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GENERAL & APPLIED ECONOMICS

Examining the factors influencing fintech adoption behaviour of gen Y in India

, &
Article: 2197699 | Received 19 Dec 2022, Accepted 28 Mar 2023, Published online: 26 Apr 2023

References

  • Afandi, M. Y. (2021). Antecedents of digitizing ZIS payments: A TAM and THEORY of PLANNED BEHAVIOUR Approaches. Journal of Finance and Islamic Banking, 41, 55–25
  • Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23. https://doi.org/10.1016/j.jretconser.2014.09.003
  • Ahmed Alshari, H., & Lokhande, M. A. (2022). The impact of demographic factors of clients’ attitudes and their intentions to use FinTech services on the banking sector in the least developed countries. Cogent Business & Management, 9(1), 2114305. https://doi.org/10.1080/23311975.2022.2114305
  • 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
  • Akhtar, F., & Das, N. (2019). Predictors of investment intention in Indian stock markets: Extending the theory of planned behavior. International Journal of Bank Marketing, 37(1), 97–119. https://doi.org/10.1108/IJBM-08-2017-0167
  • Aldammagh, Z., Abdeljawad, R., & Obaid, T. (2021). Predicting mobile banking adoption: An integration of TAM and THEORY of PLANNED BEHAVIOUR with trust and perceived risk. Financial Internet Quarterly ‘E-Finance, 17(3), 35–46. https://doi.org/10.2478/fiqf-2021-0017
  • Almajali, D., Al-Radaideh, A., Nussir, N., Eid, A., Al-Fakeh, F., & Masad, F. (2023). Antecedents of mobile banking app adoption during COVID19: A perspective of Jordanian consumer. International Journal of Data and Network Science”, 7(1), 477–488. https://doi.org/10.5267/j.ijdns.2022.8.011
  • Antonius, D. (2022). The Effect of Regulatory Sandbox on the Behaviour of FinTech Actors in Indonesia Using Theory of Planned Behaviour Approach ICEBE. EAI. https://doi.org/10.4108/eai.7-10-2021.2316146
  • Bahl, K., Kiran, R., & Sharma, A. (2022). Impact of Drivers of Change (Digitalisation, Demonetisation, and Consolidation of Banks) with Mediating Role of Nature of Training and Job Enrichment on the Banking Performance. SAGE Open, 12(2), No.2. https://doi.org/10.1177/21582440221097393
  • Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
  • Belanche, D., Casaló, L. V., & Flavián, C. (2019). Artificial Intelligence in fintech: Understanding robo-advisors adoption among customers. Industrial Management and Data Systems, 119(7), 1411–1430. https://doi.org/10.1108/IMDS-08-2018-0368
  • Bentler, P. M., & Bonetl, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structure. Psychological Bulletin, 88(3), 588. https://doi.org/10.1037/0033-2909.88.3.588
  • Bhasin, N. K., & Gulati, K. (2021). Challenges of COVID-19 During 2020 and Opportunities for fintech in 2021 for Digital Transformation of Business and Financial Institutions in India. In Zhao, J., & Richards, J. (Eds.), E-Collaboration Technologies and Strategies for Competitive Advantage Amid Challenging Times (pp. 282–299). IGI Global publisher.
  • Bhatt, V., Ajmera, H., & Nayak, K. (2020). An Empricial Study on Analyzing A User‘s Intention Towards Using Mobile Wallets; Measuring The Mediating Effect of Perceived Attitude and Perceived Trust. Turkish Journal of Computer and Mathematics Education, 12(10), 5332–5353. https://doi.org/10.17762/turcomat.v12i10.5336
  • Bizer, C., & Cyganiak, R. (2009). Quality-driven information filtering using the WIQA policy framework. Web Semantics: Science, Services, and Agents on the World Wide Web, 7(1), 10. https://doi.org/10.1016/j.websem.2008.02.005
  • Business Today. (2022), “Digital economy to see exponential growth to $800 billion by 2030: FM Sitharaman,” Business Today, March 12, available at https://www.businesstoday.in/latest/economy/story/digital-economy-to-see-exponential-growth-to-800-billion-by-2030-fm-sitharaman-325726-2022-03-12 (accessed on March 23,2023).
