Predictors of customers’ continuance intention of mobile banking from the perspective of the interactivity theory

Figures & data

Figure 1. Research model.

Data Source: This Paper.

Table 1. Measurement model statistics.

Constructs	Item #	Factor Loading	Cronbach α	CR	AVE
HHI	HHI1	0.946	0.926	0.953	0.871
	HHI2	0.947
	HHI3	0.905
HII	HII1	0.811	0.847	0.897	0.686
	HII2	0.781
	HII3	0.883
	HII4	0.835
HSI	HSI1	−0.081	0.776	0.617	0.472
	HSI2	0.821
	HSI3	0.858
PU	PU1	0.777	0.804	0.872	0.631
	PU2	0.783
	PU3	0.784
	PU4	0.831
PEU	PEU1	0.839	0.909	0.932	0.732
	PEU2	0.861
	PEU3	0.862
	PEU4	0.849
	PEU5	0.867
PPS	PPS1	0.872	0.852	0.910	0.772
	PPS2	0.838
	PPS3	0.924
SA	SA1	0.861	0.870	0.920	0.794
	SA2	0.912
	SA3	0.899
CI	CI1	0.917	0.857	0.914	0.781
	CI2	0.920
	CI3	0.810

Notes: HHI: Human-Human Interaction, HII: Human-Information Interaction, HSI: Human-System Interaction, PU: Perceived Usefulness, PEU: Perceived Ease of Use, PPS: Perceived Privacy Security, SA: Satisfaction, CI: Continuance Intention, CR: Composite Reliability, AVE: Average Variance Extracted.

Data Source: This Paper.

Table 2. Construct correlations and square roots of average variance extracted.

Constructs	Mean	S.D.	HHI	HII	HSI	PU	PEU	PPS	SA	CI
HHI	2.6562	0.9361	0.9333
HII	2.4298	0.7215	0.603**	0.8283
HSI	2.7899	0.6371	0.407**	0.438**	0.6870
PU	2.1103	0.5464	0.461**	0.616**	0.416**	0.7944
PEU	2.1633	0.6211	0.424**	0.408**	0.345**	0.637**	0.8556
PRS	2.1452	0.6565	0.340**	0.377**	0.340**	0.463**	0.501**	0.8786
SA	2.1356	0.5970	0.440**	0.436**	0.398**	0.665**	0.747**	0.540**	0.8911
CI	2.0840	0.5276	0.351**	0.392**	0.428**	0.642**	0.576**	0.490**	0.706**	0.8837

Notes: [1]. HHI: Human-Human Interaction, HII: Human-Information Interaction, HSI: Human-System Interaction, PU: Perceived Usefulness, PEU: Perceived Ease of Use, PPS: Perceived Privacy Security, SA: Satisfaction, CI: Continuance Intention.

[2]. For each latent construct, the square root of AVE is displayed in italics.

[3]. Correlations significant at *p < 0.05, **p < 0.01, ***p < 0.001.

Data Source: This Paper.

Table 3. HTMT test results.

Constructs	HHI	HII	HSI	PU	PEU	PPS	SA	CI
HHI	1.000
HII	0.678	1.000
HSI	0.662	0.742	1.000
PU	0.522	0.729	0.963	1.000
PEU	0.457	0.459	0.654	0.752	1.000
PPS	0.383	0.443	0.618	0.560	0.573	1.000
SA	0.488	0.507	0.798	0.805	0.840	0.628	1.000
CI	0.374	0.443	0.864	0.778	0.656	0.570	0.815*	1.000

Notes: HHI: Human-Human Interaction, HII: Human-Information Interaction, HSI: Human-System Interaction, PU: Perceived Usefulness, PEU: Perceived Ease of Use, PPS: Perceived Privacy Security, SA: Satisfaction, CI: Continuance Intention.

Figure 2. Results of structural equation modeling analysis of the hypothesized model.

Note: *p<0.05; **p<0.01; ***p<0.001; ns, non-significant.

