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Articles

Online banking adoption in Spanish cities and towns. Finding differences through TAM application

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Pages 854-872 | Received 20 Jan 2021, Accepted 15 Jun 2021, Published online: 09 Jul 2021

References

  • 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
  • Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
  • Aldás‐Manzano, J., Lassala‐Navarré, C., Ruiz‐Mafé, C., & Sanz‐Blas, S. (2009). Key drivers of internet banking services use. Online Information Review, 33(4), 672–695. https://doi.org/10.1108/14684520910985675
  • Almogbil, A. M. A. (2005). Security, perceptions, and practices. Challenges facing adoption of online banking in Saudi Arabia [ProQuest Dissertations and Theses]. The George Washington University.
  • Al-Somali, S. A., Gholami, R., & Clegg, B. (2008). Internet banking acceptance in the context of developing countries: an extension of the technology acceptance model. European Conference on Management of Technology, 12(9), 1–16.
  • Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29(2), 130–141. https://doi.org/10.1016/j.technovation.2008.07.004
  • Banu, A. M., Mohamed, N. S., & Parayitam, S. (2019). Online banking and customer satisfaction: Evidence from India. Asia-Pacific Journal of Management Research and Innovation, 15(1–2), 68–80. https://doi.org/10.1177/2319510X19849730
  • Barroso, C., Carrión, G. C., & Roldán, J. L. (2010). Applying maximum likelihood and PLS on different sample sizes: Studies on SERVQUAL model and employee behavior model. In Handbook of Partial Least Squares (pp. 427–447). Springer.
  • Bing Tan, P. J., Robert Potamites, P., & Wens’Chi, L. (2012). Applying the TAM to understand the factors affecting use of online banking in the Pescadores. ARPN Journal of Science and Technology, 2(11), 1022–1028. https://cutt.ly/4jTU9WH
  • Blut, M., Wang, C., & Schoefer, K. (2016). Factors influencing the acceptance of self-service technologies. Journal of Service Research, 19(4), 396–416. https://doi.org/10.1177/1094670516662352
  • Chawla, D., & Joshi, H. (2018). The moderating effect of demographic variables on mobile banking adoption: An empirical investigation. Global Business Review, 19(3_suppl), S90–S113. https://doi.org/10.1177/0972150918757883
  • Crosman, P. (2020). Digital banking is surging during the pandemic. Will it last. American Banker, 185(81), 1.
  • Dash, M., Mohanty, A. K., Pattnaik, S., Mohapatra, R. C., & Sahoo, D. S. (2011). Using the TAM model to explain how attitudes determine adoption of internet banking. European Journal of Economics, Finance and Administrative Sciences, 36(1), 50–59.
  • Davinson, N., & Sillence, E. (2014). Using the health belief model to explore users’ perceptions of ‘being safe and secure’ in the world of technology mediated financial transactions. International Journal of Human-Computer Studies, 72(2), 154–168. https://doi.org/10.1016/j.ijhcs.2013.10.003
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
  • Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies, 38(3), 475–487. https://doi.org/10.1006/imms.1993.1022
  • Davis, F. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results [Doctoral Dissertation]. Massachusetts Institute of Technology. https://doi.org/10.1016/S0378-7206(01)00143-4
  • Eckhardt, A., Laumer, S., & Weitzel, T. (2009). Who influences whom? Analyzing workplace referents’ social influence on it adoption and non-adoption. Journal of Information Technology, 24(1), 11–24. https://doi.org/10.1057/jit.2008.31
  • Ege Oruç, Ö., & Tatar, Ç. (2017). An investigation of factors that affect internet banking usage based on structural equation modeling. Computers in Human Behavior, 66, 232–235. https://doi.org/10.1016/j.chb.2016.09.059
  • Eriksson, K., Kerem, K., & Nilsson, D. (2008). The adoption of commercial innovations in the former Central and Eastern European markets. International Journal of Bank Marketing, 26(3), 154–169. https://doi.org/10.1108/02652320810864634
  • Gardner, B. (2020). Dirty banknotes may be spreading the coronavirus, WHO suggests. Daily Telegraph, 8p.
  • Gefen, D. (2003). TAM or just plain habit. Journal of Organizational and End User Computing, 15(3), 1–13. https://doi.org/10.4018/joeuc.2003070101
  • Giovanis, A., Assimakopoulos, C., & Sarmaniotis, C. (2019). Adoption of mobile self-service retail banking technologies. International Journal of Retail & Distribution Management, 47(9), 894–914. https://doi.org/10.1108/IJRDM-05-2018-0089
  • Grabner‐Kräuter, S., & Faullant, R. (2008). Consumer acceptance of internet banking: the influence of internet trust. International Journal of Bank Marketing, 26(7), 483–504. https://doi.org/10.1108/02652320810913855
  • Haider, Z., Rahim, A., & Aslam, F. (2019). Antecedents of online banking adoption in Pakistan: An empirical study. International Research Journal of Arts and Humanities, 47(47), 197–214. https://sujo-old.usindh.edu.pk/index.php/IRJAH/article/view/5135/3232
  • Hair, J., Jr., Hult, G. T., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE.
