In
light of Sri Lankans’ widespread usage of mobile phones and other mobile
devices, the objective of the aforementioned research, which was conducted by the author, is to analyse users’ acceptance of
Quick Response (QR) code mobile-driven payment systems. Using the UTAUT2 (Unified Theory of Acceptance
and Use of Technology 2) model, the current study was developed. This study creates a conceptual
model to identify the key elements affecting user
intention, perceived satisfaction, and recommendation to utilize QR code
payments as a platform for payments when shopping and using services in retail.
484 results from an online survey conducted in Sri Lanka were used in the study
model. The study looked at how innovativeness, use stress, and social influence affected how satisfied users felt
and whether they would promote QR Code payment methods to others. The
study found that ease of use, perceived usefulness, and attitude all had a
substantial impact on users’ intentions to use QR Code payment methods, which
in turn affected users’ perceptions of their pleasure with the technology and
recommendations to use the technology. The study also found a strong moderating
impact of social influence and use stress on
users’ perceptions of satisfaction and recommendations for QR Code
payment methods. It was evident that, in the Sri Lankan context, perceived risk
and innovation had a negative effect on the intention to adopt QR code payment
methods. Also, the entire study focuses on consumers’ acceptability of using QR
Code payment platforms in Sri Lanka, and academics might conduct further research into the topic of Sri Lankan merchants.
232journal papers were examined for
the total literature assessment, and the UTAUT2 theory was identified.
References
[1]
Abhishek, K., Rajesh, K. C., Saroj, K. M., Sanjay, K. K., & Rohit, B. (2022). The Growth Trajectory of UPI-Based Mobile Payments in India: Enablers & Inhibitors. Indian Journal of Finance and Banking, 11, 45-59. https://doi.org/10.46281/ijfb.v11i1.1855
[2]
Aithal, R. K., Vikram, C., Harshit, M., Debasis, P., & Dev Narayan, S. (2022). Factors Influencing Technology Adoption amongst Small Retailers: Insights from Thematic Analysis. International Journal of Retail & Distribution Management, 51, 81-102. https://doi.org/10.1108/IJRDM-02-2022-0042
[3]
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behaviour and Human Decision Process, 50, 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
[4]
Akturan, U., & Tezcan, N. (2012). Mobile Banking Adoption of the Youth Market: Perceptions and Intentions. Marketing Intelligence & Planning, 30, 444-459. https://doi.org/10.1108/02634501211231928
[5]
Ama, H. E., Tara, A. M., Syriac, N., & Tan, S. T. (2022). Factors Influencing Consumer’s Behavioural Intention towards the Adoption of Mobile Payment in Kuala Lumpur. International Journal of Professional Business Review, 7, e0584.
[6]
Arif, M. S., Min, Y. S., Zakaun, N., & Ishak, N. (2012). The Impact of Computer Self-Efficacy and Technology Acceptance Model on Behavioural Intention in Internet Banking System. Review of Integrative Business and Economics, 2, 587-601.
[7]
Balakrishnan, V., & Nor, L. M. (2021). Drivers and Inhibitors for Digital Payment Adoption Using the Cashless Society Readiness-Adoption Model in Malaysia. Technology in Society, 65, Article ID: 101554. https://doi.org/10.1016/j.techsoc.2021.101554
[8]
Bandura, A. (1997). Self Efficacy toward a Unifying Theory of Behavioral Change (pp. 191-215). WH Freeman and Company. https://doi.org/10.1037/0033-295X.84.2.191
[9]
Bandura, A. (2004). Swimming against the Mainstream: The Early Years from Chilly Tributary to Transformative Mainstream. Behaviour Research and Therapy, 42, 613-630. https://doi.org/10.1016/j.brat.2004.02.001
[10]
Benbasat, I., & Barki, H. (2007). Quo Vadis TAM. Journal of Association of Information Systems, 8, 211-218. https://doi.org/10.17705/1jais.00126
[11]
Berndt, A. D., Saunders, S. G., & Petzer, D. J. (2010). Readiness for Banking Technologies in Developing Countries. Southern African Business Review, 14, 47-76.
[12]
Calzada, J., & Estruch, A. (2011). Telefonia Moril en Espana: Regulacion y resultados. Cuadernos Economicos de ICE, 81, 39-70. https://doi.org/10.32796/cice.2011.81.6007
[13]
Cansu, T., Burak, C. A., & Abdullah, O. (2022). Understanding User Acceptance of QR Code Mobile Payment Systems in Turkey: An Extended TAM. Technological Forecasting and Social Change, 184, Article ID: 121968.
[14]
Central Bank of Sri Lanka (2020). Launch of the LANKA QR National Initiative. Central Bank of Sri Lanka.
[15]
Central Bank of Sri Lanka (2021). Payments Bulletin 2021 3Q. Central Bank of Sri Lanka.