Data Source: This Paper.

Table 4. Results of study hypotheses testing.

Hypotheses	β	t-Value	p (sig. level)	Result
H1a: HHI→PU	0.104	1.977	*	Supported
H1b: HHI → PEU	0.242	4.027	***	Supported
H1c: HHI → PPS	0.134	2.160	*	Supported
H2a: HII→ PU	0.482	8.979	***	Supported
H2b: HII → PEU	0.191	3.125	**	Supported
H2c: HII → PPS	0.212	3.376	***	Supported
H3a: HSI →PU	0.162	3.456	***	Supported
H3b: HIS→PEU	0.163	3.058	**	Supported
H3c: HIS →PPS	0.193	3.508	***	Supported
H4: PU→SA	0.277	6.433	***	Supported
H5: PEU→ SA	0.486	11.035	***	Supported
H6: PPS→SA	0.169	4.406	***	Supported
H7: SA →CI	0.706	18.556	***	Supported
HHI→CI	0.351	6.98	***	Supported
HII→CI	0.392	7.946	***	Supported
HIS→CI	0.428	8.819	***	Supported
PU→CI	0.642	15.611	***	Supported
PEU→CI	0.576	13.123	***	Supported
PPS→CI	0.490	10.474	***	Supported
Control variable
H8a: Age →CI	0.096	1.610	ns	Reject
H8b: Gender →CI	−0.029	-.513	ns	Reject
H8c: Income → CI	−0.247	−3.938	***	Supported
H8d: Education→ CI	0.046	0.818	ns	Reject

Notes: [1] HHI: Human-Human Interaction, HII: Human-Information Interaction, HSI: Human-System Interaction, PU: Perceived Usefulness, PEU: Perceived Ease of Use, PPS: Perceived Privacy Security, SA: Satisfaction, CI: Continuance Intention.

[2] ^*p<0.05; ^**p<0.01; ^***p<0.001; ns, non-significant.

Data Source: This Paper.

Table

Constructs	Item #	Measures	Sources
Human-Human Interaction	HHI1	I think the mobile banking app makes it easy for me to communicate with human customer service.	Hsu et al. (2015), Lin et al. (2017)
	HHI2	I think I can easily express my needs through the mobile banking App and human customer service.
	HHI3	I think the mobile banking app makes it easy for me to get in touch with human customer service.
Human- Information Interaction	HII1	I can efficiently use the mobile banking App to search for financial-related information.	Hsu et al. (2015), Lee and Lee (2019)
	HII2	The mobile banking App can actively filter information that is useful to me.
	HII3	I can efficiently search for information I am interested in through the mobile banking App.
	HII4	I can efficiently obtain meaningful information through the mobile banking App.
Human-System Interaction	HSI1	Using mobile banking App makes me feel that I am a dispensable customer of the bank.	Yang and Lai (2011), Lu et al. (2010)
	HSI2	I feel that I highly rely on the mobile banking App.
	HSI3	Using the mobile banking App makes me feel that I am a valuable customer of the bank.
Perceived Usefulness	PU1	mobile banking App can help me provide more financial products and service information.	Sampaio et al., 2017, Davis (1989)
	PU2	Using Mobile banking App allows me to find the services and information I want more quickly.
	PU3	Using mobile banking App can improve my work efficiency.
	PU4	In general, using mobile banking App is very useful in my life and work.
Perceived Ease of Use	PEU1	I think it’s easy to learn to use a mobile banking App.	Sharma (2019), Davis et al. (1989)
	PEU2	I think it’s very easy to operate mobile banking App.
	PEU3	I think the mobile banking App system function design is easy to understand and clear.
	PEU4	I think the mobile banking App operation page makes it easy for me to find the relevant functions I need.
	PEU5	In general, I think the mobile banking App system page is easy to use.
Perceived Privacy Security	PPS1	I think it’s safe to transact in the mobile banking App.	Jebarajakirthy and Shankar (2021), Sharma (2019)
	PPS2	I think my account bank Ability to provide effective technology to prevent unauthorized intrusion of my account by others.
	PPS3	I have confidence in the security of my mobile banking App transactions.
Satisfaction	SA1	I find the mobile banking App is very useful.	Hsu et al. (2015), Tandon et al. (2016)
	SA2	I am very familiar with the functions of the mobile banking App.
	SA3	"In general, I am very satisfied with how I use the mobile banking App.
Continuance Intention	CI1	I plan to use the mobile banking app in the future.	Hsu et al. (2015), Sharma (2019)
	CI2	I plan to continue using the mobile banking App.
	CI3	I will recommend the mobile banking App to friends.

