questionnaire dissertation methodology

How To Write The Methodology Chapter

The what, why & how explained simply (with examples).

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | September 2021 (Updated April 2023)

So, you’ve pinned down your research topic and undertaken a review of the literature – now it’s time to write up the methodology section of your dissertation, thesis or research paper . But what exactly is the methodology chapter all about – and how do you go about writing one? In this post, we’ll unpack the topic, step by step .

Overview: The Methodology Chapter

• The purpose  of the methodology chapter
• Why you need to craft this chapter (really) well
• How to write and structure the chapter
• Methodology chapter example
• Essential takeaways

What (exactly) is the methodology chapter?

The methodology chapter is where you outline the philosophical underpinnings of your research and outline the specific methodological choices you’ve made. The point of the methodology chapter is to tell the reader exactly how you designed your study and, just as importantly, why you did it this way.

Importantly, this chapter should comprehensively describe and justify all the methodological choices you made in your study. For example, the approach you took to your research (i.e., qualitative, quantitative or mixed), who  you collected data from (i.e., your sampling strategy), how you collected your data and, of course, how you analysed it. If that sounds a little intimidating, don’t worry – we’ll explain all these methodological choices in this post .

Why is the methodology chapter important?

The methodology chapter plays two important roles in your dissertation or thesis:

Firstly, it demonstrates your understanding of research theory, which is what earns you marks. A flawed research design or methodology would mean flawed results. So, this chapter is vital as it allows you to show the marker that you know what you’re doing and that your results are credible .

Secondly, the methodology chapter is what helps to make your study replicable. In other words, it allows other researchers to undertake your study using the same methodological approach, and compare their findings to yours. This is very important within academic research, as each study builds on previous studies.

The methodology chapter is also important in that it allows you to identify and discuss any methodological issues or problems you encountered (i.e., research limitations ), and to explain how you mitigated the impacts of these. Every research project has its limitations , so it’s important to acknowledge these openly and highlight your study’s value despite its limitations . Doing so demonstrates your understanding of research design, which will earn you marks. We’ll discuss limitations in a bit more detail later in this post, so stay tuned!

Need a helping hand?

How to write up the methodology chapter

First off, it’s worth noting that the exact structure and contents of the methodology chapter will vary depending on the field of research (e.g., humanities, chemistry or engineering) as well as the university . So, be sure to always check the guidelines provided by your institution for clarity and, if possible, review past dissertations from your university. Here we’re going to discuss a generic structure for a methodology chapter typically found in the sciences.

Before you start writing, it’s always a good idea to draw up a rough outline to guide your writing. Don’t just start writing without knowing what you’ll discuss where. If you do, you’ll likely end up with a disjointed, ill-flowing narrative . You’ll then waste a lot of time rewriting in an attempt to try to stitch all the pieces together. Do yourself a favour and start with the end in mind .

Section 1 – Introduction

As with all chapters in your dissertation or thesis, the methodology chapter should have a brief introduction. In this section, you should remind your readers what the focus of your study is, especially the research aims . As we’ve discussed many times on the blog, your methodology needs to align with your research aims, objectives and research questions. Therefore, it’s useful to frontload this component to remind the reader (and yourself!) what you’re trying to achieve.

In this section, you can also briefly mention how you’ll structure the chapter. This will help orient the reader and provide a bit of a roadmap so that they know what to expect. You don’t need a lot of detail here – just a brief outline will do.

Section 2 – The Methodology

The next section of your chapter is where you’ll present the actual methodology. In this section, you need to detail and justify the key methodological choices you’ve made in a logical, intuitive fashion. Importantly, this is the heart of your methodology chapter, so you need to get specific – don’t hold back on the details here. This is not one of those “less is more” situations.

Let’s take a look at the most common components you’ll likely need to cover. 

Methodological Choice #1 – Research Philosophy

Research philosophy refers to the underlying beliefs (i.e., the worldview) regarding how data about a phenomenon should be gathered , analysed and used . The research philosophy will serve as the core of your study and underpin all of the other research design choices, so it’s critically important that you understand which philosophy you’ll adopt and why you made that choice. If you’re not clear on this, take the time to get clarity before you make any further methodological choices.

While several research philosophies exist, two commonly adopted ones are positivism and interpretivism . These two sit roughly on opposite sides of the research philosophy spectrum.

Positivism states that the researcher can observe reality objectively and that there is only one reality, which exists independently of the observer. As a consequence, it is quite commonly the underlying research philosophy in quantitative studies and is oftentimes the assumed philosophy in the physical sciences.

Contrasted with this, interpretivism , which is often the underlying research philosophy in qualitative studies, assumes that the researcher performs a role in observing the world around them and that reality is unique to each observer . In other words, reality is observed subjectively .

These are just two philosophies (there are many more), but they demonstrate significantly different approaches to research and have a significant impact on all the methodological choices. Therefore, it’s vital that you clearly outline and justify your research philosophy at the beginning of your methodology chapter, as it sets the scene for everything that follows.

Methodological Choice #2 – Research Type

The next thing you would typically discuss in your methodology section is the research type. The starting point for this is to indicate whether the research you conducted is inductive or deductive .

Inductive research takes a bottom-up approach , where the researcher begins with specific observations or data and then draws general conclusions or theories from those observations. Therefore these studies tend to be exploratory in terms of approach.

Conversely , d eductive research takes a top-down approach , where the researcher starts with a theory or hypothesis and then tests it using specific observations or data. Therefore these studies tend to be confirmatory in approach.

Related to this, you’ll need to indicate whether your study adopts a qualitative, quantitative or mixed  approach. As we’ve mentioned, there’s a strong link between this choice and your research philosophy, so make sure that your choices are tightly aligned . When you write this section up, remember to clearly justify your choices, as they form the foundation of your study.

Methodological Choice #3 – Research Strategy

Next, you’ll need to discuss your research strategy (also referred to as a research design ). This methodological choice refers to the broader strategy in terms of how you’ll conduct your research, based on the aims of your study.

Several research strategies exist, including experimental , case studies , ethnography , grounded theory, action research , and phenomenology . Let’s take a look at two of these, experimental and ethnographic, to see how they contrast.

