The Use of the Technology Acceptance Model to analyse the Cloud-Based Payment Systems: A Comprehensive Review of the Literature

Domingos Mondego, Ergun Gide


Over the past decades, organisations worldwide driven by the growth in e-commerce transactions have been investing in new payment methods in order to gradually align with the current trend of cashless transactions among individuals, businesses and governments. As a result, payments conducted over the internet or cloud-based payment systems (CBPS) have significantly increased. In this sense, the aim of this study is to provide a comprehensive review of studies that used the technology acceptance model (TAM) to analyse the CBPS. The findings of this study found 134 studies conducted between 2013 and 2020, which have applied the TAM. 118 new variables were tested alongside with the 5 basic constructs of TAM. Surveys are the preferred research method of data collection. Users have been the main focus of academics. China was the country with more studies conducted in CBPS using TAM as a research-based model, followed by India, Indonesia, Spain and Malaysia. Trust was the most used construct by academics to investigate the CBPS adoption, followed by perceived risk and perceived compatibility. SEM was the preferred research instrument for analysing the relationship among constructs followed by regression analysis and multi-group analysis.


Cloud-based payment systems, CBPS, Technology Acceptance Model, TAM, Influencing factors

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Aboelmaged, MG & Gebba, TR 2013, Mobile banking adoption: an examination of technology acceptance model and theory of planned behavior, International Journal of Business Research and Development, vol. 2, no. 1, pp. 35‐50.

Agyei, J, Sun, S, Abrokwah, E, Penney, EK & Ofori-Boafo, R 2020, Mobile banking adoption: examining the role of personality traits, Sage Open, pp. 1-15.

Ahmed, M, Almotairi, MA, Ullah, S & Alam, A 2014, Mobile banking adoption: a qualitative approach towards the assessment of TAM model in an emerging economy, Academic Research International, vol. 5, no.6, pp. 248-259.

Alaeddin O, Rana A, Zainudin Z. & Kamarudin F 2018, From physical to digital:

investigating consumer behaviour of switching to mobile wallet, Polish Journal Of Management Studies, vol. 17, no. 2, pp. 18-30.

Alalwan, AA, Dwivedi, YK, Rana, NP & Williams, MD 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, vol. 29, no. 1, pp. 118-139.

Albashrawi, MA 2017, Understanding mobile banking usage behavior: a multi-model perspective, PhD thesis, University of Massachusetts Lowell.

Aldhaban, FA 2016, Exploratory study of the adoption and use of the smartphone technology in emerging regions: case of Saudi Arabia, PhD thesis, Portland State University.

Alkhowaiter, WA 2020, ‘Digital payment and banking adoption research in Gulf countries: a systematic literature review’, International Journal of Information Management, v.53, pp.1-17.

Almasri, M & Alshareef, H 2019, Mobile cloud-based e-payment systems in Saudi Arabia: a case study, paper presented at 3rd International Conference on Business and Information Management (pp. 5-10), viewed 14 May 2020,

Andrews, S & Schmitz, KM 2019, ‘Chapter 10 - FinTech as disruptive technology in emerging markets’, in Reinventing business through disruptive technologies - sector trends and investment opportunities for firms in emerging markets, pp. 68-74, International Financial Corporation - World Bank Group, Washington.

Anthony, D & Mutalemwa, DK 2014, ‘Factors influencing the use of mobile payments in Tanzania: insights from Zantel’s Z-pesa services’, Journal of Language, Technology & Entrepreneurship in Africa, vol. 5, no. 2, pp. 69-90.

Apanasevic, T, Markendahl, J, Arvidsson, N 2016, Stakeholders' expectations of mobile payment in retail: lessons from Sweden, International Journal of Bank Marketing, vol. 34, no. 1, pp. 37-61.

Ardiansah, M, Chariri, A & Januarti, I 2019, Empirical study on customer perception of ecommerce: mediating effect of electronic payment security. Jurnal Dinamika Akuntansi, vol. 11, no. 2, pp. 122-131.

Ardiansaha, MN, Charirib, A, Rahardjab, S & Udin 2020, The effect of electronic payments security on e-commerce consumer perception: An extended model of technology acceptance, Management Science Letters, vol. 10, pp. 1473–1480.

Arif, I, Afshan, S & Sharif, A 2016, Resistance to mobile banking adoption in a developing country: evidence from modified TAM, Journal of Finance & Economics Research, vol. 1, no.1, pp. 25-42.

Ariffin, SK & Lim, KT 2020, Investigating Factors Affecting Intention to Use Mobile Payment Among Young Professionals in Malaysia, Advances in Economics, Business and Management Research, vol. 141, pp. 6-11.

Arvidsson, N 2014,’Consumer attitudes on mobile payment services - results from a proof of concept test’, International Journal of Bank Marketing, vol. 32, no. 2, pp. 150-170.

Atlam, HF, Walters, RJ & Wills, GB 2018, Intelligence of things: opportunities & challenges, Paper presented at 2018 3rd Cloudification of the Internet of Things (CIoT), pp. 1-6.

Australian Payments Network (n.d.), Australia’s move towards a less cash economy, viewed 25 April 2020,

Australian Payments Network 2018, Towards an internet of payments - Global platforms redefining the payments landscape, viewed 4 February 2020,

Aydin, G, Burnaz, S 2016, Adoption of mobile payment systems: a study on mobile wallets, Journal of Business, Economics and Finance, vol. 5, no. 1, pp. 73-92.

Baganzi, R & Lau, AK 2017, Examining trust and risk in mobile money acceptance in Uganda, Sustainability 2017, vol. 9, no. 12, 2233, pp. 1-22.

Bagla, RK & Sancheti V 2018, Gaps in customer satisfaction with digital wallets: challenge for sustainability, Journal of Management Development, vol. 37 no. 6, pp. 442-451.

Bailey, AA, Pentina, I, Mishra, AS & Mimoun, MSB 2017, Mobile payments adoption by US consumers: an extended TAM, International Journal of Retail & Distribution Management, vol. 45, no. 6, pp. 626-640.

