A Study on Behavioral Intention and Use Behavior Toward Mobile Payment Among University Students in Nanning, China
DOI:
https://doi.org/10.14456/au-ejir.2025.14Keywords:
Mobile Payments, Perceived Usefulness Behavioral Intention, Use Behavior, Higher EducationAbstract
Purpose: The study examines key factors influencing behavioral intention and actual use of mobile payment services among university students in Nanning, China. The proposed framework explores the relationships among Social Influence (SI), Effort Expectancy (EE), Trust (TS), Perceived Usefulness (PU), Perceived Risk (PR), Habit (HB), Behavioral Intention (BI), and Use Behavior (UB). Research design, data and methodology: The researcher conducted a questionnaire survey among 500 university students in Nanning, China. Participants were purposefully selected from four main colleges of Guangxi University, following stratified random sampling guidelines. Data were collected online using a convenience sampling approach. For analysis, CFA and SEM were applied to evaluate model fit, reliability, and structural validity. Results: The findings indicate that social influence, effort expectancy, trust, perceived usefulness, perceived risk, and habit significantly affect behavioral intention. Behavioral intention, in turn, strongly influences use behavior. Among these factors, perceived usefulness had the greatest impact on behavioral intention, followed by trust and social influence. Conclusions: The statistical results supported all seven research hypotheses, confirming that the study successfully met its objectives. To enhance mobile payment adoption, policymakers and service providers should prioritize key influencing factors and implement effective optimization strategies.
References
Aarts, H., & Dijksterhuis, A. (2001). The automatic activation of goal-directed behavior: The case of travel habit. Journal of Environmental Psychology, 20(1), 75-82. https://doi.org/10.1006/jevp.1999.0156
Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28-44.
https://doi.org/10.1016/j.ijinfomgt.2019.11.002
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.
https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Alyabes, A. F., & Alsalloum, O. (2018). Factors affecting consumers’ perception of electronic payment in Saudi Arabia. European Journal of Business and Management, 10(27), 36-45.
Anggraini, E. L., & Rachmawati, I. (2019). Analysis of factors influencing the adoption of mobile payment using the UTAUT2 model: A case study of OVO in Indonesia. International Journal of Scientific Research and Engineering Development, 2(3), 168-175.
Baishya, K., & Samalia, H. V. (2019). Extending the unified theory of acceptance and use of technology with perceived monetary value for smartphone adoption at the bottom of the pyramid. International Journal of Information Management, 51, 102036. https://doi.org/10.1016/j.ijinfomgt.2019.11.004
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.
https://doi.org/10.1016/j.chb.2015.04.024
Baptista, G., & Oliveira, T. (2016). A weight and a meta-analysis on mobile banking acceptance research. Computers in Human Behavior, 63, 480-489. https://doi.org/10.1016/j.chb.2016.05.074
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246.
https://doi.org/10.1037/0033-2909.107.2.238
Chauhan, S. (2015). Acceptance of mobile money by poor citizens of India: Integrating trust into the technology acceptance model. Info, 17(3), 58-68. https://doi.org/10.1108/info-02-2015-0018
Chawla, D., & Joshi, H. (2019). Consumer attitude and intention to adopt mobile wallet in India: An empirical study. International Journal of Bank Marketing, 37(7), 1590-1618. https://doi.org/10.1108/ijbm-09-2018-0256
Chen, L. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), 32-52. https://doi.org/10.1504/ijmc.2008.015997
Chen, X. M., & Wang, L. (2021). Exploring the linkage between mobile payment habits and customer loyalty. Marketing Letters, 32(3), 345-358.
Chen, Y., Dai, R., Yao, J., & Li, Y. (2019). Donate time or money? The determinants of donation intention in online crowdfunding. Sustainability, 11(16), 4269. https://doi.org/10.3390/su11164269
Choi, J. H. (2018). Determinants of continuous intention to use over extended use of smartphone apps. Telematics and Informatics, 35(5), 1133-1144. https://doi.org/10.1016/j.tele.2018.01.006
Choi, S., Kim, H., Chung, M., & Lee, S. Y. (2018). Online donation experiences, donation awareness, and intention of future donation among teenagers in South Korea. Journal of Social Service Research, 45(5), 622-633. https://doi.org/10.1080/01488376.2018.1487363
Chopdar, P. K., & Sivakumar, V. J. (2018). Understanding continuance usage of mobile shopping applications in India: The role of espoused cultural values and perceived risk. Behaviour & Information Technology, 38(1), 42-64.
https://doi.org/10.1080/0144929x.2018.1513563
Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14(5), 265-284. https://doi.org/10.1016/j.elerap.2015.07.006
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Doctoral dissertation]. MIT Sloan School of Management, Cambridge, MA.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
Deng, Z., & Lu, Y. (2017). An empirical analysis of user acceptance of mobile payment in China. International Journal of Mobile Communications, 15(3), 233-252.
