enough power. The statistician can also suggest tests of significance appropriate to your survey, such as Student’s t-test or the chi-square test.

Conclusions

Survey research is a unique way of gathering information from a large cohort. Advantages of surveys include having a large population and therefore a greater statistical power, the ability to gather large amounts of information and having the availability of validated models. However, surveys are costly, there is sometimes discrepancy in recall accuracy and the validity of a survey depends on the response rate. Proper design is vital to enable analysis of results and pilot studies are critical to this process.

Addressing the challenges posed by energy poverty in Latin American countries

• Open access
• Published: 12 September 2024
• Volume 5 , article number  262 , ( 2024 )

Cite this article

You have full access to this open access article

• Walter Leal Filho   ORCID: orcid.org/0000-0002-1241-5225 1 , 2 ,
• Halima Begum   ORCID: orcid.org/0000-0002-6424-4966 3 , 4 ,
• Rosley Anholon   ORCID: orcid.org/0000-0003-3163-6119 5 ,
• Osvaldo Quelhas   ORCID: orcid.org/0000-0001-6816-1677 6 ,
• Izabela Rampasso   ORCID: orcid.org/0000-0003-1633-6628 7 ,
• Ayyoob Sharifi   ORCID: orcid.org/0000-0002-8983-8613 8 , 9 ,
• José Baltazar Salgueirinho Osório de Andrade Guerra   ORCID: orcid.org/0000-0002-6709-406X 10 , 11 ,
• Andrea Gatto   ORCID: orcid.org/0000-0003-1005-3571 12 , 13 , 14 ,
• Matthew Lovett   ORCID: orcid.org/0000-0003-3599-7886 15 ,
• Luis Velazquez   ORCID: orcid.org/0000-0002-3370-7761 16 ,
• Pastor David Chávez Muñoz   ORCID: orcid.org/0000-0001-7012-2167   nAff17 ,
• A. S. A. Ferdous Alam   ORCID: orcid.org/0000-0003-2413-3046 18 , 22 ,
• Luciana Brandli   ORCID: orcid.org/0000-0002-0763-7149 19 ,
• Amanda Lange Salvia   ORCID: orcid.org/0000-0002-4549-7685 20 ,
• Nelson Amaro 21 &
• João Henrique Paulino Pires Eustachio   ORCID: orcid.org/0000-0002-6782-3904 1  

Many of the energy systems functioning across the developing world are poorly designed and largely inadequate to meet a country's commercial and domestic energy needs. This is especially so in Latin America, where poverty trends have been exacerbated by limited access to energy, which could be used towards supporting industrial and small-scale commercial activities. This has characterised the widespread trend of energy poverty. This phenomenon poses a major barrier towards achieving the UN Sustainable Development Goals (SDGs) and addressing climate change, since lack of access to reliable energy generation systems hinders the development of economic activities and limits the comfort of living conditions. This paper reports on a study aimed at catering to a better understanding of the challenges related to energy poverty in Latin America and identifying some of the tools that may be deployed to address them. The methodological procedures used were bibliometric analysis and survey. The main findings of this research evidence that reducing energy poverty in Latin American countries is crucial to alleviating household costs since a considerable part of family income is used to pay the energy needs. Less use of coal, greater access to electricity—including those from renewable generation—as well as the use of technologies and programs subsidized by governments would significantly contribute to increasing the Latin American citizens' quality of life and achieving the SDGs.

Similar content being viewed by others

Addressing the Energy Challenges: Needs and Perspectives

The Impacts of Policy on Energy Justice in Developing Countries

The Energy Poverty Situation: A Review of Developing Countries

Explore related subjects.

• Medical Ethics

Avoid common mistakes on your manuscript.

1 Introduction: energy and development

The 17 sustainable development goals (SDGs), launched in 2015 by the United Nations, can be characterised as important drivers for debates and conjoint projects to be implemented and developed by developed countries towards a better future [ 1 ]. In particular, SDG7 establishes targets related to the provision of clean and accessible energy for all people on Earth [ 1 , 2 ]. According to the [ 3 ], the demand for energy in the world is increasing considerably, and at the same time, the fossil-based energy models widely used in the world are proving to be inadequate in order to contribute to an economy aligned with sustainable development. Climate change is the clearest example of how these models are inadequate [ 4 , 5 ].

It is recognised that energy, in its global conception and if properly used and accessible for all people, can provide well-being and a better quality of life. This reduces poverty and promotes economic and social development [ 5 , 6 , 7 ]. Energy is a key element for developing countries, and energy provision helps to construct resilient economies [ 8 ]. In a report published by the [ 9 ], energy was called "The Oxygen of the Economy" [ 9 ]. In the real world, however, the energy production model causes many environmental impacts, and energy benefits are not accessible to many people. [ 10 ] showed that energy access for a greater number of people in a country is directly correlated not only with macroeconomic conditions, but also with transparency of companies' financial information and audit mechanisms.

For [ 7 , 11 ], global energy production needs to be expanded to consider a change towards renewable energy modalities. It is expected that world energy consumption will grow by 50% by 2050, according to projections [ 5 ], and renewable energy modalities are the sustainable path to meet this demand without compromising environmental issues [ 4 , 5 , 12 ]. It is also important to emphasise that the generation of renewable energy also has the potential to generate other benefits, such as jobs and economic production [ 13 ].

To increase the use of renewable energies around the world, particularly in developing countries, governments should pay closer attention to energy policies, which are critical to ensuring clean and affordable energy for all projects [ 14 ]. Energy policies need to be developed that consider the context of each country, according to [ 4 ], and they should better consider renewable energy sources as part of their energy matrix [ 14 ]. A detailed analysis of energy policies trends needs to include the current and future demands in terms of domestic, commercial and industrial consumption; in addition, it also needs to take into account the need to provide better living conditions for all citizens [ 15 , 16 , 17 ]. As already emphasised by [ 4 ], the aspects associated with energy policies may vary from nation to nation.

Unfortunately, in many countries, barriers are still observed, which prevent debates and a better definition of an adequate energy policy as well as its implementation [ 14 ]. Adelaja [ 14 ] cites some examples of barriers: lack of a clear and pragmatic vision of national objectives; lack of an integrated structure of regulatory agencies; corruption problems; fragmentation of powers; excessive focus on regimentation; inadequate focus on incentives to investors and stakeholders, and lack of transparency in agency activities, among others. All of these problems contribute to unequal energy resource access and the promotion of energy poverty.

Focusing mainly on Latin American countries, [ 18 ] highlight that more than half of the region's residents do not reach an adequate energy efficiency standard, and there are still many problems related mainly to rural electrification and access to quality energy in more remote regions; as a consequence, these regions end up developing precariously and at a slower pace when compared to other regions. González and Ibáñez-Martín [ 19 ] mention that there has been an evolution in some indicators related to the supply and distribution of energy in Latin America in recent decades; however, there is still a lot to be done, especially in terms of the quality of the energy offered and accessibility. Mohsin et al. [ 18 ] also emphasise that Latina America's energy matrix corresponds to 25% of the global energy matrix, with 41% of the sources coming from petroleum; solving problems associated with this matrix and making it even more renewable can significantly contribute to reducing energy poverty in the world.

It is also essential to highlight the taxes charged for energy supply in Latin American countries (higher than in other regions of the world); such taxes burden the budget of low-income Latin American families, making their lives increasingly difficult. In the same, high-energy costs also discouraged, for example, the creation of small new enterprises, which could significantly improve the financial situation of family groups [ 18 , 19 ] also highlight other problems in Latin American countries, such as the long time to obtain electrical connections in some economies (Bolivia, for example).

Structuring public policies to have more agile, clean, and inclusive energy sectors, means that governments in Latin American countries need be more active in engaging in efforts to reduce energy poverty [ 18 , 19 ].

1.1 Objective and research approach

To fill this research gap, this paper aims to provide a better understanding of the challenges related to energy poverty in Latin America and identify some of the tools that may be deployed to address them. Therefore, we seek to answer the following research question: What are the possible barriers and challenges posed by energy poverty in Latin American (LA) countries? The findings of the study will be used as an information source for policymakers to overcome the recent barriers in the studied LA countries.

Therefore, to achieve these goals, this research is structured as follows. Section  2 presents the theoretical background which reviews the concept of energy poverty and its challenges from a global perspective, focusing on Latin American countries. The third section entails the main methods used for data collection as well as data analysis. The bibliometric analysis that was used to select the methods for assessing the challenges of energy poverty is described. Section  3 also identifies the variables of the study for collecting survey data and provides an explanation of the detailed methodology for using them in the analysis. The evaluation of energy poverty outcomes is used to interpret the results, the main discussion and key findings show the actual challenges of energy poverty in LA countries in Section 4 , and lastly, the conclusions and recommendations are presented in Section 5 .

2 Energy poverty in Latin America

2.1 concept and challenges of energy poverty.

