[Agidi, R. Ch. (2018). Biometrics: The future of banking and financial service industry in Nigeria. International Journal of Electronics and Information Engineering, 9(2), 91–105. https://doi.org/10.13140/RG.2.2.23408.92161]Search in Google Scholar
[Al-Janahi, N., Abd-El-Barr, M., & Qureshi, K. (2021). Evaluation and performance comparison of a model for adoption of biometrics in online banking. Kuwait Journal of Science, 48(2). https://doi.org/10.48129/kjs.v48i2.8800]Search in Google Scholar
[Alpar, O. (2018). Biometric touchstroke authentication by fuzzy proximity of touch locations. Future Generation Computer Systems, 86, 71–80. https://doi.org/10.1016/j.future.2018.03.030]Search in Google Scholar
[Amankwaa, A., & McCartney, C. (2020). Gaughran vs the UK and public acceptability of forensic biometrics retention. Science and Justice, 60(3), 204–205. https://doi.org/10.1016/j.scijus.2020.04.001]Search in Google Scholar
[Baichoo, S., Khan, M. H. M., Bissessur, P., Pavaday, N., Boodoo-Jahangeer, N., & Purmah, N. R. (2018). Legal and ethical considerations of biometric identity card: Case for Mauritius. Computer Law & Security Review, 34(6), 1333–1341. https://doi.org/10.1016/j.clsr.2018.08.010]Search in Google Scholar
[Bauer, H. H., Barnes, S. J., Reichardt, T., & Neumann, M. M. (2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of Electronic Commerce Research, 6(3), 181–192.]Search in Google Scholar
[Breward, M., Hassanein, K., & Head, M. (2017). Understanding consumers’ attitudes toward controversial information technologies: A contextualization approach. Information Systems Research, 28(4), 760–774. https://doi.org/10.1287/isre.2017.0706]Search in Google Scholar
[Byun, S., & Byun, S. E. (2013). Exploring perceptions toward biometric technology in service encounters: A comparison of current users and potential adopters. Behaviour & Information Technology, 32(3), 217–230. https://doi.org/10.1080/0144929X.2011.553741]Search in Google Scholar
[Carpenter, D., McLeod, A., Hicks, Ch., & Maasber, M. (2018). Privacy and biometrics: An empirical examination of employee concerns. Information Systems Frontiers, 20, 91–110. https://doi.org/10.1007/s10796-016-9667-5]Search in Google Scholar
[Cramer, J. S. (2003). Logit models from economics and other fields. Cambridge University Press.]Search in Google Scholar
[Dang, V. T., Nguyen, N., Nguyen, H. V., Nguyen, H., Van Huy, L., Tran, V. T., & Nguyen, T. H. (2022). Consumer attitudes toward facial recognition payment: An examination of antecedents and outcomes. International Journal of Bank Marketing, 40(3), 511–535. https://doi.org/10.1108/IJBM-04-2021-0135]Search in Google Scholar
[Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008]Search in Google Scholar
[Dhrymes, P. (2017). Introductory econometrics. Springer. https://doi.org/10.1007/978-3-319-65916-9]Search in Google Scholar
[Fouad, K. M., Hassan, B. M., & Hassan, M. F. (2016). User authentication based on dynamic keystroke recognition. International Journal of Ambient Computing and Intelligence, 7(2), 1–32. https://doi.org/10.4018/IJACI.2016070101]Search in Google Scholar
[Ganesh, M. I. (2018, January 25). Data and discrimination: Fintech, biometrics and identity in India. The Society Pages. https://thesocietypages.org/cyborgology/2018/01/25/fintech-aadhaar-and-identity-in-india/]Search in Google Scholar
[Garrido, F., Reascos, I., Alvarez, F., & Lanchimba, A. (2024). Effects of facial biometric system at Universidad Técnica del Norte, Ecuador: An analysis using the Technology Acceptance Model (TAM). SN Computer Science, 5(50), 1–11. https://doi.org/10.1007/s42979-023-02418-4]Search in Google Scholar
[Gomez-Barrero, M., & Galbally, J. (2020). Reversing the irreversible: A survey on inverse biometrics. Computers & Security, 90, 101700. https://doi.org/10.1016/j.cose.2019.101700]Search in Google Scholar
[Hino, H. (2015). Assessing factors affecting consumers’ intention to adopt biometric authentication technology in e-shopping. Journal of Internet Commerce, 14(1), 1–20. https://doi.org/10.1080/15332861.2015.1006517]Search in Google Scholar
