Factor Coefficient Matrix Results of Organizational Culture Dimensions Measurement Factors

With the Eigenvalue criterion greater than 1, 2 factors are extracted from 5 variables included in the analysis and these 2 newly extracted factors explain 73.01% of the variation of observed variables.

The two factors that are drawn are:

The first factor : includes 3 variables DS1, DS3, DS4 measuring the factor "Dedication" so factor 1 is named DS .

The second factor : includes 2 variables MV1, MV4 measuring the factor "Linking to public values", so factor 2 is named VM .

Two new factors are also written into equations based on the results of Table 4.23.

Table 4.23: Factor coefficient matrix results of factors measuring public service motivation

Factor 1: DS = 0.818*DS1 + 0.815*DS3 + 0.756*DS4.

Factor 2: VM = 0.891*VM1 + 0.882*VM4.

Summary: After testing the reliability of the research scales, the retained variables were included in the factor analysis.

After EFA factor analysis, 6 new factors were extracted to measure "Organizational culture factors" and coded in the following order: LR, FC, MR, AS, AW, BW.

After EFA factor analysis, two new factors were extracted for measurement.

“Public Service Motivation” and its coding are: DS and VM.

4.4. Regression analysis to test hypotheses.

After testing the reliability of the scales using Cronbach's Alpha coefficient and grouping factors using EFA analysis, the initial variables that did not meet the criteria were removed from the research model.

With 2 EFA analyses, 8 new factors were extracted. Next, the study will use these 8 factors to test the proposed hypotheses:

H1a: Job autonomy positively affects motivation to engage in public values.

H1b: Job autonomy positively affects commitment motivation.

give.

H2a: A clear performance appraisal system has a positive impact on

the driving force behind public values.

H2b: A clear performance appraisal system has a positive impact on motivation to contribute.

H3a: Direct supervisor concern positively affects motivation to engage in public values.

H3b: The concern of direct manager has a positive impact on motivation to contribute.

H4a: A responsible public organization work environment positively affects the motivation to engage in public values.

H4b: Responsible public organization work environment positively affects motivation to contribute.

H5a: The pioneering role of leaders positively affects the motivation to engage in public values.

H5b: The pioneering role of the leader has a positive impact on dedication motivation.

H6a: Bureaucracy negatively affects the motivation to commit to values

labour.

H6b: Bureaucracy has a negative impact on motivation to contribute.

Because the factor "Public service motivation" after EFA factor analysis extracted 2 new factors measuring this factor, which are the factor "Public value engagement" and the factor "Dedication" , therefore, when analyzing the regression to test the 6 hypotheses above, the study will run the regression 2 times corresponding to these 2 new factors.

4.4.1. Factor regression analysis of “Attachment to public values”

1

2

3

4

5

6

To measure the factors of “Organizational culture characteristics” such as: LR, FC, MR, AS, AW, BW, how they affect the variable “Commitment to public values” – VM, we use a regression model to analyze the coefficients and prove the hypotheses. We will put 6 independent variables: LR, FC, MR, AS, AW, and the dependent variable VM into the specific regression equation as follows:

DS = a +

In there:

LR +

FC +

MR +

AS +

AW+

BW + e

job"

VM : is the dependent variable, explaining “The engagement of public values”

LR : is the independent variable, explaining “Leadership Role”

FC : is the independent variable, explaining the factor "Working environment and conditions" MR : is the independent variable, explaining the factor "Role of direct manager" AS : is the independent variable, explaining the factor "Performance evaluation system"

AW : is the independent variable, explaining the factor “Autonomy at work”

BW : is the independent variable, explaining the factor "Level of bureaucracy"

i is the coefficient of the independent variables – indicating the direction and level of impact

of independent variables to dependent variable.

Regression analysis of variables linking fairness values ​​using SPSS 20 software produces the following result tables: ( See details in Appendix 19)

Table 4-24: Summary results of the regression model of the variable “Linking to public values”

Tissue

image

a. Independent variables: BW, AW, AS, MR, FC, LR

b. Dependent variable: VM

Figure 4.4: Regression chart of value-added

Table 4-25: Results of analysis of variance (ANOVA) of the variable “Attachment to

public values”

Model

a. Dependent variable: VM

b.Independent variables: BW, AW, AS, MR, FC, LR

less than the 5% significance level, so the coefficients are statistically significant and considered.

Table 4-26: Regression results of the variable “Linking to public values”

Independent variable

Table 4-26 gives the coefficients of the independent variables, specifically as follows:

- Variable FC : Has a positive regression coefficient of 0.167 and sig is less than 0.05, so this coefficient is also significant and proves hypothesis H4. In other words, when considering the "Public value engagement" aspect of public service motivation, the working environment and conditions have a positive impact on this aspect.

- MR variable : This variable also has a positive regression coefficient of 0.151 and has a sig less than 0.05, so it is also significant in the research model and this regression coefficient has proven hypothesis H3. In other words, the role of the direct manager has a positive influence on the aspect of "Connecting public values" of civil servants.

- AS variable : Has a significant regression coefficient of 0.451 because the sig is less than 0.05. The coefficient of this variable has the largest value, showing that the impact of AS variable on VM variable is the strongest. The positive regression coefficient proves hypothesis H2 in terms of "Connecting public values", or the Performance Evaluation System clearly has a positive impact on "Connecting public values".

- Variable BW : Has a positive regression coefficient of 0.117 because it has a sig less than 5%.

But this regression coefficient gives results that are not as expected.

- Variables LR, AW: The regression coefficients are not significant because the sig values ​​are all greater than 0.05, so the coefficients of these variables are not statistically significant in the research model. With the survey data, considering the Motivation to serve the public according to the aspect of "Commitment to public values", it shows that the role of the leader and Autonomy in work do not have a significant impact on this aspect.

The VIF coefficient of this regression model has a value less than 10, so there is no multicollinearity phenomenon in this model.

4.4.2. Regression analysis of the factor “Dedication”

To see the level of influence of the variables measuring “organizational culture” such as: LR, FC, MR, AS, AW, BW on the variable “Dedication” – DS, we use the regression analysis method to find the coefficients. We will put 6 independent variables: LR, FC, MR, AS, AW, BW in the correct order of the extracted factors and the dependent variable DS into the specific regression equation as follows: