What Is Research Scope? How to Define and Present It
You open Chapter 1 of your thesis and reach the section titled “Research Scope”, but you are unsure how specific it needs to be. This section does not require you to retell the entire study. It answers four practical questions: who you are studying, what you are studying, where the data were collected, and when the data were collected.
A clear scope tells readers which group your results may apply to, in what context, and where you should avoid generalising. When you run SPSS or SmartPLS, the scope also directly affects how you select the sample, design the questionnaire, define the variables, and interpret the results.
What Is Research Scope
Research scope is the set of boundaries you establish for a study. It usually includes the scope of content, population, setting, and time. These boundaries define the research question, the data, and the conclusions. For example, the topic “Factors Affecting Students’ Intention to Use E-Wallets in Ho Chi Minh City” already shows four clear layers of scope: intention to use e-wallets is the content, students are the population, Ho Chi Minh City is the setting, and the survey period must be stated separately.
Your research scope must be consistent with the title, objectives, model, hypotheses, and questionnaire. If the title only refers to final-year students but the questionnaire also collects responses from employed people, the sample has moved outside the stated scope. If the topic concerns customers in Hanoi but the methods section only collects data from one district, state that limitation clearly instead of writing as if the sample represents the entire city.
You can also read research population to distinguish between “who you study” and the participants or group providing the data. Scope is the broader picture, while the research population is the specific component on which the study focuses.
The Meaning of Research Scope in Quantitative Research
In quantitative research, scope turns a broad topic into a model that can be measured. Only after defining the scope can you decide what the dependent variable is, which independent variables to include, who is eligible to answer the questionnaire, and which data should remain in the .sav or .csv file.
For example, “customer satisfaction with digital banking services” could include individual customers, businesses, app users, people who transact at branches, and customers in many locations. Without boundaries, you may design a questionnaire that is too broad and have no clear basis for deciding which sample is appropriate. Adding the condition “individual customers who have used Bank X’s mobile banking application in Hanoi during the past six months” makes both the model and the screening criteria clearer.
Scope also limits your conclusions. If you survey 250 students from three universities in Da Nang, you can draw conclusions about that sample and research context. You should be careful when writing that the findings represent all students in Vietnam. A larger sample does not automatically remove limits related to location, sampling method, or population group.
The four common scope categories are presented below:
- Content scope: the concepts, relationships, or issues being tested.
- Population scope: the people, organisations, or units providing observations for the study.
- Setting scope: the location, industry, business, university, or platform being surveyed.
- Time scope: the study period, data-collection period, or period reflected by the data.
You can place this section next to research field. The field tells readers which body of knowledge the topic belongs to, while the scope shows how far your particular study goes.
How Much Research Scope Is Adequate
There is no single number that determines whether a research scope is adequate. A suitable scope is specific enough for another person to identify the sample, variables, setting, and time, but not so narrow that it cannot answer the research objective.
The table below is a practical checklist. Sources are included in the rows related to methodological and sample-size requirements. The decision about where to draw the boundaries still has to follow your research questions.
| Component to define | Check question | Sign that the scope is appropriate | Source or basis |
|---|---|---|---|
| Content | Which relationship are you testing | The dependent variable, independent variables, and model are clearly named | Study objectives and hypotheses |
| Population | Who is eligible to respond | Screening criteria are available and match the unit of analysis | (Nguyen Dinh Tho, 2011) |
| Setting | Where were the data collected | The location, organisation, industry, or platform is specified | Study sampling design |
| Time | Which period do the data reflect | A date or data-collection period is stated | Research design |
| Number of observations | How many responses were collected | The number fits the variables and analysis method | 5 to 10 observations per item (Hair et al., 2010) |
| Analysis model | Which test can the data support | The scope does not claim more than the model you ran | Regression sample size from 50 + 8m (Tabachnick and Fidell, 2013) |
If the questionnaire contains 25 items, the rule of 5 to 10 observations per item suggests a reference range from 125 to 250 observations (Hair et al., 2010). This is not permission to expand the scope without limit. You still need to check whether the population is accessible, whether the data are valid, and whether the sampling method is described honestly.
How to Read Research Scope in the Output
Research scope usually does not appear as a separate table in SPSS or SmartPLS. You check it through demographic tables, variable names, and the number of observations included in the analysis. If the scope says “final-year students”, the Frequencies table should show that the year-of-study variable was checked. If the scope says “people who have used the service during the past six months”, the questionnaire needs a screening item and the data must show that condition.
The following is illustrative output, not the result of a real study. Assume that the topic surveys students who have used e-wallets in Ho Chi Minh City. After cleaning the data, you run Analyze > Descriptive Statistics > Frequencies for the demographic variables.
| SPSS table | Variable | Category | Frequency | Percent | Valid Percent |
|---|---|---|---|---|---|
| Frequencies | Gender | Female | 142 | 56.8 | 56.8 |
| Frequencies | Gender | Male | 108 | 43.2 | 43.2 |
| Frequencies | Year of study | Year 3 | 96 | 38.4 | 38.4 |
| Frequencies | Year of study | Year 4 | 154 | 61.6 | 61.6 |
| Frequencies | E-wallet use | Yes | 250 | 100.0 | 100.0 |
| Descriptive Statistics | Age | Mean | 21.84 | ||
| Descriptive Statistics | Age | Std. Deviation | 1.12 |
This illustrative output lets you check three things. First, the number of valid observations is 250, which matches the number reported in the methods chapter. Second, the e-wallet-use condition has been kept consistent. Third, the study-year groups in the table must match the scope you stated.
