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Research Article

Navigating Trust in Mobile Payments: Using Necessary Condition Analysis to Identify Must-Have Factors for User Acceptance

ORCID Icon, ORCID Icon & ORCID Icon
Received 09 Jan 2024, Accepted 29 Mar 2024, Published online: 25 Apr 2024

References

  • Abbasi, M. S. (2011). Culture, demography and individuals’ technology acceptance behaviour: A PLS based structural evaluation of an extended model of technology acceptance in South-Asian country context (pp. 397–397). Brunel University.
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
  • 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.2019.04.008
  • Almaiah, M. A., Al-Rahmi, A., Alturise, F., Hassan, L., Lutfi, A., Alrawad, M., Alkhalaf, S., Al-Rahmi, W. M., Al-Sharaieh, S., & Aldhyani, T. H. H. (2022). Investigating the effect of perceived security, perceived trust, and information quality on mobile payment usage through near-field communication (NFC) in Saudi Arabia. Electronics, 11(23), 3926. https://doi.org/10.3390/electronics11233926
  • Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with mobile websites: The impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258–274. https://doi.org/10.1108/NBRI-01-2014-0005
  • Anckar, B., & D'Incau, D. (2002). Value creation in mobile commerce: Findings from a consumer survey. The Journal of Information Technology Theory and Application, 4(1), 43–65.
  • Atinc, G., Simmering, M. J., & Kroll, M. J. (2011). Control variable use and reporting in macro and micro management research. Organizational Research Methods, 15(1), 57–74. https://doi.org/10.1177/1094428110397773
  • Au, Y. A., & Kauffman, R. J. (2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application. Electronic Commerce Research and Applications, 7(2), 141–164. https://doi.org/10.1016/j.elerap.2006.12.004
  • Awa, H. O., Uko, J. P., & Ukoha, O. (2016). An empirical study of some critical adoption factors of ERP software. International Journal of Human–Computer Interaction, 33(8), 609–622. https://doi.org/10.1080/10447318.2016.1265828
  • Belanger, F., Hiller, J. S., & Smith, W. J. (2002). Trustworthiness in electronic commerce: The role of privacy, security, and site attributes. The Journal of Strategic Information Systems, 11(3–4), 245–270. https://doi.org/10.1016/S0963-8687(02)00018-5
  • Braun, M. T. (2013). Obstacles to social networking website use among older adults. Computers in Human Behavior, 29(3), 673–680. https://doi.org/10.1016/j.chb.2012.12.004
  • Buabeng-Andoh, C. (2018). Predicting students’ intention to adopt mobile learning. Journal of Research in Innovative Teaching & Learning, 11(2), 178–191. https://doi.org/10.1108/JRIT-03-2017-0004
  • Cheng, A., Ma, D., Pan, Y., & Qian, H. (2023). Enhancing museum visiting experience: investigating the relationships between augmented reality quality, immersion, and TAM using PLS-SEM. International Journal of Human–Computer Interaction, 1–12. https://doi.org/10.1080/10447318.2023.2227832
  • Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G.A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Lawrence Erlbaum Associates Publishers.
  • Cohen, J. (1988). Statistical power analysis for the behavioral siences (2nd ed.), Lawrence Erlbaum Associates.
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037//0033-2909.112.1.155
  • Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 7(2), 165–181. https://doi.org/10.1016/j.elerap.2007.02.001
  • 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
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
  • Di Pietro, L., Guglielmetti Mugion, R., Mattia, G., Renzi, M. F., & Toni, M. (2015). The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical application to public transport. Transportation Research Part C: Emerging Technologies, 56, 463–479. https://doi.org/10.1016/j.trc.2015.05.001
  • Dul, J. (2015). Necessary condition analysis (NCA). Organizational Research Methods, 19(1), 10–52. https://doi.org/10.1177/1094428115584005
  • Dul, J. (2016). Necessary condition analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10–52. https://doi.org/10.1177/1094428115584005
  • Dul, J. (2020). Conducting Necessary Condition Analysis., Sage.
  • Dul, J., Hauff, S., & Bouncken, R. B. (2023). Necessary condition analysis (NCA): review of research topics and guidelines for good practice. Review of Managerial Science, 17(2), 683–714. https://doi.org/10.1007/s11846-023-00628-x
  • Dul, J., van der Laan, E., & Kuik, R. (2018). A statistical significance test for necessary condition analysis. Organizational Research Methods, 23(2), 385–395. https://doi.org/10.1177/1094428118795272
  • Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2016). A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), 174–187. https://doi.org/10.1016/j.giq.2015.06.003
  • Flatraaker, D. I. (2013). Mobile payments changing the landscape of retail banking: Hype or reality. Journal of Payments Strategy & Systems, 7(2), 150–158.
