Explanatory research; definition; methodology; methods; characteristics; examples and advantages

1.1 Definition

Explanatory research is a type of research Classified under “purpose of research” and it is the systematic investigation which entails an explanation as to “why things happen the way they happen”. The research aims at justifying the happening of an event, which is already known. For instance, in African context;

-Why do women shy away from men most of the times?

-Why men in a certain region marry at an old age is explained by explanatory research.


Things to know about Explanatory Research;

One; explanatory research is suitable in a case where by the research problem was not well researched. Yes, we know this is how things happen. But why they happen in that manner is not empirically proven.

Two; explanatory research brings in the details which are missing in a concept.

The research explains the point of detail of research theories and advance knowledge about underlying process.

Three; explanatory research does not provide the researcher with conclusive evidence but only increase his or her understanding on the problem at hand.

Four; explanatory research examines the current situation and provide avenues for further enquiries over a certain matter.

Five; explanatory research is the building block for other detailed research activities.

Six; this kind of research portrays the cause-effect link between variables especially when there is no enough information which is available. Therefore, it is also commonly referred to as causal research. 

Explanatory research methodology

2.1 Definition

Explanatory Research Methodology is the logical process or step by step layout on how to solve a research problem in an area where no much information as to why things happen in a certain manner. In other words, there is curiosity by the researcher to know the “why” aspect of a phenomenon.

Explanatory Research methodology involves choosing a logical procedure on the topic to be studied. That is the research problem, how specific objectives and research hypotheses of the study will be identified/or formulated. Identification of knowledge gaps to be filled, the methods used in identification of the study population and sample size determination, type of data to be collected and how it will be collected and analyzed, data presentation and interpretations thereof and the reporting of the research findings with suggestion on further researches to be undertaken in the future.

The aforementioned description /definition on explanatory research methodology is in agreement with Kothari (1984) who proposed that research methodology is the plausibility behind the diverse methods used in the study. This justifies why one uses a particular method or technique at a particular stage in the research process and not others so as to allow for successful evaluation of the research results by the concerned parties. 

2.1.1 Questions Explanatory Research Methodology tries to Answer

Explanatory research methodology answers the following questions;





The what and why questions aid in bringing more understanding of an issue or concept which had not been previously well understood. So, this type of research shades light on a matter or gives clarity which can be used to promote further research. Examples of such questions include and not limited to;

Why most students in form one first term perform lowly than in the proceeding academic years?

Why are women in the early age of 27 to 32 years aggressive in their place of work?

You see at the end of it all, the researcher will have gotten some reasons or some causes for the above two questions which will be representing the predictor variables. Therefore, more knowledge is discovered on the causes of changes on the dependent or response variable apart from may be what was initially known.

The following matrix portrays the link between explanatory type of research and the type of research methodology adopted and then an explanation of the logical approach associated with this category and then in the last column, the research method(s) used in formulating the research problem as indicated in Table 1.1

2.2 Explanatory Research Methodology-Diagrammatic Approach

The following diagram as represented in Figure 1.1is a summary of logical blueprint to be adhered to in Explanatory research methodology.

2.3 Logical Steps; Explanatory Research Methodology

The following logical steps describe the explanatory research methodology. From step one to eight, it represents a logical way of dealing with the subject matter in a systematic manner. Remember that in this approach, the researcher is curious to find out why things happen the way they do happen.

2.3.1 Step One; Development of Research Question

In step one, we are assuming that the researcher is familiar with the area of interest that he or she is focusing on. Then, another thing we need to note is that this type of research is concerned with answering the question “why” hence in step one, the researcher develops the relevant question first.

For example, let us assume that the researcher is interested in knowing why some Chief Executive Officers (CEOs) are better performers in their middle age between 35 to 48 years.

From past studies, the researcher has established that CEOs of different organizations perform well between the age of 35 to 48, beyond which they decline in their productivity.

The researcher is interested in knowing the influence of age diversity on performance of CEOs of different organizations.

2.3.2 Step Two; Formulate a Hypothesis

Based on past literature, the researcher can establish the basis of formulating a hypothesis of his or her postulation or expectations. If literature is missing or is tool narrow to provide a hint on how to establish a hypothesis, then any other closely related topic the researcher can use as a foundation for his/her hypothesis can be used. Formulation of hypothesis can be established as follows as guided by our 2.3.1 example above.

The researcher expects that CEOs aged between 35 to 48 years to perform better in their respective organizations.

Then that postulation can be either expressed in terms of null (H0) or alternative hypothesis (H1) or both. In most cases, especially in academia, we use either null or alternative hypothesis which is also commonly referred to as research hypothesis. In our case we will use both for your comprehensive understanding.

H0: There is no significant influence of CEOs age of between 35-48 and their performance in their respective organizations.

H1: There is significant influence of CEOs age of between 35-48 and their performance in their respective organizations.

Note: If the questions that the researcher has are more than one, then the hypotheses will be equally the same number. For now, since we have used only one question, we stick then to the one question for the sake of your understanding.