  • Hair, J., Jr., Hult, G. T., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE.
  • Hair, J., Jr., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
  • Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442–458. https://doi.org/10.1108/IMDS-04-2016-0130
  • Hanafizadeh, P., Keating, B. W., & Khedmatgozar, H. R. (2014). A systematic review of Internet banking adoption. Telematics and Informatics, 31(3), 492–510. https://doi.org/10.1016/j.tele.2013.04.003
  • Hossain, S. A., Bao, Y., Hasan, N., & Islam, F. (2020). Perception and prediction of intention to use online banking systems. International Journal of Research in Business and Social Science, 9, 112–116.
  • Jindal, M., & Sharma, V. L. (2020). Usability of online banking in India during COVID-19 pandemic. International Journal of Engineering and Management Research, 10(6), 69–72.
  • Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183. https://doi.org/10.2307/249751
  • Kline, R. B. (2015). Principles and practice of structural equation modelling. The Guilford Press.
  • Kumar Sharma, S., & Madhumohan Govindaluri, S. (2014). Internet banking adoption in India. Journal of Indian Business Research, 6(2), 155–169. https://doi.org/10.1108/JIBR-02-2013-0013
  • Laukkanen, T. (2007). Internet vs mobile banking: Comparing customer value perceptions. Business Process Management Journal, 13(6), 788–797. https://doi.org/10.1108/14637150710834550
  • Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB 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
  • Liébana-Cabanillas, F., Muñoz-Leiva, F., Sánchez-Fernández, J., & Viedma-del Jesús, M. I. (2016). The moderating effect of user experience on satisfaction with electronic banking: empirical evidence from the Spanish case. Information Systems and e-Business Management, 14(1), 141–165. https://doi.org/10.1007/s10257-015-0277-4
  • Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN). International Journal of Information Management, 34(2), 151–166. https://doi.org/10.1016/j.ijinfomgt.2013.12.006
  • Lu, C., Lai, K., & Cheng, T. C. E. (2006). Adoption of internet services in liner shipping: An empirical study of shippers in Taiwan. Transport Reviews, 26(2), 189–206. https://doi.org/10.1080/01441640500246713
  • Malaquias, R. F., & Hwang, Y. (2019). Mobile banking use: A comparative study with Brazilian and U.S. participants. International Journal of Information Management, 44, 132–140. https://doi.org/10.1016/j.ijinfomgt.2018.10.004
  • Masrek, M. N., Halim, M. S. A., Khan, A., & Ramli, I. (2018). The impact of perceived credibility and perceived quality on trust and satisfaction in mobile banking context. Asian Economic and Financial Review, 8(7), 1013–1025. https://ideas.repec.org/a/asi/aeafrj/2018p1013-1025.html https://doi.org/10.18488/journal.aefr.2018.87.1013.1025
  • McKechnie, S., Winklhofer, H., & Ennew, C. (2006). Applying the technology acceptance model to the online retailing of financial services. International Journal of Retail & Distribution Management, 34(4/5), 388–410. https://doi.org/10.1108/09590550610660297
  • Montazemi, A. R., & Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information & Management, 52(2), 210–226. https://doi.org/10.1016/j.im.2014.11.002
  • Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), 25–38. https://doi.org/10.1016/j.sjme.2016.12.001
  • Naeem, M., & Ozuem, W. (2021). The role of social media in internet banking transition during COVID-19 pandemic: Using multiple methods and sources in qualitative research. Journal of Retailing and Consumer Services, 60, 102483. https://doi.org/10.1016/j.jretconser.2021.102483
  • National Institute of Statistics. (2019). Survey on equipment and use of information and communications technology in households. Year 2019. https://www.ine.es/prensa/tich_2019.pdf
  • National Observatory of Telecommunications and Information Society. (2019). Report on the information society and telecommunications and the ICT and content sector in Spain by autonomous communities (Spain). https://www.ontsi.red.es/sites/ontsi/files/2019-10/InformeEspaña.pdf
  • Nui Polatoglu, V., & Ekin, S. (2001). An empirical investigation of the Turkish consumers’ acceptance of internet banking services. International Journal of Bank Marketing, 19(4), 156–165. https://doi.org/10.1108/02652320110392527
  • OECD. (2018). Bridging the rural digital divide. OECD Digital Economy Papers 265. https://doi.org/10.1787/852bd3b9-en
  • Oyeleye, O., Sanni, M., & Shittu, T. (2015). An investigation of the effects of customer’s educational attainment on their adoption of e-banking in Nigeria. The Journal of Internet Banking and Commerce, 20(3), 133. https://doi.org/10.4172/1204-5357.1000133
  • Özbay, R. D., Dinçer, H., & Hacioglu, Ü. (2011). Internet based innovation strategy for the banks in the era of 2008 global financial crisis. International Journal of Business and Social Science, 2(22).