Bansal, S, Bruno, P, Denecker, O & Niederkorn, M 2018, Global payments 2018: A dynamic industry continues to break new ground, viewed14 May 2020,

Banu, AM, Mohamed, NS & Parayitam, S 2019, Online banking and customer satisfaction: evidence from India, Asia-Pacific Journal of Management Research and Innovation, vol. 15, no. 1–2, pp. 68–80.

Barkhordari, M, Nourollah, Z, Mashayekhi, H, Mashayekhi, Y & Ahangar, MS 2017, ‘Factors influencing adoption of e-payment systems: an empirical study on Iranian customers’, Information Systems and e-Business Management, vol. 15, no. 1, pp. 89-116.

Barkhordari, M, Nourollah, Z, Mashayekhi, H, Mashayekhi,Y, Ahanga, MS 2017, Factors influencing adoption of e-payment systems: an empirical study on Iranian customers, Information Systems, E-Business Management vol. 15, pp. 89–116.

Barratt, A 2020, The future of payments in the cloud – misconceptions that hold brands back from embracing cloud, viewed 27 April 2020,

Baskoro, HA & Amini, A 2020, Analysis of factors influencing consumer intention toward Indonesia QR mobile payment, paper presented at Understanding Digital Industry: Proceedings of the Conference on Managing Digital Industry, Technology and Entrepreneurship (CoMDITE 2019), Bandung, Indonesia, pp. 112-116, viewed 29 August 2020,

Bhardwaj, M & Aggarwal, R 2018, Understanding dynamics of mobile banking adoption by youth: empirical evidence from India, FIIB Business Review, vol. 5, no.2, pp. 46-56.

Biddle, S 2018, Facebook uses artificial intelligence to predict your future actions for advertisers, says confidential document, viewed 24 May 2020,

Boateng, R & Sarpong, MYP 2019, A literature review of mobile payments in Sub-Saharan Africa, Conference Papers - International Federation for Information Processing (IFIP) 2019, pp.128-146.

Bonga, D 2018, Business to consumer mobile commerce in the Democratic Republic of the Congo: a case study, PhD thesis, Northcentral University.

Briliana, V, Deitiana, T & Ruswidiono, W 2019, Attitudes toward mobile app payment systems: a case study among Indonesian millennials, Advances in Economics, Business and Management Research, vol. 145, pp. 321-325.

Brill, T, Munoz, L & Miller, RJ 2019, ‘Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications’, Journal of Marketing Management, vol. 35, no. 15–16, pp. 1401–1436.

Bullock, M 2019, Modernising Australia's payments system, RBA Speech to the Central

Bank Payments Conference, pp. 1-7, viewed 24 April 2020, (2017), How Artificial Intelligence is Improving Customer Experience, viewed 10 February 2020,

Cao, TK, Dang, PL & Nguyen, HA 2016, ‘Predicting consumer intention to use mobile payment services: empirical evidence from Vietnam’, International Journal of Marketing Studies, vol. 8, no. 1, pp. 117-124.

Capgemini 2019, World payments report 2019, Capgemini Research Institute, viewed 28 April 2020,

Chakravorti, B & Mazzotta, B 2014, The cost of cash in India, viewed 28 June 2017, lowres.pdf

Chandra, YU, Kristin, DM, Suhartono, J, Sutarto, FS & Sung, M 2018, Analysis of determinant factors of user acceptance of mobile payment system in Indonesia (a case study of go-pay mobile payment), paper presented at 2018 International Conference on Information Management and Technology (ICIMTech), Jakarta, Indonesia, pp. 454-459, viewed 27 August 2020,

Chawla, D & Joshi, H 2017, High versus low consumer attitude and intention towards adoption of mobile banking in India: an empirical study, Vision, vol. 21, no. 4, pp. 410–424.

Chawla, D & Joshi, H 2018, The moderating effect of demographic variables on mobile banking adoption: an empirical investigation, Global Business Review, vol. 19, no.3S, pp. 90S–113S.

Chawla, D & Joshi, H 2019, Scale development and validation for measuring the adoption of mobile banking services, Global Business Review, vol 20, no. 2, pp. 434–457.

Chawla, D & Joshi, H 2020, Role of mediator in examining the influence of antecedents of mobile wallet adoption on attitude and intention, Global Business Review, pp. 1–17.

Chen, LY & Wu, WN 2017, ‘An exploration of the factors affecting users’ satisfaction with mobile payments’, International Journal of Computer Science & Information Technology (IJCSIT), vol. 9, no.3, pp.97-105.

Chen, Z, Khoa, LD, Teoh, EN, Nazir, A, Karuppiah, EK & Lam, KS 2018, ‘Machine learning techniques for anti-money laundering (AML) solutions in suspicious transaction detection: a review’, Knowledge and Information Systems, vol. 57, no. 2, pp. 245-285.

Chin, LP & Ahmad, ZA 2015, Perceived enjoyment and Malaysian consumers’ intention to use a single platform e-payment, SHS Web of Conferences, viewed 24 August 2020,

Chowdhury, N 2018, Factors influencing the adoption of cloud computing driven by big data technology: a quantitative study, PhD thesis, Capella University.

CIO review 2019, How is cloud influencing payments?, viewed 27 April 2020,

Cohen, L, Manion, L & Morrison, K 2007, Research method in education, 6th edn, Routlage, New York.

Creswell, JW 2007, Qualitative inquiry & research design – choosing among five approaches, Sage Publications, Thousand Oaks.

Dastan, I & Gürler C 2016, ‘Factors affecting the adoption of mobile payment systems: an Empirical Analysis’, Emerging Markets Journal, vol.6, no.1, pp.17-24.

Davis, FD 1989, ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS quarterly, pp. 319-340.

Dawson, C 2002, Practical research methods: a user-friendly guide to mastering research techniques and projects, How to books Ltd, viewed 11 January 2018,

de Reuver, M, Verschuur, E, Nikayin, F, Cerpa, N & Bouwman, H 2015, ‘Collective action for mobile payment platforms: a case study on collaboration issues between banks and telecom operators’, Electronic Commerce Research and Applications, vol. 14, no. 5, pp. 331-344.

Deloitte Insights 2018, The fourth industrial revolution is here—are you ready?, viewed 22 April 2020,

Digalaki, E 2019, The impact of artificial intelligence in the banking sector & how AI is being used in 2020, viewed 20 August 2020,

Donoghue, M 2018, Six reasons you need to consider a cloud-based payment system, viewed 4 February 2020,

Doyle, MA, Fisher, C Tellez, E & Yadav, A 2017a, How Australians pay: evidence from the 2016 Consumer Payments Survey, RBA Bulletin, pp. 1-41.