Experimental research makes use of the scientific method , where one group is the control group (in which no variables are manipulated ) and another is the experimental group (in which a specific variable is manipulated). This type of research is undertaken under strict conditions in a controlled, artificial environment (e.g., a laboratory). By having firm control over the environment, experimental research typically allows the researcher to establish causation between variables. Therefore, it can be a good choice if you have research aims that involve identifying causal relationships.

Ethnographic research , on the other hand, involves observing and capturing the experiences and perceptions of participants in their natural environment (for example, at home or in the office). In other words, in an uncontrolled environment.  Naturally, this means that this research strategy would be far less suitable if your research aims involve identifying causation, but it would be very valuable if you’re looking to explore and examine a group culture, for example.

As you can see, the right research strategy will depend largely on your research aims and research questions – in other words, what you’re trying to figure out. Therefore, as with every other methodological choice, it’s essential to justify why you chose the research strategy you did.

Methodological Choice #4 – Time Horizon

The next thing you’ll need to detail in your methodology chapter is the time horizon. There are two options here: cross-sectional and longitudinal . In other words, whether the data for your study were all collected at one point in time (cross-sectional) or at multiple points in time (longitudinal).

The choice you make here depends again on your research aims, objectives and research questions. If, for example, you aim to assess how a specific group of people’s perspectives regarding a topic change over time , you’d likely adopt a longitudinal time horizon.

Another important factor to consider is simply whether you have the time necessary to adopt a longitudinal approach (which could involve collecting data over multiple months or even years). Oftentimes, the time pressures of your degree program will force your hand into adopting a cross-sectional time horizon, so keep this in mind.

Methodological Choice #5 – Sampling Strategy

Next, you’ll need to discuss your sampling strategy . There are two main categories of sampling, probability and non-probability sampling.

Probability sampling involves a random (and therefore representative) selection of participants from a population, whereas non-probability sampling entails selecting participants in a non-random  (and therefore non-representative) manner. For example, selecting participants based on ease of access (this is called a convenience sample).

The right sampling approach depends largely on what you’re trying to achieve in your study. Specifically, whether you trying to develop findings that are generalisable to a population or not. Practicalities and resource constraints also play a large role here, as it can oftentimes be challenging to gain access to a truly random sample. In the video below, we explore some of the most common sampling strategies.

Methodological Choice #6 – Data Collection Method

Next up, you’ll need to explain how you’ll go about collecting the necessary data for your study. Your data collection method (or methods) will depend on the type of data that you plan to collect – in other words, qualitative or quantitative data.

Typically, quantitative research relies on surveys , data generated by lab equipment, analytics software or existing datasets. Qualitative research, on the other hand, often makes use of collection methods such as interviews , focus groups , participant observations, and ethnography.

So, as you can see, there is a tight link between this section and the design choices you outlined in earlier sections. Strong alignment between these sections, as well as your research aims and questions is therefore very important.

Methodological Choice #7 – Data Analysis Methods/Techniques

The final major methodological choice that you need to address is that of analysis techniques . In other words, how you’ll go about analysing your date once you’ve collected it. Here it’s important to be very specific about your analysis methods and/or techniques – don’t leave any room for interpretation. Also, as with all choices in this chapter, you need to justify each choice you make.

What exactly you discuss here will depend largely on the type of study you’re conducting (i.e., qualitative, quantitative, or mixed methods). For qualitative studies, common analysis methods include content analysis , thematic analysis and discourse analysis . In the video below, we explain each of these in plain language.

For quantitative studies, you’ll almost always make use of descriptive statistics , and in many cases, you’ll also use inferential statistical techniques (e.g., correlation and regression analysis). In the video below, we unpack some of the core concepts involved in descriptive and inferential statistics.

In this section of your methodology chapter, it’s also important to discuss how you prepared your data for analysis, and what software you used (if any). For example, quantitative data will often require some initial preparation such as removing duplicates or incomplete responses . Similarly, qualitative data will often require transcription and perhaps even translation. As always, remember to state both what you did and why you did it.

Section 3 – The Methodological Limitations

With the key methodological choices outlined and justified, the next step is to discuss the limitations of your design. No research methodology is perfect – there will always be trade-offs between the “ideal” methodology and what’s practical and viable, given your constraints. Therefore, this section of your methodology chapter is where you’ll discuss the trade-offs you had to make, and why these were justified given the context.

Methodological limitations can vary greatly from study to study, ranging from common issues such as time and budget constraints to issues of sample or selection bias . For example, you may find that you didn’t manage to draw in enough respondents to achieve the desired sample size (and therefore, statistically significant results), or your sample may be skewed heavily towards a certain demographic, thereby negatively impacting representativeness .

In this section, it’s important to be critical of the shortcomings of your study. There’s no use trying to hide them (your marker will be aware of them regardless). By being critical, you’ll demonstrate to your marker that you have a strong understanding of research theory, so don’t be shy here. At the same time, don’t beat your study to death . State the limitations, why these were justified, how you mitigated their impacts to the best degree possible, and how your study still provides value despite these limitations .

Section 4 – Concluding Summary

Finally, it’s time to wrap up the methodology chapter with a brief concluding summary. In this section, you’ll want to concisely summarise what you’ve presented in the chapter. Here, it can be a good idea to use a figure to summarise the key decisions, especially if your university recommends using a specific model (for example, Saunders’ Research Onion ).

Importantly, this section needs to be brief – a paragraph or two maximum (it’s a summary, after all). Also, make sure that when you write up your concluding summary, you include only what you’ve already discussed in your chapter; don’t add any new information.

Methodology Chapter Example

In the video below, we walk you through an example of a high-quality research methodology chapter from a dissertation. We also unpack our free methodology chapter template so that you can see how best to structure your chapter.

Wrapping Up

And there you have it – the methodology chapter in a nutshell. As we’ve mentioned, the exact contents and structure of this chapter can vary between universities , so be sure to check in with your institution before you start writing. If possible, try to find dissertations or theses from former students of your specific degree program – this will give you a strong indication of the expectations and norms when it comes to the methodology chapter (and all the other chapters!).

Also, remember the golden rule of the methodology chapter – justify every choice ! Make sure that you clearly explain the “why” for every “what”, and reference credible methodology textbooks or academic sources to back up your justifications.

