The Effect of Perceived Usefulness, Perceived Ease of Use, and Social Influence on the Use of Mobile Banking through the Mediation of Attitude Toward Use

Denny Indra Prastiawan, Siti Aisjah, Rofiaty Rofiaty

Abstract


Mobile banking is one of the channels of banking service provided by banking institutions in forms of modern platforms that are fully based on digital technology and displace physical interaction between banks and their customers. For banking industry, mobile banking is more than a service option; it is a strategic plan to facilitate customer’s changes in behavior. However, the acceptance of such platform by the public, particularly micro entrepreneurs, is still in question. The objective of this research is to identify factors influencing the use of mobile banking based on the perception of micro customers of Bank DKI in Surabaya. The variables used in this study were developed from previous researches that also examined the same matter with adjustment on the characteristics of micro customers. The variables, developed through the theoretical review, were then empirically assessed using SEM-PLS. the data was collected from questionnaires distributed to 266 micro customers who received financing from Bank DKI. The surcey discovered that perceived usefulness, perceived ease of use, and social influence are empirically proven to have both direct effects on the use of mobile banking and indirect effects through attitude toward use. Practical implications also discussed in this paper.

 


Keywords


mobile banking; perceived ease of use; attitude toward use; social influence; micro customer

Full Text:

PDF

References


Chang, S-H & Lin, R. (2015). Building a Total Customer Experience Model: Applications for the Travel Experiences in Taiwan’s Creative Life Industry. Journal of Travel & Tourism Marketing, 32(4), 438-453.

Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655-690). Springer, Berlin, Heidelberg.

Chin, W. W., Peterson, R. A., & Brown, S. P. (2008). Structural equation modelling in marketing: Some practical reminders. Journal of Marketing Theory and Practice, 16(4), 287–298. doi:10.2753/MTP1069-6679160402

Lee, K. C. & Chung, N. (2009). Understanding Factors Affecting Trust in and Satisfaction with Mobile Banking in Korea: A Modified DeLone and McLean’s model perspective. Interacting with Computer, 21(5/6), 385-392.

Liang, C. J., Wang, W. H., & Farquhar, J. D. (2009). The influence of customer perceptions on financial performance in financial services. International Journal of Bank Marketing.

Limayem, M., & Cheung, C. M. (2011). Predicting the continued use of Internet-based learning technologies: the role of habit. Behaviour & Information Technology, 30(1), 91-99.

Malhotra, N. K., & Malhotra, N. K. (2012). Basic marketing research: Integration of social media. Boston: Pearson.

Martins, C., Oliveira, T. & Popovic, A. (2014). Understanding the Internet Banking Adoption: A Unified Theory of Acceptance and Use of Technology and Perceived Risk Application. International Journal of Information Management, 34(1), 1-13.

Afshan, S., & Sharif, A. (2016). Acceptance of mobile banking framework in Pakistan. Telematics and infomatics, 33, 370–387.

Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun cognitive ab- sorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694.

Aker, J. C., & Mbiti, I. M. (2010). Mobile phones and economic development in Africa. Journal of Economic Perspectives, 24(3), 207–232.

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110.

AlAlwan, A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118–139.

Al-Gahtani, S. (2001). The applicability of TAM outside North America: An empirical test in the United Kingdom. Information Resources Management Journal, 14(3), 37–46.

Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 19, 130–141.

Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52.

Baptista, G., & Oliveira, T. (2015). Understanding Mobile Banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430.

Baptista, G., & Oliveira, T. (2016). A weight and meta-analysis on mobile banking ac- ceptance research. Computers in Human Behavior, 63, 480–489.

Bhatiasevi, V. (2015). An extended UTAUT model to explain the adoption of mobile banking Information Development, 1–16 Published online before print.

Bons, R. W. H., Alt, R., Lee, H. G., & Weber, B. (2012). Banking in the Internet and mobile era. Electronic Markets, 22(4), 192–202.

Calisir, F., & Gumussoy, C. A. (2008). Internet banking versus other banking channels: Young consumers’ view. International Journal of Information Management, 28, 215–221. Graph

Chin, W. W. (2000). Frequently asked questions – Partial Least Aquares & PLS- Graph. Home page [on-line]. Last update: 21 December 2004. Available at:http://disc-nt.cba.uh. edu/chin/plsfaq/plsfaq.htm.

Cole, S., Sampson, T., & Zia, B. (2011). Prices or Knowledge? What drives demand for

financial services in emerging markets? The Journal of Finance, 66(6), 1933–1967.

Colley, A., & Maltby, J. (2008). Impact of the Internet on our lives: Male and female personal perspectives. Computers in Human Behavior, 24, 2005–2013.

Cull, R., Demirgüç-Kunt, A., & Morduch, J. (2009). Microfinance meets the market. The Journal of Economic Perspectives, 23(1), 167–192.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quaterly, 13(3), 319–340.

Dwivedi, Y. K., Kapoor, K. K., Williams, M. D., & Williams, J. (2013). RFID systems in libraries: An empirical examination of factors affecting system use and user sa- tisfaction. International Journal of Information Management, 33(2), 367–377.

Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2016). A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), 174–187.

Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, M. (2017).

An empirical validation of a unified model of electronic government adoption (UMEGA). Government Information Quaterly, 34(2), 211–230.

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2017). Re- examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 1–16.

Febraban - Brazilian Federation of Banks (2016). Relatorio Annual 2015, Annual Report Retrieved. from: https: // relatorioanual 2015. febraban. org. br/en/index.htm.

FED - Board of Governors of the Federal Reserve System (2016). Consumers and mobile financial service 2016 Retrieved from:https://www.federalreserve.gov/econresdata/consumers-and-mobile financial-services-report-201603.pdf.