The concept of energy poverty by the Energy Poverty Advisory Hub (EPAH) & European Commission (EU) highlighted the significant financial strain that energy bills place on consumers, along with the negative impact on their ability to meet other financial obligations and maintain their overall health and well-being. This definition mainly highlights the significance of affordability and the consequences of excessive energy costs on households. Likewise, many scholars provide a precise and concise explanation of energy poverty in developing nations and LA, which refers to the lack of access to modern energy services or the inability to afford sufficient energy for basic needs such as cooking, heating, lighting, and using appliances [ 20 , 21 , 22 ]. This condition affects a substantial number of people worldwide, particularly in developing nations, where there is a scarcity of reliable and affordable energy sources. The same authors mention that EP in Latin America denotes the state in which individuals or households do not have access to energy services that are reasonably priced, dependable, and environmentally friendly [ 21 ]. This lack of access has negative consequences on their quality of life, health, and socio-economic welfare. This idea incorporates multiple dimensions, such as the price, accessibility, reliability, and quality of energy services.

Energy poverty in Latin America is noteworthy, affecting a substantial portion of the population who have challenges in affording sufficient energy services. The concept is exacerbated by the limited availability of dependable electricity and clean cooking fuel, impeding growth, and intensifying social inequality [ 23 ]. Hence, resolving the issue of energy poverty in LA necessitates customised solutions that take into account the distinct requirements and conditions of the region. In order to prevent misunderstandings and guarantee the success of initiatives aimed at tackling energy poverty in Latin America, it is crucial for researchers and policymakers to enhance and customise definitions and strategies to fit specific local circumstances [ 24 ]. When establishing interventions and policies to improve energy access and affordability, it is important to take into account the socio-economic conditions of each country, and their communities. This is especially important in Latin America, a region characterised by a great socio-economic diversity. This will enable them to build more precise and impactful policies, thereby improving the well-being of populations throughout the region [ 25 ].

On the contrary, considering the relevance of energy for sustainable development, energy poverty is one problem which is associated with it, and which needs to be better understood. [ 26 ]. The concept of energy poverty was first described in 1979 after the petroleum crisis caused inflation in fuel prices. It was later defined briefly as having an adequate amount of energy for 10% of income [ 27 ] and termed as the inability to maintain a level of energy consumption that is sufficient to meet basic needs, such as maintaining a residence at the appropriate temperature or preparing food. This is complemented by the fact that more than 1 billion people do not have access to electricity [ 28 ]. Reliable, sustainable, modern and affordable energy access is part of the United Nations (UN) 2030 Agenda, representing the seventh Sustainable Development Goal (SDG) [ 84 ].

Energy poverty has also an associated term, namely energy access. This refers to an inability to meet energy needs at affordable rates. This is influenced by several factors, including low income, the high cost of energy, limited access to energy, and outdated technologies. Both energy poverty and energy access have further implications, such as health issues (e.g., mass winter deaths) and mental health issues [ 29 ]. Admittedly, it is not an easy task to define energy poverty, as the concept varies according to the energy resources from one country to another [ 30 ]. However, [ 31 ] asserted that a scientific assessment of energy poverty may serve as the foundation and assurance for developing and enacting public measures aimed at mitigating the issue.

Energy poverty is a problem, especially relevant to households with low income, which often struggle to afford adequate energy services, leading to inadequate heating, cooling, and lighting. This is mostly attributed to poor household insulation and low income [ 32 , 33 ]. Domestic energy poverty, a widespread global problem, is especially acute in developing countries [ 34 ], since many people there are affected by unemployment or underemployment. They often have reduced financial capacity to cover energy costs and, unlike in rich countries, have no government social net they can reply on. Nevertheless, it is important to recognise that energy poverty is a worldwide problem that impacts both emerging and developed countries, albeit in different ways and to different extents. Emphasising the initiatives and strategies, especially in the EU, to combat and measure energy poverty could provide a more holistic perspective on the global approach to this problem.

In this line of reasoning, [ 35 ] emphasise the importance of considering contextual issues to evaluate energy poverty, such as economic, geographic, and cultural aspects. According to the authors, measurements based on access or quality standards may overestimate or underestimate the reality. Among the regions that should be carefully analysed, developing economies are highlighted. Analysing three developing country regions, [ 36 ] verified that despite differences among studies, energy poverty is a widespread reality for Sub-Saharan African, South and Southeast Asian, and Latin American and Caribbean populations.

Access to energy is central to overcoming several development challenges, including poverty, gender inequality and climate change, in addition to food security, health and education [ 37 ]. Concepts such as economic development and measurements such as the Human Development Index (HDI) are also linked to energy use, as they are often measured by terms such as electricity consumption in each home and CO 2 emissions. In addition, the literature shows that economic advancement and development have a high impact on a country's energy use, as exemplified by the case of China: between the years 1970 and 2010, during which China demonstrated great economic growth, it also started to consume up to 20 times more electricity [ 30 , 38 ].

2.2 Challenges posed by energy poverty in Latin American countries

The main corpus of this study was concerned with the topic of energy poverty in LA countries. A number of studies have shown recent problems, the barriers created by energy poverty, and how to overcome the challenges in LA countries [ 37 , 38 , 39 , 40 ]. For instance, as remarked by [ 41 ], several studies have investigated energy poverty challenges in Spain, Scotland, Mexico, and Ecuador until 2020, which may indicate that energy poverty needs ongoing research to carry out assessments [ 40 ]. Energy poverty affects many people in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, French Guiana, and other Latin American countries, but there are no survey investigations on energy poverty-posed challenges in this entire region that assess multi-scale mapping of fuel poverty, vulnerability of households, energy development, affordability and sustainability, emissions, security transport impacts, winter incidence, and improvement in mortality, and related issues. However, a scientometric analysis for seven LA countries were performed by [ 39 ] recently.

As argued by [ 39 ], although Latin America presents great problems related to energy poverty, there is little research about this in the literature. These authors, using the MEPI (Multidimensional Energy Poverty Index), analysed seven Latin American countries (Peru, Colombia, Honduras, Guatemala, Dominican Republic, Mexico and Haiti) and verified that there is a strong correlation between MEPI and HDI, showing that addressing energy poverty can also be important to improving HDI levels, although further investigation is necessary and the connection between these concepts might oversimplify the complex interactions among various social, economic, and environmental factors. In addition, the study also verified that, among these countries, Haiti presents the lowest MEPI level: more than 97% of its population does not have a basic energy service. The critical situation in Haiti is corroborated by the [ 42 ] report, which shows that only 39% of Haitians had access to electricity in 2019. Also using MEPI, proposed by [ 37 , 43 ] adapted the index to analyse thermal comfort in Mexico, considering the relevance of this energy element in different regions of the country. In [ 40 ], the authors proposed their own index for assessing energy poverty in Ecuador and compared it with MEPI.

Moreover, considering the challenges faced by Latin American countries regarding energy poverty, [ 44 ] emphasise the need for the governments of these countries to use renewable energy technologies as tools to facilitate access to cheap energy (e.g., solar).

Focusing on five Latin American countries (Argentina, Colombia, Brazil, Mexico, and Cuba), [ 23 ] combined literature and documents review to analyze the current context of these Latin American countries. In their analysis, the authors indicate the need to separate different dimensions of energy poverty, since exclusive focus on service-based or expenditure-based approaches can generate incomplete analyses and conclusions. The authors also emphasise the lack of qualitative studies focused on the region.

Despite the difficulties of energy access for families living in remote areas, Latin American countries also present these difficulties for low-income families living within urban centres. This is the case of the Brazilian favelas, which are communities with high levels of energy poverty [ 45 ]. Regarding energy supply structure improvements for the sector in this region, and in analysing changes in electricity sector governance in Latin American countries and the Caribbean, [ 46 ] argue that energy poverty was not significantly affected by these changes. However, energy poverty is termed energy injustice [ 47 ] and is one of the difficulties of social justice [ 41 ], where energy is consumed by individuals for human needs in Latin America [ 48 ].

Despite the problems evidenced in developing economies, energy poverty is also observed in developed countries such as Germany and Belgium, where energy efficiency remains a problem [ 34 ]. Aside from this, studies have shown that a large percentage of households are unable to achieve adequate indoor temperatures through their heating or cooling systems due to energy poverty. This has serious implications for the physical and mental health of individuals as well as for productivity. This is a common problem in developed countries. The problem is further influenced by global warming, as many regions are experiencing increased temperatures and extreme heat waves [ 49 ]. Taking this into consideration, energy poverty can be broken down into two main categories, namely availability and affordability. Developing countries often fall under the availability category, as there is a lack of access to basic energy needs such as electricity. However, developed countries, including Latin American countries, have high costs for socially necessitated energy such as heating or cooling systems, thus they belong to the affordability category of energy poverty [ 48 , 85 ].

In conjunction with energy poverty, energy vulnerability refers to factors that influence the precariousness of people or areas [ 34 ]. These factors include the composition of the household (number of old or young people), the professional status of household members, whether the property is rented or owned (rented property is generally less energy efficient), and the health status of members (who may require additional heating or cooling). These factors increase a household’s susceptibility to energy poverty [ 50 ], and the findings mentioned that losses and damages incurred energy poverty rather than overcoming it [ 39 ].

