THE ADOPTION OF DIGITAL CURRENCY ELECTRONIC PAYMENT IN CHINA
Keywords:
Theory of Acceptance Model, central bank digital currency, , digital currency electronic payment, Fin-Tech, ChinaAbstract
The misuse of unregulated digital currency with the absence of regulation is recognized by the central banks worldwide. In response to this, the Central Bank Digital Currency (or CBDC), a regulated digital currency was developed which have many advantages over unregulated digital currency. In China, the Digital Currency Electronic Payment (DC/EP or “digital yuan”) was introduced in 2014 with the aim to improve its monetary and financial supervision. To date, the development of the effectiveness and acceptance level of DC/EP among the people of the Republic of China is still at the infant stage after it underwent its first trial in 2019. Using mixed method design, this study aims to develop the conceptual framework based on combination of two underpinning theories namely Theory of Reasoned Action (TRA) and Theory of Acceptance Model (TAM). The outcomes of this research provide a theoretical basis for future research on the implementation of Digital Currency Electronic Payment.
References
Abdulwahab, A. (2019). Gender effect on cloud computing services adoption by university students: Case study of Saudi Arabia. International Journal of Innovation, 7, 155-177. DOI: 10.5585/iji.v7i1.351.
Ajzen, I., & Fishbein, M. (1980). The theory of planned behavior. Organizational Behavior and Human Decision Processes,50 (2), 179–211. ISSN 0749-5978. DOI: 10.1016/0749-5978(91)90020-T.
Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior Englewood Cliffs, NJ: Prentice-Hall.
Baker, E. (2006). Enabling laptop exams using secure software: Applying the Technology Acceptance Model. Journal of Information Systems Education, 17 (4), 413–420.
Bhattacherjee, A. (2002). Acceptance of e-commerce services: The case of electronic brokerages. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans. 30 (4), 411-420.
Carolin, P. (2012). Technology adoption and performance impact in innovation domains. Industrial Management & Data Systems, 112, 748-765. DOI: 10.1108/02635571211232316.
Coinbase. (2020). 2020 in review. Retrieved from https://www.coinbase.com/prime/2020-in-review on 4 April 2021.
Compeau, D. R. & Higgins, C. A. (1995). Computer Self-Efficacy: Development of a Measure and Initial Test. MIS Quarterly, 19 (2), 189–211.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–342.
Donna, L. H. (1999). Building consumer trust online. 42 (4), 80–85. DOI: https://doi.org/10.1145/299157.299175.
Dzandu, M. (2016). Social media adoption among university students: the role of gender, perceived usefulness and perceived ease of use. Int. J. of Social Media and Interactive Learning Environment, 4,124-136.
Flavián, C. (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty, 1–14.
Folkinshteyn, D. & Lennon, M. (2017). Braving Bitcoin: A technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 184, 220-249. DOI: 10.1080/15228053.2016.1275242.
Ham, M. (2015). The role of subjective norms in forming the intention to purchase green food. Economic Research-Ekonomska Istraživanja, 28(1), 738-748, DOI: 10.1080/1331677X.2015.1083875.
Hashim, A.S. (2017). A study on acceptance of mobile school at secondary school in Malaysia: Urban vs rural. AIP Publishing. DOI: heep://doi.org/10.1063/1.5005383.
Internet Organized Crime Threat Assessment. (2015). Retrieved from https://www.europol.europa.eu/activities-services/main-reports/internet-organised-crime-threat-assessment-iocta-2015 on 4 April 2021.
James, T. A. (2021). China Creates Its Own Digital Currency, a First for Major Economy. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/china-creates-its-own-digital-currency-a-first-for-major-economy-11617634118 on 30 April 2021.
Jarvenpaa, S. (2000). Consumer trust in an Internet Store. International Journal of Information Technology and Management. DOI: 1. 10.1023/A:1019104520776.
John, S. P. (2013). Influence of computer self-efficacy on information technology adoption. International Journal of Information Technology, 19 (1).
Koksal, Y., & Penez, S. (2015). An investigation of the important factors influences web trust in online shopping. Journal of Marketing & Management, 6 (1), 28-40.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13, 205-223. DOI: 10.1287/isre.13.2.205.83.