[Huterska, A., Piotrowska, A. I., & Szalacha-Jarmużek, J. (2021). Fear of the COVID-19 pandemic and social distancing as factors determining the change in consumer payment behavior at retail and service outlets. Energies, 14(14), 4191. https://doi.org/10.3390/en14144191]Search in Google Scholar
[Jeddy, N., Radhika, T., & Nithya, S. (2017). Tongue prints in biometric authentication: A pilot study. Journal of Oral and Maxillofacial Pathology, 21(1), 176–179. https://doi.org/10.4103/jomfp.JOMFP_185_15]Search in Google Scholar
[Jünger, M., & Mietzner, M. (2020). Banking goes digital: The adoption of FinTech services by German households. Finance Research Letters, 34, 101260. https://doi.org/10.1016/j.frl.2019.08.008]Search in Google Scholar
[Kagerbauer, M., Manz, W., & Zumkeller, D. (2013). Analysis of PAPI, CATI, and CAWI methods for a multiday household travel survey. In J. Zmud, M. Lee-Gosselin, M. Munizaga, & J. A. Carrasco (Eds.), Transport surveys methods: Best practice for decision making (pp. 289–304). Emerald Group Publishing Ltd.]Search in Google Scholar
[Kim, J. H., Song, W. K., & Lee, H. C. (2023). Exploring the determinants of travelers’ intention to use the airport biometric system: A Korean case study. Sustainability, 15, 14129. https://doi.org/10.3390/su151914129]Search in Google Scholar
[Kim, J. S., Brewer, P., & Bernhard, B. (2008). Hotel customer perceptions of biometric door locks: Convenience and security factors. Journal of Hospitality & Leisure Marketing, 17(1–2), 162–183. https://doi.org/10.1080/10507050801978323]Search in Google Scholar
[Kim, M., Kim, S., & Kim, J. (2019). Can mobile and biometric payments replace cards in the Korean offline payments market? Consumer preference analysis for payment systems using a discrete choice model. Telematics and Informatics, 38, 46–58. https://doi.org/10.1016/j.tele.2019.02.003]Search in Google Scholar
[Kindt, E. J. (2018). Having yes, using no? About the new legal regime for biometric data. Computer Law & Security Review, 34(3), 523–538. https://doi.org/10.1016/j.clsr.2017.11.004]Search in Google Scholar
[Kochaniak, K., & Ulman, P. (2020). Risk-intolerant but risk-taking—towards a better understanding of inconsistent survey responses of the euro area households. Sustainability, 12(17), 6912. https://doi.org/10.3390/su12176912]Search in Google Scholar
[Kufel, T. (2011). Ekonometria. Rozwiązywanie problemów z wykorzystaniem programu Gretl. Wydawnictwo Naukowe PWN.]Search in Google Scholar
[Kumari, P., & Seeja, K. R. (2022). Periocular biometrics: A survey. Journal of King Saud University – Computer and Information Sciences, 34(4), 1086–1097. https://doi.org/10.1016/j.jksuci.2019.06.003]Search in Google Scholar
[Liébana-Cabanillas, F., Muñoz-Leiva, F., Molinillo, S., & Higueras-Castillo, E. (2022). Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users’ viewpoint. Financial Innovation, 8(22). https://doi.org/10.1186/s40854-021-00328-z]Search in Google Scholar
[Liu, Z., Ben, S., Zhang, R. (2019). Factors affecting consumers’ mobile payment behavior: A meta-analysis. Electronic Commerce Research, 19, 575–601. https://doi.org/10.1007/s10660-019-09349-4]Search in Google Scholar
[Lumini, A., & Nanni, L. (2017). Overview of the combination of biometric matchers. Information Fusion, 33, 71–85. https://doi.org/10.1016/j.inffus.2016.05.003]Search in Google Scholar
[Maddala, G. S. (1992). Introduction to econometrics (2nd ed.). Macmillan Publishing Company.]Search in Google Scholar
[Mastercard. (2018). A Mastercard market intelligence report. Biometrics: Meeting the challenge of authentication and payments technology. https://www.master-card.us/content/dam/public/mastercardcom/na/us/en/documents/biometrics_updated_030619.pdf]Search in Google Scholar
[Miltgen, C. L., Popovič, A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the “Big 3” of technology acceptance with privacy context. Decision Support Systems, 56, 103–114. https://doi.org/10.1016/j.dss.2013.05.010]Search in Google Scholar
[Morosan, C. (2011). Customers’ adoption of biometric systems in restaurants: An extension of the Technology Acceptance Model. Journal of Hospitality Marketing & Management, 20(6), 661–690. https://doi.org/10.1080/19368623.2011.570645]Search in Google Scholar