Due to the burden placed on households by increased energy tariffs, researchers have stated that a decrease in energy poverty is essential for alleviating pressure on household income. Studies have shown that one of the major ways to reduce energy poverty is by investing in modern energy sources, especially renewable energy such as solar energy, which may be used to improving life quality and access to income generating activities such as conservation of produce and trade. Furthermore, the use of biomass energy and other renewable energy sources (e.g. wind) can significantly alleviate pressure on household incomes [ 83 ]. Provided that more renewable energy may be made more widely available to households, problems such as those seen in Mexico, where high energy costs are taking a larger portion of people´s income [ 39 ] may be avoided.

This review also shows gaps in the literature and highlights the scarcity of papers focusing on energy poverty, especially focusing on LA countries. Accordingly, as mentioned, the main objective of the present study is to evaluate the challenges of energy poverty in Latin American populations by identifying their current trends. Hence, the study indicators, variables, and indices are the key elements for scrutiny in the study and in addressing tailored policies. Nevertheless, detailed information regarding the literature reviews can be found in the proposed methodology for bibliometric analysis by [ 37 ], whose energy poverty indicators were used for the analysis of the study. Additionally, this inquiry is distinctive because it includes a random sample from a wide range of Latin American countries, and the types of questions addressed give information on the current situation in Latin American families to fight energy poverty.

3 Methodology

3.1 approach used in the bibliometric analysis.

To gain an overview of the state of knowledge on global energy poverty in Latin America, we conducted bibliometric analyses using VOSviewer. This software tool is designed to map, among other things, scientific literature and highlight major focus areas. The input data was the literature published on energy poverty, indexed in the Web of Science (WoS) [ 51 ]. WoS was used due to its wide coverage of quality peer-reviewed articles on this topic. To gain global as well as Latin American-based perspectives, we developed two databases: one with a global focus that included 2021 articles, and another one focused on Latin America that only included 129 articles. The search strings used to develop these input databases are available in Appendix 1. The term co-occurrence analysis of VOSviewer was used to identify dominant research topics in energy poverty. This analysis maps the co-occurrence frequency of terms related to the topic. It can also be used to identify major research clusters. The results are presented in the form of nodes and links, where node size is proportional to the frequency of occurrence, and link width is proportional to the strength of the connection between two terms. Additionally, the terms that are located near each other have co-occurred more frequently and form research clusters.

3.2 Online survey

An online survey was applied to establish ‘the Challenges Posed by Energy Poverty in Latin American Countries’ for the exploratory component. The questionnaire was developed, comprising 26 questions and 3 main sections. A set of 26 questions was presented to the participants in order to report the extent of the problem, list the challenges they have been facing, the impacts of limited energy access, the availability of fossil fuel and renewable energy, and some of the measures they feel are needed to address the problem. The survey also asked which changes are needed to provide more adequate, reliable, and affordable energy services. Nonetheless, the three main sections included:

Part 1—The demographic profile of the respondents.

Part 2—Household’s importance and challenges in receiving adequate, reliable and affordable energy services to fight energy poverty.

Part 3—Household’s level of consumption and access to energy, lighting, heating appliances, information and communication technology appliances, air conditioning, cooking appliances, refrigeration appliances.

The Chair of the "Association of Medical Ethics Committees in Germany" approved the questionnaire, confirming that the study complied with all regulations and that informed consent was obtained (see Appendix 2). The questionnaire was validated by a group of researchers and then shared with several networks to reach the LA country's households, through the team of the Inter-University Sustainable Development Research Programme (IUSDRP, https://www.haw-hamburg.de/en/ftz-nk/programmes/iusdrp/ ), which surveyed more than 10 countries in LA. The study followed a non-probability sampling methodology, as the researchers shared the survey with their networks and contacts. The questionnaire remained active between March and August 2021 and collected 222 responses after data clean-up, removing countries not in the area of study, from 11 LA countries—Peru, Brazil, Mexico, Chile, Uruguay, Colombia, Bolivia, Argentina, Venezuela, Guatemala, and Ecuador—as shown in Fig.  1 .

Participating countries and number of respondents (n) per country

The final sampling consisted of 222 respondents out of a hidden online population. As non-probability sampling methods through Internet recruitment of hidden populations traditionally reach small samples [ 82 ], this sampling size is considered acceptable for the purpose of this paper. However, it is not possible to make inferences over broader populations.

Participants in this survey were from eleven Latin American countries, with greater representation from Peru (44.1%), Brazil (26.5%), Mexico (16.6%), Chile (7.66%), Uruguay, Colombia, Bolivia, and Argentina respectively (1%), Venezuela, Guatemala, and Ecuador (0.5%) respectively; see Table  1 . The overall gender distribution among the respondents was 53% male and 47% female.

Regarding their age, 38% of the respondents are between 18 and 29 years of age, 14% are 30–39, 22% are 40–49, 17% are 50–59, and 9% are 60 years of age or older. 24% of the respondents earn a net monthly household income of US $600 to $1350. A monthly income of more than US$4000 is achieved by 17% of the respondents. About 12% of participants earn US $1350–2000, and 11% of them make US $2700–3400. 8% of respondents earn a net monthly income in the range of US $2000–2700, US $3400–4000, or below US $680. A considerable number of respondents hold a postgraduate or graduate degree, 49% and 42% respectively. However, only 9% finished high school. The occupations of the respondents were distributed as follows: student 32%, administrative staff 11%, trained professional 14%, junior management 12%, self-employed/partner 9%, upper management 7%, consultant 6%, retired 4%, temporary employee 3%, unemployed 2%. The respondents predominantly live in a flat, 43%, but a considerable segment of them live in detached houses, 36%. A few more live in semi-detached houses, 18%. Predominantly, there are two adults per house in 43% of the sample, although a considerable percentage (30%) of the sample declared four or more per house. 55% of the respondents claimed that no minors live in their homes, and 31% of the participants indicated one child living at home. A summary of the demographic characteristics of the respondents is shown in Table  1 .

4 Results and discussion

4.1 results of bibliometric analysis.

Results of the global term co-occurrence analysis for a minimum occurrence threshold of 13 keywords are shown in Fig.  2 . It can be seen that, in addition to energy poverty, terms such as fuel poverty, climate change, consumption, renewable energy, energy, rural electrification, energy access, households, efficiency, and health are frequently used in the literature. Four major clusters can be identified. In the largest cluster (in red), renewable energy and rural electrification are central and have strong connections with terms related to accessibility and different types of renewable energy, and with location-based terms such as Africa, Sub-Saharan Africa and India. This indicates a major emphasis on the importance of electrification and renewable energy sources for addressing energy poverty in a sustainable manner [ 30 , 52 ]. Renewable energy and the electrification of rural areas play a significant role in improving access to energy and combating energy poverty, particularly in developing regions [ 53 ]. The utilization of renewable technologies directly addresses the issue of electricity scarcity, which impacts many people globally, especially in Sub-Saharan Africa and India [ 54 ]. By harnessing local resources like solar, wind, and hydro power, rural communities can circumvent traditional centralized energy systems without requiring expensive and time-consuming grid extensions. This decentralized approach not only grants immediate access to electricity but also fosters long-term economic development by facilitating education opportunities, improving health outcomes, and enhancing agricultural productivity [ 55 , 56 , 86 ]. Furthermore, involving community participation ensures that the benefits of accessing energy are equitably distributed based on each community's specific needs—making rural electrification through renewable sources a sustainable solution for addressing energy poverty while empowering communities to meet their energy requirements aligning with global environmental goals [ 57 , 58 ]. In the second noteworthy cluster (green), terms such as fuel poverty, indicators, and households are central. Also, the term COVID-19 is highly linked to the other terms in this cluster. The term fuel poverty has co-occurred frequently with the term Europe and is closely linked to others such as justice and vulnerability from the same cluster and health and thermal comfort from the yellow cluster. The connection to Europe indicates that energy poverty may also occur in developed countries, thereby causing health problems. Appropriate policies are needed to ensure energy justice and minimise impacts on vulnerable groups [ 59 , 60 ]. Fuel poverty could have significant consequences for households, especially in terms of vulnerability and justice. Households struggling with fuel poverty often face difficult decisions about heating/cooling versus other basic needs. This dilemma exacerbates existing vulnerabilities, impacting children, the elderly, and individuals with underlying health conditions by increasing their susceptibility to respiratory issues, inadequate nutrition, and mental health challenges. The concept of energy justice emphasizes the inequities in energy access and the unequal burden of energy costs on already marginalized groups, highlighting the need for policies to address these inequalities [ 40 , 61 , 62 , 63 ].