If you need a helping hand with your research methodology (or any other component of your research), be sure to check out our private coaching service , where we hold your hand through every step of the research journey. Until next time, good luck!

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Harvard University Program on Survey Research

• How to Frame and Explain the Survey Data Used in a Thesis

Surveys are a special research tool with strengths, weaknesses, and a language all of their own. There are many different steps to designing and conducting a survey, and survey researchers have specific ways of describing what they do.

This handout, based on an annual workshop offered by the Program on Survey Research at Harvard, is geared toward undergraduate honors thesis writers using survey data.

PSR Resources

• Managing and Manipulating Survey Data: A Beginners Guide
• Finding and Hiring Survey Contractors
• Overview of Cognitive Testing and Questionnaire Evaluation
• Questionnaire Design Tip Sheet
• Sampling, Coverage, and Nonresponse Tip Sheet
• Introduction to Surveys for Honors Thesis Writers
• PSR Introduction to the Survey Process
• Related Centers/Programs at Harvard
• General Survey Reference
• Institutional Review Boards
• Select Funding Opportunities
• Survey Analysis Software
• Professional Standards
• Professional Organizations
• Major Public Polls
• Survey Data Collections
• Major Longitudinal Surveys
• Other Links

Questionnaires

Questionnaires can be classified as both, quantitative and qualitative method depending on the nature of questions. Specifically, answers obtained through closed-ended questions (also called restricted questions) with multiple choice answer options are analyzed using quantitative methods. Research findings in this case can be illustrated using tabulations, pie-charts, bar-charts and percentages.

Answers obtained to open-ended questionnaire questions (also known as unrestricted questions), on the other hand, are analyzed using qualitative methods. Primary data collected using open-ended questionnaires involve discussions and critical analyses without use of numbers and calculations.

There are following types of questionnaires:

Computer questionnaire . Respondents are asked to answer the questionnaire which is sent by mail. The advantages of the computer questionnaires include their inexpensive price, time-efficiency, and respondents do not feel pressured, therefore can answer when they have time, giving more accurate answers. However, the main shortcoming of the mail questionnaires is that sometimes respondents do not bother answering them and they can just ignore the questionnaire.

Telephone questionnaire .  Researcher may choose to call potential respondents with the aim of getting them to answer the questionnaire. The advantage of the telephone questionnaire is that, it can be completed during the short amount of time. The main disadvantage of the phone questionnaire is that it is expensive most of the time. Moreover, most people do not feel comfortable to answer many questions asked through the phone and it is difficult to get sample group to answer questionnaire over the phone.

In-house survey .  This type of questionnaire involves the researcher visiting respondents in their houses or workplaces. The advantage of in-house survey is that more focus towards the questions can be gained from respondents. However, in-house surveys also have a range of disadvantages which include being time consuming, more expensive and respondents may not wish to have the researcher in their houses or workplaces for various reasons.

Mail Questionnaire . This sort of questionnaires involve the researcher to send the questionnaire list to respondents through post, often attaching pre-paid envelope. Mail questionnaires have an advantage of providing more accurate answer, because respondents can answer the questionnaire in their spare time. The disadvantages associated with mail questionnaires include them being expensive, time consuming and sometimes they end up in the bin put by respondents.

Questionnaires can include the following types of questions:

Open question questionnaires . Open questions differ from other types of questions used in questionnaires in a way that open questions may produce unexpected results, which can make the research more original and valuable. However, it is difficult to analyze the results of the findings when the data is obtained through the questionnaire with open questions.

Multiple choice question s. Respondents are offered a set of answers they have to choose from. The downsize of questionnaire with multiple choice questions is that, if there are too many answers to choose from, it makes the questionnaire, confusing and boring, and discourages the respondent to answer the questionnaire.

Dichotomous Questions .  Thes type of questions gives two options to respondents – yes or no, to choose from. It is the easiest form of questionnaire for the respondent in terms of responding it.

Scaling Questions . Also referred to as ranking questions, they present an option for respondents to rank the available answers to questions on the scale of given range of values (for example from 1 to 10).

For a standard 15,000-20,000 word business dissertation including 25-40 questions in questionnaires will usually suffice. Questions need be formulated in an unambiguous and straightforward manner and they should be presented in a logical order.

Questionnaires as primary data collection method offer the following advantages:

• Uniformity: all respondents are asked exactly the same questions
• Cost-effectiveness
• Possibility to collect the primary data in shorter period of time
• Minimum or no bias from the researcher during the data collection process
• Usually enough time for respondents to think before answering questions, as opposed to interviews
• Possibility to reach respondents in distant areas through online questionnaire

At the same time, the use of questionnaires as primary data collection method is associated with the following shortcomings:

• Random answer choices by respondents without properly reading the question.
• In closed-ended questionnaires no possibility for respondents to express their additional thoughts about the matter due to the absence of a relevant question.
• Collecting incomplete or inaccurate information because respondents may not be able to understand questions correctly.
• High rate of non-response

Survey Monkey represents one of the most popular online platforms for facilitating data collection through questionnaires. Substantial benefits offered by Survey Monkey include its ease to use, presentation of questions in many different formats and advanced data analysis capabilities.

Survey Monkey as a popular platform for primary data collection

There are other alternatives to Survey Monkey you might want to consider to use as a platform for your survey. These include but not limited to Jotform, Google Forms, Lime Survey, Crowd Signal, Survey Gizmo, Zoho Survey and many others.

My  e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach  contains a detailed, yet simple explanation of quantitative methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in simple words.

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Think Postgrad

Find out how to use a dissertation questionnaire for your masters.

Prof Martyn Denscombe, author of " The Good Research Guide, 6th edition ", gives expert advice on using a questionnaire survey for your postgraduate dissertation.

Questionnaire surveys are a well-established way of collecting data. They work with relatively small-scale research projects so design and deliver research questionnaires quickly and cheaply. When it comes to conducting research for a master’s dissertation, questionnaire surveys feature prominently as the method of choice.

Using the post for bulky and lengthy surveys is normal. Sometimes questionnaires go by hand. The popularity of questionnaire surveys is principally due to the benefits of using online web-based questionnaires. There are two main aspects to this.

Designing questionnaires

First, the software for producing and delivering web questionnaires. Simple to use features such as drop-down menus and tick-box answers, is user-friendly and inexpensive.

