Furthermore, findings reinstated that both the directional hypotheses are supported by empirical evidence and could be established that the adoption of OB is positively correlated with both the
E-Service … Gayan & Damunupola . 277 JECET; September 2019- November 2019; Sec. B; Vol.8. No.4, 265-289. . DOI: 10.24214/jecet.B.8.4.26589. adoption dimensions and TES characteristics in the context of largest three private commercial banks operating in Sri Lanka. Table 2: Correlation matrix Adoption of OB TES Adoption Adoption of OB TES Adoption 1 .875 ** .916 ** 1 .847 ** 1 ** Correlation is significant at the 0.01 level (1-tailed), Source: Survey data 2019 A multiple regression analysis was conducted using hierarchical method (each set of summary statistics is repeated at each stage of the hierarchy) to predict the degree to which independent variables; adoption and TES impact the adoption of OB (Table 3a and Table 3b). In accordance with model 1 (Table 3a), the overall variance of OB adoption explained by TES is 76.2% as per the adjusted R square figure. According to the significance value, model 1 is statistically significant. Table 3a: Regression output and coefficients t Sig. F Change df Sig. F Change Adj. R 2 Model 1 (Constant) TES 26.29 29.68 .000 .000 2.108 0.621 881.14 1 .000 .765 Dependent variable: Adoption of OB; Predictors: (Constant), TES;Source: Survey data 2019 In accordance with model 2 ( Table 3b), the overall variance of OB adoption explained by TES and adoption is 87.4% as per the adjusted R square figure. According to the significance value, model 2 is also statistically significant. As implied by the beta values and t statistics, considering the strength of the influence of each independent variable on adoption of OB, the adoption dimension is the largest contributor with 15.24 t statistic and .620 standardized beta coefficient statistics, respectively. Furthermore, it is evident that both adoption and TES variables positively influence the adoption of OB given the positive beta coefficient values and significance of same. Improvement from the model 1 to model 2 can be seen while observing the F change and R square change with the addition of adoption variable in addition to TES variable. For the model 1 F change is 881.14 and for the model 2 it is 232.27 in which both are significant. Similarly, explanation of adoption of OB only by TES was 76.6% and with the addition of adoption variable same has been increased to 87.4% reporting an R square change of 10.9%.
E-Service … Gayan & Damunupola . 278 JECET; September 2019- November 2019; Sec. B; Vol.8. No.4, 265-289. . DOI: 10.24214/jecet.B.8.4.26589. Table 3b: Regression output and coefficients t Sig. F Change df Sig. F Change Adj. R 2 Model 2 (Constant) TES Adoption 17.29 08.62 15.24 .000 .000 .000 1.339 0.249 0.496 232.27 1 .000 .874 Dependent variable: Adoption of OB; Predictors: (Constant), TES, Adoption;Source: Survey data 2019 For the current model the VIF and Tolerance values recorded as 3.535 and .283 which are well below 10 and above 0.2 subsequently; therefore, it could be safely concluded that there is no collinearity within the data. Even the average VIF which is also 3.535 is not substantially greater than 1 which also shows that there is no cause for concern.
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