  • Cai, L., & Zhu, Y. (2015). The challenges of data quality and data quality assessment in the big data era. Data Science Journal, 14(0), 2. https://doi.org/10.5334/dsj-2015-002
  • Chang, V., Baudier, P., Zhang, H., Qianwen, X., Zhang, J., & Arami, M. (2020). How Blockchain can impact financial services – the overview, challenges and recommendations from expert interviewees. Technological Forecasting and Social Change, 158, 158. https://doi.org/10.1016/j.techfore.2020.120166
  • Chin, W. W. (2010). How to Write Up and Report PLS Analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (pp. 655–690). Heidelberg, Dordrecht, London, New York: Springer. https://doi.org/10.1007/978-3-540-32827-8_29
  • Chuang, L.M., Liu, C.C., & Kao, H.K. (2016). The adoption of fintech service: TAM perspective. International Journal of Management and Administrative Sciences, 3(07), 01–15.
  • Chung, Inuk. (2007), “Roles and Impacts of IT on new Social Norms, Ethical Values, and Legal Frameworks in Shaping a Future Digital Society”, Social and economic factors shaping the future of the internet speakers’ position papers, NSF/OECD Washington, https://www.oecd.org/sti/ieconomy/37985728.pdf (Retrieved on October 10, 2022).
  • Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). Routledge.
  • Dai, M., & Van Hove, L. (2017). The impact of customer images on online purchase decisions: Evidence from a Chinese C2C Web site. First Monday, 22(10).
  • Darmansyah, F., A., B., Hendratmi, A., & Aziz, P. F. (2020). Factors determining behavioral intentions to use Islamic financial technology: Three competing models. Journal of Islamic Marketing, 12(4), 794–812.
  • The Economics Times. (2022), “Digital economy to see exponential growth bn by 2030: FM”, The Economic Times, March 31, available at: https://economictimes.indiatimes.com/news/economy/finance/digital-economy-to-see-exponential-growth-to-usd-800-bn-by-2030-fm/articleshow/90156544.cms?from=mdr (Retrieved on September 19, 2022).
  • Erwin, A. H., RA Aryanti, W. P., Antonius, R., & Marylise, H., (2020), “The Impact of Marketing Influencer and Information Quality to Purchase Intention of Instagram Users”, International Conference on Information Management and Technology (ICIMTech), Bandung, Indonesia (pp.794–799).
  • Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low-cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70–88. https://doi.org/10.1016/j.tourman.2014.01.017
  • Fanoberova, & Kuczkowska, H. (2016). Effects of source credibility and information quality on attitudes and purchase intentions of apparel products : A quantitative study of online shopping among consumers in Sweden.
  • Ferdaous, J., & Rahman, M. N. (2021). Banking Goes Digital: Unearthing the Adoption of fintech by Bangladeshi Households. Journal of Innovation in Business Studies, 1(1), 7–42.
  • Gao, J., Zhang, C., Wang, K., & Sulin, B. (2012),“Understanding Online Purchase Decision Making: The Effects of Unconscious Thought, Information Quality, and Information Quantity”, available at: https://www.semanticscholar.org/paper/Understanding-Online-Zhang/59d87c76cdd2e92a9ac251681e4d6d959e405a99 (Retrieved on October 21, 2022).
  • Gholami, Z., Abdekhoda, M., & Zarea Gavgani, V. Determinant Factors in Adopting Mobile Technology-based Services by Academic Librarians. (2018). Journal of Library & Information Technology, 38(4), 271–277. July 2018. https://doi.org/10.14429/djlit.38.4.12676
  • Gupta, S., & Agrawal, A. (2021). Analytical Study of fintech in India: Pre & Post Pandemic Covid-19. Indian Journal of Economics and Business, 20(3), 33–71.
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). USA: SAGE.
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed, a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results, and higher acceptance. Long-Range Planning, 46(1–2), 1–12. https://doi.org/10.1016/j.lrp.2013.01.001
  • Hayes. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50, 1–22. https://doi.org/10.1080/00273171.2014.962683
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Hew, T. S., & Kadir, S. L. S. A. (2016). Understanding cloud base VLE from the SPT and CET perspectives: Development and validation of measurement Instrument Computer education. Computer & Education, 101(101), 132–149. https://doi.org/10.1016/j.compedu.2016.06.004
  • 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, 142–145. https://doi.org/10.1016/j.chb.2016.01.027
  • Huang, H., Stvilia, B., Jörgensen, C., & Bass, H. W. (2012). Prioritisation of Data Quality Dimensions and Skills Requirements in Genome Annotation Work. Journal of the American Society for Information Science and Technology, 63(1), 195–207. https://doi.org/10.1002/asi.21652
  • Hu, Z., Ding, S., Li, S., Chen, L., & Yang, S. (2019). Adoption Intention of fintech Services for Bank Users: An Empirical Examination with an Extended Technology Acceptance Model. Symmetry, 11(3), 340. https://doi.org/10.3390/sym11030340
  • Hui-Wen Chuah, S., Cheng-Xi Aw, E., & Cheng, C.F. (2022). A silver lining in the COVID-19 cloud: Examining customers’ value perceptions, willingness to use and pay more for robotic restaurants. Journal of Hospitality and Marketing Management, 31(1), 49–76. https://doi.org/10.1080/19368623.2021.1926038
  • India Briefing. (2022), “What trends are driving the fintech revolution in India?”, June 9, India-briefing.com/news/what-trends-are-driving-the-fintech-revolution-in-India-23809.html/ (Retrieved October 10, 2022).