  • Foroughi, B., Senali, M. G., Iranmanesh, M., Khanfar, A., Ghobakhloo, M., Annamalai, N., & Naghmeh-Abbaspour, B. (2023). Determinants of intention to use ChatGPT for educational purposes: Findings from PLS-SEM and fsQCA. International Journal of Human–Computer Interaction, 1–20. https://doi.org/10.1080/10447318.2023.2226495
  • Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. https://doi.org/10.1016/j.jbusres.2015.12.008
  • Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737. https://doi.org/10.1016/S0305-0483(00)00021-9
  • Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519
  • 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
  • Green, S. B. (1991). How many subjects does it take to do A regression analysis. Multivariate Behavioral Research, 26(3), 499–510. https://doi.org/10.1207/s15327906mbr2603_7
  • Hair, J. F., Hult, T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equations modeling (PLS-SEM). Sage.
  • Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M., Svensson, G., & Svensson, G. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  • Haritha, P. H. (2023). 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
  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R.R. Sinkovics & P.N. Ghauri (Eds.), Advances in international marketing (pp. 277–320). Emerald Group Publishing Limited.
  • Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343–367. https://doi.org/10.1080/15391523.2011.10782576
  • Jain, N. K., Kaushik, K., & Sharma, A. (2022). What drives customers toward proximity payment services? An integrated theory of planned behavior perspective. International Journal of Consumer Studies, 47(3), 1095–1111. https://doi.org/10.1111/ijcs.12890
  • Jamshidi, D., Keshavarz, Y., Kazemi, F., & Mohammadian, M. (2018). Mobile banking behavior and flow experience. International Journal of Social Economics, 45(1), 57–81. https://doi.org/10.1108/IJSE-10-2016-0283
  • Jayarathne, P. G. S. A., Chathuranga, B. T. K., Dewasiri, N. J., & Rana, S. (2022). Motives of mobile payment adoption during COVID-19 pandemic in Sri Lanka: A holistic approach of both customers’ and retailers’ perspectives. South Asian Journal of Marketing, 4(1), 51–73. https://doi.org/10.1108/SAJM-03-2022-0013
  • 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, C., Tao, W., Shin, N., & Kim, K. S. (2010). An empirical study of customers’ perceptions of security and trust in e-payment systems. Electronic Commerce Research and Applications, 9(1), 84–95. https://doi.org/10.1016/j.elerap.2009.04.014
  • Knol, W. H., Slomp, J., Schouteten, R. L. J., & Lauche, K. (2018). Implementing lean practices in manufacturing SMEs: Testing ‘critical success factors’ using Necessary Condition Analysis. International Journal of Production Research, 56(11), 3955–3973. https://doi.org/10.1080/00207543.2017.1419583
  • Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131
  • Leong, C. M., Tan, K. L., Puah, C. H., & Chong, S. M. (2020). Predicting mobile network operators users m-payment intention. European Business Review, 33(1), 104–126. https://doi.org/10.1108/EBR-10-2019-0263
  • Leong, L. Y., Hew, T. S., Tan, G. W. H., & Ooi, K. B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604–5620. https://doi.org/10.1016/j.eswa.2013.04.018
  • Lew, S., Tan, G. W., Loh, X. M., Hew, J. J., & Ooi, K. B. (2020). The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model. Technology in Society, 63, 101430. https://doi.org/10.1016/j.techsoc.2020.101430
  • Li, X., Zhao, X., Xu, W., & Pu, W. (2020). Measuring ease of use of mobile applications in e-commerce retailing from the perspective of consumer online shopping behaviour patterns. Journal of Retailing and Consumer Services, 55, 102093. https://doi.org/10.1016/j.jretconser.2020.102093
  • Liébana-Cabanillas, F., Japutra, A., Molinillo, S., Singh, N., & Sinha, N. (2020). Assessment of mobile technology use in the emerging market: Analyzing intention to use m-payment services in India. Telecommunications Policy, 44(9), 102009. https://doi.org/10.1016/j.telpol.2020.102009
  • Liébana-Cabanillas, F., Molinillo, S., & Japutra, A. (2021). Exploring the Determinants of Intention to Use P2P Mobile Payment in Spain. Information Systems Management, 38(2), 165–180. https://doi.org/10.1080/10580530.2020.1818897
  • Liébana-Cabanillas, F. J., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Antecedents of the adoption of the new mobile payment systems: The moderating effect of age. Computers in Human Behavior, 35, 464–478. https://doi.org/10.1016/j.chb.2014.03.022
  • Lisana, L. (2024). Understanding the key drivers in using mobile payment among Generation Z. Journal of Science and Technology Policy Management, 15(1), 122–141. https://doi.org/10.1108/JSTPM-08-2021-0118
  • Loh, X. M., Lee, V. H., Tan, G. W. H., Ooi, K. B., & Dwivedi, Y. K. (2020). Switching from cash to mobile payment: What’s the hold-up? Internet Research, 31(1), 376–399. https://doi.org/10.1108/INTR-04-2020-0175
  • McKinsey (2020). Perspectives on retail and consumer goods. www.,mckinsey.com (accessed 21 June 2021).