Output of the term co-occurrence analysis

The COVID-19 outbreak has exacerbated the challenges linked to fuel poverty. Higher home occupancy and lockdowns have led to increased domestic energy consumption, while income reductions due to the pandemic have made it even harder for many people to afford energy expenses. Consequently, more households have grappled with fuel poverty, leading some to resort to unsafe heating and lighting methods or face heightened financial difficulties. The pandemic has underscored the significance of tackling fuel poverty as a matter of public health and social justice [ 64 ]. Terms in the green cluster are closely linked to those in the yellow cluster which is mainly focused on climate change, efficiency, and health. The issues of climate change and energy poverty are closely interconnected, especially in developing nations. Limited access to modern energy services makes communities more vulnerable to the adverse effects of climate change. As extreme weather events and unpredictable seasons become more frequent due to climate change, those dealing with energy poverty lack essential resources such as heating or cooling systems [ 65 ]. Moreover, relying on traditional biomass for energy in impoverished areas contributes to deforestation and greenhouse gas emissions that worsen climate change further [ 66 ]. Transitioning towards renewable energy sources can mitigate the impacts of climate change while enhancing the resilience and adaptability of populations most affected by these challenges [ 65 , 66 ]. There are concerns about climate mitigation ramifications of energy poverty alleviation measures. Mitigation and poverty alleviation efforts should, therefore, be complementary, and major efficiency improvements are needed to ensure energy poverty challenges are addressed using renewable and sustainable energy solutions [ 67 , 68 ]. Well-designed policies can offer opportunities to maintain thermal comfort in buildings while minimizing trade-offs for health and climate change mitigation [ 43 , 49 , 69 ].

Finally, there is a blue cluster that is dominated by terms such as consumption, economic growth, GHGs, income, inequality, and multidimensional energy poverty. Consumption patterns, income levels, and inequality are closely interconnected with the complex nature of energy poverty and the wider concept of energy security. Energy poverty extends beyond mere lack of access to energy; it encompasses various issues such as the quality, affordability, and reliability of energy services. Lower-income households often bear a disproportionate burden when it comes to energy expenditure, spending a larger portion of their income on meeting their energy needs [ 70 ]. This can lead them to limit their use of energy in order to avoid financial strain, which could exacerbate health risks and social disparities. Furthermore, income inequality can escalate energy insecurity by creating disparities in both access to and usage of energy within communities as well as between them—often leaving disadvantaged groups trapped in enduring states with insufficient access to adequate sources of energy [ 71 ]. Economic growth, education, and financial development are closely connected to the challenges of energy poverty. While economic growth can drive up energy demand, it may not necessarily result in better access to energy for the impoverished without comprehensive policies. Education plays a critical role in promoting awareness about energy efficiency and the advantages of renewable energy, empowering individuals and communities to make well-informed decisions. Financial development through initiatives like microfinance and subsidies can facilitate access to modern energy services by addressing initial cost barriers linked with renewable energy technologies [ 72 , 73 ]. Overall, it is clear that addressing these issues requires a comprehensive approach that takes into account the complex interplay among consumption patterns, income levels, and inequality in order to ensure fair energy security and mitigate the multifaceted elements of energy poverty.

The term co-occurrence analysis for Latin American countries is shown in Fig.  3 . Overall, the clusters are similar to the global clusters. However, a unique characteristic of the term co-occurrence map for Latin America is that issues related to air pollution and gender, which are also addressed globally, are more highlighted. In Latin American nations, the connection between air pollution and energy poverty is a critical environmental and societal concern. Energy poverty often leads to limited availability of clean and affordable energy resources, causing households to rely on traditional biomass and other polluting fuels for cooking and heating. This dependency significantly contributes to indoor and outdoor air pollution, with adverse effects on health and the environment. In urban areas, the lack of access to clean energy worsens pollutant emissions from informal settlements where inefficient combustion processes are prevalent. Economic limitations related to energy poverty hinder the adoption of cleaner technologies, perpetuating a cycle of pollution and health hazards. Therefore, efforts aimed at addressing energy poverty in this region should prioritize transitioning towards cleaner energy sources not only for improving air quality but also considering broader implications for environmental justice and equity [ 23 , 74 , 75 ]. Issues related to fuel poverty and gender are closely linked to wider concerns of vulnerability and justice. Women, especially those in low-income or rural settings, are disproportionately affected by fuel poverty due to a combination of socio-economic factors and traditional gender roles. The "female poverty penalty" is evident as women, particularly during their most productive years, experience higher levels of financial hardship compared to men. This is exacerbated by their caregiving responsibilities and the lack of alternative care options. Additionally, the situation is complicated by women's tendency to work part-time jobs, face job segregation based on gender, and encounter barriers in their career paths. As a result, households led by single mothers or where women take on primary caregiver roles are more likely to experience fuel poverty and subsequently higher rates of overall poverty within these families. This not only exposes women to greater health risks due to inadequate heating and cooking facilities but also restricts their opportunities for economic progress. It is crucial to address these gender-specific aspects of fuel poverty to promote energy justice and reduce vulnerability among the most affected population in Latin America [ 76 , 77 , 78 ].

Output of the term co-occurrence analysis for Latin American countries

An important issue to note is that, as can also be understood from the limited number of papers (only 129 compared to 2021 for the global analysis), existing knowledge on energy poverty in Latin American countries is relatively limited. The limited available knowledge emphasises the need for electrification and renewable energy-based measures to tackle energy poverty issues. Such measures and policies may also provide co-benefits in terms of health and air quality improvement [ 79 ]. Overall, this overview analysis indicates that understanding and addressing energy poverty in Latin America warrants further research, and this research aims to contribute to providing a better understanding in this regard.

4.2 Fighting energy poverty

Tackling energy poverty is amongst the most urgent issues that our societies are called to solve. To this end, both the Global South and the Global North are required to face energy poverty by adopting multi-layered strategies, targeting diversified societal, economic, and environmental aspects [ 80 ]. Latin America is no exception to this. This part of the paper reports on the results of the survey.

Figure  4 presents an overview of the housing characteristics and its energy conditions. Of the 222 survey respondents, 92.3% described their living areas as ‘urban’, 6.3% as ‘peri-urban’ and 1.4% as ‘rural’. The majority stated that the main energy source for heating their household was electricity (56%), followed by gas (13%), and heating oil and wood/pellets, both at 1%. 27% reported that there were no heating options in their house, and less than 1% answered that they used solar, or a combination of gas, electricity and wood.

Overview of housing energy conditions and characteristics

Among the respondents, 27% reported they were slightly familiar with the term ‘energy poverty. 26% were somewhat familiar with it, 21% were not at all familiar, 17% were moderately familiar, and 9% were extremely familiar with the term.

Regarding how often they felt uncomfortably cold or hot in their household during the winter or summer period, the majority of respondents (47%) answered 'sometimes'. 27% answered 'rarely', 17%, 'very often', 5%, 'never', and 4%, 'always. Of these, 26% stated that the main reason for the uncomfortable temperature was that the house lacked an efficient cooling system, 23% stated that the house’s construction material did not favour thermal comfort, and 10% said that their house lacked insulation. 18% cited varying combinations of all three of the previous factors, and 3% of answers cited more specific reasons for discomfort, including house design, power shortages and climate. On the other hand, 18% stated that they never felt uncomfortable, and 2% said that they rarely felt uncomfortable.

Respondents were also asked a series of questions about the priorities for tackling energy poverty in their respective countries (Fig.  5 ). Regarding the importance of keeping the infrastructure of a house free of the types of problems that can cause additional energy expenditure, for example, broken windows or leaks in walls, 43% saw this as being extremely important, 29% as very important, 19% as moderately important, 6% as slightly important, and 3% as not at all important. 43% saw electricity produced from renewable energy sources as an extremely important factor in combating energy poverty, 37% saw it as being very important, 10% as moderately important, 5% as slightly important, and 5% as not at all important.

Priorities for tackling energy poverty

In terms of rating the importance of their country in becoming self-sufficient in electricity production and not relying on imports from other countries, 42% of respondents saw this as being extremely important. 31% rated this as very important, and 15% as moderately important. It is worth noting that a relatively high proportion of the respondents—7%—rated energy self-sufficiency as not at all important, and 5% saw it as being slightly important. Similarly, [ 59 ] claimed that producing one's electricity is necessary for long-term energy development.

Based on their country's context, respondents were asked which changes they felt were needed to receive more adequate, reliable and affordable energy services (Fig.  6 ). In response, 44% felt that making investments in electrification on and off the grid was extremely important as in solar energy systems for homes. 40% saw this as being very important, 10% as moderately important, 5% as slightly important, and 1% as not at all important. Regarding creating financing structures that are well adapted for the electrification of cities and communities, 51% saw this as being extremely important, 32% as very important, 11% as moderately important, 5% as slightly important, and 1% as not at all important. In terms of improving energy efficiency, the overwhelming majority—58%—rated this as extremely important. 26% saw this as being very important, 12% as moderately important, 3% as slightly important, and 1% as not at all important. Likewise, [ 39 ] claim the fact that Latin America has enormous challenges related to energy poverty that need to be resolved in a sustainable manner. A high majority—55%—felt that improving the use of renewable energies in electricity generation was an extremely important change to make. 34% saw this as being very important, 7% as moderately important, 2% as slightly important, and 2% as not at all important. Regarding using public policies to promote energy security, 51% saw this as being extremely important, 27% as very important, 18% as moderately important, 3% as slightly important, and 1% as not at all important.

