Aceptación e uso da tecnoloxía: a influencia no consumo no sector bancario colombiano
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Este traballo de investigación pretende identificar a relación entre os elementos da Teoría Unificada de Aceptación e Uso da Tecnoloxía (UTAUT), a intención conductual de uso da tecnoloxía e o consumo real da mesma entre usuarios do sector bancario colombiano. Utilizouse unha análise factorial e un modelo de ecuacións estruturais para analizar o impacto da expectativa de desempeño, a expectativa de esforzo, a influencia social e as condicións facilitadoras sobre a intención conductual e o consumo real de tecnoloxía nunha mostra de 556 consumidores do sector bancario colombiano. Os resultados suxiren que a expectativa de esforzo e as condicións facilitadoras predín a intención de comportamento e o consumo real de tecnoloxía na poboación estudada, mentres que a influencia social e a expectativa de desempeño non o fan. En conclusión, recoméndase ás entidades financeiras entender o comportamento do consumidor para manter relacións relevantes, competitivas e rendibles cos seus clientes nunha contorna financeira dinámica.
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Alam, S. S., Makmor, N., Masukujjaman, M., Makhbul, Z. K. M., Ali, M. H., & Al Mamun, A. (2023). Integrating the social support theory and technology acceptance model of social commerce websites. Revista Galega de Economía, 32(2), 1-24. https://doi.org/10.15304/rge.32.2.8558
Al-Mamary, Y. H. (2022). Understanding the use of learning management systems by undergraduate university students using the UTAUT model: Credible evidence from Saudi Arabia. International Journal of Information Management Data Insights, 2(2), 100092. https://doi.org/10.1016/j.jjimei.2022.100092
Almogren, A. S. (2022). Art education lecturers’ intention to continue using the blackboard during and after the COVID-19 pandemic: An empirical investigation into the UTAUT and TAM model. Frontiers in Psychology, 13, 944335. https://doi.org/10.3389/fpsyg.2022.944335
Antioco, M. & Kleijnen, M. (2010). Consumer adoption of technological innovations: Effects of psychological and functional barriers in a lack of content versus a presence of content situation. European Journal of Marketing, 44(11/12), 1700-1724. https://doi.org/10.1108/03090561011079846
Arfi, W. B., Nasr, I. B., Kondrateva, G., & Hikkerova, L. (2021). The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context. Technological Forecasting and Social Change, 167, 120688. https://doi.org/10.1016/j.techfore.2021.120688
Bercht, A. L. (2019). Sleepwalking into disaster? Understanding coping in the broader field of mental barriers. Examples from the Norwegian Arctic in the face of climate change. Disaster Research and the Second Environmental Crisis: Assessing the Challenges Ahead, 137-160. https://doi.org/10.1007/978-3-030-04691-0_7
Bhatt, V. (2021). An empirical study to evaluate factors affecting customer satisfaction on the adoption of Mobile Banking Track: Financial Management. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 5354-5373. https://doi.org/10.17762/turcomat.v12i10.5338
Calvo Dopico, D., del Castillo Puente, Á. M., & Arias Montero, S. R. (2021). Marketing strategies of global and local brands in developing economies: a comparative study in the Ecuadorian chocolate market. Revista Galega de Economía, 30(4), 1-19. https://doi.org/10.15304/rge.30.4.7824
Camoiras-Rodríguez, Z., & Varela-Neira, C. (2020). Mobile commerce purchase behaviour: The importance of personality traits. Revista Galega de Economía, 29(3), 1-22. https://doi.org/10.15304/rge.29.3.6787
Chan, C. K. Y., & Lee, K. K. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments, 10(1), 60. https://doi.org/10.1186/s40561-023-00269-3
Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652. https://doi.org/10.3389/fpsyg.2019.01652
