Transforming commitment into performance: a study of digital transformation in the Cambodian public sector amidst a pandemic

Figures & data

Table 1. Factor loadings, reliability, and validity.

Constructs	Loadings
Affective Organizational Commitment (AC) (Cronbach’s Alpha = 0.874, CR = 0.909, AVE = 0.665)
AC1	0.832
AC2	0.819
AC3	0.862
AC4	0.788
AC5	0.774
Normative Organizational Commitment (NC) (Cronbach’s Alpha = 0.871, CR = 0.906, AVE = 0.659)
NC1	0.841
NC2	0.816
NC3	0.843
NC4	0.759
NC5	0.795
Continuance Organizational Commitment (CC) (Cronbach’s Alpha = 0.894, CR = 0.918, AVE = 0.651)
CC1	0.851
CC2	0.851
CC3	0.802
CC4	0.728
CC5	0.793
CC6	0.810
Digital Transformation (DT) (Cronbach’s Alpha = 0.881, CR = 0.914, AVE = 0.680)
DT1	0.806
DT2	0.738
DT3	0.887
DT4	0.874
DT5	0.810
Individual Performances (IP) (Cronbach’s Alpha = 0.876, CR = 0.907, AVE = 0.619)
IP1	0.805
IP2	0.850
IP3	0.811
IP4	0.817

Table 2. Discriminant validity-fornell & larcker criterion.

	AC	CC	DT	IP	NC
AC	0.816
CC	0.594	0.807
DT	0.548	0.577	0.825
IP	0.529	0.473	0.468	0.821
NC	0.342	0.276	0.410	0.274	0.812
Heterotrait-monotrait ratio (HTMT)
AC	–
CC	0.658
DT	0.613	0.624
IP	0.617	0.529	0.538
NC	0.388	0.290	0.459	0.319	–

Table 3. Hypotheses testing.

	Path coefficient	t-value	p-value	Decision
H1: AC → IP	0.314	3.822	0.000	Supported
H2: AC → DT	0.257	4.960	0.000	Supported
H3: DT → IP	0.179	3.252	0.001	Supported
H4: NC → IP	0.046	0.740	0.459	Not-Supported
H5: NC → DT	0.222	4.173	0.000	Supported
H6: CC → IP	0.171	2.437	0.015	Supported
H7: CC → DT	0.363	5.144	0.000	Supported
	R^2		Q^2
IP	0.343		0.211
DT	0.441		0.289

Table 4. Mediation analysis.

	Total effects		Direct effects
	Coefficient	t-value	Coefficient	t-value
AC → IP	0.360	4.610	0.314	3.822
NC → IP	0.085	1.428	0.046	0.740
CC → IP	0.236	3.523	0.171	2.437
Indirect effects
Hypotheses	Coefficient	t-value	p-value	CI [2.5%–97.5%]
H8: AC → DT → IP	0.046	2.657	0.008	.016–.083
H9: NC → DT → IP	0.040	2.392	0.017	.012–.078
H10: CC → DT → IP	0.065	2.852	0.004	.024–.114