An automatic classification system for consumer regulatory focus by analyzing web shopping logs

According to regulatory focus theory, a representative theory on consumer behavior, human personality can be divided into two types: promotion and prevention. These two personality types have much influence on the consumer's decision in many diverse areas, such as information exploration, information processing, and the evaluation of alternatives. In this research, we try to classify the consumer's regulatory focus using web shopping logs as the groundwork for adapting it to personalized recommendation. For this purpose, we define the consumer's behavior variables, utilitarian preference index, and information exploration activity index by analyzing the web shopping logs. We then use these variables as inputs to learn a classifier for predicting the consumer's regulatory focus. This research shows the possibility of systematization of the consumer behavior theory as an interdisciplinary research of social science and information technology. Based on this attempt, research can be extended to IT services adapting social science theories to a variety of areas, apart from the consumer behavior area.