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A Systematic Review of Mobile Payment Studies from the Lens of the UTAUT Model

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Recent Advances in Technology Acceptance Models and Theories

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 335))

Abstract

While the use of Mobile payment (M-payment) systems has been well-perceived across several sectors, the factors affecting its adoption are still not apparent. Since the UTAUT is believed to provide a better understanding of the variance in the behavioral intention to use several technologies, this systematic review aims to analyze the M-payment studies from the lens of the UTAUT model. Out of 377 studies collected, a total of 25 research articles were synthesized and analyzed. The taxonomy of the analyzed studies was based on publication years, contexts, research methods, active countries, databases, factors and their types, participants, and research purposes. The main results pointed out that 48% of the analyzed studies were undertaken in the industrial sectors. Further, 80% of the analyzed studies have mainly relied on questionnaire surveys for data collection. Moreover, perceived risk and perceived trust were found to be the most dominant predictors of M-payment adoption. It is believed that the results of this systematic review will provide an inclusive source for conducting further research in M-payment.

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References

  1. Al-Emran, M., Mezhuyev, V.: Examining the effect of knowledge management factors on mobile learning adoption through the use of importance-performance map analysis (IPMA). In: International Conference on Advanced Intelligent Systems and Informatics, pp. 449–458 (2019)

    Google Scholar 

  2. Al-Emran, M., Mezhuyev, V., Kamaludin, A.: An innovative approach of applying knowledge management in m-learning application development: a pilot study. Int. J. Inf. Commun. Technol. Educ. 15(4), 94–112 (2019)

    Article  Google Scholar 

  3. Al-Emran, M., Shaalan, K.: Academics’ awareness towards mobile learning in Oman. Int. J. Comput. Digit. Syst. 6(1), 45–50 (2017). https://doi.org/10.12785/IJCDS/060105

    Article  Google Scholar 

  4. Al-Saedi, K., Al-Emran, M., Ramayah, T., Abusham, E.: Developing a general extended UTAUT model for M-payment adoption. Technol. Soc. 62, (2020). https://doi.org/10.1016/j.techsoc.2020.101293

  5. Dass, R., Pal, S.: A meta analysis on adoption of mobile financial services. Indian Inst. Manag. Ahmedabad 2(1), 1–26 (2011)

    Google Scholar 

  6. Srivastava, S.C., Chandra, S., Theng, Y.-L.: Evaluating the role of trust in consumer adoption of mobile payment systems: an empirical analysis. Commun. Assoc. Inf. Syst. 27(1), 561–588 (2010)

    Google Scholar 

  7. Lu, Y., Cao, Y., Wang, B., Yang, S.: A study on factors that affect users’ behavioral intention to transfer usage from the offline to the online channel. Comput. Human Behav. 27(1), 355–364 (2011). https://doi.org/10.1016/j.chb.2010.08.013

    Article  Google Scholar 

  8. Petrova, K., Mehra, R.: Mobile payment: an exploratory study of customer attitudes. In: 2010 6th International Conference on Wireless and Mobile Communications, pp. 378–383 (2010). https://doi.org/10.1109/icwmc.2010.59

  9. Alqahtani, M.A., Al-Badi, A.H., Mayhew, P.J.: Exploratory study of m-transaction: user’s perspectives. Electron. J. Inf. Syst. Dev. Ctries. 60(1), 1–22 (2014). https://doi.org/10.1002/j.1681-4835.2014.tb00428.x

    Article  Google Scholar 

  10. Hao, H., Lu, L., Jianjun, W.: Diffusion of mobile commerce application in the market. (2008) https://doi.org/10.1109/icicic.2007.265

  11. Yang, K.: Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services. J. Consum. Mark. 27(3), 262–270 (2010). https://doi.org/10.1108/07363761011038338

    Article  Google Scholar 

  12. Gilbert, A.L., Han, H.: Understanding mobile data services adoption: demography, attitudes or needs? Technol. Forecast. Soc. Change 72(3), 327–337 (2005). https://doi.org/10.1016/j.techfore.2004.08.007

  13. Zhou, T.: An empirical examination of continuance intention of mobile payment services. Decis. Support Syst. 54(2), 1085–1091 (2013). https://doi.org/10.1016/j.dss.2012.10.034

    Article  Google Scholar 

  14. Zhou, T.: Exploring mobile user acceptance based on UTAUT and contextual offering. Proc. Int. Symp. Electron. Commer. Secur. ISECS 2008, 241–245 (2008). https://doi.org/10.1109/ISECS.2008.10

    Article  Google Scholar 

  15. Al-Qaysi, N., Mohamad-Nordin, N., Al-Emran, M.: Employing the technology acceptance model in social media: a systematic review. Educ. Inf. Technol. 1–42 (2020). https://doi.org/10.1007/s10639-020-10197-1