Second, online surveys make it possible to contact people across the globe without travelling anywhere. Given the time and resource constraints faced when producing a dissertation, makes online surveys all the more enticing. Social media such as Facebook, Instagram and WhatsApp is great for contacting people to participate in the survey.

In the context of a master’s dissertation, however, the quality of the survey data is a vital issue. The grade for the dissertation will depend on being able to defend the use of the data from the survey. This is the basis for advanced, master’s level academic enquiry.

Pro's and con's

It is not good enough to simply rely on getting 100 or so people to complete your questionnaire. Be aware of the pros and cons of questionnaire surveys. You need to justify the value of the data you have collected in the face of probing questions, such as:

• Who are the respondents and how they were selected?
• How representative are the respondents of the whole group being studied?
• What response rate was achieved by the survey?
• Are the questions suitable in relation to the topic and the particular respondents?
• What likelihood is there that respondents gave honest answers to the questions?

This is where The Good Research Guide, 6th edition becomes so valuable.

It identifies the key points that need to be addressed in order to conduct a competent questionnaire survey. It gets right to the heart of the matter, with plenty of practical guidance on how to deal with issues.

In a straightforward style, using plain language, this bestselling book covers a range of alternative strategies and methods for conducting small-scale social research projects and outlines some of the main ways in which the data can be analysed.

Read Prof Martyn Denscombe's advice on using a Case Study for your postgraduate dissertation.

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Library Guides

Dissertations 4: methodology: methods.

• Introduction & Philosophy
• Methodology

Primary & Secondary Sources, Primary & Secondary Data

When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.  

Definitions  

There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:  

Secondary sources 

Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.  

Primary sources 

Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123). 

Primary data 

Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316). 

Secondary data 

Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).   

Comparison between primary and secondary data   

Use  

Virtually all research will use secondary sources, at least as background information. 

Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'. 

The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.    

Ultimately, you should state in this section of the methodology: 

What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis. 

If using primary data, why you employed certain strategies to collect them. 

What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature). 

Quantitative, Qualitative & Mixed Methods

The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages. 

Quantitative research 

Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496). 

Qualitative research  

Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs.  

Mixed methods 

Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years.  

When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138). 

Ultimately, your methodology chapter should state: 

Whether you used quantitative research, qualitative research or mixed methods. 

Why you chose such methods (and refer to research method sources). 

Why you rejected other methods. 

How well the method served your research. 

The problems or limitations you encountered. 

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:

LinkedIn Learning Video on Academic Research Foundations: Quantitative

The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.

Link to quantitative research video

Some Types of Methods

There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis. 

Whatever methods you will use, you will need to consider: 

why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose? 

what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?) 

ethical considerations (see also tab...)  

safety considerations  

validity  

feasibility  

recording  

procedure of the research (see box procedural method...).  

Check Stella Cottrell's book  Dissertations and Project Reports: A Step by Step Guide  for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.  

Experiments 

Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations. 

For more information on Scientific Method, click here . 

Observations 

Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.  

Questionnaires and surveys 

Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements. 

Interviews  

Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142). 

This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods. 

Focus groups   

In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views. 

This video focuses on strategies for conducting research using focus groups.  

Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box. 

Case study 

Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.     

Content analysis 

Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.

Extra links and resources:  

Research Methods  

A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection. 

Doing your dissertation during the COVID-19 pandemic  

Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts; 

• Virtual Focus Groups Guidance on managing virtual focus groups

5 Minute Methods Videos

The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication. 

Case Study Research

Research Ethics

Quantitative Content Analysis 

Sequential Analysis 

Qualitative Content Analysis 

Thematic Analysis 

Social Media Research 

Mixed Method Research 

Procedural Method

In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!). 

Include specifics about participants, sample, materials, design and methods. 

If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.  

Describe all materials used for the study, including equipment, written materials and testing instruments. 

Identify the study's design and any variables or controls employed. 

Write out the steps in the order that they were completed. 

Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected. 

Specify statistical techniques applied to the data to reach your conclusions. 

Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design. 

Highlight any drawbacks that may have limited your ability to conduct your research thoroughly. 

You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research. 

Bibliography

Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.

Lombard, E. (2010). Primary and secondary sources.  The Journal of Academic Librarianship , 36(3), 250-253

Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015).  Research Methods for Business Students.  New York: Pearson Education. 

Specht, D. (2019).  The Media And Communications Study Skills Student Guide . London: University of Westminster Press.  

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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.

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• 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.

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Dissertation surveys: Questions, examples, and best practices

Collect data for your dissertation with little effort and great results.

Dissertation surveys are one of the most powerful tools to get valuable insights and data for the culmination of your research. However, it’s one of the most stressful and time-consuming tasks you need to do. You want useful data from a representative sample that you can analyze and present as part of your dissertation. At SurveyPlanet, we’re committed to making it as easy and stress-free as possible to get the most out of your study.

With an intuitive and user-friendly design, our templates and premade questions can be your allies while creating a survey for your dissertation. Explore all the options we offer by simply signing up for an account—and leave the stress behind.

How to write dissertation survey questions

The first thing to do is to figure out which group of people is relevant for your study. When you know that, you’ll also be able to adjust the survey and write questions that will get the best results.

The next step is to write down the goal of your research and define it properly. Online surveys are one of the best and most inexpensive ways to reach respondents and achieve your goal.

Before writing any questions, think about how you’ll analyze the results. You don’t want to write and distribute a survey without keeping how to report your findings in mind. When your thesis questionnaire is out in the real world, it’s too late to conclude that the data you’re collecting might not be any good for assessment. Because of that, you need to create questions with analysis in mind.

You may find our five survey analysis tips for better insights helpful. We recommend reading it before analyzing your results.

Once you understand the parameters of your representative sample, goals, and analysis methodology, then it’s time to think about distribution. Survey distribution may feel like a headache, but you’ll find that many people will gladly participate.

Find communities where your targeted group hangs out and share the link to your survey with them. If you’re not sure how large your research sample should be, gauge it easily with the survey sample size calculator.

Need help with writing survey questions? Read our guide on well-written examples of good survey questions .

Dissertation survey examples

Whatever field you’re studying, we’re sure the following questions will prove useful when crafting your own.