  • Memon, M. A., Ting, H., Ramayah, T., Chuah, F., & Cheah, J.-H. (2017). A review of the methodological misconceptions and guidelines related to the application of structural equation modeling: A malaysian scenario. Journal of Applied Structural Equation Modeling, 1(1), i–xiii. https://doi.org/10.47263/JASEM.1(1)01
  • Merhi, M., Hone, K., & Tarhini, A. (2019). A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust. Technology in Society, 59, 101151. https://doi.org/10.1016/j.techsoc.2019.101151
  • Moghavvemi, S., Mei, T. X., Phoong, S. W., & Phoong, S. Y. (2021). Drivers and barriers of mobile payment adoption: Malaysian merchants’ perspective. Journal of Retailing and Consumer Services, 59, 102364. https://doi.org/10.1016/j.jretconser.2020.102364
  • Morosan, C., & DeFranco, A. (2016). It’s about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17–29. https://doi.org/10.1016/j.ijhm.2015.11.003
  • Norazah Mohd, S., & Norbayah Mohd, S. (2011). User’ behaviour towards ubiquitos M-learning. The Turkish Online Journal of Distance Education, 12(3), 118–129.
  • 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
  • Ooi, K. B., & Tan, G. W. H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33–46. https://doi.org/10.1016/j.eswa.2016.04.015
  • Pai, C. K., Wang, T. W., Chen, S. H., & Cai, K. Y. (2018). Empirical study on Chinese tourists’ perceived trust and intention to use biometric technology. Asia Pacific Journal of Tourism Research, 23(9), 880–895. https://doi.org/10.1080/10941665.2018.1499544
  • Pai, R. R., & Alathur, S. (2019). Determinants of individuals’ intention to use mobile health: Insights from India. Transforming Government: People, Process and Policy, 13(3–4), 306–326. https://doi.org/10.1108/TG-04-2019-0027
  • 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
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  • Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/10.1146/annurev-psych-120710-100452
  • Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408
  • Qin, L., Kim, Y., & Tan, X. (2018). Understanding the intention of using mobile social networking apps across cultures. International Journal of Human–Computer Interaction, 34(12), 1183–1193. https://doi.org/10.1080/10447318.2018.1428262
  • Richter, N. F., Hauff, S., Kolev, A. E., & Schubring, S. (2023). Dataset on an extended technology acceptance model: A combined application of PLS-SEM and NCA. Data in Brief, 48, 109190. https://doi.org/10.1016/j.dib.2023.109190
  • Richter, N. F., Schubring, S., Hauff, S., Ringle, C. M., & Sarstedt, M. (2020). When predictors of outcomes are necessary: Guidelines for the combined use of PLS-SEM and NCA. Industrial Management & Data Systems, 120(12), 2243–2267. https://doi.org/10.1108/IMDS-11-2019-0638
  • Sahi, A. M., Khalid, H., Abbas, A. F., & Khatib, S. F. A. (2021). The evolving research of customer adoption of digital payment: Learning from content and statistical analysis of the literature. Journal of Open Innovation: Technology, Market, and Complexity, 7(4), 230. https://doi.org/10.3390/joitmc7040230
  • Sarstedt, M., & Danks, N. P. (2021). Prediction in HRM research–A gap between rhetoric and reality. Human Resource Management Journal, 32(2), 485–513. https://doi.org/10.1111/1748-8583.12400
  • Sathye, S., Prasad, B., Sharma, D., Sharma, P., & Sathye, M. (2018). Factors influencing the intention to use of mobile value-added services by women-owned microenterprises in Fiji. The Electronic Journal of Information Systems in Developing Countries, 84(2), e12016. https://doi.org/10.1002/isd2.12016
  • Shahjehan, A., Afsar, B., & Shah, S. I. (2019). Is organizational commitment-job satisfaction relationship necessary for organizational commitment-citizenship behavior relationships? A Meta-Analytical Necessary Condition Analysis. Economic Research-Ekonomska Istraživanja, 32(1), 2657–2679. https://doi.org/10.1080/1331677X.2019.1653784
  • Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823. https://doi.org/10.1016/j.elerap.2018.100823
  • Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552–4564. https://doi.org/10.1016/j.jbusres.2016.03.049