Doyle, MA, Fisher, C Tellez, E & Yadav, A 2017b, How Australians pay: new survey evidence, RBA Bulletin, pp. 59-66.

Duan, X 2012, An integrated solution to the adoption of electronic market in Australian small-and-medium sized enterprises, PhD thesis, RMIT University.

Dutot, V 2015, Factors influencing Near Field Communication (NFC) adoption: an extended TAM approach, Journal of High Technology Management Research, vol. 26, pp. 45–57.

Eelu, S & Nakakawa, A 2018, Framework towards enhancing adoption of electronic payment in a developing economy: a case of Uganda, The African Journal of Information Systems: vol. 10, no. 3, pp. 222-245.

Elhag, HM 2015, Enhancing online banking transaction authentication by using tamper proof & cloud computing, PhD thesis, University of Surrey.

eMarketer 2019, Contactless competition and digital limitations stifle proximity mobile payment growth in the UK, viewed 8 September 2020,

Engwanda, MN 2014, Factors Affecting Mobile Banking Adoption in the United States, PhD thesis, Walden University.

Fintech News 2019, The critical role of artificial intelligence in payments tech, viewed 5 February 2020,

Fonchamnyo, DC 2013, Customers’ perception of e-banking adoption in Cameroon: an empirical assessment of an extended TAM, International Journal of Economics and Finance, vol. 5, no. 1, pp. 166-176.

Gao, L & Waechter, KA 2015, ‘Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation’, Information Systems Frontiers, pp. 1-24.

Gavrilović, Z & Maksimović, M 2019, The concept of cloud marketing, paper presented at 7th International Scientific Symposium „EkonBiz: Modern business in the function of the development of the national economy―, Bijeljina, 20-21nd June 2019.

Genovese, W 2017, Accelerating success in the 4th industrial revolution, viewed 27 April 2020,

Global Market Insights 2019, Cloud POS Market Share 2019-2025, Industry Forecast Report, viewed 28 April 2020,

Gossett, S 2019, 10 AI in banking examples you should know, viewed 20 August 2020,

Govender, I & Sihlali, W 2014, A study of mobile banking adoption among university students using an extended TAM, Mediterranean Journal of Social Sciences, vol. 5, no. 7, pp. 451-459.

Government Accountability Office (GAO) 2018, Artificial intelligence: emerging opportunities, challenges, and implications for policy and research, viewed 28 April 2020,

Grix, J 2010, The foundations of research, 2nd edn, Palgrave Macmillan, London.

Guhr, N, Wiegard, TLR, & Breitner, MH 2013, Technology readiness in customers’ perception and acceptance of m(obile)-payment: an empirical study in Finland, Germany, the USA and Japan, paper presented at 11th International Conference on Wirtschaftsinformatik, Leipzig, Germany, pp. 1-8, viewed 26 August 2020,

Gumussoy, CA, Kaya, A & Ozlu, E 2018, Determinants of mobile banking use: an extended TAM with perceived risk, mobility access, compatibility, perceived self-efficacy and subjective norms, Lecture Notes in Management and Industrial Engineering, pp. 225-238, viewed 26 August 2020,

Hair, JF, Risher, JJ, Sarstedt, M & Ringle, CM 2019, When to use and how to report the results of PLS-SEM, European Business Review, vol. 31, n.1, pp. 2-24, https://

Hampshire, C 2016, Exploring UK consumer perceptions of mobile payments using smart phones and contactless consumer devices through an extended technology adoption model, PhD thesis, University of Chester.

Hankun, H, Yafang, L, Xuemei, H & Jing, F 2016, A comparative study of China and US users' acceptance of online payment, paper presented at 2016 13th International Conference on Service Systems and Service Management (ICSSSM), Hangzhou, China, viewed 29 August 2020,

Hashim, NAAN, Zulkifli,WFW, Aziz, RC, Nawi, NMM, Awang, Z, Muhammad, NH &

Yusoff, AM 2020, Grab Pay app: the factors influencing tourists’ behavioural intention-to-use, Talent Development & Excellence, vol. 12, no. 3s, pp. 820-828.

Hebie, AP 2017, Improving mobile phone banking usefulness, usability, risk, cost, and intention to adopt, DBA dissertation, Walden University.

Hinojo-Lucena, FJ, Aznar-Díaz, I, Cáceres-Reche, MP & Romero-Rodríguez, JM, 2019, ‘Artificial intelligence in higher education: a bibliometric study on its impact in the scientific literature’, Education Sciences, vol. 9, no. 1, p. 51.

Ho, E, Apostu, S, Michahelles, F & Ilic, A 2013, Digital receipts: fostering mobile payment adoption, International Joint Conference on Ambient Intelligence, vol. 8309, pp. 140-149.

Hossain, A & Udin, MN 2018, A differentiate analysis for credit card fraud detection, Paper presented at 2018 2nd International Conference on Innovations in Science, Engineering and Technology (ICISET), Bangladesh, 27-28 October, viewed 27 April 2020,

Hossain, R & Mahmud, I 2016, Influence of cognitive style on mobile payment system adoption: an extended technology acceptance model, paper presented at 2016 International Conference on Computer Communication and Informatics (ICCCI -2016), Coimbatore, India, viewed 27 August 2020,

Hyson, DE 2014, Factors influencing the adoption of cloud computing by medical facility managers, PhD thesis, Capella University.

Imran, M, ul Hameed, W & ul Haque, A 2018, ‘Influence of industry 4.0 on the production and service sectors in Pakistan: evidence from textile and logistics industries’, Social Sciences, vol. 7, no. 12, pp. 1-21.

Jenkins, P & Ophoff, J 2016, Factors influencing the intention to adopt NFC mobile payments - a South African perspective, Refereed papers from the International Conference on Information Resources Management (CONF-IRM), pp. 1-12, viewed 28 December 2017,

Jiao, Y 2018, Applications of artificial intelligence in e-commerce and finance, PhD thesis, Telecom SudParis.

