An investigation for consumers' gas stations selections using the analytical hierarchy process (AHP) approach

Today, environmental awareness on environmental degradation have become one of the main factors affecting consumers' consumption habits and buying behaviors. Consumers whose increasing level of consciousness on global warming danger caused by greenhouse gas emission stemming from transportation, tend to start considering green transportation and adjust their fuel-oil buying behavior in accordance with this consciousness. With the competition in the fuel-oil market in Turkey, it becomes of greater significance for gas stations to develop strategies which fit into this changing consumer profile, understand the consumers, determine their changing needs and meet these needs in beating their competitors. For this reason, the aim of this study is to identify factors influencing gas station preferences and determine to what extend consumers' environmental attitude and behavior affect gas station preferences. For data collection, face to face survey was conducted in the city of Ankara on 400 consumers, chosen by convenience-sampling, to identify the factors influencing consumers' gas station preferences and then 150 consumers, again chosen by convenience sampling, in order to determine relative importance weights of these factors. Collected data was applied Exploratory Factor Analysis (EFA) using SPSS 22 and Analytic Hierarchy Process (AHP) using Expert Choice 11. EFA showed that sales promotion, price, payment opportunities, brand, location of station and technical services factors are the most effective factors on gas station preferences. According to AHP results, it was determined that environmental responsibility and transparency and environmental practices considerably affect environment conscious consumers' gas station preference. Keywords: Oil, Gasoline Products, Green Marketing, Consumer Preferences, Gas Station, Gasoline Consumers,Environmentally Conscious Consumers, Analytical Hierarchy Process, Multiple-Criteria Decision Analysis.