Multilevel logistic regression analysis of factors influencing the usage of credit cards

Credit cards have become one of the most widely accepted, useful and profitable financial products around the world. Many consumers and merchants around the world accept it as a routine payment instrument for the full range of products and services. The study aimed to recognize the factors affecting for usage of credit cards with multilevel logistic regression analysis. Especially, whether gender is effective on the use of credit cards. It is useful to understand hierarchical data structures such as multi-level models, students in class, employees in firms, customers in bank branches. Multilevel (hierarchical) logistic regression analysis is the method of finding the relationship between two variables or more for the multilevel data and the dependent variable of multilevel logistic regression is the dichotomous variable, which is distributed as the Bernoulli distribution such as using credit cards, marrying, adopting a new technology. In this article, we were applied the multilevel analysis approach to the 399 bank customer data and were studied the characteristics of credit card users nested within 59 bank branches. According to the results of the study, gender, marital status, occupation and income was found to be significantly influence on credit card usage. And the Credit card usage averages were varied in bank branches. Keywords: Multilevel Logistic Regression Analysis, Usage Of Credit Cart