Lindblom, K. (2011). The impact of computer self-efficacy, computer anxiety, and perceived usability and acceptability on the efficacy of a decision support tool for colorectal cancer screening. J Am Med Inform Assoc, 19, 407-412. DOI:10.1136/amiajnl-2011-000225.
Mayer, R. C. (1995). An integrative model of organizational trust. Academy of Management Review, 20 (3), 709-734. DOI:10.2307/258792.
Mira, K. (2013). A Conceptual Framework for Assessing Electronic Banking Continued Use. 8th International Conference on Information Technology in Asia (CITA). DOI: 10.1109/CITA.2013.6637550.
Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58 (3), 20–38. DOI: https://doi.org/10.2307/125230.
Mukherjee, A. & Nath, P. (2007). Role of electronic trust in online retailing. A re-examination of the commitment-trust theory. European Journal of Marketing, 41 (9), 1173-1202. DOI 10.1108/03090560710773390.
Nadeem, M. A. (2021). Investigating the Adoption Factors of Cryptocurrencies—A Case of Bitcoin: Empirical Evidence from China. Sage Journals, 11 (1). DOI: http://doi.org/10.1177/2158244021998704.
Naderifar, M. (2017). Snowball Sampling: A Purposeful Method of Sampling in Qualitative Research. Strides in Development of Medical Education. In Press. 10.5812/sdme.67670.
Ndubisi, N. (2006). Factors of online learning adoption: A comparative juxtaposition of the theory of planned behaviour and the Technology Acceptance Model. International Journal on E-Learning, 5 (4), 571–591.
Ngabiyanto, N. A. (2021). Teacher's intention to use online learning; an extended Technology Acceptance Model (TAM) investigation. Journal of Physics: Conference Series. DOI: 10.1088/1742-6596/1783/1/012123.
Nguyen, T. T. H. (2019). Investigating Consumer Attitude and Intention towards Online Food Purchasing in an Emerging Economy: An Extended TAM Approach. Foods, 8 (576). DOI: 10.3390/foods811057.
Norman, G. (2010). Likert scales, levels of measurement and the "laws” of statistics. Advances in Health Science Education, 15(5), 625–632.
Osama, I. (2016). Perceived usefulness, perceived ease of use, perceived compatibility, and net benefits: An empirical study of internet usage among employees in Yemen, 899-919.
Rehman, S. (2019). The moderating role of trust and commitment between consumer purchase intention and online shopping behavior in the context of Pakistan. Journal of Global Entrepreneurship Research. DOI: 9.10.1186/s40497-019-0166-2
Roca, J. C. (2006). Understanding e-learning continuance. intention: An extensiom of the Technology Acceptance Model. International Journal of Human-Computer Studies. Vol 64 (8), 683–696.
Shi, Qing & Sun, Xiaoqi. (2020). A Scientometric Review of Digital Currency and Electronic Payment Research: A Network Perspective. Complexity, 1-17. DOI: 10.1155/2020/8876017.
Shi, Ye & Zhou, Shucheng. (2020). Central bank digital currencies: Towards a Chinese approach design choices of digital currency electronic payment. Jönköping, UNIVERSITY International Business School.
Teichmann, F.M.J., & Falker, M.C. (2020). Cryptocurrencies and financial crime: Solutions from Liechtenstein. Journal of Money Laundering Contral. DOI: 10.1108/JMLC-05-2020-0060.
Tella, A., & Olasina, G. 2014. Predicting users' continuance intention toward e-payment system: An extension of TAM. International Journal of Information Systems and Social Change, 5 (1), 47-67.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. DOI: 10.1111/J.1540-5915.2008.00192.X.
Venkatesh, V. & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186-204. DOI: 10.1287/mnsc.46.2.186.11926.
Venkatesh, V. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27, 425-478. DOI: 10.2307/30036540.
Venkatesh, V. (2011). Extending the two‐stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Information Systems Journal, 21 (6), 527-555. DOI: https://doi.org/10.1111/j.1365-2575.2011.00373.x.
Weng, Fumei. (2018). A TAM-Based study of the attitude towards use intention of multimedia among school teachers. Appl. Syst. Innov. DOI:10.3390/asi1030036.
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