Chaouali, W. & Souiden, N. (2019). The role of cognitive age in explaining mobile banking resistance among elderly people. Journal of Retailing and Consumer Services, 50, 342-350. https://doi.org/10.1016/j.jretconser.2018.07.009
Chen, P. Y., Yang, C. M., & Morin, C. M. (2015). Validating the cross-cultural factor structure and invariance property of the Insomnia Severity Index: evidence based on ordinal EFA and CFA. Sleep medicine, 16(5), 598-603. https://doi.org/10.1016/j.sleep.2014.11.016
Chung, K. C., & Liang, S. W. J. (2020). Understanding factors affecting innovation resistance of mobile payments in Taiwan: An integrative perspective. Mathematics, 8(10), 1841. https://doi.org/10.3390/math8101841
Cichosz, M., Wallenburg, C. M., & Knemeyer, A. M. (2020). Digital transformation at logistics service providers: barriers, success factors and leading practices. The International Journal of Logistics Management, 31(2), 209-238. https://doi.org/10.1108/IJLM-08-2019-0229
Dauda, S. Y., & Lee, J. (2015). Technology adoption: A conjoint analysis of consumers׳ preference on future online banking services. Information Systems, 53, 1-15. https://doi.org/10.1016/j.is.2015.04.006
Davis, F.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
Dos Santos, P. M., & Cirillo, M. Â. (2023). Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions. Communications in Statistics-Simulation and Computation, 52(4), 1639-1650. https://doi.org/10.1080/03610918.2021.1888122
Escobedo P. M. T., Hernández G. J. A., Estebané Ortega, V. y Martínez Moreno, G. (2016). Modelos de ecuaciones estructurales: características, fases, construcción, aplicación y resultados. Ciencia & trabajo, 18(55), 16-22. http://dx.doi.org/10.4067/S0718-24492016000100004
Filotto, U., Caratelli, M., & Fornezza, F. (2021). Shaping the digital transformation of the retail banking industry. Empirical evidence from Italy. European Management Journal, 39(3), 366-375. https://doi.org/10.1016/j.emj.2020.08.004
González Núñez, J. C., & Mariné Osorio, F. J. (2021). An econometric analysis of private insurance in the urban and rural population in Mexico. Revista Galega de Economía, 30(4), 1-19. https://doi.org/10.15304/rge.30.4.7682
Grieder, S. & Steiner, M. D. (2022). Algorithmic jingle jungle: A comparison of implementations of principal axis factoring and promax rotation in R and SPSS. Behavior research methods, 54(1), 54-74. https://doi.org/10.3758/s13428-021-01581-x
Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of enterprise information management, 28(6), 788-807.
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer Nature https://doi.org/10.1007/978-3-030-80519-7
Hayes, A. F. & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures, 14(1), 1-24. https://doi.org/10.1080/19312458.2020.1718629
Hossain, S. F. A., Xi, Z., Nurunnabi, M., & Hussain, K. (2020). Ubiquitous role of social networking in driving M-Commerce: evaluating the use of mobile phones for online shopping and payment in the context of trust. Sage Open, 10(3), https://doi.org/10.1177/2158244020939536
Huth, K. B., de Ron, J., Goudriaan, A. E., Luigjes, J., Mohammadi, R., van Holst, R. J., ... & Marsman, M. (2023). Bayesian analysis of cross-sectional networks: A tutorial in R and JASP. Advances in Methods and Practices in Psychological Science, 6(4), 251-264. https://doi.org/10.1177/2515245923119333
Kaur, S. J., Ali, L., Hassan, M. K., & Al-Emran, M. (2021). Adoption of digital banking channels in an emerging economy: exploring the role of in-branch efforts. Journal of Financial Services Marketing, 26, 107-121. https://doi.org/10.1057/s41264-020-00082-w
Khanra, S., Dhir, A., Kaur, P., & Joseph, R. P. (2021). Factors influencing the adoption postponement of mobile payment services in the hospitality sector during a pandemic. Journal of Hospitality and Tourism Management, 46, 26-39. https://doi.org/10.1016/j.jhtm.2020.11.004