2.3.3 Step Three; Design Experimental Research Methodology

In step three, the designing of the research methodology to use is pegged on the research question of WHY hence it leads us to cause-effect concerns. Commonly, experimental methodology is used to investigate potential causal relationships.


Also, note that caution must be undertaken for when students hear of experimental methodology, they think of an experiment being undertaken in a Laboratory. This is not true for experimental research refers to an investigation of cause-effect type which can be in a laboratory setting or field based. Hence referred to as field experiment research. Experimental methodology is a logical procedure which entails two sets used to collect data from where by the researcher sets one group to be the control group and the second group to be the treatment group.

Let me walk you through the steps using an example.


Now, since the researcher is interested in testing a causal relationship. He/she will gather a group of those CEOs working in different organizations and are aged between 35-48. He will also gather other CEOs either with less than 35 years or more than 48 years for comparison purposes. In our case, let us assume that the researcher wants to compare the middle age and the old age CEOs overall performance.

So, he will compare overall performance of;

CEOs who are aged between 35 to 48 years

CEOs who are aged between 49 to 63 years

CEOs who are aged between 64 to 78 years

CEOs who are above 78 years

During the study, he/she will test their strategic performance twice in a research design that has three stages:


Pre-test: In this case, he will conduct several performance tests to establish any differences between groups pre-intervention.

Intervention: Next, he will provide all groups with overall performance task scenario to provide a practical solution within 5 hours.

Post-test: The researcher will then again conduct several overall performance test to establish any differences between groups post-intervention.

The researcher should take caution to ensure that control of any confounding variables, such as work experience, nature of organization one is working for etc.

Since he has chosen a between-subjects variable (diversity in age) and a within-subjects variable (pre-test vs. post-test), he has to decide to conduct a mixed ANOVA.

2.3.4 Step Four; Collect Relevant Data

With literature review in mind, the researcher has to collect the relevant data which should be characterized by additional information more than what already exists. You see, the point here is, that it is already in the body of knowledge those certain variables relate in a certain manner in the physical or natural phenomenon. Therefore, the additional data should clarify the “why” aspect as stated earlier on in this article.


2.3.5 Step Five; Analyze Data

After data collection is complete, the next step is to analyze data and report the results.

Under 2.2.3 step we have just discussed, the researcher should come up with an analysis method that does not only portray correlation but a causal-effect link. You see, for correlation analysis approach, the study will portray the mere strength or weakness of the relationship in addition to the direction the relationship takes. But this does not mean that for example if X changes when Y changes, Then Y is the cause of the change. “NO”. this is not the case. So, it should be noted that correlation is not causation.”

Now causation implies the changes that take place on the independent variable bring about changes in the dependent variable. That is, there is a direct causality relationship between the study variables.

Cause-Effect Criteria

For one to conclude the matter is of cause-effect relationship, the following THREE conditions need to be met. That is;

  1. Temporal Condition or criteria: Always, cause variable takes the lead and then the effect variable in that order but it cannot be the reverse.
  2. Variation: The aspect of intervening action undertaken in the explanatory research should be significant as far as the link between the independent variable and dependent variable is concerned.
  3. Absence of Nonsense Correlation: Any factor(s) with spurious influence to the dependent or outcome variable should be excluded in the model.

Therefore, in order to get conclusive causal effect outcome, the researcher need to undertake full experimental research design.

Therefore, Data analysis will mostly entail determination of whether the performance result differences are significant by use of mixed ANOVA. The ANOVA outcome may portray that all differences are not significant for the pre-test, but they are significant for the post-test.

2.3.6 Step Six; Establish Research Findings

At this stage, the researcher needs to find out the results of the data analysis step five. In this stage, no interpretation at all. It purely entails stating the outcome of data analysis process as it is.


2.3.7 Step Seven; Data Interpretation

In this step, data analysis outcome is interpreted using ANOVA. If the F-Test is significant, that is p value is less than 0.05 critical value, then we conclude that there is statistically significant difference between the two groups and hence the null hypothesis is rejected so as to adopt the alternative hypothesis.

2.3.8 Step Eight; Report Writing

Explanatory Research is a build-up of the existing links of variables in their natural phenomenon. Therefore, in this stage, the researcher needs to disclose to the users of the research findings whether there is underlying reason(s) other than the one which is apparently known to be the existing one in a certain relationship or association between or amongst variables.

Explanatory research data collection methods

Research methods are all the techniques that are utilized in all the stages of research processes. They are tools used to ensure the end results of research task are accomplished. These techniques vary from one stage of research process to another. These methods are further classified in to two categories, namely;

  1. a) Pre-Data analysis methods
  2. b) Data Analysis related methods


As per Table 1.1 in this article, the explanatory research methods indicated in that table (refer), namely; Case study, Literature review and Surveys/polls methods are for the purposes of formulating the research problem and are some of the methods which fall under pre-data analysis category.  However, in this discussion of explanatory research, we will focus first on the FOUR main methods of data collection which are also pre-data analysis in nature. That is; Literature Review, Focus Groups, Depth Interview and Case Analysis.