  • Jain, A., Joshi, N., & Mayee, A. J. (2021). Millennial’s Tide Over the COVID-19 Crises: Buying Behaviour of Indian Millennial’s Post-COVID-19 Crises. Jindal Journal of Business Research, 10(2), 214–221. https://doi.org/10.1177/22786821211045196
  • Jeong, M., & Lambert, C. U. (2001). Adaptation of an information quality framework to measure customers’ behavioral intentions to use lodging Web sites. International Journal of Hospitality Management, 20(2), 129–146. https://doi.org/10.1016/S0278-4319(00)00041-4
  • Jose, P. E. (2013). Doing Statistical Mediation and Moderation. The Guilford Press.
  • Khwaja, M. G., Jusoh, A., & Nor, K. M. (2019). Does online social presence lead to purchase intentions?. Int. J. Econ. Policy Emerg. Econ, 12, 198–206.
  • Kim, A. J., & Johnson, K. K. P. (2016). Power of consumers using social media: Examining the influences of brand-related user-generated content on Facebook. Computers in Human Behavior, 58, 98–108. https://doi.org/10.1016/j.chb.2015.12.047
  • Kim, H., & Niehm, L. S. (2009). The impact of website quality on information quality, value, and loyalty intentions in apparel retailing. Journal of Interactive Marketing, 23(3), 221–233. https://doi.org/10.1016/j.intmar.2009.04.009
  • Knewtson, H. S., & Rosenbaum, Z. A. (2020). Toward understanding fintech and its industry. Managerial Finance, 46(8), 1043–1060. https://doi.org/10.1108/MF-01-2020-0024
  • Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101
  • Kock, Lynn, Kock, N., & Lynn, G. (2012). Lateral Collinearity and Misleading Results in Variance-Based SEM: An Illustration and Recommendations. Journal of the Association for Information Systems, 13(7), 546–580. https://doi.org/10.17705/1jais.00302
  • Krivkovich, A., White, O., Townsend, Z., & Euart, J. (2020). How US customers’ attitudes to fintech are shifting during the pandemic. McKinsey & Company, December, 17.
  • Lee, M.C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and THEORY of PLANNED BEHAVIOUR 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
  • Lee, E.J. Do tech products have a beauty premium? The effect of visual aesthetics of wearables on willingness-to-pay premium and the role of product category involvement. (2022). Journal of Retailing and Consumer Services, 65(102872), 102872. article no. https://doi.org/10.1016/j.jretconser.2021.102872
  • Lee, T. S., Ariff, M. S. M., Zakuan, N., Sulaiman, Z., & Saman, M. Z. M. (2016). Online sellers’ website quality influencing online buyers’ purchase intention. [Paper presentation] IOP Conference Series: Materials Science and Engineering, Bali, Indonesia
  • Leong, L. Y., Hew, T. S., Ooi, K. B., & Lin, B. (2019). Do electronic word-of-mouth and elaboration likelihood model influence hotel booking? Journal of Computer Information Systems, 59(2), 146–160. https://doi.org/10.1080/08874417.2017.1320953
  • Lestari, M. R., & Nita, A. (2021). The Influence of Sustainable Product’s Attributes Toward the Willingness to Pay for Sustainable Products. Malaysian Journal of Social Sciences and Humanities (MJSSH), 6(8), 542–551. https://doi.org/10.47405/mjssh.v6i8.981
  • Maiti, D., Castellaci, F., & Melchior, A. (2020), “Digitalisation and development: Issues for India and beyond”, January, available at https://www.researchgate.net/publication/338320003_Digitalisation_and_Development_Issues_for_India_andBeyondIssues_ (Retrieved September 25, 2022).