  • Sim, A. K. S., Tan, K. L., Sia, J. K. M., & Hii, I. S. H. (2020). Students’ choice of international branch campus in Malaysia: A gender comparative study. International Journal of Educational Management, 35(1), 87–107. https://doi.org/10.1108/IJEM-01-2020-0027
  • Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52, 101894. https://doi.org/10.1016/j.jretconser.2019.101894
  • 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
  • Tan, K. L., Gim, G., Hii, I., & Zhu, W. (2023). STARA fight or flight: A two-wave time-lagged study of challenge and hindrance appraisal of STARA awareness on basic psychological needs and individual competitiveness productivity among hospitality employees. Current Issues in Tourism, 1–19. https://doi.org/10.1080/13683500.2023.2224550
  • Tan, K. L., Hii, I. S. H., Lim, X. J., & Wong, C. Y. L. (2023). Enhancing purchase intentions among young consumers in a live-streaming shopping environment using relational bonds: Are there differences between “buyers” and “non-buyers”? Asia Pacific Journal of Marketing and Logistics, 36(1), 48–65. https://doi.org/10.1108/APJML-01-2023-0048
  • Tan, K. L., Memon, M. A., Sim, P. L., Leong, C. M., Soetrisno, F. K., & Hussain, K. (2019). Intention to use mobile payment system by ethnicity: A partial least squares multi-group approach. Asian Journal of Business Research, 9(1), 36–59. https://doi.org/10.14707/ajbr.190055
  • Tew, H. T., Tan, G. W. H., Loh, X. M., Lee, V. H., Lim, W. L., & Ooi, K. B. (2021). Tapping the next purchase: Embracing the wave of mobile payment. Journal of Computer Information Systems, 62(3), 527–535. https://doi.org/10.1080/08874417.2020.1858731
  • 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
  • The Star Online. (2018). Redesigning Malaysia’s higher education system. www.thestar.com.my (accessed 8 August 2018).
  • Tóth, Z., Dul, J., & Li, C. (. (2019). Necessary condition analysis in tourism research. Annals of Tourism Research, 79, 102821. https://doi.org/10.1016/j.annals.2019.102821
  • van der Valk, W., Sumo, R., Dul, J., & Schroeder, R. G. (2016). When are contracts and trust necessary for innovation in buyer-supplier relationships? A necessary condition analysis. Journal of Purchasing and Supply Management, 22(4), 266–277. https://doi.org/10.1016/j.pursup.2016.06.005
  • Venkatesh, V., Morris, M.G., Davis, G.B. and 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
  • WARC. (2019). The war of Malaysia’s e-wallets. https://www.warc.com/newsandopinion/news/the-war-of-malaysias-e-wallets/42990.
  • Wong, L. W., Tan, G. W. H., Hew, J. J., Ooi, K. B., & Leong, L. Y. (2020). Mobile social media marketing: A new marketing channel among digital natives in higher education? Journal of Marketing for Higher Education, 32(1), 113–137. https://doi.org/10.1080/08841241.2020.1834486
  • Wong, W. P. M., Tan, K. L., Inkgo, I. A., & Lim, C. Y. (2019). The effect of technology trust on customer e-loyalty in online shopping and the mediating effect of trustworthiness. Journal of Marketing Advances and Practices, 1(2), 39–52.
  • Yadav, R., Sharma, S. K., & Tarhini, A. (2016). A multi-analytical approach to understand and predict the mobile commerce adoption. Journal of Enterprise Information Management, 29(2), 222–237. https://doi.org/10.1108/JEIM-04-2015-0034
  • Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Understanding perceived risks in mobile payment acceptance. Industrial Management & Data Systems, 115(2), 253–269. https://doi.org/10.1108/IMDS-08-2014-0243
  • Zarmpou, T., Saprikis, V., Markos, A., & Vlachopoulou, M. (2012). Modeling users’ acceptance of mobile services. Electronic Commerce Research, 12(2), 225–248. https://doi.org/10.1007/s10660-012-9092-x
  • Zhang, J., Luximon, Y., & Song, Y. (2019). The role of consumers’ perceived security, perceived control, interface design features, and conscientiousness in continuous use of mobile payment services. Sustainability, 11(23), 6843. https://doi.org/10.3390/su11236843
  • Zhou, J., Rau, P. L. P., & Salvendy, G. (2013). Age-related difference in the use of mobile phones. Universal Access in the Information Society, 13(4), 401–413. https://doi.org/10.1007/s10209-013-0324-1
  • Zhou, T. (2011). The effect of initial trust on user adoption of mobile payment. Information Development, 27(4), 290–300. https://doi.org/10.1177/0266666911424075