Desired changes to receiving reliable and affordable energy services

Over half—58%—of the respondents rated education and awareness raising as extremely important in terms of renewable energies and sustainability changes. 31% saw this as very important, 6% as slightly important, 5% as moderately important, and less than 1% rated this as unimportant. In terms of strengthening international and regional cooperation, 41% saw this as extremely important, 32% as very important, 19% as moderately important, 5% as slightly important, and 3% as not at all important.

Approximately 39% saw making reforms to energy markets to attract private sector investment as extremely important. 29% saw this as very important. 23% as moderately important, 5% as slightly important, and 4% as not at all important. 52% rated the adoption of sustainable city strategies as extremely important. 36% saw this as being very important, 7% as moderately important, 4% as slightly important, and 1% as not at all important.

Finally, 60% of respondents stated that research and development in the field of energy, especially in energy efficiency and renewable and clean energy is an extremely important change. 20% rated research and development as very important, 14% as moderately important, 5% as slightly important, and 1% as not at all important.

Respondents were also asked to indicate their sources of information on energy poverty (Fig.  7 ). The vast majority of interviewees reported that they heard about it from the internet and social media (77%) and traditional media (45%) such as newspapers, TV and radio. Approximately 21% of them declared that they had received information from the work environment, and 14% indicated that they received information from friends and family.

Information sources on energy poverty

The survey also aimed to understand the lack of capacity to cope with electricity expenses and the frequency of this occurrence. Figure  8 brings this scenario where the vast majority of respondents declared not to have faced difficulties in the past 12 months (77%). Following this, 17% of the sample announced that they had issues lasting between 1–4 months. The remainder of the inquired population replied that they experienced issues for 5–8 months, or for 8 months or more (3% per each group).

Domestic purchasing power of energy

Similarly, the interviewees were asked about their perceptions regarding the domestic purchasing power connected with energy expenses. A large portion of the surveyed population perceived the prices to be high when compared to their income (44%). Conversely, 28% of respondents had the perception that the expenses were moderate. Another 19% of participants assessed the prices as very high. Lastly, 6% of the inquired people said that the prices were low, and for 2% of the population these were very low.

In order to deepen our knowledge on this issue, panellists were asked about the share of their income used to fulfil the monthly household's energy needs. The vast majority (68%) of the respondents declared spending around 1–10% of their income for their household's energy needs. Next, 23% of respondents said their energy costs were circa 11–30% of their income. 2% of the sample assessed the ratio as about 31–50%. 6% of the sample was not aware of this issue, whereas only 1% of them declared not to have expenses.

Lastly, respondents were asked about possible strategies to overcome energy poverty, where low-cost and behavioural change measures were among the most frequent answers (75% and 71%, respectively) in Fig.  9 . Also, approximately 53% of the respondents stated that improving the building's energy performance is essential for tackling energy poverty, and another 6% provided different answers. The replies included: Behavioural change measures, low-cost measures, and actions for improving the building's energy performance combined with solar PV, optimising energy supply systems to reduce user costs. The study found renewable energy projects to improve the poor's well-being or use of energy consumption indicators, as [ 52 ] also emphasised the use of renewable energy sources for sustainability. Behavioural change measures, low-cost measures, and either boosting low-cost access to foster solar energy or gas use. Behavioural change measures, actions for improving the building's energy performance, and government policies. Actions to improve the building's energy performance and an extensive drop in expenses for the poor. Affordable financing to change the lighting and appliances in the house. Financial contributions. Inversion of energy sources and distribution in poor areas. Low-cost measures, actions for improving the building's energy performance and either public policies for renewables implementation; or clear policy on the promotion of low-cost energy sources, focusing on the consumer and production of clean and efficient energy. Lowering gas and light prices. On the other hand, [ 30 ] findings highlight the need to produce clean and efficient renewable energy sources to address energy poverty.

Effective measures to tackle energy poverty

4.3 Levels of energy consumption

The survey also aimed to identify the level of energy consumption among the 222 respondents. Figure  10 shows the answers regarding the access to items/appliances that require electricity to function. Accordingly, approximately 95% of the participants reported having access to lighting and 85% full access to energy. In comparison, only 20% of the respondents indicated that they have full access to energy and to all appliances such as lighting, heating, information and communication technology, air conditioning, cooking, and refrigeration, which according to [ 81 ], are essential in ensuring comfort. In addition, 44% of the 222 respondents mentioned not having air conditioning and 40% heating appliances, while all other listed items (cooking, refrigeration and information, and communication technology appliances) were individually found present in more than 93% of participants´ answers.

Access to energy appliances

The respondents were also asked about the types of household energy they use (Fig.  11 ). About 31% mentioned using only electricity; electricity and liquefied gas (20%); natural gas and electricity (18%); natural gas, electricity, candles and batteries (11%); natural gas, electricity, and liquefied gas: (1%); natural gas, electricity and liquefied gas, candles and batteries (1%); natural gas, electricity, firewood (2%); natural gas, electricity, firewood, candles and batteries (1%); solar energy, natural gas, electricity (2%); solar energy, natural gas, electricity, firewood (1%); solar energy, and electricity (1%). On the other hand, the panellists also rated their consumption levels of energy at their houses as users of solar energy, electricity, coal energy; candles, batteries, natural gas (1%); solar energy, and electricity (1%); solar energy, electricity, coal energy (1%); solar energy, electricity, liquefied gas, candles, and batteries (1%); carbon energy, electricity, candles, batteries, kerosene (2%); electricity, candles and batteries (5%) etc. Nonetheless, there is a preference for using kerosene (1%) with electricity. Regardless, the findings revealed that a small percentage of respondents use coal, which is often associated with low living standards [ 67 , 68 ].

The households energy consumption level

The participants also rated the share of renewable energy use in their households. 61% of the respondents declared that no share of renewable energy is used in their household, but 21% of the interviewees do partially use renewable energy (between 1 and30%), 3% use between 30 and70%, 14% do not know, and 1% indicated that 70% of their energy use is renewable (Fig.  12 ).

The households RE consumption level

The interviewees were also asked about their perceptions regarding approximate monthly fuel costs for their vehicle, such as gasoline, diesel or kerosene (Fig.  13 ). Among the 222 respondents, only 201 respondents answered, indicating that the different cost ranges were: below US$50 (22%), US$51–100 (9%), US$101–150 (28%), US$151–200 (10%), above US$200 (0%), and some participants (7%) were unaware or not usually track the monthly fuel costs.

The households fuel costs level

Respondents were also asked whether they use or have an energy efficiency mechanism to reduce domestic energy consumption; 80% of the respondents claimed that their households do not use any energy efficiency mechanism to reduce domestic energy consumption. However, of the 222 respondents, 20% claimed that they are using devices for energy efficiency such as thermo timers, stabilisers, timers to heat using thermal gas instead of electricity, low-consumption lighting and gas appliances, solar heaters, ventilation/lighting using windows, solar detection cells, LED lights, and motion detectors where appropriate to turn off lights and devices when not in use.

5 Conclusions and policy implications

In Latin American countries, reducing energy poverty is crucial for alleviating household cost difficulties, as the countries present great problems related to energy poverty. In order to deepen our knowledge on this issue, one must look at the household income share used to fulfil the monthly household's energy needs. This trend is detrimental to reaching the United Nations Sustainable Development Goals since a lack of access to reliable energy generation systems inhibits economic growth and affects living comfort. In order to combat energy poverty, households should have greater access to electricity, but also to natural gas or biogas for household activities. The less they depend on coal, the greater the health benefits are. In addition, the use of thermo timers, stabilisers, low-consumption lighting and gas appliances, and solar heaters, may lead to additional gains. Indeed, a greater use of renewable energy may be a positive step forward and be part of a possible strategy to overcome energy poverty in urban and rural areas of Latin American countries—which could be a potential topic for future investigations. One of the advantages is that renewable energy may also provide some co-benefits through significant reductions in pollution levels.

Some measures being applied by the most prominent countries in this study, and that should be considered by Latin American countries, including the expansion of electricity coverage, including programs that subsidise grid extension projects and electrification, especially in rural areas; the implementation of subsidised social tariffs for low-income families to facilitate their access to energy services; energy efficiency programs, with the implementation of initiatives that promote the use of energy-efficient appliances and lighting; promotion of renewable energy, with policies that encourage the development and use of renewable energy sources, especially solar.

As this paper has shown, energy poverty in Latin America is a pressing issue affecting many communities across the Region. It has significant policy implications that governments and stakeholders must address to ensure equitable access to energy resources. One of the key policy implications is the need for enhanced infrastructure Investment. Here, governments need to prioritise investments in energy infrastructure, especially in rural and underserved areas. This involves not only expanding the grid but also enhancing its reliability to reduce frequent power outages which disproportionately affect the poor. Also, in order to combat energy poverty sustainably, policies should facilitate the adoption of renewable energy sources. These are particularly relevant for Latin America given its vast potential in solar, wind, and hydroelectric power. Subsidies, incentives, and supportive regulatory frameworks can encourage both private and community-level renewable energy projects. A further policy area is related to energy subsidies reforms. While subsidies aim to make energy affordable for low-income households, they often benefit all consumers regardless of their income level. Policymakers should consider restructuring these subsidies to target the needy more effectively, ensuring that assistance reaches those in actual need without encouraging wasteful consumption. Finally, addressing energy poverty requires coordinated policies that integrate energy, economic, and social policies. This could involve linking energy access initiatives with social welfare programmes to provide comprehensive support to low-income households.