At the beginning of every questionnaire, inform respondents of your topic and provide a consent form. After that, start with questions like:

• Please select your gender:
• What is the highest educational level you’ve completed?
• High school
• Bachelor degree
• Master’s degree
• On a scale of 1-7, how satisfied are you with your current job?
• Please rate the following statements:
• I always wait for people to text me first.
• Strongly Disagree
• Neither agree nor disagree
• Strongly agree
• My friends always complain that I never invite them anywhere.
• I prefer spending time alone.
• Rank which personality traits are most important when choosing a partner. Rank 1 - 7, where 1 is the most and 7 is the least important.
• Flexibility
• Independence
• How openly do you share feelings with your partner?
• Almost never
• Almost always
• In the last two weeks, how often did you experience headaches?

Dissertation survey best practices

There are a lot of DOs and DON’Ts you should keep in mind when conducting any survey, especially for your dissertation. To get valuable data from your targeted sample, follow these best practices:

Use the consent form.

The consent form is a must when distributing a research questionnaire. A respondent has to know how you’ll use their answers and that the survey is anonymous.

Avoid leading and double-barreled questions

Leading and double-barreled questions will produce inconclusive results—and you don’t want that. A question such as: “Do you like to watch TV and play video games?” is double-barreled because it has two variables.

On the other hand, leading questions such as “On a scale from 1-10 how would you rate the amazing experience with our customer support?” influence respondents to answer in a certain way, which produces biased results.

Use easy and straightforward language and questions

Don’t use terms and professional jargon that respondents won’t understand. Take into consideration their educational level and demographic traits and use easy-to-understand language when writing questions.

Mix close-ended and open-ended questions

Too many open-ended questions will annoy respondents. Also, analyzing the responses is harder. Use more close-ended questions for the best results and only a few open-ended ones.

Strategically use different types of responses

Likert scale, multiple-choice, and ranking are all types of responses you can use to collect data. But some response types suit some questions better. Make sure to strategically fit questions with response types.

Ensure that data privacy is a priority

Make sure to use an online survey tool that has SSL encryption and secure data processing. You don’t want to risk all your hard work going to waste because of poorly managed data security. Ensure that you only collect data that’s relevant to your dissertation survey and leave out any questions (such as name) that can identify the respondents.

Create dissertation questionnaires with SurveyPlanet

Overall, survey methodology is a great way to find research participants for your research study. You have all the tools required for creating a survey for a dissertation with SurveyPlanet—you only need to sign up . With powerful features like question branching, custom formatting, multiple languages, image choice questions, and easy export you will find everything needed to create, distribute, and analyze a dissertation survey.

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• Knowledge Base
• Starting the research process
• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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What Is a Dissertation Methodology?

How to choose your methodology, final thoughts, how to write your dissertation methodology.

Updated September 30, 2021

Due to the complexities of the different research methods, writing your dissertation methodology can often be the most challenging and time-consuming part of your postgraduate dissertation .

This article focuses on the importance of writing a good PhD or master's dissertation methodology – and how to achieve this.

A postgraduate dissertation (or thesis) is usually formed of several detailed sections, including:

Abstract – A summary of your research topic.

Introduction – Provides background information on your topic, putting it into context. You will also confirm the main focus of your study, explain why it will add value to your area of interest and specify your key objectives.

Literature Review – A critical review of literature that relates to your chosen research topic. You will also need to identify which gap in the literature your study aims to address.

Methodology – Focuses on the research methods used within your research.

Results – Used to report on your main findings and how these relate to your research question.

Conclusion – Used to confirm the answer to your main research question, reflect on the research process and offer recommendations on future research.

The dissertation methodology forms the skeleton of any research project. It provides the reader with a clear outline of the methods you decided to use when carrying out your research.

By studying your dissertation methodology, the reader will be able to assess your research in terms of its validity and reliability.

In line with the outline given above, the methodology chapter usually appears after the literature review . Your methodology should be closely linked to the research that you conducted as part of this review, as well as the questions you aim to answer through your research and analysis.

Taking the time to find out about the different types of research available to you will allow you to identify any potential drawbacks to the method you have chosen to use. You should then be able to make allowances or adjustments to address these when it comes to carrying out your research.

Choosing your methodology will largely depend on the discipline of the qualification you are studying for and the question your dissertation will seek to answer. In most cases, you will use quantitative or qualitative research methods, although some projects will benefit from using a combination of both.

Quantitative research methods are used to gather numerical information. This research method is particularly useful if you are seeking to count, categorise, measure or identify patterns in data. To collect quantitative data, you might choose to conduct experiments, tests or surveys.

Qualitative research methods are used to gather non-statistical data. Instead of using numbers to create charts or graphs, you will need to categorise the information according to identifiers. This research method is most useful if you are seeking to develop a hypothesis. To collect qualitative data, you might choose to conduct focus groups, interviews or observations.

What to Include in Your Dissertation Methodology

Below is a dissertation methodology example to show you what information to include:

You will need to reiterate your research topic or question and give an overview of how you plan to investigate this. If there were any ethical or philosophical considerations to be made, give details.

For example, you may have sought informed consent from the people taking part in interviews or surveys.

Outline of the Methods Chosen

Confirm whether you have chosen to use quantitative research, qualitative research or a combination of both.

When choosing between qualitative and quantitative research methods, you will need to carry out initial literature and textbook research to establish the standard research methods that are normally used within your chosen area of research.

If you are not sure where to start, you could visit the library at your college or university and ask one of the librarians to help you to identify the most relevant texts.

Explanation of the Methods Chosen

Explain your rationale for selecting your chosen research methods. You should also give an overview of why these were more appropriate than using another research method.

Think about where and when the research took place and who was involved. For example, this might include information on the venue used for interviews or focus groups, dates and timescales, and whether participants were part of a particular demographic group.

Here are some examples of the type of information you may wish to include:

Qualitative Research Methods

Personal observations – Where and when did you conduct the observations? Who did you observe? Were they part of a particular community or group? How long did each observation take? How did you record your findings – did you collect audio recordings, video footage or written observations?

Focus groups – Where and when did the focus group take place? Who was involved? How were they selected? How many people took part? Were the questions asked structured, unstructured or semi-structured? Remember to include a copy of the questions that were used as an appendix.