[16]
Cham, T.-H. et al. (2022). I Am Too Old for This! Barriers Contributing to the Non-Adoption of Mobile Payment. International Journal of Bank, 40, 1017-1050. https://doi.org/10.1108/IJBM-06-2021-0283
[17]
Cheng, T. C., Lam, D., & Yeung, A. (2006). Adoption of Internet Banking: An Empirical Study in Hong Kong. Decision Support System, 42, 1558-1572. https://doi.org/10.1016/j.dss.2006.01.002
[18]
Chin, A. G., Harris, M., & Brookshive, R. (2020). An Empirical Investigation of Intent to Adopt Mobile Payment Systems Using a Trust-Based Extended Valence Framework. Information Systems Frontiers, 24, 329-347. https://doi.org/10.1007/s10796-020-10080-x
[19]
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35, 982-1002. https://doi.org/10.1287/mnsc.35.8.982
[20]
Denso Wave (2022, April 23). https://www.denso-wave.com/en/technology/vol1.html
[21]
Deshveejit, K. (2022, July 19). Tech Wire Asia. https://techwireasia.com/2022/07/five-southeast-asian-nations-to-link-their-qr-code-payment-systems-heres-what-it-means-for-travelers/
[22]
Digital (2022, April 16). Digital 2022. https://datareportal.com/reports/digital-2022-sri-lanka
[23]
Do, N. H., Tham, J., Azam, S. F., & Khatibi, A. A. (2020). The Effects of Factors Influencing on User Behaviour Intention to Use Mobile Payment; Evidence from Cambodia. International Journal of Data and Network Science, 4, 213-224. https://doi.org/10.5267/j.ijdns.2019.12.004
[24]
Dwivedi, Y., Rana, N. P., Janssen, M., Lal, B., Williams, M., & Clement, M. (2017). An Empirical Validation of a Unified Model of Electronic Government Adoption (UMEGA). Government Information Quarterly, 34, 211-230. https://doi.org/10.1016/j.giq.2017.03.001
[25]
Giovanis, A., Binioriys, S., & Polychronopoulos, G. (2012). An Extension of TAM Model with IDT and Security/Privacy Risk in the Adoption of Internet Banking Services in Greece. EuroMed Journal of Business, 7, 24-53. https://doi.org/10.1108/14502191211225365
[26]
Handri, M. N., & Winny, A. (2021). The Effect of Perceived Cost, Trust, Usefulness and Customer Value Addition on Intention to Use of Go-Pay Mobile Payment Services in Small Merchants. Journal of Business and Management Review, 2, 715-732. https://doi.org/10.47153/jbmr210.2392021
[27]
Haritha, P. H. (2022). Mobile Payment Service Adoption: Understanding Customers for an Application of Emerging Financial Technology. Information and Computer Security. (Ahead-of-Print)
[28]
Hasan, K., & Ahmet, K. K. (2022). The Effect of Trust on Mobile Banking Usage: The Mediating Roles of Perceived Usefulness and Perceived Ease of Use. Econviews—Review of Contemporary Business, Entrepreneurship and Economic Issues, 35, 231-246. https://doi.org/10.51680/ev.35.2.1
[29]
Hawazen, A. (2022). Examining Retailing Sustainability in the QR Code-Enabled Mobile Payments Context during the COVID-19 Pandemic. International Journal of Customer Relationship Marketing Management, 13, 1-22.
[30]
Hwang, R., Shiau, S., & Jan, D. (2007). A New Mobile Payment Scheme for Roaming Services. Electronic Commerce Research and Applications, 6, 184-191. https://doi.org/10.1016/j.elerap.2006.07.002
[31]
ITU (International Telecommunication Union) (2020, May 21). https://www.itu.int/en/Pages/default.aspx
[32]
Kim, G. S., Park, S. B., & Oh, J. (2008). An Examination of Factors Influencing Consumer Adoption of Short Message Service (SMS). Psychology and Marketing, 25, 769-786. https://doi.org/10.1002/mar.20238
[33]
Li, H., Sarathy, R., & Hu, H. (2011). The Role of Affect and Cognition on Online Consumers’ Decision to Disclose Personal Information to Unfamiliar Online Vendors. Decision Support System, 51, 434-445. https://doi.org/10.1016/j.dss.2011.01.017
[34]
Liébana-Cabanillas, F. L.-R. (2017). Predictive and Explanatory Modelling Regarding Adoption of Mobile Payment Systems. Technological Forecasting and Social Change, 120, 32-40. https://doi.org/10.1016/j.techfore.2017.04.002
[35]
Liébana-Cabanillas, F., Marinkovic, V., Luna, I., & Kalinic, Z. (2018). Predicting the Determinants of Mobile Payment Acceptance: A Hybrid SEM-Neural Network Approach. Technical Forecasting & Social Change, 129, 117-130. https://doi.org/10.1016/j.techfore.2017.12.015
[36]
Senali, M. G., Cripps, H., & Ryann, M. (2021). A Comparison of Australian’s Chinese and Sri Lankan’s Payment Performance at Point of Sale. Marketing Intelligence and Planning, 40, 18-32. https://doi.org/10.1108/MIP-07-2021-0235
[37]
Magotra, I., Sharma, J., & Sharma, S. K. (2019). Adoption of Self Service Technologies among Banking Customers. International Journal of Applied Management and Technology, 18, 67-72. https://doi.org/10.5590/IJAMT.2019.18.1.05
[38]
Mahabub, B., Kethan, M., & Rajasulochana, A. (2022). An Empirical Study on the Factors Influencing Usage of Mobile Payments with Reference to Bangalore City. Journal of Corporate Finance Management and Banking System, 3, 23-34. https://doi.org/10.55529/jcfmbs.31.
