Discovery and analysis of shopping behavior of older customers decide to buy organic products: The combination of clustering and decision tree

Analysis decision-making patterns of buying behavior of customers and providing a predictive model is one of the challenges and areas of interest to researchers which can be widely used in the field of localization products. This study aimed to analyze and model the behavior of older customers decide to buy organic products with the hybrid approach. The research was done in two steps linked together. In the first step the reliability and validity of a questionnaire with 33 question was evaluated respectively by Cronbach's alpha and confirmatory factor analysis first and second order was approved. Opinion of 388 old customer using nine indicators were collected, then, using cluster analysis K-means based on Davies-Bouldin and sylvite criterion the optimal clusters was identified. And elderly clients in the two clusters were unwilling and eager to buy organic products was classified. In the second step purchasing behavior using decision tree models were analyzed and the optimum model was extracted "if-then" rules associated with each cluster were presented. The results showed that in both unwilling and eager cluster, education index predict the decisive factor in the decision to buy organic products, It also seems that the consumption of organic products among the elderly is not in good condition in this context proposals were presented for each cluster.