Esawe, A. T. (2022). Understanding mobile e-wallet consumers’ intentions and user behavior. Spanish Journal of Marketing - ESIC, 26(3), 363-384. https://doi.org/10.1108/sjme-05-2022-0105
Falk, T., Kunz, W. H., Schepers, J. J. L., & Mrozek, A. J. (2016). How mobile payment influences the overall store price image. Journal of Business Research, 69(7), 2417-2423. https://doi.org/10.1016/j.jbusres.2016.01.011
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, 19(3), 525-548. https://doi.org/10.1007/s10796-015-9611-0
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90. https://doi.org/10.2307/30036519
Glick, W. H. (1985). Conceptualizing and measuring organizational and psychological climate: Pitfalls in multilevel research. The Academy of Management Review, 10(3), 601. https://doi.org/10.2307/258140
Gupta, K., & Arora, N. (2019). Investigating consumer intention to accept mobile payment systems through unified theory of acceptance model. South Asian Journal of Business Studies, 9(1), 88-114. https://doi.org/10.1108/sajbs-03-2019-0037
Ha, H. (2020). The cashless economy in Vietnam - The situation and policy implications. Journal of Reviews on Global Economics, 9, 216-223. https://doi.org/10.6000/1929-7092.2020.09.20
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Pearson Prentice Hall.
Haritha, P. H. (2022). Mobile payment service adoption: Understanding customers for an application of emerging financial technology. Information & Computer Security, 31(2), 145-171. https://doi.org/10.1108/ics-04-2022-0058
Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Lin, B. (2016). Mobile social commerce: The booster for brand loyalty? Computers in Human Behavior, 59, 142-154. https://doi.org/10.1016/j.chb.2016.01.027
Hossain, R., & Mahmud, I. (2016). Influence of cognitive style on mobile payment system adoption: An extended technology acceptance model. International Conference on Computer Communication and Informatics (ICCCI), 1-6.
https://doi.org/10.1109/iccci.2016.7479973
Hsu, M.-H., & Chiu, C.-M. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38(3), 369-381. https://doi.org/10.1016/j.dss.2003.08.001
Istijanto, A., & Handoko, Y. I. (2022). Customers’ continuance usage of mobile payment during the COVID-19 pandemic. Spanish Journal of Marketing - ESIC, 26(3), 345-362. https://doi.org/10.1108/SJME-02-2022-0016
Karjaluoto, H., Shaikh, A. A., Leppäniemi, M., & Luomala, R. (2019). Examining consumers’ usage intention of contactless payment systems. International Journal of Bank Marketing, 38(2), 332-351. https://doi.org/10.1108/ijbm-04-2019-0155
Kasri, R. A., & Yuniar, A. M. (2021). Determinants of digital zakat payments: Lessons from Indonesian experience. Journal of Islamic Accounting and Business Research, 12(3), 362-379. https://doi.org/10.1108/jiabr-08-2020-0258
Khalilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC-based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460-474. https://doi.org/10.1016/j.chb.2017.01.001
Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322. https://doi.org/10.1016/j.chb.2009.10.013
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544-564. https://doi.org/10.1016/j.dss.2007.07.001
Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: Predicting mobile payment adoption. The Service Industries Journal, 35(10), 537-554. https://doi.org/10.1080/02642069.2015.1043278
Kumari, N., & Biswas, A. (2023). Does M-payment service quality and perceived value co-creation participation magnify M-payment continuance usage intention? Moderation of usefulness and severity. International Journal of Bank Marketing, 41(6), 1330-1359. https://doi.org/10.1108/ijbm-11-2022-0500
Lee, M. C. (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, 8(3), 130-141. https://doi.org/10.1016/j.elerap.2008.11.006
Li, H., Sarathy, R., & Xu, H. (2011). The role of affect and cognition on online consumers’ decision to disclose personal information to unfamiliar online vendors. Decision Support Systems, 51(3), 434-445. https://doi.org/10.1016/j.dss.2011.01.017
Li, Y. N., & Zhang, H. (2020). Cognitive and affective factors in the formation of mobile payment habits and their impact on behavioral intentions. Journal of Consumer Behaviour, 19(6), 590-603.
Li, Y.-Z., He, T. L., Song, Y. R., Yang, Z., & Zhou, R.-T. (2017). Factors impacting donors’ intention to donate to charitable crowdfunding projects in China: A UTAUT-based model. Information, Communication & Society, 21(3), 404-415. https://doi.org/10.1080/1369118x.2017.1282530
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705. https://doi.org/10.2307/25148817
Lin, W. R., Lin, C. Y., & Ding, Y. H. (2020). Factors affecting the behavioral intention to adopt mobile payment: An empirical study in Taiwan. Mathematics, 8(10), 1851. https://doi.org/10.3390/math8101851
Liu, L., & Zhang, J. (2022). Understanding mobile payment adoption: An empirical study in China. Journal of Electronic Commerce Research, 19(4), 1-18.
