A logistic Regression Model of Factors Predicting Demand of Bank Loans by Customers in Greece

Abstract:

Developing appropriate marketing strategies requires from commercial banks to identify customer-related factors that lead to bank loaning. The objective of the present paper is to identify these factors that influence customers decision to take a loan from commercial banks. We hypothesized that demographics, service quality and satisfaction influence the decision of taking a loan. A general population sample of Greek citizens was chosen to examine this research question (n= 277). The scales used were self-determined; our instrument was validated through confirmatory factor analysis, which presented overall good fit. Binary logistic regression showed that significant predictors of taking loans were Personal Marital Status, Customer service, shop design (number of automatic transaction machines, bank branches and personnel education) and Interest Rates whose odds ratios were all significantly above 1. These results have important implications for bank managers who should focus giving loans to single individuals as well as change their interest rates policy by decreasing the rates for all kinds of loans, especially housing loans.