The Impact of Security, Service Quality, Perceived Usefulness, Perceived Ease of Use, Trust, and Price Value on Users’ Satisfaction in Cloud-Based Payment Systems in Australia: A Pls-Sem Analysis
DOI:
https://doi.org/10.4301/S1807-1775202421004Keywords:
Cloud-based payment systems, CBPS, user satisfaction, influence factors, demographics, TAM, PLS-SEM analysisAbstract
Over the past years, the ubiquity and versatility of cloud-based payment systems (CBPS) have become an evolutionary path in the payment process. However, despite is undeniable the various advantages of using the CPBS, compared to other countries the adoption rates are still very low in Australia. This suggests that people might not know the benefits of using them or they might not be satisfied with the current payment systems. In this context, the purpose of this research was to examine the impact of security and service quality on the factors (perceived usefulness, perceived ease of use, trust and price value) that have influence on users’ satisfaction in cloud-based payment systems in Australia. Qualtrics was used to gather the data of 411 respondents to an online questionnaire survey. After that, the PLS-SEM (Partial Least Square Structural Equation Modeling) analysis took place. The findings suggest that security, service quality, trust, perceived usefulness, and price value have impact on user satisfaction and this, in turn, affects CBPS adoption. Perceived ease of use has no influence on user satisfaction, and therefore, it has no impact on CBPS adoption. Besides, it was found that, overall, demographics have no impact on user satisfaction in CBPS.References
Albashrawi, M.A. (2017). Understanding mobile banking usage behaviour: A multi-model perspective, PhD thesis, University of Massachusetts Lowell, Massachusetts, USA. https://www.qatifscience.com/wp-content/uploads/2018/08/PhD-Dissertation_UNDERSTANDING-MOBILE-BANKING-USAGE-BEHAVIOR-A-MULTI-MODEL-PERSPECTIVE.pdf
Alkhowaiter, W.A. 2020. Digital payment and banking adoption research in Gulf countries: A systematic literature review. International Journal of Information Management, 53, 1-17. https://doi.org/10.1016/j.ijinfomgt.2020.102102
Arvidsson, N. (2014). Consumer attitudes on mobile payment services–results from a proof of concept test. International Journal of Bank Marketing, 32(2), 150-170. https://doi.org/10.1108/IJBM-05-2013-0048
Banu, A.M., Mohamed, N.S. & Parayitam, S. (2019). Online banking and customer satisfaction: Evidence from India. Asia-Pacific Journal of Management Research and Innovation, 15(1–2), 68–80. https://doi.org/10.1177/2319510X19849730
Boateng, R. & Sarpong, M.Y.P. (2019, May 19). A literature review of mobile payments in Sub-Saharan Africa [Paper presentation]. International Federation for Information Processing (IFIP) 2019, 128-146. https://doi.org/10.1007/978-3-030-20671-0_9
Bradney-George, A. (2021). How old do you have to be to get a credit card? Finder. How old do you have to be to get a credit https://www.finder.com.au/how-old-do-you-have-to-be-to-apply-for-a-credit-card card? | Finder
Chandra, S., Srivastava, S.C. & Theng, Y.L. (2010). Evaluating the role of trust in consumer adoption of mobile payment systems: an empirical analysis. Communications of the Association for Information Systems, 27(1), 561-588.
Chen, Z., Khoa, L.D., Teoh, E.N., Nazir, A., Karuppiah, E.K. & Lam, K.S. (2018). Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review. Knowledge and Information Systems, 57(2), 245-285.
Chong, A.Y.L. (2013). Predicting m-commerce adoption determinants: a neural network approach. Expert Systems with Applications, 40(2), 523-530.
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
Donoghue, M. (2018). Six reasons you need to consider a cloud-based payment system. IPSI. https://ipsi.com.au/six-reasons-need-consider-cloud-based-payment-system/
Duan, X. (2012). An integrated solution to the adoption of electronic market in Australian small-and-medium sized enterprises, PhD thesis, RMIT University, Melbourne, Australia.