Lu, Y., Yang, S., Chau, P. Y. K., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48(8), 393-403. https://doi.org/10.1016/j.im.2011.09.006
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. https://doi.org/10.1016/j.chb.2004.03.003
Makanyeza, C., & Mutambayashata, S. (2018). Consumers’ acceptance and use of plastic money in Harare, Zimbabwe. International Journal of Bank Marketing, 36(2), 379-392. https://doi.org/10.1108/ijbm-03-2017-0044
Mukherjee, M., & Roy, S. (2017). E-commerce and online payment in the modern era. International Journal of Advanced Research in Computer Science and Software Engineering, 7(5), 1-5. https://doi.org/10.23956/ijarcsse/sv7i5/0250
Mulia, D. (2019). The differences in risk perception between millennials and baby boomers in online transactions. Jurnal Manajemen, 23(3), 375. https://doi.org/10.24912/jm.v23i3.570
Musyaffi, A. M., Sari, D. A. P., & Respati, D. K. (2021). Understanding digital payment usage during the COVID-19 pandemic: A study of the UTAUT extension model in Indonesia. The Journal of Asian Finance, Economics and Business, 8(6), 475-482.
https://doi.org/10.13106/jafeb.2021.vol8.no6.0475
Negm, E. M. (2023). Consumers’ acceptance intentions regarding e-payments: A focus on the extended unified theory of acceptance and use of technology (UTAUT2). Management & Sustainability: An Arab Review. https://doi.org/10.1108/msar-04-2023-0022
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 Behavior, 61, 404-414.
https://doi.org/10.1016/j.chb.2016.03.030
Pal, A., Herath, T., De, R., & Rao, H. R. (2021). Why do people use mobile payment technologies and why would they continue? An examination and implications from India. Research Policy, 50(6), 104228.
https://doi.org/10.1016/j.respol.2021.104228
Palash, A. S., Talukder, S., Islam, A. K. M. N., & Bao, Y. (2022). Positive and negative valences, personal innovativeness, and intention to use facial recognition for payments. Industrial Management & Data Systems, 122(4), 1081-1108.
https://doi.org/10.1108/imds-04-2021-0230
Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly, 30(1), 115-143. https://doi.org/10.2307/25148720
Pedroso, R., Zanetello, L., Guimarães, L., Pettenon, M., Gonçalves, V., Scherer, J., Kessler, F., & Pechansky, F. (2016). Confirmatory factor analysis (CFA) of the Crack Use Relapse Scale (CURS). Archives of Clinical Psychiatry (São Paulo), 43(3), 37-40. https://doi.org/10.1590/0101-60830000000081
Pham, T. T. T., & Ho, J. C. (2015). The effects of product-related, personal-related factors, and attractiveness of alternatives on consumer adoption of NFC-based mobile payments. Technology in Society, 43, 159-172. https://doi.org/10.1016/j.techsoc.2015.05.004
Phonthanukitithaworn, C., Sellitto, C., & Fong, M. W. L. (2016). An investigation of mobile payment (m‐payment) services in Thailand. Asia-Pacific Journal of Business Administration, 8(1), 37-54. https://doi.org/10.1108/apjba-10-2014-0119
Qasim, H., & Abu-Shanab, E. (2015). Drivers of mobile payment acceptance: The impact of network externalities. Information Systems Frontiers, 18(5), 1021-1034. https://doi.org/10.1007/s10796-015-9598-6
Rastogi, S., Panse, C., Sharma, A., & Bhimavarapu, V. M. (2021). Unified payment interface (UPI): A digital innovation and its impact on financial inclusion and economic development. Universal Journal of Accounting and Finance, 9(3), 518-530. https://doi.org/10.13189/ujaf.2021.090326
Rovinelli, R. J., & Hambleton, R. K. (1976). On the use of content specialists in the assessment of criterion-referenced test item validity. Dutch Journal of Educational Research, 2(1), 49-60.
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209-216. https://doi.org/10.1016/j.elerap.2009.07.005
Sekaran, U. (1992). Research methods for business: A skill-building approach. John Wiley & Sons.
