The mediating role of behavioral intention on factors influencing user behavior in the E-government state financial application system at the Indonesian Ministry of Finance

Figures & data

Figure 1. Research model.

Table 1. Respondent demographic.

Respondent demographic	Category	Total	Percentage
Gender	Male	150	55,35%
	Female	121	44.,65%
Age	21–40	178	63,69%
	40–59	93	34,31%
Operators	Payments operators	96	35,8%
	Budgeting operators	100	36,6%
	Commitment operators	75	27,6%
Experience	<1 year	55	20.29%
	1–2 year	105	38.74%
	3–5 year	111	40.97%

Table 2. Non-response bias test.

Respondent answer	N	Means	Levene’s test		t-test
			F	Sig	t	Sig (2-tailed)
On time	241	123,88	5,716	0,018	−0,684	0,495
Late	30	125,94			−0,920	0,362

Table 3. Descriptive statistics.

Variable	N	Minimum	Maximum	Mean	Std. deviation
PE	271	9	20	17.04	2.602
EE	271	9	20	16.10	2.755
SI	271	10	20	16.54	2.298
FC	271	8	20	16.85	2.322
HM	271	8	20	16.21	2.604
H	271	9	20	16.61	2.349
BI	271	7	15	12.57	1.921
B	271	7	15	12.20	1.979

Figure 2. Results of the outer model assessment.

Table 4. Evaluation of outer loading, CR and AVE.

Variable		Outer loading	CR	AVE
Performance expectancy	PE1	0,847	0,890	0,669
	PE2	0,834
	PE3	0,847
	PE4	0,740
Effort expectancy	EE1	0,830	0,892	0,673
	EE2	0,815
	EE3	0,816
	EE4	0,821
Social influence	SI1	0,646	0,837	0,563
	SI2	0,799
	SI3	0,787
	SI4	0,759
Facilitating condition	FC1	0,747	0,861	0,607
	FC2	0,783
	FC3	0,830
	FC4	0,755
Habit	H1	0,749	0,876	0,638
	H2	0,821
	H3	0,805
	H4	0,817
Hedonic motivation	HM1	0,769	0,889	0,668
	HM2	0,842
	HM3	0,845
	HM4	0,811
Behavioral intention	BI1	0,892	0,884	0,719
	BI2	0,858
	BI3	0,790
Behavior	B1	0,796	0,875	0,700
	B2	0,847
	B3	0,866

Table 5. Fornell-Larcker.

	B	BI	EE	FC	H	HM	PE	SI
B	0,837
BI	0,688	0,848
EE	0,628	0,718	0,821
FC	0,622	0,696	0,697	0,779
H	0,617	0,708	0,675	0,673	0,799
HM	0,612	0,702	0,708	0,744	0,749	0,817
PE	0,615	0,691	0,751	0,650	0,621	0,689	0,818
SI	0,549	0,629	0,601	0,633	0,661	0,643	0,573	0,750

Bold is the value of square root of AVE for each construct.

Table 6. Heterotrait-monotrait ratio (HTMT).

	B	BI	EE	FC	H	HM	PE	SI
B
BI	0,863
EE	0,767	0,870
FC	0,788	0,872	0,858
H	0,766	0,867	0,818	0,842
HM	0,747	0,847	0,843	0,830	0,852
PE	0,755	0,843	0,899	0,802	0,751	0,820
SI	0,711	0,802	0,762	0,832	0,852	0,825	0,726

Table 7. VIF outer and inner value.

Variable		Outer VIF	Inner VIF values
			Behavioral intention	Behavior
Performance expectancy	PE1	2,111	2,654	–
	PE2	2,059
	PE3	1,480
	PE4	2,111
Effort expectancy	EE1	1,876	3,056	–
	EE2	1,713
	EE3	1,919
	EE4	1,868
Social influence	SI1	1,151	2,102	–
	SI2	1,716
	SI3	1,733
	SI4	1,454
Facilitating condition	FC1	1,471	2,774	2,217
	FC2	1,779
	FC3	1,987
	FC4	1,494
Habit	H1	1,552	2,790	2,295
	H2	1,892
	H3	1,748
	H4	1,927
Hedonic motivation	HM1	1,546	3,373	–
	HM2	2,005
	HM3	2,264
	HM4	1,954
Behavioral intention	BI1	2,137	–	2,436
	BI2	1,830
	BI3	1,558
Behavior	B1	1,552	–	–
	B2	1,631
	B3	1,883

Table 8. R2 value and Q2 value.

	R^2	Adjusted R^2	Q^2
Behavioral intention	0,661	0,654	0,462
Behavioral	0,528	0,522	0,356

Figure 3. Results of inner model assessment.

Table 9. Results of hypothesis testing.

Hypothesis	Path	t-statistic	p value	Decision	Mediation
H1	PE →BI	2,348	0,019	Accepted	–
H2	EE →BI	2,812	0,005	Accepted	–
H3	SI →BI	1,769	0,077	Rejected	–
H4a	FC →BI	2,364	0,018	Accepted	–
H4b	FC →B	2,987	0,003	Accepted	–
H4c	FC →BI B	2,112	0,035	Accepted	Partial mediation
H5a	H →BI	3,114	0,002	Accepted	–
H5b	H →B	2,652	0,008	Accepted	–
H5c	H →BI →B	2,645	0,008	Accepted	Partial mediation
H6	HM →BI	1,151	0,250	Rejected	–
H7	BI →B	5,848	0,000	Accepted	–

Table

Variable		Indicators
Performance expectancy	1.	SAKTI is an application that is useful in my work.
	2.	SAKTI makes it easier for me to do my job.
	3.	SAKTI allows me to do my work faster than other financial applications.
	4.	My productivity can increase by using SAKTI.
Effort expectancy	1.	I will not have difficulty learning how to use the SAKTI application.
	2.	I feel comfortable doing my job using the SAKTI application.
	3.	It is easy for me to become proficient in using the SAKTI application.
	4.	Overall, I find SAKTI easy to use.
Social influence	1.	People I respect suggest that I use SAKTI.
	2.	People important to me think that I should use SAKTI.
	3.	People in my environment who use the SAKTI application have higher prestige than those who do not.
	4.	I use the SAKTI application for work because many people also use it.
Facilitating condition	1.	I have the necessary resources (computer/internet) to use the SAKTI application.
	2.	I have the necessary knowledge to use the SAKTI application.
	3.	SAKTI is compatible with other systems that I use.
	4.	SAKTI has guidelines for its usage.
Hedonic motivation	1.	Using the SAKTI application is enjoyable for me.
	2.	Using the SAKTI application is very entertaining for me.
	3.	Using the SAKTI application is very rewarding for me.
	4.	Using the SAKTI application is very interesting and enhances my prestige.
Habits	1.	Using the SAKTI application is a habit for every operator at the DJPb agency level.
	2.	I feel satisfied when using the SAKTI application.
	3.	Every operator at the DJPb agency level should use the SAKTI application.
	4.	Using the SAKTI application is something I do without thinking for my job.
Behavioral intention	1.	I intend to continue utilizing SAKTI in my future work.
	2.	I will use SAKTI in my daily life.
	3.	Considering that I have a computer capable of accessing the internet, I will continue to use the SAKTI application.
Use behavior	1.	Sometimes, I use SAKTI for my work.
	2.	I often use the SAKTI application to perform daily tasks.
	3.	I always use the SAKTI application in all of my work.

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.