This paper has some limitations. Firstly, it focused on 11 countries in Latin America, from which four were particularly prominent, namely Peru, Brazil, Mexico, and Chile. Secondly, the sample of 222 respondents is too small to allow definitive conclusions to be made, even though some trends were identified. But despite these constraints, the paper provides a welcome addition to the literature on matters related to energy poverty in Latin America, a region characterised by deep social inequalities. Upcoming research may want to enlarge the spectrum of analysis, including additional countries.

Moving forward, the findings from the research suggest that a combination of awareness-raising initiatives on the advantages of alternatives for energy generation, along with the dissemination of low-cost solutions, may assist the ongoing efforts to overcome energy poverty in the region.

Data availability

Data will be available upon request.

United Nations—Department of Economic and Social Affairs. SDG7—ensure access to affordable, reliable, sustainable and modern energy for all. 2015. https://sdgs.un.org/goals/goal7 .

Leal Filho W, Marisa Azul A, Brandli L, Lange Salvia A, Wall T, editors. Affordable and clean energy. Cham: Springer International Publishing; 2021. https://doi.org/10.1007/978-3-319-95864-4_300078 .

Book   Google Scholar  

Plataforma Agenda 2030. Os 17 Objetivos de Desenvolvimento Sustentável—ODS7. 2020. http://www.agenda2030.com.br/ods/7/ .

Hafeznia H, Aslani A, Anwar S, Yousefjamali M. Analysis of the effectiveness of national renewable energy policies: a case of photovoltaic policies. Renew Sustain Energy Rev. 2017;79:669–80. https://doi.org/10.1016/j.rser.2017.05.033 .

Article   Google Scholar  

Halkos GE, Gkampoura E-C. Reviewing usage, potentials, and limitations of renewable energy sources. Energies. 2020;13(11):2906. https://doi.org/10.3390/en13112906 .

Drago C, Gatto A. Gauging energy poverty in developing countries with a composite metric of electricity access. Utilities Policy. 2023;81: 101486. https://doi.org/10.1016/j.jup.2022.101486 .

Newell RG, Raimi D, Villanueva S, Prest B. Global Energy Outlook 2020: energy transition or energy addition? 2020. https://media.rff.org/documents/GEO_2020_Report.pdf .

World Economic Forum. Fostering effective energy transition. 2019. http://www3.weforum.org/docs/WEF_Fostering_Effective_Energy_Transition_2019.pdf .

World Economic Forum. Energy for economic growth. 2012. http://www3.weforum.org/docs/WEF_EN_EnergyEconomicGrowth_IndustryAgenda_2012.pdf .

Mertzanis C, Garas S, Abdel-Maksoud A. Integrity of financial information and firms’ access to energy in developing countries. Energy Econ. 2020;92: 105005. https://doi.org/10.1016/j.eneco.2020.105005 .

Khribich A, Kacem RH, Dakhlaoui A. Causality nexus of renewable energy consumption and social development: evidence from high-income countries. Renew Energy. 2021;169:14–22. https://doi.org/10.1016/j.renene.2021.01.005 .

Gebreslassie MG. Development and manufacturing of solar and wind energy technologies in Ethiopia: challenges and policy implications. Renew Energy. 2021;168:107–18. https://doi.org/10.1016/j.renene.2020.11.042 .

Milani R, Caiado Couto L, Soria R, Szklo A, Lucena AFP. Promoting social development in developing countries through solar thermal power plants. J Clean Prod. 2020;246: 119072. https://doi.org/10.1016/j.jclepro.2019.119072 .

Adelaja AO. Barriers to national renewable energy policy adoption: insights from a case study of Nigeria. Energy Strat Rev. 2020;30: 100519. https://doi.org/10.1016/j.esr.2020.100519 .

Branca TA, Fornai B, Colla V, Pistelli MI, Faraci EL, Cirilli F, Schröder AJ. Skills demand in energy intensive industries targeting industrial symbiosis and energy efficiency. Sustainability. 2022;14(23):15615. https://doi.org/10.3390/su142315615 .

Malka L, Bidaj F, Kuriqi A, Jaku A, Roçi R, Gebremedhin A. Energy system analysis with a focus on future energy demand projections: the case of Norway. Energy. 2023;272: 127107. https://doi.org/10.1016/j.energy.2023.127107 .

Article   CAS   Google Scholar  

Mastrucci A, Niamir L, Boza-Kiss B, Bento N, Wiedenhofer D, Streeck J, Pachauri S, Wilson C, Chatterjee S, Creutzig F, Dukkipati S, Feng W, Grubler A, Jupesta J, Kumar P, Marangoni G, Saheb Y, Shimoda Y, Shoai-Tehrani B, … van Ruijven B. Modeling low energy demand futures for buildings: current state and research. Annual Review of Environment and Resources, Volume 48, 20232023.

Mohsin M, Taghizadeh-Hesary F, Shahbaz M. Nexus between financial development and energy poverty in Latin America. Energy Policy. 2022;165: 112925. https://doi.org/10.1016/j.enpol.2022.112925 .

González FAI, Ibáñez-Martín MM. Six decades of energy poverty: reducing disparities in Latin America and the Caribbean? Revista INVI. 2023;38(109):71–99. https://doi.org/10.5354/0718-8358.2023.70125 .

Mahlknecht J, González-Bravo R, Loge FJ. Water-energy-food security: a nexus perspective of the current situation in Latin America and the Caribbean. Energy. 2020;194: 116824.

Ravillard P, Carvajal F, Soto DDL, Chueca JE, Antonio K, Ji Y, Hallack MCM. Towards greater energy efficiency in Latin America and the Caribbean: progress and policies, Vol 784. Inter-American Development Bank. 2019.

Warner KJ, Jones GA. Energy and population in Sub-Saharan Africa: energy for four billion? Environments. 2018;5(10):107.

Thomson H, Day R, Ricalde K, Brand-Correa LI, Cedano K, Martinez M, Santillán O, Delgado Triana Y, Luis Cordova JG, Milian Gómez JF, Garcia Torres D, Mercado C, Castelao Caruana ME, Pereira MG. Understanding, recognizing, and sharing energy poverty knowledge and gaps in Latin America and the Caribbean—because conoceres resolver. Energy Res Soc Sci. 2022;87: 102475. https://doi.org/10.1016/j.erss.2021.102475 .

Guzowski C, Martin MMI, Zabaloy MF. Energy poverty: conceptualization and its link to exclusion. Brief review for Latin America. Ambiente Sociedade. 2021;24: e00272.

World Bank. Productive inclusion in Latin America: policy and operational lessons. World Bank. 2020.

Malaquias RF, Borges Junior DM, Malaquias FFdO, Albertin AL. Climate protection or corporate promotion? Energy companies, development, and sustainability reports in Latin America. Energy Res Soc Sci. 2019;54:150–6. https://doi.org/10.1016/j.erss.2019.04.001 .

Castaño-Rosa R, Solís-Guzmán J, Rubio-Bellido C, Marrero M. Towards a multiple-indicator approach to energy poverty in the European Union: a review. Energy Build. 2019;193:36–48. https://doi.org/10.1016/j.enbuild.2019.03.039 .

Faiella, I., Lavecchia, L. Energy poverty indicators. In Urban fuel poverty. Elsevier; 2019. pp. 127–141. https://doi.org/10.1016/B978-0-12-816952-0.00006-5 .

Dobbins A, Nerini FF, Deane P, Pye S. Strengthening the EU response to energy poverty. Nat Energy. 2019;4(1):2–5. https://doi.org/10.1038/s41560-018-0316-8 .

González-Eguino M. Energy poverty: an overview. Renew Sustain Energy Rev. 2015;47:377–85. https://doi.org/10.1016/j.rser.2015.03.013 .

Wang K, Wang YX, Li K, Wei YM. Energy poverty in China: an index based comprehensive evaluation. Renew Sustain Energy Rev. 2015;47:308–23.

Bouzarovski S, Petrova S, Sarlamanov R. Energy poverty policies in the EU: a critical perspective. Energy Policy. 2012;49:76–82. https://doi.org/10.1016/j.enpol.2012.01.033 .

Teschner N, Sinea A, Vornicu A, Abu-Hamed T, Negev M. Extreme energy poverty in the urban peripheries of Romania and Israel: policy, planning and infrastructure. Energy Res Soc Sci. 2020;66: 101502. https://doi.org/10.1016/j.erss.2020.101502 .

Bouzarovski S, Petrova S. A global perspective on domestic energy deprivation: overcoming the energy poverty–fuel poverty binary. Energy Res Soc Sci. 2015;10:31–40. https://doi.org/10.1016/j.erss.2015.06.007 .

