Explaining and modeling the behavior of tire buyers based on the four factors of personal, market, store and product

Understanding the car tire market is very important for both producers and consumers due to its impact on the final price of the car, incurring fixed costs for the car owner and the high amount of financial transactions. The purpose of the current research is to explain and model the behavior of tire buyers based on four factors using a combined approach. In the first step, by reviewing the literature and the background of the research, the factors affecting the purchase of Iranian or foreign tires were identified according to the four factors of personal, market, store and product. In the second step, in order to analyze the behavior of Iranian or foreign rubber buyers, using non-hierarchical cluster analysis (mean k) and based on the 24 factors of the analyzed population and the number of optimal clusters according to the Davis-Bouldin index, Then, using artificial neural networks, the independent variables of the research (four factors of personal, market, store and product) were used to predict the dependent variable (purchase of Iranian or foreign tires). The statistical population of the research was Iranian or foreign rubber buyers in the west of Mazandaran province, and due to the unlimited population of the research, the unlimited population formula was used to determine the sample size, the minimum sample size was 384 and the analysis was done on 527 usable questionnaires. The results of the research showed that in the first cluster, in the order of price, safety standards, image and reputation of the store, and in the second cluster, in the order of proximity, friendly behavior of sellers, and the breadth of choice, they have obtained the most centers of the clusters. The use of neural networks showed that the independent variables of the research have a good predictive ability and by using them, 0.886 changes of the dependent variable can be predicted.