Kitsios, F., Giatsidis, I., & Kamariotou, M. (2021). Digital transformation and strategy in the banking sector: Evaluating the acceptance rate of e-services. Journal of Open Innovation: Technology, Market, and Complexity, 7(3), 204. https://doi.org/10.3390/joitmc7030204
Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. L. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537-554. https://doi.org/10.1080/02642069.2015.1043278
Laukkanen, T. (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
Leesakul, N., Oostveen, A. M., Eimontaite, I., Wilson, M. L., & Hyde, R. (2022). Workplace 4.0: Exploring the implications of technology adoption in digital manufacturing on a sustainable workforce. Sustainability, 14(6), 3311. https://doi.org/10.3390/su14063311
Li, C. H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior research methods, 48, 936-949. https://doi.org/10.3758/s13428-015-0619-7
Liang, X., & Luo, Y. (2020). A comprehensive comparison of model selection methods for testing factorial invariance. Structural Equation Modeling: A Multidisciplinary Journal, 27(3), 380-395. https://doi.org/10.1080/10705511.2019.1649983
López-Rodríguez, C. E., & Sandoval-Escobar, M. (2023). Dimensions of brand equity for the banking sector: A study in the elderly segment. Journal of International Studies, 16(4), 205-219. https://doi.org/10.14254/2071-8330.2023/16-4/14
López-Rodríguez, C. E., & Cardozo-Munar, C. E. (2023). Current global overview of perceptions of mobile banking usage: a bibliometric analysis and systematic literature review. Universidad y Sociedad, 15(5), 395-409. https://rus.ucf.edu.cu/index.php/rus/article/view/4086
López-Rodríguez, C. E., & López-Ordoñez, D. A. (2022). Financial education in colombia: challenges from the perception of its population with socioeconomic vulnerability. Economics & Sociology, 15(1), 193-204. https://doi.org/10.14254/2071-789X.2022/15-1/12
López-Rodríguez, C. E., Sandoval-Escobar, M., & Sepúlveda Maldonado, J. A. (2024). Resistance to technological innovation and brand equity in the banking sector. Management & Marketing, 19(1). https://doi.org/10.2478/mmcks-2024-0006
López-Rodríguez, C. E., Sotelo-Muñoz, J. K., Muñoz-Venegas, I. J., & López-Aguas, N. F. (2024). Análisis de la multidimensionalidad del brand equity para el sector bancario: un estudio en la generación Z. RETOS. Revista de Ciencias de la Administración y Economía, 14(27), 9-20. https://doi.org/10.17163/ret.n27.2024.01
Louw, C., & Nieuwenhuizen, C. (2020). Digitalisation strategies in a South African banking context: A consumer services analysis. South African Journal of Information Management, 22(1), 1-8. https://sajim.co.za/index.php/SAJIM/article/view/1153
Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International journal of medical informatics, 84(1), 36-47. https://doi.org/10.1016/j.ijmedinf.2014.09.004
Marinković, V., Đorđević, A., & Kalinić, Z. (2020). The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: a UTAUT-based perspective. Technology Analysis & Strategic Management, 32(3), 306-318. https://doi.org/10.1080/09537325.2019.1655537
Martínez Jiménez, S. A. (2021). Retos del sistema financiero colombiano en la Cuarta Revolución Industrial. Semestre Económico, 24(56), 253-270. https://doi.org/10.22395/seec.v24n56a11
Maydeu-Olivares, A. (2017). Maximum likelihood estimation of structural equation models for continuous data: Standard errors and goodness of fit. Structural Equation Modeling: A Multidisciplinary Journal, 24(3), 383-394. https://doi.org/10.1080/10705511.2016.1269606
Mbama, C. I., & Ezepue, P. O. (2018). Digital banking, customer experience and bank financial performance: UK customers’ perceptions. International journal of bank marketing, 36(2), 230-255. https://doi.org/10.1108/IJBM-11-2016-0181