  • Majid, R. (2021). The role of religiosity in explaining the intention to use Islamic fintech among MSME actors. International Journal of Islamic Economics and Finance (IJIEF), 4(2), 207–232.
  • Mazambani, L., & Mutambara, E. (2020). Predicting fintech innovation adoption in South Africa: The case of cryptocurrency. African Journal of Economic and Management Studies, 11(1), 30–35. https://doi.org/10.1108/AJEMS-04-2019-0152
  • McKinsey Global Institute. (2019), “Digital India- Technology to transform a connected nation,” available at McKinsey Global Institute, March, available at: https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/digital%20india%20technology%20to%20transform%20a%20connected%20nation/digital-india-technology-to-transform-a-connected-nation-full-report.pdf (Retrieved September 21, 2022).
  • Mehta, D., & Kumari, S. (2021). Drivers fintech in India – a study of customers’ attitude and adoption. Zenith International Journal of Multidisciplinary, 11(1), 29–41.
  • Meyliana, M., Fernando, E., & Surjandy, S. (2019). The Influence of Perceived Risk and Trust in Adoption of fintech Services in Indonesia. Commit Journal, 13(1), 31–37. https://doi.org/10.21512/commit.v13i1.5708
  • Mikalef, P., Giannakos, M., & Pateli, A. (2013). Shopping and Word-of-Mouth Intentions on Social Media. Journal of Theoretical and Applied Electronic Commerce Research, 8(1), 17–34. https://doi.org/10.4067/S0718-18762013000100003
  • Minh, T. H. L. (2021). Examining factors that boost intention and loyalty to use fintech post COVID-19 lockdown as a new normal behavior. Cell Press Heliyon, 7(8), 1–9. https://doi.org/10.1016/j.heliyon.2021.e07821
  • Mohammad, K., & Nawayseh, A. (2020). Fintech in COVID-19 and beyond: What factors are affecting customers’ choice of fintech applications? Journal of Open Innovation, Technology, Market, and Complexity, 6(4), 1–15. https://doi.org/10.3390/joitmc6040153
  • Mohanasundaram, T., Sathyanarayana, S., & Rizwana, M.(2021), “Disruption on India’s fintech landscape: The 5G wave”, International Conference on Innovative Technology for Sustainable Development,Vol.37,https://www.itmconferences.org/articles/itmconf/abs/2021/02/itmconf_icitsd2021_01008/itmconf_icitsd2021_01008.html (Retrieved October 10, 2022).
  • Muller, D., Judd, C. M., & Yzerbyt, V. Y. (2005). When moderation is mediated, and mediation is moderated. Journal of Personality and Social Psychology, 89(6), 852. https://doi.org/10.1037/0022-3514.89.6.852
  • Myers, M. B., Calantone, R. J., Page, T. J., Jr., & Taylor, C. R. (2000). Academic insights: An application of multiple-group causal models in assessing cross-cultural measurement equivalence. Journal of International Marketing, 8(4), 108–121. https://doi.org/10.1509/jimk.8.4.108.19790
  • Nagaraju, S. (2015). Mobile Banking- Perception of Customers and Bankers. International Journal of Business Administration Research Review, 3(9), 236.
  • Nakagawa, K., & Yellowlees, P. (2020). Inter-generational Effects of Technology: Why Millennial Physicians May Be Less at Risk for Burnout Than Baby Boomers. Current Psychiatry Report, 22(9), No.9, pp. 45. https://doi.org/10.1007/s11920-020-01171-2
  • Nayanajith, G., & Damunupola, K. A. (2019). Relationship of perceived behavioral control and adoption of internet banking in the presence of a moderator. Asian Journal of Multidisciplinary Studies, 2(2), 30–41.
  • Niswah, F., Mutmainah, L., & Legowati, D. (2019). Muslim millennial’s intention of donating to charity using fintech platform. Journal of Islamic Monetary Economics and Finance, 5(3), 623–644. https://doi.org/10.21098/jimf.v5i3.1080
  • Nitzl, C., Roldan, J. L., & Cepeda-Carrion, G. (2016). Mediation Analysis in Partial Least Squares Path Modeling: Helping Researchers Discuss More Sophisticated Models. Industrial Management & Data Systems.
