Service organizations in today’s globalized competitive business environment engaged in marketing strategies are geared toward responding to consumer needs and preferences and, at the same time, improve their competitive edge. Investigating the determinants of consumer preference is one of the important approaches to improving competitive edge of petrol station business. Despite significant studies on consumer behavior, especially factors that affect a new brand or products, there is limited empirical investigation on the premise of determinants of consumer preference particularly in petrol station business, thus creating a gap in this area. To this effect, this article intends to contribute in filling the knowledge gap by investigating the determinants of consumer preference and their impact on service station business in the Gambia. This article also identifies key marketing strategies that petrol station business can use to increase their market share. Using non-probability convenience sampling, data were collected from 200 customers of petrol stations using self-administered questionnaires. Descriptive statistics, correlation and regression analysis were applied to analyze data using IBM SPSS statistics Version 22. The results of regression analysis identify marketing program and additional ser- vices out of the eight variables (marketing program, additional services, petrol station image, location, price, product assortment, service quality and management of service station) as the major determinants of service station consumer preference in the Gambia. This implies that petrol station companies should engage key marketing program strategies such as sales promotion, innovative product advertising, event sponsorship or association besides the provision of additional services like windscreen cleaning, water and air pumping, convenience store, fuel and motor product accessories sales plus services in order to increase sales as well as retain a large number of buyers as loyal customers.
additional services, consumer preference, marketing programs, multiple regression analysis, petrol station, sustainable energy market
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