[39]
Martins, C., Tiago, O., & 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, 1-13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
[40]
Masamila, B., Mtenzi, J., & Said: Tinabo, R. (2010). A Secured Mobile Payment Model for Developing Markets. Communications in Computer and Information Science, 87, 175-182. https://doi.org/10.1007/978-3-642-14292-5_20
[41]
Md. Abu, S. P., Md, S. T., & Yukun, B. (2022). Positive and Negative Valences, Personal Innovativeness and Intention to Use Facial Recognition for Payments. Industrial Management and Data Systems, 122, 1081-1107. https://doi.org/10.1108/IMDS-04-2021-0230
[42]
Moore, G., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting and Information Technology Innovation. Information Systems Research, 2, 192-222. https://doi.org/10.1287/isre.2.3.192
[43]
Moser, F. (2015). Mobile Banking a Fashionable Concept or an Institutionalized Channel in Future Retail Banking? Analyzing Patterns in the Practical and Academic Mobile Literature. International Journal of Marketing, 33, 162-177. https://doi.org/10.1108/IJBM-08-2013-0082
[44]
Murali, S., & Mallikarjuna, V. (2014). Consumer Adoption of Net Banking in Tier-111, Cities of Andhra Pradesh. An Empirical Study. International Journal of Scientific Research, 3, 269-272. https://doi.org/10.15373/22778179/APR2014/94
[45]
Mutaz, M. A.-D., Abdeljaber, O., Yajid, M. S., Ali, K., Sultan, A. M., & Tham, J. (2021). The Role of Service Quality and Online Trust in Maintaining Clients for Malaysian Online Enterprises. International Journal of eBusiness and eGovernment Studies, 13, 149-167.
[46]
Nasri, W., & Charfeddine, L. (2012). An Exploration of Facebook.com Adoption in Tunisia Using Technology Acceptance Model (TAM) and Theory of Reasoned Action (TRA) Interdisciplinary. Journal of Contemporary Research in Business, 4, 948-968.
[47]
Nitin, U., Shalini, U., Abed, S. S., & Yogesh, K. D. (2021). Consumer Consumption of Mobile Payment Services during, COVID-19, Extending Meta-UTAUT with Perceived Severity and Self-Efficacy. International Journal of Bank Management, 40, 960-991. https://doi.org/10.1108/IJBM-06-2021-0262
[48]
Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile Payment: Understanding the Determinants of Customer Adoption and Intention to Recommend the Technology. Computers in Human Behaviour, 61, 404-414. https://doi.org/10.1016/j.chb.2016.03.030
[49]
Parasuraman, A. (2000). Technology Readiness Index (TRI): A Multi-Item Scale to Measure Readiness to Embrace New Technologies. Journal of Science Research, 2, 307-320. https://doi.org/10.1177/109467050024001
[50]
Patria, L., Suharyanto, S., & Yohanes, F. C. (2022). Determining Factors of Continuance Intention in Mobile Payment: Fintech Industry Perspective. Asia Pacific Journal of Marketing and Logistics. (Ahead-of-Print)
[51]
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnilala, S. (2004). Consumer Acceptance of Online Banking: An Extension of Technology Acceptance Model. Internet Research, 14, 224-235. https://doi.org/10.1108/10662240410542652
[52]
Podder, B. (2005). Factors Influencing the Adoption and Usage of Internet Banking: A New Zealand Perspective (pp. 1-53). Master’s Thesis, Auckland University of Technology.