Shah, J., & Khanna, M. (2023). Determining the post-adoptive intention of millennials for MOOCs: An information systems perspective. Information Discovery and Delivery, 52(2), 243-260. https://doi.org/10.1108/idd-11-2022-0109
Sharma, G. P., Verma, R. C., & Pathare, P. (2005). Mathematical modeling of infrared radiation thin layer drying of onion slices. Journal of Food Engineering, 71(3), 282-286. https://doi.org/10.1016/j.jfoodeng.2005.02.010
Shi, S., & Chow, W. S. (2015). Trust development and transfer in social commerce: Prior experience as a moderator. Industrial Management & Data Systems, 115(7), 1182-1203. https://doi.org/10.1108/imds-01-2015-0019
Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354. https://doi.org/10.1016/j.chb.2009.06.001
Shin, S., & Lee, W. J. (2014). The effect of technology readiness and technology acceptance on NFC MPS in Korea. Journal of Applied Business Research (JABR), 30(6), 1615-1625. https://doi.org/10.19030/jabr.v30i6.8873
Shin, S., & Lee, W. J. (2021). Factors affecting user acceptance for NFC mobile wallets in the U.S. and Korea. Innovation & Management Review, 18(4), 417-433. https://doi.org/10.1108/inmr-02-2020-0018
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M. A. Lange (Ed.), Leading-edge psychological tests and testing research (pp. 27-50).
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
Sinha, M., Majra, H., Hutchins, J., & Saxena, R. (2019). Mobile payments in India: The privacy factor. International Journal of Bank Marketing, 37(1), 192-209. https://doi.org/10.1108/ijbm-05-2017-0099
Sinha, N., & Singh, N. (2022). Moderating and mediating effect of perceived experience on merchants’ behavioral intention to use mobile payments services. Journal of Financial Services Marketing, 28, 448-465. https://doi.org/10.1057/s41264-022-00163-y
Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209-223.
https://doi.org/10.1080/0965254x.2014.914075
Smith, J., & Chen, H. (2015). Understanding mobile payment use behavior: A study of Chinese consumers. Journal of Electronic Commerce Research, 16(2), 145-162.
Sobti, N. (2019). Impact of demonetization on diffusion of mobile payment service in India. Journal of Advances in Management Research, 16(4), 472-497. https://doi.org/10.1108/jamr-09-2018-0086
Tan, G. W.-H., Ooi, K.-B., Chong, S.-C., & Hew, T.-S. (2014). NFC mobile credit card: The next frontier of mobile payment? Telematics and Informatics, 31(2), 292-307. https://doi.org/10.1016/j.tele.2013.06.002
Thakur, R. (2013). Customer adoption of mobile payment services by professionals across two cities in India: An empirical study using modified technology acceptance model. Business Perspectives and Research, 1(2), 17-30.
https://doi.org/10.1177/2278533720130203
Tossy, T. (2014). Modelling the adoption of mobile payment system for primary and secondary school student examination fees in developing countries: Tanzanian experiences. International Journal of Information Technology and Business Management, 27(1), 1-12.
Tran, H. T. T., & Corner, J. (2016). The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing, 34(1), 78-109. https://doi.org/10.1108/ijbm-06-2014-0073
Upadhyay, N., Upadhyay, S., Abed, S. S., & Dwivedi, Y. K. (2022). Consumer adoption of mobile payment services during COVID-19: Extending meta-UTAUT with perceived severity and self-efficacy. International Journal of Bank Marketing, 40(5). https://doi.org/10.1108/ijbm-06-2021-0262
Upadhyay, N., Upadhyay, S., & Dwivedi, Y. K. (2021). Theorizing artificial intelligence acceptance and digital entrepreneurship model. International Journal of Entrepreneurial Behavior & Research, 28(5). https://doi.org/10.1108/ijebr-01-2021-0052
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. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Wood, W., & Neal, D. T. (2007). A new look at habits and the habit-goal interface. Psychological Review, 114(4), 843-863.
https://doi.org/10.1037/0033-295x.114.4.843
Wu, J.-H., & Wang, Y.-M. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s model. Information & Management, 43(6), 728-739. https://doi.org/10.1016/j.im.2006.05.002
Yang, M., Mamun, A. A., Mohiuddin, M., Nawi, N. C., & Zainol, N. R. (2021). Cashless transactions: A study on intention and adoption of e-wallets. Sustainability, 13(2), 831. https://doi.org/10.3390/su13020831
Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129-142.
https://doi.org/10.1016/j.chb.2011.08.019
Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13, 104-121.
Zhao, Y., & Bacao, F. (2021). How does the pandemic facilitate mobile payment? An investigation on users’ perspective under the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 18(3), 1-22.
https://doi.org/10.3390/ijerph18031016
Zhou, T. (2014). Understanding the determinants of mobile payment continuance usage. Industrial Management & Data Systems, 114(6), 936-948. https://doi.org/10.1108/imds-02-2014-0068
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767. https://doi.org/10.1016/j.chb.2010.01.013
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Zehua Tang
This work is licensed under a Creative Commons Attribution 4.0 International License.
A separate Copyright Form will be sent to authors whose paper is accepted for publication.