Table

Measure	Category	Frequency (persons)	Frequency (%)
Gender	Male	150	42.98
	Female	199	57.02
Age, years	≤20	11	3.15
	21-30	43	12.32
	31-40	156	44.70
	41-50	110	31.52
	51-60	27	7.74
	≥60	2	0.57
Monthly income, USD	No income	32	9.17
	≤310	12	3.44
	311-770	50	14.33
	771-1542	125	35.82
	≥1543	130	37.25
Education level	High school or below	31	8.88
	College or junior college degree	276	79.08
	Graduate degree or above	42	12.03

Hsu, M. H., Chang, C. M., Lin, H. C., & Lin, Y. W. (2015). Determinants of continued usage toward social media: The perspectives of uses and gratifications theory and perceived interactivity. Information Research, 20(2), 671–686.

 Web of Science ®Google Scholar

Lin, H. C., Chiu, Y. H., Chen, Y. J., Wuang, Y. P., Chen, C. P., Wang, C. C., Huang, C. L., Wu, T. M., & Ho, W. H. (2017). Continued use of an interactive computer game-based visual perception learning system in children with developmental delay. International Journal of Medical Informatics, 107, 76–87.

 PubMed Web of Science ®Google Scholar

Lee, J. H., & Lee, C. F. (2019). Extension of TAM by perceived interactivity to understand usage behaviors on ACG social media sites. Sustainability, 11, 1–19.

 Web of Science ®Google Scholar

Yang, H., & Lai, C. Y. (2011). Understanding knowledge sharing behaviour in Wikipedia. Behaviour & Information Technology, 30(1), 131–142. https://doi.org/10.1080/0144929X.2010.516019

 Web of Science ®Google Scholar

Lu, H. P., Lin, J. C. C., Hsiao, K. L., & Cheng, L. (2010). Information sharing behaviour on blogs in Taiwan: Effects of interactivities and gender differences. Journal of Information Science, 36(3), 401–416. https://doi.org/10.1177/0165551510363631

 Web of Science ®Google Scholar

Sampaio, C. H., Ladeira, W. J., & Santini, F. D. O. (2017). Apps for mobile banking and customer satisfaction: A cross-cultural study. International Journal of Bank Marketing, 35(7), 1133–1153. https://doi.org/10.1108/IJBM-09-2015-0146

 Web of Science ®Google Scholar

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008

 Web of Science ®Google Scholar

Sharma, S. K. (2019). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 21(4)‏, 815–827. https://doi.org/10.1007/s10796-017-9775-x

 Web of Science ®Google Scholar

Davis, F. D., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982

 Web of Science ®Google Scholar

Jebarajakirthy, C., & Shankar, A. (2021). Impact of online convenience on mobile banking adoption intention: A moderated mediation approach. Journal of Retailing and Consumer Services, 58(23), 102312–102323. https://doi.org/10.1016/j.jretconser.2020.102323

 Google Scholar

Tandon, U., Kiran, R., & Sah, A. N. (2016). Customer satisfaction using website functionality, perceived usability, and perceived usefulness towards online shopping in India. Information Development, 32(5), 1657–1673. https://doi.org/10.1177/0266666915621106

 Web of Science ®Google Scholar