Monroy-Perdomo, L., Cardozo-Munar, C., Torres-Hernández, A., Tena-Galeano, J., & López-Rodríguez, C. E. (2022). Formalization of a new stock trend prediction methodology based on the sector price book value for the Colombian market. Heliyon, e09210. https://doi.org/10.1016/j.heliyon.2022.e09210
Morales, K., Casarín, A. V., & Salas, L. M. (2015). Apropiación tecnológica: Una visión desde los modelos y las teorías que la explican. Perspectiva Educacional, Formación de Profesores, 54(2), 109-125. https://doi.org/10.4151/07189729
Parida, V., Mostaghel, R. & Oghazi, P. (2016). Factors for elderly use of social media for health‐related activities. Psychology and Marketing, 33(12), 1134-1141. https://doi.org/10.1002/mar.20949
Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020). Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal. International Journal of Information Management, 54, 102144. https://doi.org/10.1016/j.ijinfomgt.2020.102144
Petersen, J. A., Kushwaha, T., & Kumar, V. (2015). Marketing communication strategies and consumer financial decision making: The role of national culture. Journal of marketing, 79(1), 44-63. https://doi.org/10.1509/jm.13.0479
Puspitasari, N., Firdaus, M. B., Haris, C. A., & Setyadi, H. J. (2019). An application of the UTAUT model for analysis of adoption of integrated license service information system. Procedia Computer Science, 161, 57-65. https://doi.org/10.1016/j.procs.2019.11.099
Samartha, V., Shenoy Basthikar, S., Hawaldar, I. T., Spulbar, C., Birau, R., & Filip, R. D. (2022). A study on the acceptance of mobile-banking applications in India—unified theory of acceptance and sustainable use of technology model (UTAUT). Sustainability, 14(21), 14506. https://doi.org/10.3390/su142114506
Shaikh, A. A., & Karjaluoto, H. (2015). Mobile banking adoption: A literature review. Telematics and informatics, 32(1), 129-142. https://doi.org/10.1016/j.tele.2014.05.003
Schulze, A., Townsend, J. D., & Talay, M. B. (2022). Completing the market orientation matrix: The impact of proactive competitor orientation on innovation and firm performance. Industrial Marketing Management, 103, 198-214. https://doi.org/10.1016/j.indmarman.2022.03.013
Theis, S., Lefore, N., Meinzen-Dick, R., & Bryan, E. (2018). What happens after technology adoption? Gendered aspects of small-scale irrigation technologies in Ethiopia, Ghana, and Tanzania. Agriculture and human values, 35, 671-684. https://doi.org/10.1007/s10460-018-9862-8
Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding concepts and applications. American Psychological Association. https://doi.org/10.1037/10694-000
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1994). Influence of experience on personal computer utilization: Testing a conceptual model. Journal of management information systems, 11(1), 167-187. https://doi.org/10.1080/07421222.1994.11518035
Tsindeliani, I. A., Proshunin, M. M., Sadovskaya, T. D., Popkova, Z. G., Davydova, M. A., & Babayan, O. A. (2022). Digital transformation of the banking system in the context of sustainable development. Journal of Money Laundering Control, 25(1), 165-180. https://doi.org/10.1108/JMLC-02-2021-0011
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
Venkatesh, V., Morris, M., Davis, G. & Davis, F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 27(3), 703–708. https://doi.org/10.2307/30036540
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428
Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology (UTAUT): a literature review. Journal of enterprise information management, 28(3), 443-488. https://doi.org/10.1108/JEIM-09-2014-0088
Yu, L., Chen, Z., Yao, P., & Liu, H. (2021). A study on the factors influencing users’ online knowledge paying-behavior based on the UTAUT model. Journal of theoretical and applied electronic commerce research, 16(5), 1768-1790. https://doi.org/10.3390/jtaer16050099