As a leading Asia-Pacific tourism destination, Japan is experiencing a strong recovery in its tourism sector. With rising tourist spending, the influence of payment methods on overall travel satisfaction is gaining attention. This study employed Innovation Diffusion Theory and Innovation Resistance Theory to examine antecedents of mobile payment usage among domestic travelers in Japan, and how usage and digital literacy affect satisfaction. Data were collected from 542 respondents via an online survey and analyzed using SmartPLS 4. Results reveale that perceived relative advantage and observability positively influenced actual use, while risk barrier had a negative impact. Notably, digital literacy exerted a stronger influence on transaction satisfaction than on actual usage. In addition, actual usage significantly enhanced both transaction and travel satisfaction. These findings suggest that promoting mobile payments not only supports the development of smart tourism but also contribute to a more seamless and satisfying travel experience in Japan.
AbdallahW.TfailyF.HarrafA. (2025). The impact of digital financial literacy on financial behavior: Customers’ perspective. Competitiveness Review: An International Business Journal, 35(2), 347–370. https://doi.org/10.1108/cr-11-2023-0297
2.
AgagG.El-MasryA. A. (2016). Understanding consumer intention to participate in online travel community and effects on consumer intention to purchase travel online and WOM: An integration of innovation diffusion theory and TAM with trust. Computers in Human Behavior, 60, 97–111. https://doi.org/10.1016/j.chb.2016.02.038
3.
AgarwalR.PrasadJ. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557–582. https://doi.org/10.1111/j.1540-5915.1997.tb01322.x
4.
Al-JabriI.SohailM. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379–391.
5.
AmorosoD. L.Magnier-WatanabeR. (2012). Building a research model for mobile wallet consumer adoption: The case of mobile Suica in Japan. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 94–110. https://doi.org/10.4067/s0718-18762012000100008
6.
ArefM. M.OkashaA. E. (2019). Evaluating the online shopping behavior among Egyptian college-educated community. Review of Economics and Political Science, 5(1), 21–37. https://doi.org/10.1108/reps-10-2018-0013
7.
ChewF.GrantW.ToteR. (2004). Doctors on-line: Using diffusion of innovations theory to understand internet use. Family Medicine, 36(9), 645–650.
8.
ClaudyM. C.GarciaR.O’DriscollA. (2015). Consumer resistance to innovation—A behavioral reasoning perspective. Journal of the Academy of Marketing Science, 43(4), 528–544. https://doi.org/10.1007/s11747-014-0399-0
DavisF. 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
11.
DeLoneW. H.McLeanE. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748
12.
DeVellisR. F.ThorpeC. T. (2021). Scale development: Theory and applications. Sage publications.
13.
De VosJ.MokhtarianP. L.SchwanenT.Van AckerV.WitloxF. (2016). Travel mode choice and travel satisfaction: Bridging the gap between decision utility and experienced utility. Transportation, 43(5), 771–796. https://doi.org/10.1007/s11116-015-9619-9
14.
De VosJ.WitloxF. (2017). Travel satisfaction revisited. On the pivotal role of travel satisfaction in conceptualising a travel behaviour process. Transportation Research Part A: Policy and Practice, 106, 364–373. https://doi.org/10.1016/j.tra.2017.10.009
15.
DibraM. (2015). Rogers theory on diffusion of innovation-the most appropriate theoretical model in the study of factors influencing the integration of sustainability in tourism businesses. Procedia - Social and Behavioral Sciences, 195, 1453–1462. https://doi.org/10.1016/j.sbspro.2015.06.443
FanL.ZhangX.RaiL.DuY. (2021). Mobile payment: The next frontier of payment systems? An empirical study based on push-pull-mooring framework. Journal of Theoretical and Applied Electronic Commerce Research, 16(2), 155–169. https://doi.org/10.4067/s0718-18762021000200112
18.
Fernández-DíazE.Jambrino-MaldonadoC.Iglesias-SánchezP. P.de las Heras-PedrosaC. (2023). Digital accessibility of smart cities-tourism for all and reducing inequalities: Tourism agenda 2030. Tourism Review, 78(2), 361–380. https://doi.org/10.1108/TR-02-2022-0091
19.
GaoB. W.LaiI. K. W. (2015). The effects of transaction-specific satisfactions and integrated satisfaction on customer loyalty. International Journal of Hospitality Management, 44, 38–47. https://doi.org/10.1016/j.ijhm.2014.10.004
GrovesR. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly, 70(5), 646–675. https://doi.org/10.1093/poq/nfl033
22.
HairJ. F. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Sage.
23.
HairJ. F.RingleC. M.SarstedtM. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/mtp1069-6679190202
24.
HameedI.MubarikM. S.KhanK.WarisI. (2022). Can your smartphone make you a tourist? Mine does: Understanding the consumer’s adoption mechanism for mobile payment system. Human Behavior and Emerging Technologies, 2022(1), 4904686. https://doi.org/10.1155/2022/4904686
25.
HansenM. H.MadowW. G.TeppingB. J. (1983). An evaluation of model-dependent and probability-sampling inferences in sample surveys. Journal of the American Statistical Association, 78(384), 776–793. https://doi.org/10.2307/2288182
26.
HenselerJ.RingleC. M.SarstedtM. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
27.
HossainZ. (2023). A modified innovation resistance theory approach to E-Tourism resistance intention in Bangladesh. Journal of Technology Management and Innovation, 18(4), 59–71. https://doi.org/10.4067/s0718-27242023000400059
28.