  • Njanja, L., Ogutu, M., & Ogutu, R. O. (2014), “The Moderating Effect of Subjective Norms, Perceived Behavioural Control and Gender on the Relationship Between Attitude Towards Internet Advertising and Purchase Intention of University Students in Kenya,” available at: https://www.semanticscholar.org/paper/the-moderating-effect-of-subjective-norms%2c-control-njanja-ogutu/21d1bfec355e9d5bd5d65aa81717e2877788102e, Retrieved on October 23, 2022)
  • Nomura, N., & Akai, M. (2004). Willingness to pay for green electricity in Japan as estimated through contingent valuation method. Applied Energy, 78(4), 453–463. https://doi.org/10.1016/j.apenergy.2003.10.001
  • Pascual-Miguel, F. J., Agudo-Peregrina, Á. F., & Chaparro-Pelaez, J. (2015). Influences of gender and product type on online purchasing. Journal of Business Research, 68(7), 1550–1556. https://doi.org/10.1016/j.jbusres.2015.01.050
  • Peters, E., Dieckmann, N., Dixon, A., Hibbard, J. H., & Mertz, C. K. (2007). Less is more in presenting quality information to consumers. Medical Care Research and Review, 64(2), No2, pp. 169–190. https://doi.org/10.1177/10775587070640020301
  • Philippon, T., (2016). The fintech Opportunity. NBER Working Paper No. 22476, August.
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. 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), pp.No.5, pp.879–903. https://doi.org/10.1037/0021-9010.88.5.879
  • Priyadarshini, C., Sreejesh, S., & Anusree, M. R. (2017). Effect of information quality of employment website on attitude toward the website: A moderated mediation study. International Journal of Manpower, 38(5), No.5, pp. 729–745. https://doi.org/10.1108/IJM-12-2015-0235
  • Purwantini, A. H., Athief, F. H. N., & Waharini, F. M. (2020). Indonesian consumers’ intention of adopting islamic financial technology services. Shirkah, 5(2), 171–196.
  • Putranto, B. D., & Sobari, N. (2021). Predicting Intention of Using Fintech Lending to Bank Users in Indonesia. In 18th International Symposium on Management (INSYMA 2021) (pp. 206–211). Atlantis Press.
  • Ramchandran, T., & Stella, M. (2022). Behavioural intention towards cryptocurrency adoption among students: A fintech innovation. Journal of Positive School Psychology, 5(6), 5046–5053.
  • Razak, M. M., Aminudin, N., Amir, A. F., & Ismail, M. A. (2013). Assessing consumer behavior from a main website of tourism product. Hospitality and Tourism: Synergizing Creativity and Innovation in Research, 452–459.
  • Ringle, C., Da Silva, D., & Bido, D. (2015). Modelagem de Equações Estruturais com Utilização do Smartpls. Brazilian Journal of Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717
  • RM, O. (2007). A Caution Regarding Rules of Thumb for Variance Inflation Factors. Quality & Quantity, 41(5), 673–690. https://doi.org/10.1007/s11135-006-9018-6
  • Ryu, H. -S. (2018). What makes users willing or hesitant to use fintech? the moderating effect of user type. Industrial Management & Data Systems, 118(3), 541–569. https://doi.org/10.1108/IMDS-07-2017-0325
  • Saba, I., Kouser, R., & Sharif Chaudhry, I. (2019). Fintech and Islamic Finance-Challenges and Opportunities. Review of Economics and Development Studies (READS), 5(4), 581–590. https://doi.org/10.26710/reads.v5i4.887
  • Sahni, J. (2021). Employee Engagement Among Millennial Workforce: Empirical Study on Selected Antecedents and Consequences. SAGE Open, 11(1), No.1. https://doi.org/10.1177/21582440211002208
  • School of Health Management and Medical Informatics. Tabriz University of Medical Sciences.
  • Setiawan. (2020). Digital financial literacy, current behavior of saving and spending and its future foresight, Econ (pp. 1–19). Innovation and Technology.
  • Setiawan, B., Pandu Nugraha, D., & Irawan, A.; Zoltan, Z. (2021). Robert Jeyakumar Nathan. Journal Open Innovation Technology, Market and Complexity, 7(3), 188. https://doi.org/10.3390/joitmc7030188
  • Shaikh, I. M., Qureshi, M. A., Noordin, K., Shaikh, J. M., Khan, A., & Shahbaz, M. S. (2020). Acceptance of Islamic financial technology (fintech) banking services by Malaysian users: An extension of technology acceptance model. Foresight, 22(3), 367–383. https://doi.org/10.1108/FS-12-2019-0105
  • Sheokand, K., & Gupta, N. (2017). Digital India programme and impact of digitalization on the Indian economy. Indian Journal of Economics and Development, 5(5).