Kagermann, H, Helbig ,J, Hellinger, A & Wahlster, W 2013, Recommendations for implementing the strategic initiative industrie 4.0: securing the future of German manufacturing industry, final report of the industrie 4.0 working group, Forschungsunion.

Kalinic, Z, Marinkovica, V, Molinillo, S & Liébana-Cabanillas, F 2019, A multi-analytical approach to peer-to-peer mobile payment acceptance prediction, Journal of Retailing and Consumer Services, vol. 49, pp. 143–153.

Karim, W, Haque, A, Ulfy, MA, Hossain, A, Anis, Z 2020, Factors influencing the use of e-wallet as a payment method among Malaysian young adults, Journal of International Business and Management, vol. 3, no. 2, pp. 1-12.

Keller, B., Baleis, J., Starke, C. and Marcinkowski, F. 2019, Machine Learning and artificial intelligence in higher education: a state-of-the-art on the German university landscape, pp.1-31, viewed 2 January 2020,

Khalilzadeh, J, Ozturk, AB & Bilgihan, A 2017, ‘Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry’, Computers in Human Behavior, vol. 70, pp. 460-474.

Killian, D, & Kabanda, S 2017, Mobile payments In South Africa: middle income earners' perspective, Refereed papers from the Twenty First Pacific Asia Conference on Information Systems (PACIS), Langkawi, viewed 27 December,

Klug, WE 2014, The determinants of cloud computing adoption by colleges and universities, PhD thesis, Northcentral University.

Kongarchapatara, B & Rodjanatara, C 2018, Factors affecting adoption versus behavioral intention to use QR code payment application, paper presented at International Conference on e-Commerce, e-Administration, e-Society, e-Education, and e-Technology, Osaka, Japan, viewed 29 August 2020,

Köster, A, Matt, C & Hess, T 2016,’Carefully choose your (payment) partner: how payment provider reputation influences m-commerce transactions’, Electronic Commerce Research and Applications, vol. 15, pp. 26-37.

Kristensen, SM 2016, Understanding factors influencing Danish consumers’ intention to use mobile payment at point-of-sale, MSc thesis, Aarhus University.

Kumar, R & O’Brien, S 2019, 2019 Findings from the Diary of Consumer Payment choice, Cash Product Office, Federal Reserve System, viewed 24 April 2020,

Kumar, R 2011, ‘Research methodology: a step-by-step guide for beginners’, 3rd edition. Los Angeles, SAGE.

Kumar, VVR, Lall, A & Mane, T 2017, Extending the TAM model: intention of management students to use mobile banking: evidence from India, Global Business Review, vol. 18, no. 1, pp. 238–249.

Lai, PC 2016, Design and security impact on consumers’ intention to use single platform E-payment, Interdisciplinary Information Sciences, vol. 22, no. 1, pp. 111–122.

Lai, PC 2018a, Security as an extension to TAM model: consumers' intention to use a single platform e-payment system, Asia-Pacific Journal of Management Research and Innovation, vol. 13, no. 3–4, pp. 110–119.

Lai, PC 2018b, Single platform e-payment system consumers’ intention to use, Journal of Information Technology Management, vol. XXIX, no. 2, pp. 22-28.

Landrum, B & Garza, G 2015, ‘Mending fences: defining the domains and approaches of quantitative and qualitative research’, Qualitative Psychology, vol. 2, no. 2, pp. 199–209.

Latentview 2018, How to make Artificial Intelligence work for your organization, viewed 10 February 2020,

Lee, J, Suh, T, Roy, D & Baucus, M 2019, ‘Emerging technology and business model innovation: the case of artificial intelligence’, Journal of Open Innovation: Technology, Market, and Complexity, vol. 5, no. 3, pp. 1-13.

Lee, MC 2009, ‘Factors influencing the adoption of internet banking: an integration of TAM and TPB with perceived risk and perceived benefit’, Electronic commerce research and applications, vol. 8, no. 3, pp. 130-141.

Lee, VH, Hewa, JJ, Leong, LY, Tan, GWH & Ooi, KB 2020, Wearable payment: a deep learning-based dual-stage SEM-ANN analysis, Expert Systems with Applications, vol. 157 no. 113477, pp. 1-14.

Lesa, E & Tembo, S 2016, Study on factors affecting mobile payment systems diffusion in Zambia, Management, vol. 6, no. 2, pp. 36-45.

Li, H, Liu, Y & Heikkilä, J 2014, Understanding the factors driving NFC-enabled mobile payment adoption: an empirical investigation, paper presented at Pacific Asia Conference on Information Systems (PACIS), Chengdu, China, viewed 28 August 2020,

Li, J, Liu, JL & Ji, HY 2014, Empirical study of influence factors of adaption intention of mobile payment based on TAM model in China, International Journal of u- and e- Service, Science and Technology, vol.7, no.1, pp.119-132.

Li, J, Wang, J, Wangh, S & Zhou, Y 2019, Mobile payment with Alipay: an application of extended technology acceptance model, IEEE Access, vol. 7, pp. 50380-50387.

Liébana-Cabanillas, F, Leiva, FM & Fernández, JS 2017, ‘Examining merchants’ refusal to adopt mobile payment systems in Spain’, In Nawaz Mohamudally (Ed.), Smartphones from an Applied Research Perspective, InTech, e-book, viewed 15 January 2018, perspective/examining-merchants-refusal-to-adopt-mobile-payment-systems-in-spain

Liébana-Cabanillas, F, Marinkovic, V, Ramos de Luna, IR & Kalinic, Z 2018, Predicting the determinants of mobile payment acceptance: A hybrid SEM-Neural Network approach, Technological Forecasting & Social Change, vol. 129, pp. 117–130.

Liébana-Cabanillas, F, Munoz-Leiva, F & Rejón-Guardia, F 2013, ‘The determinants of satisfaction with e-banking’, Industrial Management & Data Systems, vol. 113, no. 5, pp. 750- 767.

Liébana-Cabanillas, F, Muñoz-Leiva, F & Sánchez-Fernández, J 2013, The impact of risk on the technological acceptance of mobile payment services, Global Business Perspective, vol.1, pp. 309–328.