[Morosan, C. (2012). Theoretical and empirical considerations of guests’ perceptions of biometric systems in hotels: Extending the technology acceptance model. Journal of Hospitality & Tourism Research, 36(1), 52–84. https://doi.org/10.1177/1096348010380601]Search in Google Scholar
[Mróz-Gorgoń, B., Wodo, W., Andrych, A., Caban-Piaskowska, K., & Kozyra, C. (2022). Biometrics innovation and payment sector perception. Sustainability, 14(15), 9424. https://doi.org/10.3390/su14159424]Search in Google Scholar
[Nakisa, B., Ansarizadeh, F., Oommen, P., & Kumar, R. (2023). Using an extended technology acceptance model to investigate facial authentication. Telematics and Informatics Reports, 12, 100099. https://doi.org/10.1016/j.teler.2023.100099]Search in Google Scholar
[Nakisa, B., Ansarizadeh, F., Oommen, P., & Shrestha, S. (2022). Technology Acceptance Model: A case study of Palm Vein authentication technology. IEEE Access, 10, 120436–120449. https://doi.org/10.1109/ACCESS.2022.3221413]Search in Google Scholar
[Nguyen, K., Fookes, C., Sridharan, S., Tistarelli, M., & Nixon, M. (2018). Super-resolution for biometrics: A comprehensive survey. Pattern Recognition, 78, 23–42. https://doi.org/10.1016/j.patcog.2018.01.002]Search in Google Scholar
[Norfolk, L., & O’Regan, M. (2021) Biometric technologies at music festivals: An extended technology acceptance model. Journal of Convention & Event Tourism, 22(1), 36–60. https://doi.org/10.1080/15470148.2020.1811184]Search in Google Scholar
[Ogbanufe, O., & Kim, D. J. (2018). Comparing fingerprint-based biometrics authentication versus traditional authentication methods for e-payment. Decision Support Systems, 106, 1–14. https://doi.org/10.1016/j.dss.2017.11.003]Search in Google Scholar
[Piotrowska, A. I., Polasik, M., & Piotrowski, D. (2017). Prospects for the application of biometrics in the Polish banking sector. Equilibrium. Quarterly Journal of Economics and Economic Policy, 12(3), 485–502. https://doi.org/10.24136/eq.v12i3.27]Search in Google Scholar
[Piotrowski, D. (2022). ICTs in the banking sector in the times of the COVID-19 pandemic: The customer’s perspective. Ekonomia i Prawo. Economics and Law, 21(3), 603–622. https://doi.org/10.12775/EiP.2022.032]Search in Google Scholar
[Polasik, M., Wisniewski, T. P., & Lightfoot, G. (2012). Modelling customers’ intentions to use contactless cards. International Journal of Banking, Accounting and Finance, 4(3), 203–231. https://doi.org/10.1504/IJBAAF.2012.051590]Search in Google Scholar
[Prince, J. T., & Wallsten, S. (2022). How much is privacy worth around the world and across platforms? Journal of Economics & Management Strategy, 31(4), 841–861. https://doi.org/10.1111/jems.12481]Search in Google Scholar
[Raj, L. V., Amilan, S., & Aparna, K. (2023). Factors influencing the adoption of cashless transactions: Toward a unified view. South Asian Journal of Marketing. https://doi.org/10.1108/sajm-11-2022-0071]Search in Google Scholar
[Rio, J. S., Moctezuma, D., Conde, C., de Diego, I. M., & Cabello, E. (2016). Automated border control e-gates and facial recognition systems. Computers & Security, 62, 49–72. https://doi.org/10.1016/j.cose.2016.07.001]Search in Google Scholar
[Sadhya, D., & Singh, S. K. (2017). Providing robust security measures to Bloom filter based biometric template protection schemes. Computers & Security, 67, 59–72. https://doi.org/10.1016/j.cose.2017.02.013]Search in Google Scholar
[Sanchez-Reillo, R., Ortega-Fernandez, I., Ponce-Hernandez, W., & Quiros-Sandoval, H. C. (2019). How to implement EU data protection regulation for R&D in biometrics. Computer Standards & Interfaces, 61, 89–96. https://doi.org/10.1016/j.csi.2018.01.007]Search in Google Scholar
[Singh, M., Singh, R., & Ross, A. (2019). A comprehensive overview of biometric fusion. Information Fusion, 52, 187–205. https://doi.org/10.1016/j.inffus.2018.12.003]Search in Google Scholar
[Sleiman, K. A. A., Juanli, L., Lei, H. Z., Rong, W., Yubo, W., Li, S., Cheng, J., & Amin, F. (2023). Factors that impacted mobile-payment adoption in China during the COVID-19 pandemic. Heliyon, 9(5), e16197. https://doi.org/10.1016/j.heliyon.2023.e16197]Search in Google Scholar
[Soh, K. L., Wong, W. P., & Chan, K. L. (2010). Adoption of biometric technology in online applications. International Journal of Business and Management Science, 3(2), 121–146.]Search in Google Scholar