  • Pallister, J. G., Wang, H. C., & Foxall, G. R. (2007). An application of the style/involvement model to financial services. Technovation, 27(1–2), 78–88. https://doi.org/10.1016/j.technovation.2005.10.001
  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. https://doi.org/10.1108/10662240410542652
  • Prodanova, J., San-Martín, S., & Jiménez, N. (2015). The present and the future of m-banking according to spanish bank customers. Universia Business Review, pp. 94–117.
  • Rawashdeh, A. (2015). Factors affecting adoption of internet banking in Jordan. International Journal of Bank Marketing, 33(4), 510–529. https://doi.org/10.1108/IJBM-03-2014-0043
  • Rifon, N. J., LaRose, R., & Choi, S. M. (2005). Your privacy is sealed: Effects of web privacy seals on trust and personal disclosures. Journal of consumer affairs, 39(2), 339–362. https://doi.org/10.1111/j.1745-6606.2005.00018.x
  • Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results. Industrial Management & Data Systems, 116(9), 1865–1886. https://doi.org/10.1108/IMDS-10-2015-0449
  • Ringle, C. M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. SmartPLS GmbH.
  • Samantha, M. K. (2020). Dirty money: The case against using cash during the coronavirus outbreak. CNN. Retrieved May 16, 2020, https://edition.cnn.com/2020/03/07/tech/mobile-payments-coronavirus/index.html
  • Sarstedt, M., Henseler, J., & Ringle, C. M. (2011). Multigroup analysis in partial least squares (PLS) path modeling: Alternative methods and empirical results. In M. Sarstedt, M. Schwalger, & C. R. Taylor (Eds.), Advances in international marketing (pp. 195–218). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2011)0000022012
  • Sathye, M. (1999). Adoption of Internet banking by Australian consumers: An empirical investigation. International Journal of Bank Marketing, 17(7), 324–334. https://doi.org/10.1108/02652329910305689
  • Sociological Research Centre. (2019). Report of activities 2018. http://www.cis.es/cis/export/sites/default/-Archivos/Memorias/MEMORIA_CIS_2018.pdf
  • Sociological Research Centre. (2020). Report of activities 2019. http://www.cis.es/cis/export/sites/default/-Archivos/Memorias/MEMORIA_CIS_2019.pdf
  • Suki, N. M. (2010). An empirical study of factors affecting the Internet banking adoption among Malaysian consumers. Journal of Internet Banking and Commerce, 15(2), 1–11. https://cutt.ly/LjTIcRZ
  • Walker, R. H., & Johnson, L. W. (2006). Why consumers use and do not use technology‐enabled services. Journal of Services Marketing, 20(2), 125–135. https://doi.org/10.1108/08876040610657057
  • White, H., & Nteli, F. (2004). Internet banking in the UK: Why are there not more customers? Journal of Financial Services Marketing, 9(1), 49–56. https://doi.org/10.1057/palgrave.fsm.4770140
  • Wu, Y. W., Wen, M. H., Chen, C. M., & Hsu, I. T. (2016). An integrated BIM and cost estimating blended learning model - Acceptance differences between experts and novice. EURASIA Journal of Mathematics, Science and Technology Education, 12(5), 1347–1363. https://doi.org/10.12973/eurasia.2016.1517a
  • Xue, M., Hitt, L. M., & Chen, P. (2011). Determinants and outcomes of internet banking adoption. Management Science, 57(2), 291–307. https://doi.org/10.1287/mnsc.1100.1187
  • Yaghoubi, N.-M., & Bahmani, E. (2010). Factors affecting the adoption of online banking: An integration of technology acceptance model and theory of planned behavior. Pakistan Journal of Social Sciences, 7(3), 231–236. https://doi.org/10.3923/pjssci.2010.231.236
  • Yang, K., & Lee, H. (2010). Gender differences in using mobile data services: Utilitarian and hedonic value approaches. Journal of Research in Interactive Marketing, 4(2), 142–156. https://doi.org/10.1108/17505931011051678
  • Ye, C., & Potter, R. (2011). The role of habit in post-adoption switching of personal information technologies: An empirical investigation. Communications of the Association for Information Systems, 28, 35. https://doi.org/10.17705/1CAIS.02835
  • Yee-Loong Chong, A., Liu, M. J., Luo, J., & Keng-Boon, O. (2015). Predicting RFID adoption in healthcare supply chain from the perspectives of users. International Journal of Production Economics, 159, 66–75. https://doi.org/10.1016/j.ijpe.2014.09.034
  • Yen, Y.-S., & Wu, F.-S. (2016). Predicting the adoption of mobile financial services: The impacts of perceived mobility and personal habit. Computers in Human Behavior, 65, 31–42. https://doi.org/10.1016/j.chb.2016.08.017
  • Zhang, T., Lu, C., & Kizildag, M. (2018). Banking “on-the-go”: Examining consumers’ adoption of mobile banking services. International Journal of Quality and Service Sciences, 10(3), 279–295. https://doi.org/10.1108/IJQSS-07-2017-0067