Fisher (2020). Contactless competition and digital limitations stifle proximity mobile payment growth in the UK. eMarketer. https://www.emarketer.com/content/contactless-competition-and-digital-limitations-stifle-proximity-mobile-payment-growth-in-the-uk
Gao, L. & Waechter, K.A. (2015). Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation, Information Systems Frontiers, pp.1-24.
Gossett, S. (2019). 10 AI in banking examples you should know. Builtin. https://builtin.com/artificial-intelligence/ai-in-banking
Government Accountability Office (2018). Artificial intelligence: emerging opportunities, challenges, and implications for policy and research. https://www.gao.gov/assets/700/692793.pdf
Hair, J.F., Ringle, C.M. & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
Hair, J.F., Risher, J.J., Sarstedt, M. & Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
Hair, J.F., Sarstedt, M., Ringle, C.M. & Mena, J.A. (2012). An assessment of the use of partial least squares structural equation modelling in marketing research. Journal of the academy of marketing science, 40(3), 414-433.
Hampshire, C. (2016). Exploring UK consumer perceptions of mobile payments using smartphones and contactless consumer devices through an extended technology adoption model. PhD thesis, University of Chester, Chester, UK.
Hossain, M.A. and Uddin, M.N., (2018). October. A Differentiate Analysis for Credit Card Fraud Detection. [Paper presentation]. 2018 International Conference on Innovations in Science, Engineering and Technology (ICISET), 328-333. https://doi.org/document/8745592
Jenkins, P. & Ophoff, J. (2016). Factors influencing the intention to adopt NFC mobile payments - a South African perspective. [Paper presentation]. International Conference on Information Resources Management (CONF-IRM), 1-12. http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1031&context=confirm2016
Kabir M.A., Saidin, S. & Ahmi A. (2015). Adoption of e-payment systems: a review of literature. [Paper presentation]. Proceedings of the International Conference on E-commerce (ICoEC 2015), 2012, 112-120.
Killian, D. & Kabanda, S. (2017). Mobile payments In South Africa: middle income earners' perspective. [Paper presentation]. Twenty-First Pacific Asia Conference on Information Systems (PACIS), Langkawi. http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1241&context=pacis2017
Kristensen, S.M. (2016). Understanding factors influencing Danish consumers’ intention to use mobile payment at point-of-sale. MSc thesis, Aarhus University, Aarhus, Denmark.
Latan & Ramil (2013), The results of partial least squares-structural equation modelling analyses (PLS-SEM). SSRN, 1-35. https://ssrn.com/abstract=2364191
Liébana-Cabanillas, F., Munoz-Leiva, F. & Rejón-Guardia, F. (2013). The determinants of satisfaction with e-banking, Industrial Management & Data Systems, 113(5), 750- 767.
Liébana-Cabanillas, F., Sánchez-Fernández, J. & Muñoz-Leiva, F. (2014). Role of gender on acceptance of mobile payment. Industrial Management & Data Systems, 114(2), 220-240.
Liu, G.S. & Tai, P.T. (2016). A study of factors affecting the intention to use mobile payment services in Vietnam. Economics, 4(6), 249-273.
Liu, Y., Wang, M., Huang, D., Huang, Q., Yang, H. & Li, Z. (2019). The impact of mobility, risk, and cost on the users’ intention to adopt mobile payments. Information Systems and e-Business Management, 17, 319–342.
Mbama, C.I. (2018). Digital banking services, customer experience and financial performance in UK banks, PhD thesis, Sheffield Hallam University, Sheffield, UK.
Mondego, D. & Gide, E. (2022). The use of the technology acceptance model to analyse the cloud-based payment systems: a comprehensive review of the literature, Journal of Information Systems and Technology Management (JISTEM), 19. DOI: 10.4301/S1807-1775202219007
Mondego, D. & Gide, E. (2021). The impact of demographics on user satisfaction in cloud-based payment systems in Australia. [Paper presentation]. 2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). Sydney, Australia. https://doi.org/10.1109/CSDE53843.2021.9718383
Mondego, D. & Gide, E. (2018). The effect of trust on mobile payment adoption: a comprehensive review of literature. International Journal of Arts & Sciences, 11(1), 375- 389.
