Internet Banking Service
Table 2: Type of Future Service Required to be Offered by Bank
Note: 115 missing cases; 292 valid cases
The hypothesis was tested by (binary) logistic regression analysis, a multivariate technique used to predict the presence or absence of a characteristic or outcome based on values of a set of predictor variables. The technique is similar to a linear regression model but is suitable for models where the dependent variable is dichotomous. Independent variables can be categorical (i.e. ordinal) interval and ratio data (Norusis, 2000). To select predictor variables, the forward stepwise regression method was used. Forward stepwise starts with a model that contains only the constant. Variables are examined based on entry and removal criteria (Norusis, 1999).
The following table summarizes all variables significantly associated with intention to adopt, where B is the regression coefficient, SE is the standard error of B and Sig. is the likelihood of the variable actually being statistically insignificant. The remaining variables were not significant and dropped from the model by the regression analysis program.
Table 3: Logistic Regression Analysis: Forward Stepwise (Wald)
ABAC Journal Vol. 22, No.3 (September - December, 2002), pp. 63 - 80