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Due to the recent development of electronic commerce (EC) technology, sale amounts on EC sites have increased rapidly. Large amounts of consumer purchase history data can now easily be obtained, and many data-based approaches to identifying consumer purchase trends have been studied. On the other hand, since diversification of consumer consciousness such as their values and lifestyles are important for marketing research, many approaches to identifying the relationship between "consumers' values and consciousness" and "consumers' preferences underlying their purchase behavior" have been discussed in the existing literature. To investigate consumers' values and consciousness, a questionnaire survey is an efficient tool. It is, however, difficult to collect questionnaire responses from all consumers due to cost issues. Therefore, it is difficult to know the values and consciousness of consumers who have not responded to the questionnaire. In this study, we propose a new model to identify both consumer purchase behavior and their consciousness based on a latent class model estimated by questionnaire responses and the purchase history data for all users. In addition, we apply the proposed model to actual data to analyze its effectiveness.

Recently, credit cards with point rewards functions (rewards credit cards) are widely used. Credit card companies can collect the users’ usage log data of various stores in multiple industries. The purposes of possessing a credit card varies depending on each user such as to use only the credit function, to use both the credit and point rewards functions, etc. Moreover, credit cards can be used in various situations in users’ lives, and the purchase history of each user is diverse. Focusing on the diversity of both card possessing purposes and purchasing behavior for each user, we propose two latent class models representing these diversities in this research.

In 2015, Nepalese people faced two serious