Causal research, also known as explanatory research is conducted in order to identify the extent and nature of cause-and-effect relationships. Causal research can be conducted in order to assess impacts of specific changes on existing norms, various processes etc. Causal studies focus on an analysis of a situation or a specific problem to explain the patterns of relationships between variables. Experiments are the most popular primary data collection methods in studies with causal research design.
|Causal research||Exploratory research||Descriptive research|
|Amount of uncertainty characterising decision situation||Clearly defined||Highly ambiguous||Partially defined|
|Key research statement||Research hypotheses||Research question||Research question|
|When conducted?||Later stages of decision making||Early stage of decision making||Later stages of decision making|
|Usual research approach||Highly structured||Unstructured||Structured|
|Examples||‘Will consumers buy more products in a blue package?’
‘Which of two advertising campaigns will be more effective?’
|‘Our sales are declining for no apparent reason’
‘What kinds of new products are fast-food consumers interested in?’
|‘What kind of people patronize our stores compared to our primary competitor?’
‘What product features are th most important to our customers?’
Examples of Causal Research (Explanatory Research)
The following are examples of research objectives for causal research design:
1. To assess the impacts of foreign direct investment on the levels of economic growth in Taiwan
2. To analyse the effects of re-branding initiatives on the levels of customer loyalty
3. To identify the nature of impact of work process re-engineering on the levels of employee motivation
Advantages of Causal Research (Explanatory Research)
1. Causal studies may play an instrumental role in terms of identifying reasons behind a wide range of processes, as well as, assessing the impacts of changes on existing norms, processes etc.
2. Causal studies usually offer the advantages of replication if necessity arises
3. This type of studies are associated with greater levels of internal validity due to systematic selection of subjects
Disadvantages of Causal Research (Explanatory Research)
1. Coincidences in events may be perceived as cause-and-effect relationships. For example, Punxatawney Phil was able to forecast the duration of Winter for five consecutive years, nevertheless, it is just a rodent without intellect and forecasting powers, i.e. it was a coincidence.
2. It can be difficult to reach appropriate conclusions on the basis of causal research findings due to the impact of a wide range of factors and variables in social environment. In other words, while casualty can be inferred, it cannot be proved with a high level of certainty.
3. It certain cases, while correlation between two variables can be effectively established; identifying which variable is a cause and which one is the impact can be a difficult task to accomplish.
My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance contains discussions of theory and application of research designs. The e-book also 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, methods of data collection, data analysis and sampling are explained in this e-book in simple words.
 Source: Zikmund, W.G., Babin, J., Carr, J. & Griffin, M. (2012) “Business Research Methods: with Qualtrics Printed Access Card” Cengage Learning