  16. Al-Qaysi, N., Mohamad-Nordin, N., Al-Emran, M.: Factors affecting the adoption of social media in higher education: a systematic review of the technology acceptance model. In: Recent Advances in Intelligent Systems and Smart Applications, Springer, pp. 571–584 (2021)

    Google Scholar 

  17. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989). https://doi.org/10.2307/249008

    Article  Google Scholar 

  18. Venkatesh, V., Morris, M., Davis, G., Davis, F.: User acceptance of information technology: toward a unified view. MIS Q. 27(3), 425–478 (2003). https://doi.org/10.2307/30036540

    Article  Google Scholar 

  19. Liu, S.F., Huang, L.S., Chiou, Y.H.: An integrated attitude model of self-service technologies: Evidence from online stock trading systems brokers. Serv. Ind. J. 32(11), 1823–1835 (2012). https://doi.org/10.1080/02642069.2011.574695

    Article  Google Scholar 

  20. Kim, C., Mirusmonov, M., Lee, I.: An empirical examination of factors influencing the intention to use mobile payment. Comput. Human Behav. 26(3), 310–322 (2010). https://doi.org/10.1016/j.chb.2009.10.013

    Article  Google Scholar 

  21. Koenig-Lewis, N., Marquet, M., Palmer, A., Zhao, A.L.: Enjoyment and social influence: predicting mobile payment adoption. Serv. Ind. J. 35(10), 537–554 (2015). https://doi.org/10.1080/02642069.2015.1043278

    Article  Google Scholar 

  22. Koivumaki, T., Ristola, A., Kesti, M.: Predicting consumer acceptance in mobile services: empirical evidence from an experimental end user environment. Int. J. Mob. Commun. 4(4), 4 (2006). https://doi.org/10.1504/ijmc.2006.008950

  23. Shaikh, A.A., Karjaluoto, H.: Mobile banking adoption: a literature review. Telematics Inform. 32(1), 129–142 (2014). https://doi.org/10.1016/j.tele.2014.05.003

    Article  Google Scholar 

  24. Dahlberg, T., Guo, J., Ondrus, J.: A critical review of mobile payment research. Electron. Commer. Res. Appl. 14(5), 265–284 (2015). https://doi.org/10.1016/j.elerap.2015.07.006

    Article  Google Scholar 

  25. Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Softw. Eng. Group, Sch. Comput. Sci. Math. Keele Univ. 1–57 (2007). https://doi.org/10.1.1.117.471

    Google Scholar 

  26. Al-Maroof, R.A., Al-Emran, M.: Research trends in flipped classroom: a systematic review. In: Recent Advances in Intelligent Systems and Smart Applications, Springer, pp. 253–275 (2021)

    Google Scholar 

  27. Fatehah, M., Mezhuyev, V., Al-Emran, M.: A systematic review of meta modelling in software engineering. In: Recent Advances in Intelligent Systems and Smart Applications, Springer, pp. 3–27 (2021)

    Google Scholar 

  28. Saa, A.A., Al-Emran, M., Shaalan, K.: Factors affecting students’ performance in higher education: a systematic review of predictive data mining techniques. Technol. Knowl. Learn. (2019). https://doi.org/10.1007/s10758-019-09408-7

    Article  Google Scholar 

  29. Al-Emran, M., Mezhuyev, V., Kamaludin, A.: Technology acceptance model in m-learning context: a systematic review. Comput. Educ. 125, 389–412 (2018)

    Article  Google Scholar 

  30. King, W.R., He, J.: A meta-analysis of the technology acceptance model. Inf. Manag. 43(6), 740–755 (2006). https://doi.org/10.1016/j.im.2006.05.003

    Article  Google Scholar 

  31. Oliveira, T., Faria, M., Thomas, M.A., Popovič, A.: Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM. Int. J. Inf. Manage. 34(5), 689–703 (2014). https://doi.org/10.1016/j.ijinfomgt.2014.06.004

    Article  Google Scholar 

  32. Zhou, T., Lu, Y., Wang, B.: Integrating TTF and UTAUT to explain mobile banking user adoption. Comput. Human Behav. 26(4), 760–767 (2010). https://doi.org/10.1016/j.chb.2010.01.013

    Article  Google Scholar 

  33. Yu, C.-S.: Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. J. Electron. Commer. Res. 13, 104–121 (2012)

    Google Scholar 

  34. Slade, E., Williams, M., Dwivedi, Y., Piercy, N.: Exploring consumer adoption of proximity mobile payments. J. Strateg. Mark. 23(3), 209–223 (2015). https://doi.org/10.1080/0965254X.2014.914075

    Article  Google Scholar 

  35. Fitriani, F., Suzianti, A.: Analysis of factors that affect Nfc mobile payment technology adoption (case study : telkomsel cash), pp. 103–109 (2017)

    Google Scholar 

  36. Hongxia, P., Xianhao, X., Weidan, L.: Drivers and barriers in the acceptance of mobile payment in China. In: 2011 International Conference on E-business and E-government (ICEE), vol. 1, no. 5, pp. 1–4 (2011). https://doi.org/10.1109/ICEBEG.2011.5887081

