One of the readers — Adwoa — requested help on consumer perception about locally produced rice after reading the post titled “Conceptual Framework: A Step-by-Step Guide on How to Make One.” This issue falls under the purview of consumer behavior analysis.
How would she come up with her conceptual framework? What are the variables she should take into consideration?
I do not exactly know why she decided to pick this topic. Perhaps she wants to know the consumers’ buying behavior in her place. It is possible that the main issue she is trying to resolve has something to do with consumer rice preference.
Thus, in framing the research issue, it is important to define the intention. What does the researcher want to achieve at the end of the study? Hence, the objectives of the study must be clear.
For discussion purposes, I presume that Adwoa would like to know if significantly more consumers in her locality buy rice produced in other places than locally-produced rice. Specifically, she might want to find out if there is a preference for imported rice. Thus the objective is:
Find out if imported rice is preferred over locally-produced rice.
To make clear the issue, let us state the problem in question form. Hence, the question that will guide our thinking shall be:
Problem Statement: Are there more people buying imported than locally-produced rice?
Consumer Behavior Analysis Framework for the Study
The variable in question must be identified to understand consumer behavior. A variable is an entity that takes on different attributes.
In our example, the variable is the source of rice, i.e., whether it is local or imported. These attributes are textual, meaning, they do not show values but just categories. Thus, the consumer is presented with only two options: to buy local or imported rice.
A research hypothesis, represented by Ha, can then be drawn:
Ha: Significantly more consumers buy imported rather than locally-produced rice.
The researcher conceptualizes that the consumer’s decision to buy depends on whether the source of rice is local or imported. Perhaps, what prompted Adwoa to conduct the study is her observation that demand for imported rice is high as evidenced by a greater volume of consumption of that type of rice.
The type of data gathered in this study is referred to as frequency data. A simple Chi-square Goodness-of-Fit test will show if more people buy (or prefer) imported to local rice.
If for example, the proportion of randomly selected people buying imported rice versus local rice in a population of 100 is 80:20, apparently it shows that more people buy imported rice than local. However, if the proportion is something like 56:44, will you conclude in the same way? That data requires statistical analysis. The Chi-square goodness of fit test takes care of that.
If indeed the consumers prefer imported to local rice, then Adwoa might wonder and ask: “Why do people prefer imported rice?” Thus, the factors that affect the choice of rice type may be explored.
The paradigm that will guide the study might look like this:
Why include age, gender, and economic status in the picture? As a researcher, Adwoa might have noticed that most of those who buy rice are young, females, and belong to the higher echelon of society. Perhaps these factors may have influenced the decision to buy imported rice.
The alternative hypothesis (Ha) for the study at this stage, therefore, will be:
Ha: Age, gender, and economic status determine rice preference.
But do age, gender, and economic status determine rice preference? Before finalizing her conceptual framework, Adwoa may review the literature on consumer behavior analysis first to find out if somebody has done a similar study. If she does find related studies, then she can cite those studies to strengthen further or enhance the conceptual framework.
Analyzing the relationship between profile and preference requires a good knowledge of the appropriate statistical test. Thus, building the conceptual framework in this instance requires the guidance of a statistician or at least a working knowledge of statistics.
Consumer behavior analysis can thus guide policy makers in drawing out policies to guide local consumers. Preference for imported rice can affect local farmers and the local economy in general. Hence, research lends help to policy making.
©2017 P. A. Regoniel
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