[Soto-Beltrán, L. L., Robayo-Pinzón, O. J., & Rojas-Berrio, S. P. (2022). Effects of perceived risk on intention to use biometrics in financial products: Evidence from a developing country. International Journal of Business Information Systems, 39(2), 170–192.]Search in Google Scholar
[Štitilis, D., & Laurinaitis M. (2017). Treatment of biometrically processed personal data: Problem of uniform practice under EU personal data protection law. Computer Law & Security Review, 33, 618–628. https://doi.org/10.1016/j.clsr.2017.03.012]Search in Google Scholar
[Sun, Y., Li, H., & Li, N. (2023). A novel cancelable fingerprint scheme based on random security sampling mechanism and relocation bloom filter. Computers & Security, 125, 103021. https://doi.org/10.1016/j.cose.2022.103021]Search in Google Scholar
[Tassabehji, R., & Kamala, M. A. (2012). Evaluating biometrics for online banking: The case for usability. International Journal of Information Management, 32(5), 489–494. https://doi.org/10.1016/j.ijinfomgt.2012.07.001]Search in Google Scholar
[Tovarek, J., Voznak, M., Rozhon, J., Rezac, F., Safarik, J., & Partila, P. (2018). Different approaches for face authentication as part of a multimodal biometrics system. Advances in Electrical and Electronic Engineering, 16(1), 118–124. https://doi.org/10.15598/aeee.v16i1.2547]Search in Google Scholar
[Trawnih, A. A., Al-Adwan, A. S., Yaseen, H., & Al-Rahmi, W. M. (2023). Determining perceptions of banking customers regarding fingerprint ATMs. Information Development, 0(0). https://doi.org/10.1177/02666669231194360]Search in Google Scholar
[Unar, J. A., Seng, W. C., & Abbasi, A. (2014). A review of biometric technology along with trends and prospects. Pattern Recognition, 47, 2673–2688. https://doi.org/10.1016/j.patcog.2014.01.016]Search in Google Scholar
[van der Cruijsen, C., Hernández, L., & Jonker, N. (2017). In love with the debit card but still married to cash. Applied Economics, 49(30), 2989–3004. https://doi.org/10.1080/00036846.2016.1251568]Search in Google Scholar
[Wahid, L. O. A., & Pratama, A. L. (2022). Factors influencing smartphone owners’ acceptance of biometric authentication methods. ILKOM Jurnal Ilmiah, 14(2), 91–98. https://doi.org/10.33096/ilkom.v14i2.1114.91-98]Search in Google Scholar
[Wang, J. S. (2021). Exploring biometric identification in FinTech applications based on the modified TAM. Financial Innovation, 7(42). https://doi.org/10.1186/s40854-021-00260-2]Search in Google Scholar
[Wang, J. S. (2023). Verification techniques in FinTech compared from user perspectives. Social Science Computer Review, 41(4), 1438–1455. https://doi.org/10.1177/08944393211058310]Search in Google Scholar
[Wang, K., Yang, G., Huang, Y., & Yin, Y. (2020). Multi-scale differential feature for ECG biometrics with collective matrix factorization. Pattern Recognition, 102, 107211. https://doi.org/10.1016/j.patcog.2020.107211]Search in Google Scholar
[Wang, M., Hu, J., & Abbass, H. A. (2020). BrainPrint: EEG biometric identification based on analyzing brain connectivity graphs. Pattern Recognition, 105, 107381. https://doi.org/10.1016/j.patcog.2020.107381]Search in Google Scholar
[Wnuk, A., Oleksy, T, & Maison, D. (2020). The acceptance of COVID-19 tracking technologies: The role of perceived threat, lack of control, and ideological beliefs. PLoS ONE, 15(9), e0238973. https://doi.org/10.1371/journal.pone.0238973]Search in Google Scholar
[Yu, J., Sun, K., Gao, F., & Zhu, S. (2018). Face biometric quality assessment via light CNN. Pattern Recognition Letters, 107, 25–32. https://doi.org/10.1016/j.patrec.2017.07.015]Search in Google Scholar
[Zhang, D., Liu, Z., & Yan, J. (2010). Dynamic tongueprint: A novel biometric identifier. Pattern Recognition, 43(3), 1071–1082. https://doi.org/10.1016/j.patcog.2009.09.002]Search in Google Scholar
[Zhang, Y., Huang, Y., Wang, L., & Yu, S. (2019). A comprehensive study on gait biometrics using a joint CNN-based method. Pattern Recognition, 93, 228–236. https://doi.org/10.1016/j.patcog.2019.04.023]Search in Google Scholar
[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), 1016. https://doi.org/10.3390/ijerph18031016]Search in Google Scholar