3.1 Literature Review

Past studies carry a lot of information pertaining concept that a researcher may be having interest in. So, review of past literature is one of the key sources of information that build thee foundation for explanatory research. It is easy to access that information unlike in the ancient times, today data or information from past studies is accessible from the internet at a fair price or cost. From the internet, it is possible to access literature materials such as past projects or academic papers, journal articles and books for reference purposes.  Literature review therefore is one of the cheapest and fastest mode of determining the hypothesis of the natural phenomenon. 

3.2 Focus Groups:

This method of data collection, the researcher identifies the specific group where he is able to collect the relevant data for analysis. So, the researcher may look for either 10 to 14 or 15 individuals who he feels that they have first-hand information pertaining the concept or the phenomenon under explanatory interrogation.

3.3 Depth Interview

Unlike the focus group approach, the depth interview focuses or concentrates on one individual with wealth of knowledge or information needed in explanatory research. The researcher identifies a professional in the field of interest and then he interrogates him or her so as to excavate all needed details to build the case of explanatory research. Whoever has the point of detail of the information needed by the researcher is the right candidate for depth interviews. 

3.4 Case Analysis

Another way of collecting data under explanatory research is use of case analysis. This is where the researcher considers similar cases or look for groups with similar experience to what the researcher wants to study. A case study will aid the researcher understand and solve the problem more effectively if a similar case or another group with similar case is incorporated. Therefore, case analysis enables the researcher to identify a business with similar experience or exposure and deal with it more efficiently.

Characteristics of explanatory research 

Explanatory research is distinguished from other types of research due to the following key features associated with it. These are and not limited to;

1). Provides additional useful information for more proper understandability of a particular topic-this type of research may and of course it does not provide conclusive research findings but it highlights underlying reasons as to why things happen the way they happen.

2). Turns a correlation perspective to cause-effect relationship-this research type provides more information which make the researcher to discover the underlying causes of a phenomenon.

3). Explanatory research is the basis with which suggestions for further research is pegged on. This type of research allows other or the same researcher to replicate studies to give them greater depth so as to acquire new and more educative insights into the study problem.

4). Exists where less information pertaining a certain phenomenon is concerned-this type of research is suitable where by the phenomenon is lacking key information to elaborate why things happen the way they happen.

5). Problem-solving-explanatory research has an element of providing an immediate answer to a certain query.

Applicability of explanatory research

Where does explanatory research apply in real life situation?

The following are some of the areas where explanatory research applies well;

1). Applicable when answering a why or when research question.

2). Applies where formulation of hypothesis is necessary to aid in future researches.

3). Used where there is need of more understanding of a particular phenomenon. That is, it just explains what and why something under investigation is occurring.

 4). Applicable where sources of information are accessible in a more flexible manner. This research is much anchored on sources of information which is easily gotten like from literature and individuals who can be cheaply interviewed.   

5). Needed where better conclusions are necessary: Explanation research is needed for further suggestions in research. Meaning that it is useful if further studies on a certain line has to continue.


1). It amplifies research results- this research type gives a bigger picture of what causes the dependent variable behave in a certain manner.

2). Flexibility-explanatory research is not fixed in suggesting which area of further study to focus on. So, it is not fully conclusive.

3). Cheap-explanatory research is cheap because the researcher can make use of an individual on local arrangement basis to collect data in case of depth interview or use Internet of Things (IOT) to collect data from past literature such as journals and magazines.

4). Improvement of internal validity of data-when using explanatory research, the research methodology incorporated so as to take care of causal-Effect association is experimental research which may entail laboratory artificial setting which improves the internal validity of the data used.

5). Improvement of external validity of data- Again, when using explanatory research, the research methodology incorporated so as to take care of causal-Effect association is experimental research which entails field setting which improves both internal and external validity of the data used.


  1. Inconclusive results-explanatory research does not give conclusive results-unlike other types of research. This type of research leaves things pending with an assumption that somebody will finalize the endeavors.
  2. Does not add new information to the already existing body of knowledge-this type of research fails to put immediate addition of new knowledge which is one of the main themes of any nature of research.
  3. Results are subjective-explanatory research is dominated by biased suggestions due to researcher’s over or under judgment.
  4. Coincidental outcome-sometimes there may be coincidental results in a manner that this may be confused with causal association. That is a spurious cause. For example, a pseudo (i.e., false) cause effect element may occur in the model and one think it is a cause-Effect issue.

Difference between explanatory and exploratory research

These two aspects of research are sometimes confusing. One, the names are almost the same. In fact, sometimes when a student is searching for materials of explanatory nature from the internet, he/she may find himself on the side of exploratory research perspective. So where is the difference. The following Table 1.2 portrays the differences based on some criteria used in each case.

About the Author - Dr Geoffrey Mbuva(PhD-Finance) is a lecturer of Finance and Accountancy at Kenyatta University, Kenya. He is an enthusiast of teaching and making accounting & research tutorials for his readers.