Interviews – Where and when did the interviews take place? Who took part? How did you select the participants? What type of questions did you ask? How did you record your findings? Remember to include a copy of the questions that were used as an appendix.

The researcher’s objective was to find out customer perceptions on improving the product range currently offered by Company Y. Semi-structured interviews were held with 15 returning customers from the key target demographic for Company Y (18- to 35-year-olds). For research purposes, a returning customer was defined as somebody who purchased products from Company Y at least two times per week during the past three months. The interviews were held in an office in the staff area of the retail premises. Each interview lasted approximately 25 minutes. Responses were recorded through note-taking as none of the respondents wished to give their consent to be filmed.

Quantitative Research Methods

Existing information or data – What were the sources of the material used? How did you select material? Did you only use data published within a particular time frame?

Experiments – What tools or equipment did you use? What techniques were required? Note that when conducting experiments, it is particularly important to provide enough information to allow another researcher to conduct the experiment and obtain the same results.

Surveys – Were respondents asked to answer multiple-choice questions or complete free-text fields? How many questions were used? How long were people given to answer all of the questions? What were the demographics of the participants? Remember to include a copy of the survey in the appendices.

The survey was made up of 10 multiple-choice questions and 5 questions to be rated using a 5-point Lickert scale. The objective was to have 250 customers of Company Z complete the survey at the Company Z HQ between 1st and 5th February 2019, between the hours of 12 p.m. and 5 p.m. For research purposes, a customer was defined as any person who had purchased a product from Company Z during 2018. Customers completing the survey were allowed a maximum of 10 minutes to answer all of the questions. 200 customers responded, however not all of the surveys were completed in full, so only 150 survey results were able to be used in the data analysis.

How Was the Data Analysed?

If you have chosen to use quantitative research methods, you will need to prepare the data before analysing it – for example, you will need to check for variables, missing data and outliers. If you have used computer software to aid with analysis, information on this should also be included.

For qualitative data, you will need to categorise and code the ideas and themes that are identified from the raw data. You may also need to use techniques such as narrative analysis or discourse analysis to interpret the meaning behind responses given.

What Materials and Equipment Were Used During the Research?

This could include anything from laboratory equipment used in a scientific experiment to computer software used to analyse the results.

Were There Any Hurdles or Difficulties Faced During the Research?

If so, what were they and how did you manage to overcome them? This could be anything from difficulties in finding participants, problems obtaining consent or a shortage of the required resources needed to conduct a scientific experiment.

This paragraph should be used to evaluate the research you have conducted and justify your reasons for choosing this approach.

You do not need to go into great detail, as you will present and discuss your results in-depth within your dissertation’s ‘Results’ section.

You will need to briefly explain whether your results were conclusive, whether there were any variables and whether your choice of methodology was effective in practice.

Tips for Writing Your Dissertation Methodology

The objective for the methodology is not only to describe the methods that you used for your research. You will also need to demonstrate why you chose to use them and how you applied them.

The key point is to show that your research was conducted meticulously.

Try to keep your writing style concise and clear; this will ensure that it is easy for the reader to understand and digest.

Here are five top tips to consider when writing your dissertation methodology:

1. Look at Other Methodology Sections

Ask your supervisor to provide you with a few different examples of previously written dissertations. Reading through methodologies that have been written by past students will give you a good idea of what your finished methodology section should look like.

2. Plan Your Structure

Whichever research methods you have chosen to use, your dissertation methodology should be a clearly structured, well written section that gives a strong and justified argument for your chosen research methods.

You may wish to use headings such as:

• Research methods
• Explanation of research methods chosen
• Data analysis and references

Once you have drafted an outline, ask your supervisor for advice on whether there is anything you have missed and whether your structure looks logical.

3. Consider Your Audience

When writing your methodology, have regard for the people who are likely to be reading it. For example, if you have chosen to use research methods that are commonly chosen within your area of research or discipline, there is no need to give a great deal of justification or background information.

If you decide to use a less popular approach, it is advisable to give much more detailed information on how and why you chose to use this method.

4. Remain Focused on Your Aims and Research Questions

Your dissertation methodology should give a clear indication as to why the research methods you have chosen are suitable for the aims of your research.

When writing your dissertation methodology, ensure that you link your research choices back to the overall aims and objectives of your dissertation. To help you to remain focused, it can be helpful to include a clear definition of the question you are aiming to answer at the start of your methodology section.

5. Refer to Any Obstacles or Difficulties That You Dealt With

If you faced any problems during the data collection or analysis phases, use the methodology section to talk about what you did to address these issues and minimise the impact.

Whether you are completing a PhD or master's degree, writing your thesis or dissertation methodology is often considered to be the most difficult and time-consuming part of completing your major research project.

The key to success when writing a methodology section is to have a clear structure. Remember, the purpose of the methodology section of your research project is to ensure that the reader has a full understanding of the methods you have chosen.

You should use your methodology section to provide clear justification as to why you have chosen a particular research method instead of other potential methods. Avoid referring to your personal opinions, thoughts or interests within your methodology; keep the information that you include factual and ensure that everything is backed up by appropriate academic references.

You might also be interested in these other Wikijob articles:

Or explore the Postgraduate / PHD sections.

• How it works

Chapter 3 – Dissertation Methodology (example)

Disclaimer: This is not a sample of our professional work. The paper has been produced by a student. You can view samples of our work here . Opinions, suggestions, recommendations and results in this piece are those of the author and should not be taken as our company views.

Type of Academic Paper – Dissertation Chapter

Academic Subject – Marketing

Word Count – 3017 words

Introduction

The current chapter presents developing the research methods needed to complete the experimentation portion of the current study. The chapter will discuss in detail the various stages of developing the methodology of the current study. This includes a detailed discussion of the philosophical background of the research method chosen. In addition to this, the chapter describes the data collection strategy, including the selection of research instrumentation and sampling. The chapter closes with a discussion on the analysis tools used to analyse the data collected.

Selecting an Appropriate Research Approach

Creswall (2013) stated that research approaches are plans and procedures that range from steps, including making broad assumptions to detailed methods of data collection, analysis, and interpretation. The several decisions involved in the process are used to decide which approach should be used in a specific study that is informed using philosophical assumptions brought to the study (Creswall 2013). Included in this are procedures of inquiry or research designs and specific research methods used for data collection, its analysis, and finally, its interpretation. However, Guetterman (2015); Lewis (2015); and Creswall (2013) argue that the selection of the specific research approach is based on the nature of the research problem, or the issue that is being addressed by any study, personal experiences of the researchers’, and even the audience for which the study is being developed for.

