Using technology acceptance model to investigate digital business intention among Indonesian students

Figures & data

Figure 1. Research framework.

Source: Own elaboration based on Vejayaratnam et al. (2019), Hasan et al. (2017), Liñán and Chen (2009), Venkatesh and Bala (2008).

Table 1. Descriptive statistics of participants.

Characteristics	% (N = 309)
Gender
Female	50.4 (156)
Male	49.6 (153)
Age Statistics
19-22 years old	60.5 (187)
23-25 years old	39.5 (122)
Min: 19 years old	9.4 (29)
Max: 25 years old	21.4 (66)
Mean	22.6
Median	23.0
SD	2.03
Year class
2019	52.1 (161)
2020	47.9 (148)
Parents’ occupation
Entrepreneur	57.6 (178)
Teacher/Lecturer	16.1 (50)
Farmers	15.8 (49)
Civil Servants	10.5 (32)
Subject
Management	33.3 (103)
Economic Education	33.6 (104)
Accounting	33.1 (102)

Table 2. Measurement model.

Items	λ	α	CR	AVE	Mean	SD
Digital entrepreneurship education (DEE)		0.899	0.925	0.713
DEE1	0.848				3.638	1.066
DEE2	0.852				3.967	0.983
DEE4	0.842				3.481	1.220
DEE5	0.833				3.543	1.060
DEE7	0.847				3.152	1.259
Digital entrepreneurial intention (DEI)		0.851	0.893	0.626
DEI1	0.792				3.933	1.089
DEI3	0.793				4.314	0.974
DEI5	0.772				3.690	1.282
DEI6	0.857				3.810	1.220
DEI7	0.740				3.652	1.230
Digital entrepreneurial self-efficacy (DESE)		0.857	0.903	0.701
DESE1	0.850				3.481	1.001
DESE2	0.806				3.595	0.922
DESE3	0.823				3.500	1.143
DESE4	0.868				3.321	1.210
Perceived usefulness (PU)		0.820	0.840	0.724
PEOU1	0.860				3.390	1.159
PEOU4	0.842				3.476	1.101
Perceived ease of use (PEOU)		0.838	0.891	0.673
PU1	0.877				3.405	1.228
PU2	0.724				3.190	1.254
PU3	0.811				3.143	1.287
PU4	0.861				3.122	1.231

Note. CR = composite reliability, α = Cronbach’s alpha, AVE = average variance extracted, λ = loading, SD = standard deviation.

Table 3. Discriminant validity.

	DEE	DEI	DESE	PEOU	PU
DEE	0.844	–	–	–	–
DEI	0.775	0.791	–	–	–
DESE	0.557	0.620	0.837	–	–
PEOU	0.672	0.690	0.612	0.851	–
PU	0.582	0.621	0.519	0.768	0.821

Note. DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Table 4. Discriminant validity using HTMT.

DEE	DEE	DEI	DESE	PEOU	PU
DEI	0.877	–	–	–	–
DESE	0.632	0.724	–	–	–
PEOU	0.898	0.841	0.836	–	–
PU	0.667	0.725	0.591	0.805	–

Note. DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Table 5. Variance inflation factor (VIF).

	DEE	DEI	DESE	PEOU	PU
DEE		1.972	1.858
DEI
DESE		1.712
PEOU		3.245	2.998
PU		2.498	2.488

Note. DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Table 6. R² estimation.

	R^2	Category
DESE	0.416	Moderate
DEI	0.680	Substantial

Note. DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Table 7. f² estimation.

	f^2	Category
DEE → DEI	0.400	Large effects
DEE → DESE	0.361	Large effects
PU → DESE	0.386	Large effects
PU → DEI	0.217	Medium effects
PEOU → DEI	0.182	Medium effects
PEOU → DESE	0.282	Medium effects

Note. DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Table 8. Evaluation result of fit model.

	Saturated model	Estimated model
SRMR	0.066	0.066
d_ULS	0.907	0.907
d_G	0.431	0.431
Chi-Square	782.723	782.723
NFI	0.916	0.916

Note. SRMR = standardized root mean squared residual, d_ULS = the squared Euclidean distance, d_G = the geodesic distance, NFI = Normed fit index.

Figure 2. The result of structural model.

Table 9. Path coefficient.

Path	β	SE	t-value	p-value	BC		Decision
					LL	UL
DEE → DEI	0.502	0.050	9.943	0.000	0.410	0.571	H1 Supported
DEE → DESE	0.257	0.066	3.926	0.000	0.155	0.370	H2 Supported
PU → DESE	0.077	0.066	1.175	0.120	−0.030	0.188	H3 Not supported
PU → DEI	0.117	0.055	2.139	0.016	0.028	0.206	H4 Supported
PEOU → DEI	0.147	0.068	2.154	0.016	0.027	0.257	H5 Supported
PEOU → DESE	0.379	0.092	4.137	0.000	0.223	0.514	H6 Supported
DESE → DEI	0.147	0.068	3.564	0.000	0.105	0.277	H7 Supported
DEE→ DESE →DEI	0.049	0.019	2.606	0.005	0.022	0.081	H8 Supported
PU→ DESE →DEI	0.015	0.014	1.923	0.155	0.005	0.042	H9 Not supported
PEOU→DESE→DEI	0.072	0.026	2.800	0.003	0.031	0.800	H10 Supported

Note. t-value >1.96, p < 0.05, BC = bias corrected, UL = upper level, LL = lower level, SE-standard error, β= path coefficient, DEE = digital entrepreneurship education, DEI = digital entrepreneurial intention, DESE = digital entrepreneurial self-efficacy, PEOU = perceived ease of use, PU = perceived usefulness.

Vejayaratnam, N., Paramasivam, T., & Mustakim, S. S. (2019). Digital entrepreneurial intention among private technical and vocational education (TVET) Students. International Journal of Academic Research in Business and Social Sciences, 9(12), 110–120.

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