Urquiza A, Amigo C, Billi M, Calvo R, Labraña J, Oyarzún T, Valencia F. Quality as a hidden dimension of energy poverty in middle-development countries. Literature review and case study from Chile. Energy Build. 2019;204: 109463. https://doi.org/10.1016/j.enbuild.2019.109463 .

Qurat-ul-Ann AR, Mirza FM. Meta-analysis of empirical evidence on energy poverty: the case of developing economies. Energy Policy. 2020;141: 111444. https://doi.org/10.1016/j.enpol.2020.111444 .

Nussbaumer P, Bazilian M, Modi V. Measuring energy poverty: focusing on what matters. Renew Sustain Energy Rev. 2012;16(1):231–43. https://doi.org/10.1016/j.rser.2011.07.150 .

Ochoa RG. Pobreza energética en América Latina. Comisión Económica para América Latina y el Caribe (CEPAL). 2014; 36. http://hdl.handle.net/11362/36661 .

Santillán OS, Cedano KG, Martínez M. Analysis of energy poverty in 7 Latin American countries using multidimensional energy poverty index. Energies. 2020;13(7):1608. https://doi.org/10.3390/en13071608 .

Quishpe SP, Taltavull LPP, Juárez TF. Energy poverty in Ecuador. Sustainability. 2019;11:6320. https://doi.org/10.3390/su11226320 .

García Ochoa R, Graizbord B. Privation of energy services in Mexican households: an alternative measure of energy poverty. Energy Res Soc Sci. 2016;18:36–49. https://doi.org/10.1016/j.erss.2016.04.014 .

IEA. SDG7: Data and projections [WWW Document]. 2020. https://www.iea.org/reports/sdg7-data-and-projections/access-to-electricity . Accessed 1 Dec 2021.

Robles-Bonilla T, Cedano KG. Addressing thermal comfort in regional energy poverty assessment with Nussbaumer’s MEPI. Sustainability. 2021. https://doi.org/10.3390/su13010352 .

Koengkan M, Poveda YE, Fuinhas JA. Globalisation as a motor of renewable energy development in Latin America countries. GeoJournal. 2020;85:1591–602. https://doi.org/10.1007/s10708-019-10042-0 .

Butera FM, Caputo P, Adhikari RS, Mele R. Energy access in informal settlements. Results of a wide on site survey in Rio De Janeiro. Energy Policy. 2019;134: 110943. https://doi.org/10.1016/j.enpol.2019.110943 .

de Halleux M, Estache A, Serebrisky T. Governance choices and policy outcomes in the Latin American and Caribbean electricity sector. Util Policy. 2020;67: 101105. https://doi.org/10.1016/j.jup.2020.101105 .

Jenkins K, McCauley D, Heffron R, Stephan H, Rehner R. Energy justice: a conceptual review. Energy Res Soc Sci. 2016;11:174–82. https://doi.org/10.1016/j.erss.2015.10.004 .

Bouzarovski S, Simcock N. Spatializing energy justice. Energy Policy. 2017;107:640–8. https://doi.org/10.1016/j.enpol.2017.03.064 .

Thomson H, Simcock N, Bouzarovski S, Petrova S. Energy poverty and indoor cooling: an overlooked issue in Europe. Energy Build. 2019;196:21–9. https://doi.org/10.1016/j.enbuild.2019.05.014 .

Meyer S, Laurence H, Bart D, Middlemiss L, Maréchal K. Capturing the multifaceted nature of energy poverty: lessons from Belgium. Energy Res Soc Sci. 2018;40:273–83. https://doi.org/10.1016/j.erss.2018.01.017 .

Van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics. 2010;84(2):523–38. https://doi.org/10.1007/s11192-009-0146-3 .

Szabó S, Bódis K, Huld T, Moner-Girona M. Sustainable energy planning: leapfrogging the energy poverty gap in Africa. Renew Sustain Energy Rev. 2013;28:500–9. https://doi.org/10.1016/j.rser.2013.08.044 .

Paudel J, Sharifi A, Khan GD. What are the drivers of sustainable energy transition? Insights from an empirical analysis of household preferences for electric induction cooking in Nepal. J Clean Prod. 2023;417: 138021. https://doi.org/10.1016/j.jclepro.2023.138021 .

Suberu MY, Mustafa MW, Bashir N, Muhamad NA, Mokhtar AS. Power sector renewable energy integration for expanding access to electricity in sub-Saharan Africa. Renew Sustain Energy Rev. 2013;25:630–42. https://doi.org/10.1016/j.rser.2013.04.033 .

Amuzu-Sefordzi B, Martinus K, Tschakert P, Wills R. Disruptive innovations and decentralized renewable energy systems in Africa: a socio-technical review. Energy Res Soc Sci. 2018;46:140–54. https://doi.org/10.1016/j.erss.2018.06.014 .

Baldwin E, Brass JN, Carley S, MacLean LM. Electrification and rural development: issues of scale in distributed generation. WIREs Energy Environ. 2015;4(2):196–211. https://doi.org/10.1002/wene.129Barnes .

Baker E, Nock D, Levin T, Atarah SA, Afful-Dadzie A, Dodoo-Arhin D, et al. Who is marginalized in energy justice? Amplifying community leader perspectives of energy transitions in Ghana. Energy Res Soc Sci. 2021;73: 101933. https://doi.org/10.1016/j.erss.2021.101933 .

Domegni KMS, Azouma YO. Productive uses of energy: a solution for promoting energy justice in rural areas in West Africa. Renew Sustain Energy Rev. 2022;160: 112298. https://doi.org/10.1016/j.rser.2022.112298 .

Thomson H, Bouzarovski S, Snell C. Rethinking the measurement of energy poverty in Europe: a critical analysis of indicators and data. Indoor Built Environ. 2017;26(7):879–901. https://doi.org/10.1177/1420326x17699260 .

Thomson H, Snell C. Quantifying the prevalence of fuel poverty across the European Union. Energy Policy. 2013;52:563–72. https://doi.org/10.1016/j.enpol.2012.10.009 .

Al Kez D, Foley A, Lowans C, Del Rio DF. Energy poverty assessment: Indicators and implications for developing and developed countries. Energy Convers Manage. 2024;307: 118324. https://doi.org/10.1016/j.enconman.2024.118324 .

Bouzarovski S. Understanding energy poverty, vulnerability and justice. In: Bouzarovski S, editor. Energy poverty: (dis)assembling Europe’s infrastructural divide. Cham: Springer International Publishing; 2018. p. 9–39.

Chapter   Google Scholar  

Butler C. Energy poverty, practice, and inequality. In: Butler C, editor. Energy poverty, practice, and policy. Cham: Springer International Publishing; 2022. p. 105–22.

Hesselman M, Varo A, Guyet R, Thomson H. Energy poverty in the COVID-19 era: mapping global responses in light of momentum for the right to energy. Energy Res Soc Sci. 2021;81: 102246. https://doi.org/10.1016/j.erss.2021.102246 .

Jessel S, Sawyer S, Hernández D. Energy, poverty, and health in climate change: a comprehensive review of an emerging literature. Front Public Health. 2019. https://doi.org/10.3389/fpubh.2019.00357 .

Daka E. Adopting clean technologies to climate change adaptation strategies in Africa: a systematic literature review. Environ Manage. 2023;71(1):87–98. https://doi.org/10.1007/s00267-022-01704-w .

Casillas CE, Kammen DM. The energy-poverty-climate nexus. Science. 2010;330(6008):1181–2. https://doi.org/10.1126/science.1197412 .

Chakravarty S, Tavoni M. Energy poverty alleviation and climate change mitigation: is there a trade-off? Energy Econ. 2013;40:S67–73. https://doi.org/10.1016/j.eneco.2013.09.022 .

Sharifi A, Pathak M, Joshi C, He BJ. A systematic review of the health co-benefits of urban climate change adaptation. Sustain Cities Soc. 2021;74:15. https://doi.org/10.1016/j.scs.2021.103190 .

Cong S, Nock D, Qiu YL, Xing B. Unveiling hidden energy poverty using the energy equity gap. Nat Commun. 2022;13(1):2456. https://doi.org/10.1038/s41467-022-30146-5 .

Halkos GE, Aslanidis P-SC. Addressing multidimensional energy poverty implications on achieving sustainable development. Energies. 2023. https://doi.org/10.3390/en16093805 .

Huang J, Wang X, Liu H, Iqbal S. Financial consideration of energy and environmental nexus with energy poverty: promoting financial development in G7 economies. Front Energy Res. 2021. https://doi.org/10.3389/fenrg.2021.777796 .

Nguyen CP, Su TD, Bui TD, Dang VTB, Nguyen BQ. Financial development and energy poverty: global evidence. Environ Sci Pollut Res. 2021;28(26):35188–225. https://doi.org/10.1007/s11356-021-13038-x .

Gouveia N, Slovic AD, Kanai CM, Soriano L. Air pollution and environmental justice in Latin America: where are we and how can we move forward? Curr Environ Health Rep. 2022;9(2):152–64. https://doi.org/10.1007/s40572-022-00341-z .