Liébana-Cabanillas, F, Muñoz-Leiva, F & Sánchez-Fernández, J 2018, A global approach to the analysis of user behavior in mobile payment systems in the new electronic environment, Service Business, vol. 12, pp. 25–64.

Liébana-Cabanillas, F, Ramos de Luna, I & Montoro-Ríos, F 2015, User behaviour in QR mobile payment system: the QR payment acceptance model, Technology Analysis & Strategic Management, vol. 27, no. 9, pp. 1031-1049.

Liébana-Cabanillas, F, Ramos de Luna, I & Montoro-Ríos, F 2017, Intention to use new mobile payment systems: a comparative analysis of SMS and NFC payments, Economic Research-Ekonomska Istraživanja, vol. 30, no. 1, pp. 892-910.

Liébana-Cabanillas, F, Sánchez-Fernández, J & Muñoz-Leiva, F 2014a, ‘Antecedents of the adoption of the new mobile payment systems: the moderating effect of age’, Computers in Human Behavior, vol. 35, pp. 464-478.

Liébana-Cabanillas, F, Sánchez-Fernández, J & Muñoz-Leiva, F 2014b, ‘Role of gender on acceptance of mobile payment’, Industrial Management & Data Systems, vol. 114, no. 2, pp. 220-240.

Liébana-Cabanillas, F, Sánchez-Fernández, J & Muñoz-Leiva, F 2014c, ‘The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN)’, International Journal of Information Management, vol. 34, no. 2, pp.151-166.

Lin, WR, Yang, FJ & Chang, YH 2020, The impact of risk factors and attitudes on use mobile payment intention, Journal of Accounting, Finance & Management Strategy, vol. 15, no. 1, pp. 129-158.

Liu, GS & Tai, PT 2016, ‘A study of factors affecting the intention to use mobile payment services in Vietnam’, Economics, vol. 4, no. 6, pp. 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, vol. 17, pp. 319–342.

Lowe, P 2019, A payments system for the digital economy, RBA - Address to the 2019 Australian payments network summit, pp.1-12, viewed 24 April 2020,

Lwoga, E & Lwoga, N 2017, User acceptance of mobile payment: the effects of user-centric security, system characteristics and gender, The Electronic Journal Information Systems in Developing Countries, vol. 81, no. 3, pp. 1-24.

Ma, L, Su, X, Yu, Y, Wang, C, Lin, K & Lin, M 2018, What drives the use of m-payment? An empirical study about Alipay and WeChat payment, paper presented at 2018 15th International Conference on Service Systems and Service Management (ICSSSM), Hangzhou, China, pp. 1-6, viewed 27 August 2020,

MacDonald, S, & Headlam, N 2008, Research methods handbook: introductory guide to research methods for social research. Manchester, Centre for Local Economic Strategies.

Maizland, L & Albert, E 2020, What is ASEAN? viewed 07 December 2020,,Singapore%2C%20Thailand%2C%20and%20Vietnam.

Malaquias, RF & Silva, AF 2020, Understanding the use of mobile banking in rural areas of Brazil, Technology in Society, vol. 62, no. 101260, pp. 1-9.

Marjetic, D. & Lesjak, D. 2018, ‘Potential usage of artificial intelligence and big data analytics in higher education enrollment in Slovenia’, Issues in Information Systems, vol. 19, n. 4, pp. 96-105.

Mbama, CI 2018, Digital banking services, customer experience and financial performance in UK banks, PhD thesis, Sheffield Hallam University.

McCarthy, J 2007, What is artificial intelligence?, Computer Science Department Stanford University, viewed 10 February 2020,

McCorduck, P 2004, Machines Who Think A Personal Inquiry into the History and Prospects of Artificial Intelligence, A K Peters, Ltd., Natick, Massachusetts.

Mehrad, D & Mohammadi, S 2016, Word of Mouth impact on the adoption of mobile banking in Iran, Telematics and Informatics, pp. 1-13, viewed 25 August 2020,

Mejia, N 2019, Artificial intelligence for payments – current capabilities and use cases, viewed 20 August 2020,

Mha, K 2015, A Mobile banking adoption model in the Jordanian market: an integration of TAM with perceived risks and perceived benefits, Journal of Internet Banking and Commerce, vol. 20, no. 3, pp. 1-35.

Mingxing, S, Jing, F & Yafang, L 2014, An empirical study on consumer acceptance of mobile payment based on the perceived risk and trust: Refereed paper from the International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery 2014, pp. 312-317, viewed 17 January 2017,

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

Mondego, D & Gide, E 2018, ‘The effect of trust on mobile payment adoption: a comprehensive review of literature’, International Journal of Arts & Sciences, vol. 11, n.1, pp. 375- 389.

Mondego, D, Gide, E & Chaudhry, G 2018, The effect of personal factors on consumers’ trust in mobile payment systems in Australia: Refereed paper from the 2018 5th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), pp. 156-163, viewed 28 June 2020,

Morosan, C 2014, ‘Toward an integrated model of adoption of mobile phones for purchasing ancillary services in air travel’, International Journal of Contemporary Hospitality Management, vol. 26, no. 2, pp. 246-271.

Morrar, R, Arman, H & Mousa, S 2017, ‘The fourth industrial revolution (industry 4.0): a social innovation perspective’, Technology Innovation Management Review, vol. 7, n. 1, pp. 12-20.

Mou, X 2019, Artificial intelligence: investment trends and selected industry uses, International Financial Corporation - World Bank Group, viewed 21 April 2020,

Muna, YP, Khalidb, H & Nadarajah, D 2017, Millennials’ perception on mobile payment services in Malaysia, Procedia Computer Science, vol. 124, pp. 397–404.

Munoz-Leiva, F, Climent-Climent, S, Liébana-Cabanillas, F 2017, Determinants of intention to use the mobile banking apps: An extension of the classic TAM model, Spanish Journal of Marketing – ESIC, vol. 21, pp. 25-38.

Mutahar, AM, Daud, NM, Ramayah, Isaac, O, Adnan H. Aldholay, AH 2018, The effect of awareness and perceived risk on the technology acceptance model (TAM): mobile banking in Yemen, International Journal of Services and Standards, vol. 12, no. 2, pp. 180-204.

