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employment stability, and participation. Overall, the SHRM scale is reliable and retained
for subsequent regression analysis.
4.3. Regression analysis results
To test the research hypotheses concerning the impact of digital transformation
factors on Sustainable Human Resource Management in tourism cooperatives, multiple
linear regression analysis was conducted. In this model, Sustainable Human Resource
Management (SHRM) serves as the dependent variable, while Digital Infrastructure (DI),
Digital Leadership (DL), Digital Capability (DC), and Digital Application (DA) are included as
independent variables.
Table 6. Model Summary b

Std. ErrorChange Statistics
Adjusted
Model R R Square of the R Square Sig. F Durbin-Watson
R Square FChange df1 df2
Estimate Change Change
1 805 a 647 .640 .46642 .647 9.470 4 195 .000 1.851
a. Predictors: (Constant), DA, DC, DI, DL
b. Dependent Variable: SHRM
Source: Author
Multiple linear regression was conducted to examine the impact of digital
transformation factors on Sustainable Human Resource Management (SHRM), with DI, DL,
DC, and DA as independent variables. The model demonstrates good fit (R = 0.805; R² =
0.647; Adjusted R² = 0.640), indicating that digital transformation explains 64.7% of the
variance in SHRM. The model is statistically significant (F = 89.470, p < 0.001), confirming
the joint effect of the independent variables. The Durbin–Watson statistic (1.851)
indicates no autocorrelation, satisfying regression assumptions. Overall, the results
confirm that digital infrastructure, leadership, capability, and application significantly
contribute to explaining variations in SHRM in tourism cooperatives.
ANOVA test of the regression model
An ANOVA test was conducted to evaluate the overall suitability of the regression
model. The results indicate that the model is statistically significant and appropriate for
the data.
Table 7. ANOVA a
Sum of Mean
Model Squares df Square F Sig.
1 Regression 77.855 4 19.464 89.470 .000 b
Residual 42.421 195 .218

Total 120.276 199
a. Dependent Variable: SHRM
b. Predictors: (Constant), DA, DC, DI, DL
Source: Author
The regression sum of squares (77.855) represents the explained variance in SHRM,
while the residual sum of squares (42.421) reflects the unexplained portion, with a total
variance of 120.276. The model is highly significant (F = 89.470, p < 0.001), indicating that
the independent variables jointly have a significant effect on SHRM. This confirms that
digital transformation factors - DI, DL, DC, and DA - collectively influence sustainable

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