HuX.MengH. (2023). Digital literacy and green consumption behavior: Exploring dual psychological mechanisms. Journal of Consumer Behaviour, 22(2), 272–287. https://doi.org/10.1002/cb.2122
29.
HuangC. D.GooJ.NamK.YooC. W. (2017). Smart tourism technologies in travel planning: The role of exploration and exploitation. Information & Management, 54(6), 757–770. https://doi.org/10.1016/j.im.2016.11.010
30.
IsmatS.UllahA.WaqarM.QureshiM.NawazH.LodhiK. (2023). Effects of E-banking on consumer satisfaction and its potential challenges: A case of private banks in Punjab. Bulletin of Business and Economics (BBE), 12(2), 381–388. https://doi.org/10.61506/01.00014
JonesM. A.SuhJ. (2000). Transaction‐specific satisfaction and overall satisfaction: An empirical analysis. Journal of Services Marketing, 14(2), 147–159. https://doi.org/10.1108/08876040010371555
34.
KapoorK. K.DwivediY. K.WilliamsM. D. (2015). Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service. Information Systems Frontiers, 17(5), 1039–1056. https://doi.org/10.1007/s10796-014-9484-7
35.
KaurP.DhirA.SinghN.SahuG.AlmotairiM. (2020). An innovation resistance theory perspective on mobile payment solutions. Journal of Retailing and Consumer Services, 55, Article 102059. https://doi.org/10.1016/j.jretconser.2020.102059
36.
KhanS.MehmoodS. (2024). Antecedents the adoption of tour itineraries from smart travel apps: An integration of experiential consumption theory and innovation resistance theory. Journal of Science and Technology Policy Management, Advance online publication. https://doi.org/10.1108/jstpm-06-2023-0095
KloppingI. M.McKinneyE. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35–48.
39.
LaukkanenT. (2016). Consumer adoption versus rejection decisions in seemingly similar service innovations: The case of the internet and mobile banking. Journal of Business Research, 69(7), 2432–2439. https://doi.org/10.1016/j.jbusres.2016.01.013
40.
LeeJ.JungT.Tom DieckM. C.García-MilonA.KimC. S. (2024). Affordance, digital media literacy, and emotions in virtual cultural heritage tourism experiences. Journal of Vacation Marketing, 31(4), 1056–1073. https://doi.org/10.1177/13567667241255383
41.
LouL.TianZ.KohJ. (2017). Tourist satisfaction enhancement using mobile QR code payment: An empirical investigation. Sustainability, 9(7), 1186. https://doi.org/10.3390/su9071186
42.
MahmoodM.BatoolS. H.RafiqM.SafdarM. (2022). Examining digital information literacy as a determinant of women's online shopping behavior. Information Technology & People, 35(7), 2098–2114. https://doi.org/10.1108/itp-05-2021-0397
43.
MinS.SoK. K. F.JeongM. (2021). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model. In Future of tourism marketing (pp. 2–15). Routledge.
MooreG. C.BenbasatI. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
47.
MoorthyK.LingC. S.FattY. W.YeeC. M.YinE. C. K.YeeK. S.WeiL. K. (2017). Barriers of mobile commerce adoption intention: Perceptions of generation X in Malaysia. Journal of Theoretical and Applied Electronic Commerce Research, 12(2), 37–53. https://doi.org/10.4067/s0718-18762017000200004
PaiC. K.LiuY.KangS.DaiA. (2020). The role of perceived smart tourism technology experience for tourist satisfaction, happiness and revisit intention. Sustainability, 12(16), 6592. https://doi.org/10.3390/su12166592
50.
ParkY.ChenJ. V. (2007). Acceptance and adoption of the innovative use of smartphone. Industrial Management & Data Systems, 107(9), 1349–1365. https://doi.org/10.1108/02635570710834009
PengR.XiongL.YangZ. (2012). Exploring tourist adoption of tourism mobile payment: An empirical analysis. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 21–33. https://doi.org/10.4067/s0718-18762012000100003
53.
PurnamaS.BangunC. S.FaaroekS. A. (2021). The effect of transaction experience using digital wallets on user satisfaction in millennial generation. Aptisi Transactions on Management (ATM), 5(2), 161–168. https://doi.org/10.33050/atm.v5i2.1593
54.
RamS.ShethJ. N. (1989). Consumer resistance to innovations: The marketing problem and its solutions. Journal of Consumer Marketing, 6(2), 5–14. https://doi.org/10.1108/eum0000000002542
55.
RogersE. M. (2003). Diffusion of innovations (5th ed.). Free Press.
56.
SivathanuB. (2019). Adoption of digital payment systems in the era of demonetization in India: An empirical study. Journal of Science and Technology Policy Management, 10(1), 143–171. https://doi.org/10.1108/jstpm-07-2017-0033
TalkeK.HeidenreichS. (2014). How to overcome pro‐change bias: Incorporating passive and active innovation resistance in innovation decision models. Journal of Product Innovation Management, 31(5), 894–907. https://doi.org/10.1111/jpim.12130
59.
TornatzkyL. G.KleinK. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, 29(1), 28–45. https://doi.org/10.1109/tem.1982.6447463
XiongS.ZhangT. (2024). Enhancing tourist loyalty through location-based service apps: Exploring the roles of digital literacy, perceived ease of use, perceived autonomy, virtual-content congruency, and tourist engagement. Plos One, 19(1), 1–18. https://doi.org/10.1371/journal.pone.0294244
