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Consumer Demand for Over-The-Counter Drugs in Nigeria: A Microeconomic Analysis

Domain:

socioeconomichealthcare

Record type:

paper
Creator:
Pel
Publisher:
IIA
Host:
Using a quantitative methodology and a sample size of 300 respondents, this study investigates the factors influencing consumer demand for over-the-counter (OTC) medications in Nigeria from a microeconomic perspective. Price, income, perceived quality, trust, and substitute preferences were all gathered through the use of a standardized questionnaire. To determine the direction and intensity of the correlations between variables that impact the use of over-thecounter drugs, statistical analyses were performed using regression and correlation tests. The results indicate that the quantity of OTC pharmaceuticals demanded is not significantly influenced by price or income, reflecting the inelastic and necessity-based nature of healthrelated consumption in Nigeria. Weak but significant associations were also observed with nonprice criteria, such as perceived quality, trust in shops, and a desire for less expensive alternatives, indicating that behavioral and informational elements have a modest influence on purchasing decisions. These findings are consistent with other research, which shows that perceived effectiveness and accessibility, rather than just economic rationale, frequently influence healthcare spending in developing nations. The study concludes that the demand for over-the-counter drugs in Nigeria is driven more by need than by financial means, highlighting the need for affordability, consumer knowledge, and quality control. Policy implications underscore the need for enhanced consumer education, more robust regulatory oversight, and transparent pricing structures. By providing micro-level insights into self-medication behavior, the study contributes to the growing empirical literature on health economics in emerging markets. To investigate causal mechanisms in more depth and the effects of changing pharmaceutical restrictions, future studies should expand the model to incorporate behavioral tests, longitudinal data, and geographical comparisons.

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