There are many ways to customise research approaches to develop an approach most suited for a particular study. However, the main three categories with which research approaches are organised include; qualitative, quantitative, and mixed research methods. Creswall (2013) comments that all three approaches are not considered so discrete or distinct from one another. Creswall (2013) states, “qualitative and quantitative approaches should not be viewed as rigid, distinct categories, polar opposite, or dichotomies” (p.32). Newmand and Benz (1998) pointed out that quantitative and qualitative approaches instead represent different ends on a continuum since a study “tends” to be more quantitative than qualitative or vice versa. Lastly, mixed methods research resides in the middle of the continuum as it can incorporate elements and characteristics of both quantitative and qualitative approaches. Lewis (2015) points out that the main distinction that is often cited between quantitative and qualitative research is that it is framed in terms of using numbers rather than words; or using closed-ended questions for quantitative hypotheses over open-ended questions for qualitative interview questions. Guetterman (2015) points out that a clearer way of viewing gradations of differences between the approaches is to examine the basic philosophical assumptions brought to the study, the kinds of research strategies used, and the particular methods implemented in conducting the strategies.

Underlying Philosophical Assumptions

An important component of defining the research approach involves philosophical assumptions that contribute to the broad research approach of planning or proposing to conduct research. It involves the intersection of philosophy, research designs and specific methods as illustrated in Fig. 1 below.

Figure 3.2-1- Research Onion (Source; Saunders and Tosey 2013)

Slife and Williams (1995) have argued that philosophical ideas have remained hidden within the research. However, they still play an influential role in the research practice, and it is for this reason that it is most identified. Various philosophical assumptions are used to construct or develop a study. Saunders et al. (2009) define research philosophy as a belief about how data about a phenomenon should be gathered, analysed and used. Saunders et al. (2009) identify common research philosophies such as positivism, realism, interpretivism, subjectivism, and pragmatism. Dumke (2002) believes that two views, positivism and phenomenology, mainly characterise research philosophy.

Positivism reflects acceptance in adopting the philosophical stance of natural scientists (Saunders, 2003). According to Remenyi et al. (1998), there is a greater preference in working with an “observable social reality” and that the outcome of such research can be “law-like” generalisations that are the same as those which are produced by physical and natural scientists. Gill and Johnson (1997) add that it will also emphasise a high structure methodology to allow for replication for other studies. Dumke (2002) agrees and explains

that a positivist philosophical assumption produces highly structured methodologies and allows for generalisation and quantification of objectives that can be evaluated by statistical methods. For this philosophical approach, the researcher is considered an objective observer who should not be impacted by or impact the subject of research.

On the other hand, more phenomenological approaches agree that the social world of business and management is too complex to develop theories and laws similar to natural sciences. Saunders et al. (2000) argue that this is the reason why reducing observations in the real world to simple laws and generalisations produces a sense of reality which is a bit superficial and doesn’t present the complexity of it.

The current study chooses positivistic assumptions due to the literature review’s discussion of the importance of Big Data in industrial domains and the need for measuring its success in the operations of the business. The current study aims to examine the impact that Big Data has on automobile companies’ operations. To identify a positive relationship between Big Data usage and beneficial business outcomes, the theory needs to be used to generate hypotheses that can later be tested of the relationship which would allow for explanations of laws that can later be assessed (Bryman and Bell, 2015).

Selecting Interpretive Research Approach

Interpretive research approaches are derived from the research philosophy that is adopted. According to Dumke (2002), the two main research approaches are deductive and inductive. The inductive approach is commonly referred to when theory is derived from observations. Thus, the research begins with specific observations and measures. It is then from detecting some pattern that a hypothesis is developed. Dumke (2002) argues that researchers who use an inductive approach usually work with qualitative data and apply various methods to gather specific information that places different views. From the philosophical assumptions discussed in the previous section, it is reasonable to use the deductive approach for the current study. It is also considered the most commonly used theory to establish a relationship between theory and research. The figure below illustrates the steps used for the process of deduction.

Data Collection

• confirmed or rejected
• Revision of theory

Based on what is known about a specific domain, the theoretical considerations encompassing it a hypothesis or hypotheses are deduced that will later be subjected to empirical enquiry (Daum, 2013). Through these hypotheses, concepts of the subject of interest will be translated into entities that are rational for a study. Researchers are then able to deduce their hypotheses and convert them into operational terms.

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Justifying the Use of Quantitative Research Method

Saunders (2003) notes that almost all research will involve some numerical data or even contain data quantified to help a researcher answer their research questions and meet the study’s objectives. However, quantitative data refers to all data that can be a product of all research strategies (Bryman and Bell, 2015; Guetterman, 2015; Lewis, 2015; Saunders, 2003). Based on the philosophical assumptions and interpretive research approach, a quantitative research method is the best suited for the current study. Haq (2014) explains that quantitative research is about collecting numerical data and then analysing it through statistical methods to explain a specific phenomenon. Mujis (2010) defends the use of quantitative research because, unlike qualitative research, which argues that there is no pre-existing reality, quantitative assumes that there is only a single reality about social conditions that researchers cannot influence in any way. Also, qualitative research is commonly used when there is little to no knowledge of a phenomenon, whereas quantitative research is used to find the cause and effect relationship between variables to either verify or nullify some theory or hypothesis (Creswall 2002; Feilzer 2010; Teddlie and Tashakkori 2012).

Selecting an Appropriate Research Strategy

There are many strategies available to implement in a study, as evidenced from Fig. 1. There are many mono-quantitative methods, such as telephone interviews, web-based surveys, postal surveys, and structured questionnaires (Haq 2014). Each instrument has its own pros and cons in terms of quality, time, and data cost. Brymand (2006); Driscoll et al. (2007); Edwards et al. (2002); and Newby et al. (2003) note that most researchers use structured questionnaires for data collection they are unable to control or influence respondents, which leads to low response rates but more accurate data obtained. Saunders and Tosey (2015) have argued that quantitative data is simpler to obtain and more concise to present. Therefore, the current study uses a survey-based questionnaire (See Appendix A).