Mondego, D., Gide, E. & Chaudhry, G. (2018). The effect of personal factors on consumers’ trust in mobile payment systems in Australia. [Paper presentation]. 2018 5th Asia Pacific World Congress on Computer Science and Engineering (APWC on CSE), Nadi, Fiji. https://doi.org/document/10.1109/APWConCSE.2018.00033
Pal, A., De, R., Herath, T. & Rao, H.R. (2019). A review of contextual factors affecting mobile payment adoption and use. Journal of Banking and Financial Technology, 3, 43-57.
Patel, R.K. (2016). Examining predictors of satisfaction with mobile payment systems among small business users. PhD Thesis, Northcentral University, San Diego, California, USA.
Patil, P.P., Rana, N.P. & Dwivedi, Y.K. (2018). Digital payments adoption research: A review of factors influencing consumer’s attitude, intention and usage. [Paper presentation]. 2018 International Federation for Information Processing (IFIP) 11195, 45-52. https://doi.org/10.1007/978-3-030-02131-3_6
Prentice, C., Lopes, S.D. & Wang, X. (2020). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 1-18. https://doi.org/10.1080/19368623.2020.1722304
Priyadarshinee, P., Raut, R.D., Jha, M.K. & Gardas, B.B. (2017). Understanding and predicting the determinants of cloud computing adoption: A two staged hybrid SEM - Neural networks approach. Computers in Human Behavior, 76, 341-362.
Sharma, G. & Lijuan, W. (2015). The effects of online service quality of e-commerce Websites on user satisfaction. The Electronic Library, 33(3), 468 – 485.
Shuhaiber, A. (2016). Factors influencing consumer trust in mobile payments in the United Arab Emirates. PhD thesis, Victoria University of Wellington, Wellington, New Zealand.
Siau, K. & Wang, W. (2018). Building trust in artificial intelligence, machine learning, and robotics. Cutter Business Technology Journal, 31(2), 47-53.
Slade, E., Williams, M., Dwivedi, Y. & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments, Journal of Strategic Marketing, 23(3), 209-223.
Talwar, S., Dhir, A., Khalil, A., Mohan, G. & Islam, A.K.M.N. (2020). Point of adoption and beyond: Initial trust and mobile-payment continuation intention, Journal of Retailing and Consumer Services, 55, 1-12.
Tam, C. and Oliveira, T. (2017). Literature review of mobile banking and individual performance. International Journal of Bank Marketing, 35(7), 1042-1065, https://doi.org/10.1108/IJBM-09-2015-0143
Teoh, W.M.Y., Chong, S.C., Lin, B. & Chua, J.W. (2013). Factors affecting consumers' perception of electronic payment: an empirical analysis. Internet Research, 3(4), 465-485.
Venkatesh, V., Thong, J. & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 157-178.
Wadhwani, P. & Gankar, S. (2019). Cloud POS market share 2019-2025 - industry forecast report. Global Market Insights. https://www.gminsights.com/industry-analysis/cloud-pos-market
Yamaguti Mondego, D. (2019). A framework to build trust in mobile payment systems for Australian consumers. Masters by Research Thesis. Central Queensland University. Sydney, Australia. http://dx.doi.org/10.25946/5cd8a80e2eb61
Yan, H. & Yang, Z. (2015). Examining mobile payment user adoption from the perspective of trust, International Journal of u-and e-Service. Science and Technology, 8(1), 117-130.
Yaokumah, W., Kumah, P. & Okai, E.S.A, (2017). Demographic influences on e-payment services. International Journal of E-Business Research (IJEBR), 13(1), 44-65.
Yuan, S., Liu, L., Su, B. & Zhang, H. (2020). Determining the antecedents of mobile payment loyalty: Cognitive and affective perspectives, Electronic
Commerce Research and Applications, 41, 1-9.
Zhang, W.K. & Kang, M.J. (2019). Factors affecting the use of facial-recognition payment: An example of Chinese consumers. IEEE Access, 7, 154360-154374.
Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091.
Zhou, T. (2015). An empirical examination of users' switch from online payment to mobile payment. International Journal of Technology and Human Interaction (IJTHI), 11(1), 55-66.
