CHAPTER 1: INTRODUCING AN INTEREST RATE COMMISSION AGENT BANKING SYSTEM (AIRCABS) 4.5. Research participants and sample size 4.6. Sample and sampling method 4.7. AIRCABS process flow model 4.8. Material and methods 4.8.1. Measurement instrument 4.8.1.1. Measurement instruments used to collect primary data by survey questionnaires 4.8.1.2. Measures of continuous data type instruments applied in the models 4.9. Method of analysis 4.9.1. Canonical correlation 4.9.1.1. Canonical Correlation Analysis 4.9.2. Multinomial logistic regression 4.9.2.1. Multinomial logistic regressions analysis 4.9.3. Merging individuals survey respondents' perception with quantitative data analysis result 107 4.10. Chapter summary vii CHAPTER 5: TESTING PERFORMANCE OF AN INTEREST RATE COMMISSION AGENT BANKING SYSTEM (AIRCABS) 5.1. Introduction 5.2. Statistical result and analysis 5.2.1. Validity and reliability of survey instruments 5.2.1.1. The statistical result of individual perception responses on Credit risk and liquidity crunch and AIRCABS survey instruments 5.2.1.2. Factor analysis for validity of credit risk and liquidity crunch and AIRCABS survey questionnaires 5.2.1.3. Measuring investor loan funding and discrete market deposit interest incentive survey instrument using the Kuder-Richardson test 5.2.1.4. Factor analysis for validity of investor loan funding and discrete market deposit interest incentive survey questionnaires 5.3. Canonical correlation statistical result 5.3.1. Level of significance of canonical correlation 5.3.2. The magnitude of canonical correlation 5.3.3. Redundancy measure of share variances 5.3.4. Individual perception of credit risk and liquidity crunch and AIRCABS survey questionnaires 5.4. Statistical result of investor loan funding and discrete market deposit interest rate incentive 5.4.1. Model fitting information 5.4.2. Goodness-of-fit 5.4.3. Pseudo R-Square 5.4.4. Likelihood Ratio Tests viii 5.4.5. Parameter estimates 5.4.6. Classification table 5.4.7. Comparing by chance accuracy with model accuracy rate 5.4.8. Individual perception on investor loan funding and discrete market deposit interest incentive 5.5. Chapter
This paper sought to analyze data and interpret statistical results in testing the performance of an interest rate commission agent banking system. Primary and secondary data were collected from banking industry in Ethiopia to test the research hypotheses, credit risk and liquidity crunch have no impact on AIRCABS, investor loan funding has a positive impact on profitability and sustainability of AIRCABS and discrete market deposit interest rate incentive has a positive impact on stable deposit mobilization in a bank. To test the hypothesis, statistical tools such as Cronbach's alpha, KuderRichardson (KR-20), canonical correlation and multinomial logistic regression were used. The result showed that credit risk and liquidity crunch have no effect on an interest rate commission agent banking system, investor loan funding has a significant strong relationship with profitability and sustainability of AIRCABS and discrete market deposit interest rate incentive has also a significant strong relationship with stable deposit mobilization. This led to a conclusion that an interest rate commission agent banking system (AIRCABS) model is viable and reliable.
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