  37. Qasim, H., Abu-Shanab, E.: Drivers of mobile payment acceptance: the impact of network externalities. Inf. Syst. Front. 18(5), 1021–1034 (2016). https://doi.org/10.1007/s10796-015-9598-6

    Article  Google Scholar 

  38. Liu, L., Zhou, M.: Empirical study of influencing factors of the users’ intention based on the survey of apple pay users. J. Interdiscip. Math. 20(6–7), 1391–1395 (2017). https://doi.org/10.1080/09720502.2017.1382143

    Article  Google Scholar 

  39. Musa, A., Khan, H.U., AlShare, K.A.: Factors influence consumers’ adoption of mobile payment devices in Qatar. Int. J. Mob. Commun. 13(6), 670 (2015). https://doi.org/10.1504/IJMC.2015.072100

    Article  Google Scholar 

  40. Teo, A.C., Tan, G.W.H., Ooi, K.B., Lin, B.: Why consumers adopt mobile payment? A partial least squares structural equation modelling (PLS-SEM) approach. Int. J. Mob. Commun. 13(5), 478 (2015). https://doi.org/10.1504/IJMC.2015.070961

    Article  Google Scholar 

  41. Lai, I.K., Lai, D.C.: Negative user adoption behaviors of mobile commerce: an empirical study from Chinese college students. In: 2010 8th International Conference on Supply Chain Management and Information, pp. 1–6 (2010)

    Google Scholar 

  42. Di Pietro, L., Guglielmetti Mugion, R., Mattia, G., Renzi, M.F., Toni, M.: The integrated model on mobile payment acceptance (IMMPA): an empirical application to public transport. Transp. Res. Part C Emerg. Technol. 56, 463–479 (2015). https://doi.org/10.1016/j.trc.2015.05.001

  43. de Abrahão, R.S., Moriguchi, S.N., Andrade, D.F.: Intention of adoption of mobile payment: an analysis in the light of the unified theory of acceptance and use of technology (UTAUT). RAI Rev. Adm. e Inovação 13(3), 221–230 (2016). https://doi.org/10.1016/j.rai.2016.06.003

  44. Chen, K.-Y., Chang, M.-L.: User acceptance of ‘near field communication’ mobile phone service: an investigation based on the ‘unified theory of acceptance and use of technology’ model. Serv. Ind. J. 33(6), 609–623 (2013). https://doi.org/10.1080/02642069.2011.622369

    Article  Google Scholar 

  45. Boonsiritomachai, W., Pitchayadejanant, K.: Determinants affecting mobile banking adoption by generation Y based on the unified theory of acceptance and use of technology model modified by the technology acceptance model concept. Kasetsart J. Soc. Sci. 1–10 (2017). https://doi.org/10.1016/j.kjss.2017.10.005

  46. Madan, K., Yadav, R.: Behavioural intention to adopt mobile wallet: a developing country perspective. J. Indian Bus. Res. 8(3), 227–244 (2016). https://doi.org/10.1108/JIBR-10-2015-0112

    Article  Google Scholar 

  47. Thakur, R., Srivastava, M.: Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Res. 24(3), 369–392 (2014). https://doi.org/10.1108/IntR-12-2012-0244

    Article  Google Scholar 

  48. Khalilzadeh, J., Ozturk, A.B., Bilgihan, A.: Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry. Comput. Human Behav. 70, 460–474 (2017). https://doi.org/10.1016/j.chb.2017.01.001

    Article  Google Scholar 

  49. Shin, D.H.: Towards an understanding of the consumer acceptance of mobile wallet. Comput. Human Behav. 25(6), 1343–1354 (2009). https://doi.org/10.1016/j.chb.2009.06.001

    Article  Google Scholar 

  50. Krishna Kishore, S.V., Sequeira, A.H.: An empirical investigation on mobile banking service adoption in rural Karnataka. SAGE Open 6(1), 1–21 (2016). https://doi.org/10.1177/2158244016633731

  51. Al-Emran, M., Mezhuyev, V., Kamaludin, A.: PLS-SEM in information systems research: a comprehensive methodological reference. In: 4th International Conference on Advanced Intelligent Systems and Informatics (AISI 2018), pp. 644–653 (2018)

    Google Scholar 

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Acknowledgements

This is an extended version of a conference paper published by the 2019 International Conference on Fourth Industrial Revolution (ICFIR).

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Correspondence to Mostafa Al-Emran .

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Al-Saedi, K., Al-Emran, M. (2021). A Systematic Review of Mobile Payment Studies from the Lens of the UTAUT Model. In: Al-Emran, M., Shaalan, K. (eds) Recent Advances in Technology Acceptance Models and Theories. Studies in Systems, Decision and Control, vol 335. Springer, Cham. https://doi.org/10.1007/978-3-030-64987-6_6

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