[53]
Ram, S. (1989). Successful Innovation Using Strategies to Reduce Consumer Resistance. Journal of Product Innovation Management, 6, 20-34. https://doi.org/10.1111/1540-5885.610020
[54]
Ram, S., & Jagdish, N. S. (1989). Consumer Resistance to Innovation: The Marketing Problem and Its Solutions. Journal of Consumer Marketing, 6, 5-14. https://doi.org/10.1108/EUM0000000002542
[55]
Rana, N., Dwivedi, Y., Williams, M., & Weerakkody, V. (2014). Investigating Success of an e-Government Initiative: Validation of an Integrated IS Success Model. Information Systems Frontier, 17, 127-142. https://doi.org/10.1007/s10796-014-9504-7
[56]
Raychaudhuri, A. (2017). Demonetization in India; Some Unsolved Economic Puzzles. Trade and Development Review, 9, 74-85.
[57]
Rogers, E. (2003). Diffusion of Innovations (5th ed.). Free Press.
[58]
Rogers, E. M. (1995). Diffusion of Innovation (4th ed.). Free Press.
[59]
Rogers, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behaviour. Addison Wesley.
[60]
Sekaran, U., & Bougie, R. (2010). Research Methods for Business—A Skill Building Approach. In U. Sekaran, & R. Bougie (Eds.), Research Methods for Business—A Skill Building Approach (pp. 69-80). Wiley.
[61]
Shella, A., Kusumo, B., Regina, D. O., & Achmod, R. S. (2022). Determining Factors of Continuance Intention to Use QR Code Mobile Payment on Urban Millennials in Indonesia Empirical Study on Mobile Payment Funds. ADI Journal on Recent Innovation, 3, 121-138.
[62]
Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining Factors in the Adoption and Recommendation of Mobile Wallet Services in India: Analysis of the Effect of Innovativeness, Stress to Use and Social Influence. International Journal of Information Management, 50, 191-205. https://doi.org/10.1016/j.ijinfomgt.2019.05.022
[63]
Singha, C., Bilal, K., & Wornchanok, C. (2021). Digital Payment System Innovations: A Marketing Perspective on Intention and Actual Use in the Retail Sector. Innovative Marketing, 17, 109-123. https://doi.org/10.21511/im.17(3).2021.09
[64]
Srijan, L. (2022). Contactless Payments in the Era of Covid-19; Behavioural Intentions to Use QR Code Payments in Bagmati State.
[65]
Sundaravej, T. (2009). Empirical Validation of Unified Theory of Acceptance and Use of Technology, Model (pp. 100-125). Ph.D. Thesis, University of Missouri.
[66]
Timaz, H., & Viet, P. D. (2022). User Perceptions of WeChat and WeChat Pay in China. Global Knowledge, Memory and Communication. (Ahead-of-Print) https://doi.org/10.1108/GKMC-12-2021-0195
[67]
Venkatesh, M. M., & Gordon, D. (2013). User Acceptance of Information Technology (pp. 425-478). Management Information Systems Research Centre, University of Minisorta.
[68]
Venkatesh, V. et al. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36, 157-178. https://doi.org/10.2307/41410412
[69]
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27, 425-478. https://doi.org/10.2307/30036540
[70]
Walczuch, R., Lemmink, J., & Streukens, S. (2007). The Effect of Service Employees’ Technology Readiness on Technology Acceptance. Information and Management, 44, 206-215. https://doi.org/10.1016/j.im.2006.12.005
[71]
Wei, M.-F. et al. (2021). Young Generation’s Mobile Payment Adoption Behavior; Analysis Based on an Extended UTAUT Model. Journal of Business and Management Review, 16, 618-637. https://doi.org/10.3390/jtaer16040037
[72]
Xuan, C. L. (2021). The Diffusion of Mobile QR-Code Payment, an Empirical Evaluation for a Pandemic. Asia Pacific Journal of Business Administration, 14, 617-636.
[73]
Yong, C., Tham, J., Azam, S. F., & Khatibi, A. (2021a). The Acceptance of Mobile Payment and Sustainable Usage Intention in Malaysia; an Analysis Based on Unified Theory of Acceptance and Use of Technology (UTAUT). European Journal of Economic and Financial Research, 5, 69-84. https://doi.org/10.46827/ejefr.v5i3.1191
[74]
Yong, C., Tham, J., Azam, S. M. F., & Khatibi, A. (2021b). An Empirical Study on Acceptance of Mobile Payment and Its Competitive Advantage in Malaysia. European Journal of Social Science Studies, 7, 175-202. https://doi.org/10.46827/ejsss.v7i1.1190
[75]
Yong, C., Tham, J., Azam, S., & Khatibi, A. (2021c). The Factors Influencing College Students Acceptance of Mobile Payments in Malaysia. European Journal of Management and Marketing Studies, 7, 92-109. https://doi.org/10.46827/ejmms.v7i1.1192
[76]
Wu, Z. D., & Liu, Y. X. (2022). Exploring Country Differences in the Adoption of Mobile Payment Service: The Surprising Robustness of the UTAUT2 Model. International Journal of Bank Management, 41, 237-268. https://doi.org/10.1108/IJBM-02-2022-0052
