Applying a Binary Logistic Regression Analysis to Evaluate the Distinction between Conventional and Islamic Banks: A Case Study of Djiboutian Banks

Abstract

The banking sector has developed dramatically during the past decades. Many banks were established and prospered. However, the experience in each banking sector can be non-identical based on many factors. Therefore, it will be ideal to investigate every aspect of conventional and Islamic banks prior to deciding which bank is favorable. The actual paper compares the conventionaland Islamic banks in Djibouti to identify which types of banks customers would find advantageous. In that context, variables such as the size of the banks, accessibility, financial instruments, and customer interest rate were explored. Moreover, a binary logistic regression analysis was utilized in order to analyze the responses of 200 individuals who use Djiboutian Islamic and conventional banks. Generally, the findings revealed that individuals have the likelihood to prefer CAC international bank which is a conventional bank over Salam Africa bank. Moreover, the predictors (the bank’s size, and accessibility) displayed a none significant p-value that is over 0.05. Whereas customer trust and the interest rate exhibited a significant p-value. The current research is significant to better comprehend the main factors that drive Djiboutian individuals to select a specific bank for their deposits. The findings will also contribute to the wide discipline of literature that always discussed the gap that exists between Islamic and conventional banks

Keywords

• conventional bank
• islamic bank
• logistic regression
• interest rate framework
• costumer trust
• size
• accessibility
• djibouti