Mutahar, AM, Daud, NM, Ramayah, Lennora Putit, T, Isaac, O 2017, Examining the effect of subjective norms and compatibility as external variables on tam: mobile banking acceptance in Yemen, Science International, vol. 29, no. 4, pp. 769-776.

Nadler S, Chen, AN & Lin, SF 2019, E-payment usage among young urban Chinese, Journal of Business Diversity, vol. 19, no. 3, pp. 75-88.

Ndofirepi, TM & Gavai, P 2019, The adoption of mobile banking among college students in Zimbabwe, African Journal of Business and Economic Research, vol. 14, no. 4, pp. 105 – 132.

Neuman WL 2014, Social research methods: qualitative and quantitative approaches, 7th edn, Pearson Education Limited, Harlow.

Nguyen, TD & Huynh, PA 2018, The roles of perceived risk and trust on e–payment adoption, Econometrics for Financial Applications, Studies in Computational Intelligence, vol. 760, pp. 926-940.

Nicholas-Donald, A 2014, The economic worth of cloud computing adoption: a financial analysis, PhD thesis, The University of Texas at El Paso.

Nigam, A & Kumari, S 2018, Adoption of United Payment Interface Application: An Empirical Investigation Using TAM Framework, CPJ Global Review, vol. X, no.2, pp. 29-36.

Ooi, KB & Tan, GWH 2016, ‘Mobile technology acceptance model: an investigation using mobile users to explore smartphone credit card’, Expert Systems with Applications, vol. 59, pp. 33-46.

Opus Consulting 2019, Why Cloud-Based payments are gaining momentum, viewed 10 February 2020,

Öztüren, A 2018, Acceptance of mobile payment technologies by the travellers visiting North Cyprus, paper presented at 7th Intentational Conference on Tourism & Hospitality Management, pp.166-175, viewed 27 August 2020,

Pal, A, De, R, Herath, T & Rao, HR 2019, ‘A review of contextual factors affecting mobile payment adoption and use’, Journal of Banking and Financial Technology, vol. 3, pp. 43-57.

Pal, D, Funilkul, S & Patra, S 2020, Paying by your messaging application? a trust model, paper presented at 11th International Conference on Advances in Information Technology (IAIT), Bangkok, Thailand, viewed 28 August 2020,

Pan, YC, Jacobs, A, Tan, C & Askool, S 2018, Extending technology acceptance model for proximity mobile payment via organisational semiotics, International Federation for Information Processing, pp. 43-52.

Patel, RK 2016, Examining predictors of satisfaction with mobile payment systems among small business users, PhD Thesis, Northcentral University.

Patil, PP, Rana, NP & Dwivedi, YK 2018, Digital payments adoption research: A review of factors influencing consumer’s attitude, intention and usage, Conference papers – International Federation for Information Processing (IFIP) 2018, pp. 45-52.

Pertiwi, D, Suprapto, W & Pratama, E 2020, Perceived usage of e-wallet among the Y generation in Surabaya based on technology acceptance model, Jurnal Teknik Industri, vol. 22, no. 1, pp. 17-24.

Pfisterer, B 2018, Why you should invest in cloud based payments this financial year, viewed 10 February 2020,

Pham, TTT & Ho, JC 2015, ‘The effects of product-related, personal-related factors and attractiveness of alternatives on consumer adoption of NFC-based mobile payments’, Technology in Society, vol. 43, pp. 159-172.

Phonthanukitithaworn, C, Sellitto, C & Fong, MW 2015, ‘User intentions to adopt mobile payment services: a study of early adopters in Thailand’, Journal of Internet Banking and Commerce, vol. 20, no. 1, pp. 1-29.

Phonthanukitithaworn, C, Sellitto, C & Fong, MW 2016, ‘An investigation of mobile payment (m-payment) services in Thailand’, Asia-Pacific Journal of Business Administration, vol. 8, no. 1, pp. 37-54.

Phoong, SW, Phoong, SY, Moghavvemi, S & Yeong, WC 2019, Are We Ready for Mobile Payment?, Advances in Business Research International Journal, pp. 1-6.

Prentice, C, Lopes, SD & Wang, X 2020, The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty, Journal of Hospitality Marketing & Management, pp. 1-18, viewed 20 August 2020,

Priyadarshinee, P, Raut, RD, Jha, MK & Gardas, BB 2017, ‘Understanding and predicting the determinants of cloud computing adoption: a two staged hybrid SEM - Neural networks approach’, Computers in Human Behavior, vol.76, pp. 341-362.

Profecta Marketing (n.d.), Tips and Strategy for your business, viewed 25 April 2020,

Psannis, KE, Batalla, JM & Ishibashi,Y 2020, Artificial intelligence for cloud based big data analytics- big data research, viewed 25 April 2020,

Qu, Y, Rong, W, Chen, H, Ouyang, Y & Xiong, Z 2018, Influencing factors analysis for a social network web based payment service in China, Journal of Theoretical and Applied Electronic Commerce Research, vol. 13, no. 3 / pp. 99-113.

Ramos de Luna, I, Montoro-Ríos, F & Liébana-Cabanillas, F 2016, Determinants of the intention to use NFC technology as a payment system: an acceptance model approach, Information Systems E-Business Management, vo. 14, pp. 293–314.

Ramos de Luna, I, Montoro-Ríos, F, Liébana-Cabanillas, F & de Luna, JG 2017, NFC technology acceptance for mobile payments: a Brazilian perspective, Review of Business Management, vol. 19, no. 63, pp. 82-103.

Ramos de Luna, IR, Liébana-Cabanillas, F, Sánchez-Fernández, J Μñoz-Leiva, F 2018, Mobile payment is not all the same: the adoption of mobile payment systems depending on the technology applied, Technological Forecasting & Social Change, pp. 1-14, viewed 27 August 2020,

Riskinanto, A, Kelana, B, Hilmawan, DR 2017, The moderation effect of age on adopting e-payment technology, paper presented at 4th Information Systems International Conference 2017, ISICO 2017, 6-8 November 2017, Bali, Indonesia, viewed 25 August 2020,

Rivera, IL 2016, Developing online trust in electronic commerce: a generational cohort study in Puerto Rico, DBA dissertation, Universidad Del Turabo.