If you use SmartPLS, you usually check the scope against the number of rows in the .csv file, the groups or categorical variables used to describe the sample, and the number of observations entered into the model. SmartPLS focuses on Outer Loadings, Path Coefficients, and model indicators, so you should not try to find a table called “Research Scope”. The scope must be supported by the sampling design and the descriptive data tables.
What to Do When the Research Scope Is Inadequate
When you review your proposal, you may find that the scope is too broad, too vague, or inconsistent with the data. Work through the following order.
Narrow the Content Before Changing the Data
If the topic contains too many variables, compare each variable with the objectives and hypotheses. A variable without a hypothesis or theoretical explanation may be making the scope unnecessarily broad. Discuss the issue with your supervisor before removing a variable from the model, because changing the model after data collection can affect the entire literature review and methods chapters.
State the Actual Setting and Sample Group
If you surveyed only one university, one business, or one district, state that exact scope. Changing the wording to a larger location so that the results appear broader creates a risk when the committee asks how the sample was selected.
Recheck the Screening Criteria
Open the data file and filter the condition variables. If many participants do not meet the criteria, determine whether they were entered incorrectly, gave invalid responses, or whether the original criterion was not designed clearly. Do not delete rows in bulk simply to make the numbers match the scope you already wrote.
Separate Limitations from Scope
Scope consists of the boundaries you deliberately set before or during the research design. Limitations are conditions that remain after the study has been conducted, such as convenience sampling, data collected in one location, or a short collection period. The two may be related, but they should not be written as substitutes for each other.
Distinguishing Research Scope from Research Population
Research scope and research population are often confused in Chapter 1. The research population answers the question, “Which issue or relationship are you analysing?” In a study of e-wallet-use intention, the research population may be the factors affecting intention to use. The participants or respondents may be students who have used an e-wallet.
Scope covers more elements. It states the issue being analysed, the people providing the data, the setting, and the time. For that reason, the sentence “the research population is students” is often inaccurate when students are only the questionnaire respondents. You can also read research population and What Is Scientific Research to organise these concepts correctly in the opening section.
Scope is also different from research methods. Methods explain how you collect and analyse data, such as using a Likert questionnaire, SPSS, regression, or SmartPLS. Scope explains who provided the data, where and when they provided it, and which question the data are intended to answer.
Common Errors
The first error is writing an overly broad scope such as “Vietnamese consumers” when the sample comes from a small subgroup. Correct this by stating the actual criteria, location, and period.
The second error is copying the scope from the proposal into Chapter 4 even though the data have changed. If you initially planned to survey three provinces but ended up with data from only one province, the results chapter must reflect the actual data.
The third error is confusing the research period with the period of the phenomenon. “The study was conducted from March to May 2026” refers to the period of data collection and processing. “Customers who have used the service during the past six months” is a condition related to the population scope. You may need to state both.
The fourth error is placing analysis results in the scope section. Indicators such as Cronbach's Alpha, KMO, R Square, and p-value belong in the results chapter, not in the research scope.
The final error is writing the scope without adjusting the questionnaire. If the scope is people who bought products online during the past three months, the questionnaire needs a matching screening item. You should also retain the number of excluded responses and the reason for each exclusion so that you can explain the decision if asked.
Frequently asked questions
What does research scope include?
Research scope usually includes content, population, setting, and time. In a quantitative thesis, you should also explain how these boundaries relate to the variables, model, questionnaire, and data included in the analysis.
Is research scope the same as research population?
The two concepts are related but different. Research population often refers to the issue, relationship, or phenomenon being analysed, while scope also includes the population, content, setting, and time. Questionnaire respondents may provide the data without being the research population itself.
Does research scope need to include time?
Yes, when time affects the context or data of the study. State the data-collection period, and add the period of service use or the screening condition if the topic requires it. If there is no reason to limit the study to a particular period, keep the explanation brief instead of creating an unsupported date range.
Can I use a template to write research scope?
You can use a structural template, but do not copy the setting, population, or time from another topic. Every sentence in the scope must match your title, questionnaire, data file, and analysis method.
Can data collected in one location support conclusions about the entire country?
You need to be cautious. Conclusions should refer to the sample group and context that were surveyed unless the sampling design and methodological reasoning support broader generalisation. A large number of responses does not automatically turn a sample from one location into a nationally representative sample.
Open Chapter 1 and your data file together, fill in the four lines for content, population, setting, and time, then compare each line with the screening variables and number of valid observations. If you need support running the analysis on your own .sav or .csv file, DoThesis M4 analysis handles this step.