Justifying the use of Survey Based Questionnaire

Surveys are considered the most traditional forms of research and are used in non-experimental descriptive designs that describe some reality. Survey-based questionnaires are often restricted to a representative sample of a potential group of the study’s interest. In this case, it is the executives currently working for automobile companies in the UK. The survey instrument is then chosen for its effectiveness at being practical and inexpensive (Kelley et al., 2003). Due to the philosophical assumptions, interpretive approach, and methodological approach, the survey design for the current study is considered the best instrument in line with these premises, besides being cost-effective.

Empirical Research Methodology

Research design.

This section describes how research is designed to use the techniques used for data collection, sampling strategy, and data analysis for a quantitative method. Before going into the strategies of data collection and analysis, a set of hypotheses were developed.

Hypotheses Development

The current study uses a quantitative research approach, making it essential to develop a set of hypotheses that will be used as a test standard for the mono-method quantitative design. The following are a set of hypotheses that have been developed from the examination of the literature review.

H1- The greater the company’s budget for Big Data initiatives (More than 1 million GBP), the greater its ability to monetise and generate new revenues.

H2- The greater the company’s budget for Big Data initiatives (More than 1 million GBP) the more decrease in expenses in found.

H3- The greatest impact of Big Data on a company is changing the way business is done.

H4- Big Data integrating with a company has resulted in competitive significance.

H5- The analytical abilities of a company allows for achieved measurable results.

H6- Investing in Big Data will lead to highly successful business results.

H7- A business’s operations function is fuelling Big Data initiatives and effecting change in operations.

H8- The implementation of Big Data in the company has positive impacts on business.

This section includes the sampling method used to collect the number of respondents needed to provide information, then analysed after collection.

Sampling Method

Collis (2009) explains that there are many kinds of sampling methods that can be used for creating a specific target sample from a population. This current study uses simple random sampling to acquire respondents with which the survey will be conducted. Simple random sampling is considered the most basic form of probability sampling. Under the method, elements are taken from the population at random, with all elements having an equal chance of being selected. According to () as of 2014, there are about thirty-five active British car manufacturers in the UK, each having an employee population of 150 or more. This is why the total population of employees in car manufacturers is estimated to be 5,250 employees. The sample, therefore, developed used the following equation;

2  ×   (1 −   )

+(   2 × (1−  ) )  2

Where; N is the population size,  e  is the margin of error (as a decimal),  z  is confidence level (as a z-score), and  p  is percentage value (as a decimal). Thus, the sample size is with a normal distribution of 50%. With the above equation, a population of 5,250; with a 95% confidence level and 5% margin of error, the total sample size needed for the current equals 300. Therefore, N=300, which is the sample size of the current study.

The survey develops (see Appendix A) has a total of three sections, A, B, and C, with a total of 39 questions. Each section has its own set of questions to accomplish. The survey is a mix of closed-end questions that look to comprehend the respondents’ demographic makeup, the Big Data initiatives of the company, and the impact that Big Data was having on their company. The survey is designed to take no longer than twenty minutes. The survey was constructed on Survey Monkey.com, and an online survey provided website. The survey was left on the website for a duration of 40 days to ensure that the maximum number of respondents were able to answer the survey. The only way that the survey was allowed for a respondent is if they passed a security question as if they were working for an automobile company in the UK when taking the survey. Gupta et al. (2004) believe that web surveys are visual stimuli, and the respondent has complete control about whether or how each question is read and understood. That is why Dillman (2000) argued that web questionnaires are expected to resemble those taken through the mail/postal services closely.

Data Analysis

The collected data is then analysed through the Statistical Package for Social Science (SPSS) version 24 for descriptive analysis. The demographic section of the survey will be analysed using descriptive statistics. Further analysis of the data includes regression analysis. Simple regression analysis includes only one independent variable and one dependent variable. Farrar and Glauber (1967) assert that the purpose of regression analysis is to estimate the parameters of dependency, and it should not be used to determine the interdependency of a relationship.

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Conclusions.

The chapter provides a descriptive and in-depth discussion of the methods involved in the current study’s research. The current study is looking towards a quantitative approach that considers positivism as its philosophical undertaking, using deductive reasoning for its interpretive approach, is a mono-quantitative method that involves the use of a survey instrument for data collection. The methodology chapter also provided the data analysis technique, which is descriptive statistics through frequency analysis and regression analysis.

Examples of results;

Question 8- Of these staff, are mostly working in or for your consumer-facing (B2C) businesses, your commercial or wholesale (B2B) businesses, or both?

Based on the illustration, nineteen (19) respondents indicated that 501-1000 employees are dedicated to analytics for both B2B and B2C. The category of using Big Data analytics for both B2B and B2C comprises the most agreement of respondents with 72 of 132 indicated.

The figure above represents the respondents’ answers to their automobile company’s plan for measuring Big Data’s success. Of the 132 participants, 44.70 per cent responded that the company is planning on using quantitative metrics associated with business performance to analyse if Big Data is actually successful. Another, 30.30 per cent indicated that their company was planning on using qualitative metrics tied to business performance. Using business performance to analyse the success of Big Data is coherent to the results of the literature review that indicated previous studies of doing such. As an automobile company, they need to know the results of using Big Data analytics, and that is only by using business performance indicators regardless of being qualitative or quantitative.

Fig. 4.3-6 portrays the response of participants in regards to actually achieving measurable results from Big Data. According to 68.18 per cent of respondents, the company that they worked for did indeed show measurable results from their investments in Big Data. However, 31.82 per cent indicated that there was indeed no measurable result in investing in Big Data.

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Perspective and its Implication for Public Relations Consultancies. diplom.de.

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ResearchGate 1–22. doi:http://dx.doi.org/10.13140/RG.2.1.1945.8640

Kelley, K., Clark, B., Brown, V., Sitzia, J., 2003. Good practice in the conduct and reporting of survey research. Int J Qual Health Care 15, 261–266. doi:10.1093/intqhc/mzg031

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Health Promotion Practice 16, 473–475. doi:10.1177/1524839915580941

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Development. Edward Elgar Publishing.

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• Explain data collection methods.
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• Analyse data.
• Ensure replicability.

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