Garbarino, E., & Strahilevitz, M. (2004). Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, 57, 768–775.

Gu, J.-C., Lee, S.-C., & Suh, Y.-L. (2009). Determinants of behavioral intention to mobile banking. Expert Systems With Applications, 36, 11605–11616.

Gurgand, M., Pederson, G., & Yaron, J. (1996). Rural finance institutions in Sub-Saharan Africa: Their outreach and sustainability. Savings and Development, 20(2), 133–169.

Ha, K.-H., Canedoli, A., Baur, A. W., & Bick, M. (2012). Mobile banking—Insights on its increasing relevance and most common drivers of adoption. Electronic Markets, 22(4), 217–227.

Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th edition). Prentice-Hall, Inc.

Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., & Tabar, M. J. S. (2014). Mobile- banking adoption by Iranian bank clients. Telematics and informatics, 31, 62–78.

Hasan, B. (2010). Exploring gender differences in online shopping attitude. Computers in Human Behavior, 26, 597–601.

ITUR - International Telecommunication Union Report (2016). Measuring the information society report, 2016Retrieved from:http://www.itu.int/en/ITU-D/Statistics/Pages/ publications/mis2016.aspx.

Jack, W., Ray, A., & Suri, T. (2013). Transaction networks: Evidence from mobile money in Kenya. The American Economic Review, 103(3), 356–361.

Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2015). Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service. Information Systems Frontiers, 17(5), 1039–1056.

Kishore, S. V. K., & Sequeira, A. H. (2016). An empirical investigation on mobile banking service adoption in rural Karnataka. Sage Open, (January-March), 1–21.

Laukkanen, T. (2016). Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the Internet and mobile banking. Journal of Business Research, 69, 2432–2439.

Laukkanen, T., Sinkkonen, S., Kivija¨rvi, M., & Laukkanen, P. (2007). Innovation re- sistance among mature consumers. Journal of Consumer Marketing, 24(7), 419–427.

Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting With Computers, 21, 385–392.

Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(1), 752–780.

Lin, H.-F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31, 252–260.

Lin, H.-F. (2013). Determining the relative importance of mobile banking quality factors.Computer Standards & Interfaces, 35(2), 195–204.

Luarn, P., & Lin, H.-H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21, 873–891.

Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222–234.

Malaquias, R. F., & Hwang, Y. (2016). An empirical study on trust in mobile banking: A developing country perspective. Computers in Human Behavior, 54, 453–461.

McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-Commerce: An integrative typology. Information Systems Research, 13(3), 334–359.

Mohammadi, H. (2015). A study of mobile banking loyalty in Iran. Computers in Human Behavior, 44, 35–47.

Montezemi, A. R., & Saremi, H. Q. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information & Management, 52, 210–226.

O’Reilly, P., Duane, A., & Andreev, P. (2012). To M-Pay or not to M-Pay-realising the potential of smart phones: Conceptual modeling and empirical validation. Electronic Markets, 22(4), 229–241.

Oliveira, T., Faria, M., Thomas, M. A., & Popovič, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34, 689–703.

Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view.

Computers in Human Behavior, 59, 265–282.

Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Towards a unified view. Information Systems Frontiers, 19(3), 549–568.

Raza, S. A., Umer, A., & Shah, N. (2017). New determinants of ease of use and perceived usefulness for mobile banking adoption. International Journal of Electronic Customer Relationship Management, 11(1), 44–65.

Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review.

Telematics and Informatics, 32, 129–142.

Shareef, M. A., Dwivedi, Y. K., Kumar, V., & Kumar, U. (2017). Content design of ad- vertisement for consumer exposure: Mobile marketing through short messaging ser- vice. International Journal of Information Management, 37(4), 257–268.

Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., & Dwivedi, Y. K. (2018). Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages. Journal of Retailing and Consumer Services, 43, 54–67.

Sharma, S. K. (2017). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 1–13.

Sharma, S., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65–75.

Slade, E., Dwivedi, Y. K., Piercy, N. L., & Williams, M. D. (2015). Modeling consumers’ adoption intentions of remote mobile payments in the UK: Extending UTAUT with innovativeness, risk and trust. Psychology & Marketing, 32(8), 860–873.

Slade, E., Williams, M., Dwivedi, Y. K., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209–223.

Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of in- trinsic motivation. MIS Quarterly, 23(2), 239–260.

Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342–365.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Management Sciences, 39(2), 273–315.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.

Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115–139.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

Venkatesh, V., Morris, M. G., Sykes, T. A., & Acherman, P. L. (2004). Individual reactions to new technologies in the workplace: The role of gender as a psychological construct. Journal of Applied Social Psychology, 34(3), 445–467.

Veríssimo, J. M. C. (2016). Enablers and restrictors of mobile banking app use: A fuzzy set qualitative comparative analysis (fsQCA). Journal of Business Research, 69, 5456–5460.

Wonglimpiyarat, J. (2014). Competition and challenges of mobile banking: A systematic review of major bank models in the Thai banking industry. Journal of High Technology Management Research, 25, 123–131.

Yuan, S., Liu, Y., Yao, R., & Liu, J. (2014). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20–34.

Zhang, Y., Weng, Q., & Zhu, N. (2018). The relationships between electronic banking adoption and its antecedents: A meta-analytic study of the role of national culture. International Journal of Information Management, 40, 76–87.

Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54, 1085–1091.

Zhou, T. (2012a). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in Human Behavior, 28, 1518–1525.

Zhou, T. (2012b). Examining mobile banking user adoption from the perspectives of trust and flow experience. Information Technology and Management, 13(1), 27–37.

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26, 760–767.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.