Martinez-Soto A, Avendaño Vera CC, Boso A, Hofflinger A, Shupler M. Energy poverty influences urban outdoor air pollution levels during COVID-19 lockdown in south-central Chile. Energy Policy. 2021;158: 112571. https://doi.org/10.1016/j.enpol.2021.112571 .

Amigo-Jorquera C, Guerrero-González MJ, Sannazzaro J, Urquiza-Gómez A. Does energy poverty have a female face in Chile? Tapuya: Latin American Science. Technol Soc. 2019;2(1):378–90. https://doi.org/10.1080/25729861.2019.1608038 .

Nguyen CP, Su TD. Does energy poverty matter for gender inequality? Global evidence. Energy Sustain Dev. 2021;64:35–45. https://doi.org/10.1016/j.esd.2021.07.003 .

World bank. Poverty is not gender neutral in Latin America and the Caribbean. 2024. https://blogs.worldbank.org/en/latinamerica/poverty-not-gender-neutral-latin-america-and-caribbean . Accessed 17 Apr 2024.

Pereira MG, Freitas MAV, da Silva NF. Rural electrification and energy poverty: empirical evidence from Brazil. Renew Sustain Energy Rev. 2010;14(4):1229–40. https://doi.org/10.1016/j.rser.2009.12.013 .

Pachauri S, Spreng D. Measuring and monitoring energy poverty. Energy Policy. 2011;39(12):7497–504. https://doi.org/10.1016/j.enpol.2011.07.008 .

Choi GY, Kim HS, Kim H, Lee JS. How do paving and planting strategies affect microclimate conditions and thermal comfort in apartment complexes? Int J Clim Change Strateg Manag. 2021;13(2):97–119. https://doi.org/10.1108/IJCCSM-06-2020-0063 .

Barratt MJ, Ferris JA, Lenton S. Hidden populations, online purposive sampling, and external validity: taking off the blindfold. Field Methods. 2015;27(1):3–21. https://doi.org/10.1177/1525822X14526838 .

Khandker SR, Barnes DF, Samad HA. Are the energy poor also income poor? Evidence from India. Energy Policy. 2012;47:1–12. https://doi.org/10.1016/j.enpol.2012.02.028 .

United Nations Organization. Transforming our world: the 2030 agenda for sustainable development. Brazilian Ministry of Foreign Affairs. 2016. https://www.undp.org/content/dam/brazil/docs/agenda2030/undp-br-Agenda2030-completo-pt-br-2016.pdf .

Okushima S. Gauging energy poverty: a multidimensional approach. Energy. 2017;137:1159–66. https://doi.org/10.1016/j.energy.2017.05.137 .

Barnes DF, Khandker SR, Samad HA. Energy poverty in rural Bangladesh. Energy Policy. 2011;39(2):894–904. https://doi.org/10.1016/j.enpol.2010.11.014 .

Download references

Acknowledgements

This paper is part of the "100 papers to accelerate the implementation of the UN Sustainable Development Goals" initiative.

Andrea Gatto wishes to acknowledge funding from the Internal Faculty Start-Up Research Grant of Wenzhou-Kean University Project No. ISRG2023014.

Author information

Pastor David Chávez Muñoz

Present address: Department of Engineering, GTR-PUCP, Pontificia Universidad Catolica del Peru, 1801 Avenida Universitaria San Miguel, 15088, Lima, Peru

Authors and Affiliations

European School of Sustainability Science and Research, Hamburg University of Applied Sciences, Hamburg, Germany

Walter Leal Filho & João Henrique Paulino Pires Eustachio

Department of Natural Sciences, Manchester Metropolitan University, Chester Street, Manchester, M1 5GD, UK

Walter Leal Filho

School of Economics, Finance and Banking, Universiti Utara Malaysia, UUM Sintok, 06010, Kedah, Malaysia

Halima Begum

Centre for Studies on European Economy, Azerbaijan State University of Economics (UNEC), Istiqlaliyyet Ave. 7, 1007, Baku, Azerbaijan

School of Mechanical Engineering, University of Campinas, Mendeleyev Street, Campinas, 200, Brazil

Rosley Anholon

Master Program in Management Systems and Doctoral Program in Sustainable Management Systems, Federal Fluminense University, Passo da Pátria Street, Niterói, 156, Brazil

Osvaldo Quelhas

Departamento de Ingeniería Industrial, Universidad Católica del Norte, Antofagasta, Chile

Izabela Rampasso

The IDEC Institute, Hiroshima University, Higashihiroshima, 739-8530, Japan

Ayyoob Sharifi

School of Architecture and Design, Lebanese American University, Beirut, Lebanon

Centre for Sustainable Development (GREENS) at the University of Southern Santa Catarina (UNISUL), Tubarao, Brazil

José Baltazar Salgueirinho Osório de Andrade Guerra

Cambridge Centre for Environment, Energy and Natural Resource Governance, (CEENRG), University of Cambridge, Cambridge, UK

College of Business and Public Management, Wenzhou-Kean University, Wenzhou, 325060, Zhejiang Province, China

Andrea Gatto

Centre for Studies on Europe, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan

Division of International Studies, College of International Studies, Korea University, 145 Anam-Ro, Seongbuk-Gu, Seoul, 02841, Republic of Korea

University of Gloucestershire, BV205 Park Campus The Park, Cheltenham, GL50 2RH, UK

Matthew Lovett

Industrial Engineering, University of Sonora, Hermosillo, Mexico

Luis Velazquez

School of Business Management, Universiti Utara Malaysia, UUM Sintok, 06010, Kedah, Malaysia

A. S. A. Ferdous Alam

Graduate Program in Civil and Environmental Engineering, University of Passo Fundo, Campus I-BR 285, Passo Fundo, São José, RS, 99052-900, Brazil

Luciana Brandli

Research and Transfer Centre “Sustainable Development and Climate Change Management”, Hamburg University of Applied Sciences, Ulmenliet 20, 21033, Hamburg, Germany

Amanda Lange Salvia

Universidad Galileo, 7a. Avenida, Calle Dr. Eduardo Suger Cofiño, Zona 10, Guatemala City, Guatemala

Nelson Amaro

Faculty of Economics, University of Algarve, 8005-139, Faro, Portugal

You can also search for this author in PubMed   Google Scholar

Contributions

W. Leal Filho—Original Ideas, Revisions; H. Begum-Introduction, literature review, data collection, methods, analysis, discussion, and conclusion, Revisions, R. Anholon—Introduction, Revisions, O. Quelhas—Introduction, I. Rampasso—Literature Review, Revisions, A. Sharifi—Methods, Revisions, J. B. S. O. de A. Guerra-Questionnaire Developed, A. Gatto—Introduction, Literature Review, Analysis, Discussion & Conclusion, Revisions, Funding, M. Lovett—Analysis & Discussion, Revisions, L. Velazquez—Analysis, Pastor David Chávez Muñoz—Analysis, A. S. A. F. Alam—Questionnaire Developed, Data collection, & Revision; L. Brandli—Professionally added, A. L. Salvia—Questionnaire developed, Data collection, Revisions, Nelson Amaro—Professionally added, J. H. P. P. Eustachio—Analysis.

Corresponding author

Correspondence to Andrea Gatto .

Ethics declarations

Ethics approval and consent to participate.

Consents to participate were obtained from all survey participants, who ticked a box expressing their agreement to take part in the study.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix 1. Search string for the bibliometric analysis

General search string: TS = (“energy poverty”)

Search string for Latin America: TS = (“energy poverty”) AND (“Argentina” OR “Bolivia” Or “Brazil” OR “Chile” or “Colombia” OR “Costa Rica” or “Cuba” OR “Dominican Republic” OR “Ecuador” OR “El Salvador” OR “Guatemala” OR “Haiti” OR “Honduras” OR “Mexico” OR “Nicaragua” OR “Panama” OR “Paraguay” OR “Peru” OR “Uruguay” OR “Venezuela” OR “central America” OR “south America” OR “latin America”).

Appendix 2. Questionnaire

2.1 addressing the challenges posed by energy poverty in latin american countries.

This questionnaire is part of the study ‘ Addressing the Challenges Posed by Energy Poverty in Latin American Countries’.

Your participation is voluntary, and there are no right or wrong answers. We are interested in knowing your personal understanding. The survey completion is expected to take around 15 min.

It should be noted that the answers given are strictly confidential, used only for statistical treatment. We commit to respect the protection of personal data, guaranteeing its confidentiality. Should you wish to receive a copy of the paper where the results are presented, please let us know: [email protected].

Thank you for your contribution!

All responses are treated anonymously. If you wish to receive a summary of the results, please send a message to: [email protected].

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Leal Filho, W., Begum, H., Anholon, R. et al. Addressing the challenges posed by energy poverty in Latin American countries. Discov Sustain 5 , 262 (2024). https://doi.org/10.1007/s43621-024-00426-9

Download citation

Received : 01 November 2023

Accepted : 19 August 2024

Published : 12 September 2024

DOI : https://doi.org/10.1007/s43621-024-00426-9

Share this article

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

• Energy development
• Energy poverty
• Posed challenges
• Bibliometric analysis
• Latin America

Advertisement

• Find a journal
• Publish with us
• Track your research