Measure assessment 1. Reliability analysis

To ascertain the reliability of the measurement scales and to check the degree to which the items that make up the scale “hang together”, Cronbach alpha

coefficient is calculated. Cronbach s alpha checks the internal consistency ‟

reliability of scales. It checks if whether the items that make up the scale actually measure the same underlying construct (Pallant, 2001). For scale to be reliable, its Cronbach alpha value should be above 0.6 (George & Mallery, 2003).

The above guideline indicates that the higher the Cronbach s alpha value is, the ‟ more reliable are the items measuring a give construct. Cronbach s alpha closer ‟ to 1.0 is preferred. A Cronbach s alpha value of 0.9 and above was regarded as ‟ the most reliable of scales, while a scale that has a Cronbach s alpha value that is ‟ below 0.5 is regarded as unreliable and cannot be used to measure a given

construct.

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Table 9: Reliability analysis for each factor

Corrected

2.941

PEU06 10.95 4.069 .569 .886

PEU07 11.52 3.471 .779 .804

PEU08 11.24

3.769

Perceived ease of use Cronbach's Alpha

ATT11

SN13

SN16

.530 .841

Subjective norm Cronbach's Alpha .846

PBC19 11.09 3.188 .692 .808

PBC20 10.37 3.261 .582 .849

PBC21 11.50 2.644 .769 .770

PBC22 10.95 2.770 .720 .793

Perceive behavioral Cronbach's Alpha .848

control

INT23 6.90 2.124 .771 .887

INT24 7.19 1.995 .856 .811

INT25 7.39 2.248 .787 .872

Intention to use MB Cronbach's Alpha .901

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Table 8 depicts a summary of the beta scores of all the response ranking of the factors that affect the intention to use mobile banking in HCM. According to the data analysis, the factor "Perceived Usefulness" Cronbach's alpha coefficient is 0.625. After delete PU03 item of this factor, then the factor "Perceived

Usefulness" Cronbach's alpha coefficient increased to 0.652. Other factors exhibit a Cronbach s alpha coefficient from 0.846 to 0.901. Among the factors, the factor‟

“intention to use mobile banking” has the highest ranking of Cronbach alpha of 0.901, followed by the factor “perceived ease of use” and “attitude” with 0.867.

The factor “subjective norm” has the lowest ranking with 0.846. Hence, six variables were retained.

4.2.2. Exploratory Factor Analysis (EFA)

The test of the measurement model includes the estimation of using item-to-total correlations (>0.5) and the convergent and discriminant validity of the instrument items. The convergent validity is demonstrated when items load highly (loading>

0.5) on their associated factors.

Dependent variable and the independent variables were analyzed independently of each factor. All the variables were extracted through the Principal axis

factoring, using the Promax rotation method. After three times of running factor analysis, the result shows that all remained variables are greater than 0.5 and a significant loading on an acceptable factor. Advanced data processing steps as follows:

The first time running factor analysis for independent variables, there are six factors with the eigenvalues that are higher than 1 (see Appendix 5). The variables PU05, PEU06, PBC20 have a cross-loading (see Appendix 6).

Therefore, they were deleted from the analysis and the loadings recalculated.

The second time running, six factors were extracted (see Appendix 8).

The last time, running factor analysis for dependent variables.

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Rotation was converged in six iterations. The generated factors, the attributes of each factor loadings are present in Table 9. All items have large and significant loadings on their corresponding factors. The composite reliabilities of the

different measures included in the model ranged from 0.645 to 0.955. Further, the shared variance is less than the amount of variance extracted by the indicators measuring the constructs. Thus, the convergent and discriminant validity are meet. Taken together, the evidence indicates the scales' had adequate

psychometric quality for usage in the next stage of analysis.

After processing factor analysis for the independent variables and the dependent variable by the Promax method has five factor are formed, there are three items (observed variables) are removed because values less than 0.5. The 22 items were selected and have values above 0.5, with significant dependent variable. The factors form after the implementation of EFA: perceived usefulness, perceived ease of use, attitude, subjective norm, perceived behavioral control, and intention to use mobile banking.

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Table 10: Key dimensions, items Dimension

Factor Loading

PU01 - Flexibility to conduct banking business 24 hours per .742

X1 -day

Perceived

PU02 - Make banking transactions quickly .648

usefulness

PU04 - MB transactions relevant to my work .497

PEU07 - Instructions in MB system are clear and .729

understandable

X2

-PEU08 - MB has many flexible ways to search your required .801

Perceived

information

ease of use

PEU09 - I feel that user-friendliness of MB services is .979

important

ATT10 - Using MB would be a wise idea .779

X3

-ATT11 - Using MB is a good idea .894

Attitude

ATT12 - I like to use MB .921

SN13 - People important to me would think that using MB

.688

would be a wise idea

SN14 - People important to me would think that using MB is a .653

good idea

X4 –

SN15 - Most people important to me would think that I should .957

use MB

Subjective

SN16 - My family important to me would think that using MB .860

norm

would be a wise idea

SN17 - My family important to me would think that using MB .902

is a good idea

SN18 - My family important to me would think that I should .783

use MB

X5

-PBC19 - I would be able to operate MB .958

Perceived

PBC21 - I have the knowledge to use MB .752

behavioral

PBC22 - I have the ability to use MB

.621

control

Y –

INT23 - Plan to use MB .815

Intention

INT24 - Intention to use it within the next tree months .948

to use

INT25 - Add MB to my favorite apps

mobile

.841

banking

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