Roy Morgan Research 2020, Afterpay, Apple Pay and Google Pay are driving the adoption of new digital payment services, viewed 27 April 2020,

Roy, S & Sinha, I 2014, Determinants of customers’ acceptance of electronic payment system in Indian banking sector – a study, vol. 5, no. 1, pp. 177-187.

Roy, S & Sinha, I 2017, Factors affecting customers’ adoption of electronic payment: an empirical analysis, IOSR Journal of Business and Management, vol. 19, no. 12, pp. 76-90.

Saji, TG & Paul, D 2018, Behavioural intention to the use of mobile banking in Kerala: an application of extended classical technology acceptance model, Metamorphosis, vol. 17, no. 2, pp. 111–119.

Sandema-Sombe, CN 2019, Relationship between perceived usefulness, ease of use, and acceptance of business intelligence systems, DBA dissertation, Walden University.

Sanders, M, Lewis, P & Thornhill, A 2009, Research methods for business students, 5th edn, Pearson Education, Harlow.

Shankar, A & Datta, B 2018, Factors affecting mobile payment adoption intention: an Indian perspective, Global Business Review, vol. 19, no.3S, pp. 72S–89S.

Sharma, G & Lijuan, W 2015,’The effects of online service quality of e-commerce Websites on user satisfaction’, The Electronic Library, vol. 33, n. 3, pp. 468 – 485.

Sharma, SK, Govindaluri, SM, Al-Muharrami, S & Tarhini, A 2017, A multi-analytical model for mobile banking adoption: a developing country perspective, Review of International Business and Strategy, vol. 27, no. 1, pp. 133-148.

Sharma, SK, Sharma, H & Dwivedi, YK 2019, A hybrid SEM-Neural Network Model for predicting determinants of mobile payment services, Information Systems Management, vol. 36, no. 3, pp. 243-261.

Sharma, SK 2019, Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: a SEM-neural network modeling, Information Systems Frontier, vol.21, pp.815-827.

Shaw, N 2014, ‘The mediating influence of trust in the adoption of the mobile wallet’, Journal of Retailing and Consumer Services, vol.21, no.4, pp. 449-459.

Shaw, N 2015, Younger persons are more likely to adopt the mobile wallet than older persons, or are they? the moderating role of age, Conference Papers - Twenty-first Americas Conference on Information Systems, Puerto Rico, pp.1-15.

Shin, S & Lee, WJ 2014, The effects of technology readiness and technology acceptance on NFC mobile payment services in Korea, The Journal of Applied Business Research, vol. 30, no. 6, pp. 1615-1626.

Shuhaiber, A 2016, Factors influencing consumer trust in mobile payments in the United Arab Emirates, PhD thesis, Victory University of Wellington.

Siau, K & Wang, W 2018, ‘Building trust in artificial intelligence, machine learning, and robotics’, Cutter Business Technology Journal, vol. 31, n. 2, pp. 47-53.

Sidek, N 2015, Determinants of electronic payment adoption in Malaysia: the stakeholders’ perspectives, PhD thesis, University of Queensland.

Simon, JP 2019, ‘Artificial intelligence: scope, players, markets and geography’, Digital policy, Regulation and Governance, vol. 21, n. 3, pp. 208-237.

Singh, B, Kumar, B & Gupta, R 2018, The role of consumer’s innovativeness & perceived ease of use to engender adoption of digital wallets in India, paper presented at 2018 International Conference on Automation and Computational Engineering (ICACE - 2018) Amity University Greater Noida Campus, U. P., India, viewed 25 August 2020,

Singh, N., Sahu, G., Rana, N., Patil, P. & Gupta, B. 2018, Critical Success Factors of the Digital Payment Infrastructure for Developing Economies, Smart Working, Living and Organising, pp. 1-13.

Singh, YK, 2006, Fundamental of research methodology and statistics, New Age International, New Delhi.

Siyal, AW, Ding, D & Siyal, S 2019, M-banking barriers in Pakistan: a customer perspective of adoption and continuity intention, Data Technologies and Applications, vol. 53, no. 1, pp. 58-84.

Siyal, AW, Ding, D, Umrani, WA, Siyal, S, & Bhand, S 2019, predicting mobile banking acceptance and loyalty in Chinese bank customers, Sage Open, pp. 1-21.

Slade, E, Williams, M, Dwivedi, Y & Piercy, N 2015, ‘Exploring consumer adoption of proximity mobile payments’, Journal of Strategic Marketing, vol. 23, no. 3, pp. 209-223.

Song, X, Yang, S, Huang, Z & Huang, T 2019, The application of artificial intelligence in electronic commerce, Refereed papers from Journal of Physics: Conference Series, vol. 1302, n. 3 pp. 1-6.

Spiess, J, T’Joens, Y, Dragnea, R, Spencer, P& Philippart, L 2014, ‘Using Big Data to Improve Customer Experience and Business Performance’, Bell Labs Technical Journal, vol. 18, n. 4, pp.3–17

Spratto, EM 2018, In search of equality: Developing an equal interval Likert response scale, PhD thesis, James Madison University.

Springfield, C 2018, The impact of cloud computing on the banking sector, International Banker, viewed 25 April 2020,

Strusani, D & Houngbonon, GV 2019, The role of artificial intelligence in supporting development in emerging markets, International Financial Corporation - World Bank Group, viewed 21 April 2020,

Su, P, Wang, L & Yan, J 2018, How users’ Internet experience affects the adoption of mobile payment: a mediation model, Technology Analysis & Strategic Management, vol. 30, no. 2, pp. 186-197.

Sumerta, K & Wardana, M 2018, Analysis Of intention to use electronic money in Denpasar city: TAM approach, Archives of Business Research, vol.6, no.10, pp. 86-103.

Sun, Y & Havidz, SAH 2019, Factors impacting the intention to use m-payment, paper presented at 2019 International Conference on Information Management and Technology (ICIMTech), Jakarta & Bali, Indonesia, pp. 290-294, viewed 27 August 2020,

Suwunniponth, W 2016, Customers’ intention to use electronic payment system for purchasing, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, vol.10, no:12, pp.3864-3869.

Sveriges Riksbank 2016, The Swedish Financial Market 2016, viewed 26 June 2017, _eng.pdf

Talwar, S, Dhir, A, Khalil, A, Mohan, G & Islam, AKMN 2020, Point of adoption and beyond. Initial trust and mobile-payment continuation intention, Journal of Retailing and Consumer Services, vol. 55, pp. 1-12.