  • Shubhangi, S., Sahni, M. M., & Kovid, R. K. (2020). What drives fintech adoption? A multi-method evaluation using an adapted technology acceptance model. Management Decision, 58(8), 1675–1697. https://doi.org/10.1108/MD-09-2019-1318
  • Sujood, B. N., Siddiqui, S., & Siddiqui, S. (2022). Consumers intention towards the use of smart technologies in tourism and hospitality (T&H) industry: A deeper insight into the integration of TAM, THEORY of PLANNED BEHAVIOUR and trust. Journal of Hospitality and Tourism Insights, ahead-of-print). https://doi.org/10.1108/JHTI-06-2022-0267
  • Talwar, S., Talwar, M., Kaur, P., & Dhir, A. (2020). Consumers’ resistance to digital innovations: A systematic review and framework. Australian Marketing Journal, 28(4), 289–299. https://doi.org/10.1016/j.ausmj.2020.06.014
  • Teo, A.C., Wei-Han Tan, G., Cheah, C.M., Ooi, K.B., & Yew, K.T. (2012). Can the Demographic and Subjective Norms Influence the Adoption of Mobile Banking? International Journal of Mobile Communications, 10(6), 578–597. https://doi.org/10.1504/IJMC.2012.049757
  • Thoradeniya, P., Lee, J., Tan, R., & Ferreira, A. (2015). Sustainability reporting and the theory of planned behavior. Accounting, Auditing & Accountability Journal, 28(7), 1099–1137. https://doi.org/10.1108/AAAJ-08-2013-1449
  • The Times of India. (2021a), “How India is outpacing the world in digital payment,” The Times of India, December 30, available at: https://timesofindia.indiatimes.com/business/india-business/explained-how-india-is-outpacing-the-world-in-digital-payments/articleshow/ (Retrieved on September 24, 2022).
  • The Times of India. (2021b), “The rise of the Indian millennial”, September 6, available at:https://timesofindia.indiatimes.com/blogs/voices/the-rise-of-the-indian-millennial/ (Retrieved September 30, 2022).
  • Tsai, M. T., Cheng, N. C., & Chen, K. S. (2011). Understanding online group buying intention: The roles of sense of virtual community and technology acceptance factors. Total Quality Management & Business Excellence, 22(10), 1091–1104. https://doi.org/10.1080/14783363.2011.614870
  • Tun-Pin, Keng-Soon, C., Choo Yen-San, W., Pui-Yee, Y., Hong Leong, C., & Teh Shwu-Shing, J. (2019). An Adoption of fintech Service in Malaysia, South East Asia journal of contemporary business. Economics and Law, 18, N0 5, pp.134–147.
  • Vicente Sales Melo, F., de Farias, S. A., & Trajano Barbosa, O. (2019). Dressing in white, a true Brazilian tradition: Social influence, values, and symbolic consumption. Revista de Administração da Universidade Federal de Santa Maria, 12(2), 215–232. https://doi.org/10.5902/1983465917984
  • Warshaw, P. R., & Davis, F. D. (1985). Disentangling behavioral intention and behavioral expectation. Journal of Experimental Social Psychology, 21(3), 213–228. https://doi.org/10.1016/0022-1031(85)90017-4
  • Yalcıntekin, T., & Saygili, M. (2020). Brand Loyalty at Smartphones Market: Linking Between Brand Passion, Hedonic and Utilitarian Values. Marketing and Management of Innovations, 1(1), 274–284. https://doi.org/10.21272/mmi.2020.1-23
  • Yan, C., Siddik, A. B., Akter, N., & Dong, Q. (2021). Factors influencing the adoption intention of using mobile financial service during the COVID-19 pandemic: The role of Fintech. Environmental Science and Pollution Research, 1–19. https://doi.org/10.1007/s11356-021-17437-y
  • Yan, C., Siddik, A. B., Yong, L., Dong, Q., Zheng, G. W., & Rahman, M. N. (2022). A Two-staged SEM-artificial neural network approach to analyze the impact of fintech adoption on the sustainability performance of banking firms: The mediating effect of green finance and innovation. Systems, 10(5), No.5, pp.148. https://doi.org/10.3390/systems10050148
  • Zhang, Y., Xiao, C., & Zhou, G. Willingness to pay a price premium for energy-saving appliances: Role of perceived value and energy efficiency labeling. (2020). Journal of Cleaner Production, 242(118555), 118555. article no. https://doi.org/10.1016/j.jclepro.2019.118555