Tan, JD, Purba, JT & Widjaya, AE 2018, Financial technology as an innovation strategy for digital payment services in the millenial generation, Advances in Social Science, Education and Humanities Research, vol. 292, pp. 364-373.

TechTarget 2019, Use of AI in payments industry is set to explode, viewed 5 February 2020,

Teoh, WMY, Chong, SC, Lin, B & Chua, JW 2013, ‘Factors affecting consumers' perception of electronic payment: an empirical analysis’, Internet Research, vol. 3, no. 4, pp. 465-485.

Tiong, WN 2020, Factors influencing behavioural intention towards adoption of digital banking services in Malaysia, International Journal of Asian Social Science, vol. 10, no. 8, pp. 450-457.

Topol, E 2019, Deep medicine: how artificial intelligence can make health care human again, Hachette Book Group, New York.

Tounekti ,O, Ruiz-Martínez, A & Gomez, AFS 2019, Users supporting multiple (mobile) electronic payment systems in online purchases: an empirical study of their payment transaction preferences, IEEE Access, vol. 8, pp. 735-766.

Tran, K 2015, E-business adoption in micro business in NSW, Australia: does the government tick the right boxes? A qualitative multiple case study, DBA dissertation, Southern Cross University, Lismore, NSW.

Trend Micro (2015) Next-Gen Payment Processing Architectures, viewed 26 April 2020,

Ungerer, L.M. 2019, AI in higher education: Considering the ecosystem in an emerging-country context, University of South Africa, pp. 19-41.

Upadhyay, P & Jahanyan, S 2016, Analyzing user perspective on the factors affecting use intention of mobile based transfer payment, Internet Research, vol. 26, no.1, pp. 38-56.

Vanneschi, L, Horn, DM, Castelli, M & Popovic, A 2018, ‘An artificial intelligence system for predicting customer default in e-commerce’, Expert Systems with Applications, vol. 104, pp. 1-21.

Vasileiadis, A 2014, Security concerns and trust in the adoption of m-commerce, Social Technologies, vol.4, no.1, pp.179-191.

Venkatesh, V, Brown, SA & Bala, H 2013, ‘Bridging the qualitative-quantitative divide: guidelines for conducting mixed methods research in information systems’, MIS Quarterly, vol. 37, no. 1, pp. 21-54.

Wadhwani, P & Gankar, S 2019, Cloud POS market share 2019-2025 – industry forecast report, viewed 27 April 2020,

Walch, K 2019, Use of AI in payments industry is set to explode, viewed 20 August 2020,

Wall, LD 2018, ‘Some financial regulatory implications of artificial intelligence’, Journal of Economics and Business, vol. 100, pp. 55-63.

Walliman, N 2010, Research methods: The basics, Routledge, viewed 11 July, 2020,

Wang, G, Putri, NM, Christianto, A & W, DH 2019, An empirical examination of characteristics of mobile payment users in Indonesia, Journal of Theoretical and Applied Information Technology, vol.96, no 1, pp. 169-182.

Widayat, W, Masudin, I & Satiti, NR 2020, E-money payment: customers’ adopting factors and the implication for open innovation, Journal of Open Innovation: Technology, Market, and Complexity, vol. 6, no. 57, pp. 1-14.

Williams, MD, Roderick, S, Davies, GH & Clement, M 2017, Risk, trust, and compatibility as antecedents of mobile payment adoption, Refereed papers from the Twenty-third Americas Conference on Information Systems, pp.1-10, Boston, viewed 5 February 2018,

Wiradinata, T 2018, Mobile payment services adoption: the role of perceived technology risk, paper presented at 2018 International Conference on Orange Technologies (ICOT), Nusa Dua, Bali, Indonesia, pp. 1-5, viewed 27 August 2020,

Wong, ATT 2018, A study of consumer acceptance of mobile payment services in Hong Kong, Journal of Economics, Management and Trade, vol. 21, no. 3, pp. 1-14.

World Economic Forum (n.d.), Fourth industrial revolution, viewed 22 April 2020 on

Xu, X 2017, The effects of website quality on customer satisfaction, use intention, and purchase intention: a comparison among three types of booking channels, PhD thesis, Iowa State University.

Yamaguti Mondego, D, 2019, A framework to build trust in mobile payment systems for Australian consumers, Master's by Research Thesis. Central Queensland University,

Yan, H & Pan, K 2014, Examine user adoption of mobile payment using the TAM: a trust transfer perspective, Refereed papers from the Wuhan International Conference on e-Business (WHICEB 2014), pp.402-409, viewed 27 December 2017,

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, vol. 8, no. 1, pp. 117- 130.

Yang, Q, Pang, C, Liu, L, Yen, DC & Tarn, JM, 2015, Exploring consumer perceived risk and trust for online payments: an empirical study in China’s younger generation, Computers in Human Behavior, vol. 50, pp. 9-24.

Yaokumah, W, Kumah, P & Okai, ESA 2017, ‘Demographic influences on e-payment services’, International Journal of E-Business Research, vol. 13, n. 1, pp. 44-65.

Yap, CM & Ng, BA 2019, Factors influencing consumers’ perceived usefulness of m-wallet in Klang Valley, Malaysia, Review of Integrative Business and Economics Research, vol. 8, no. 4 pp. 1-23.

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, vol. 41, pp. 1-9.

Yuan, S, Liu, Y, Yao, R & Liu, J 2014, An investigation of users’ continuance intention towards mobile banking in China, Information Development, vol. 32, no.1, pp. 20–34.

Zhang, WK & Kang, MJ 2019, Factors affecting the use of facial-recognition payment: an example of Chinese consumers, IEEE Access, 7, pp. 154360-154374.

Zhou, T 2013, An empirical examination of continuance intention of mobile payment services, Decision Support Systems, vol. 54, no. 2, pp. 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), vol. 11, no. 1, pp. 55-66.

Ziwei, F, Tham, J & Azam, SMF 2019, Determinants of users’ willingness to use mobile payment: an empirical study in Tongren University, China, European Journal of Management and Marketing, vol. 4, no. 4, pp. 16-38.


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