Estudio sobre la necesidad de un nuevo Modelo de Aceptación de Tecnología

Contenido principal del artículo

Fábio Corrêa
https://orcid.org/0000-0002-2346-0187
Dárlinton Barbosa Feres Carvalho
https://orcid.org/0000-0003-3844-0178
Vinícius Figueiredo de Faria
https://orcid.org/0000-0002-3924-7647
João Victor Boechat Gomide
https://orcid.org/0000-0001-6907-2692

Resumen

Esta investigación tiene como objetivo analizar las aplicaciones prácticas del Modelo de Aceptación de Tecnología para verificar si existe una mayor recurrencia de la versión original o sus variaciones. Es una investigación básica exploratoria con enfoque cualitativo para el análisis. Los documentos bibliográficos científicos se analizan mediante una revisión sistemática de la literatura y un análisis de contenido. Como resultado, en primer lugar, el predominio práctico de la aplicación del Modelo de Aceptación de Tecnología proviene de sus ampliaciones y adaptaciones y no de sus modelos originales. No significa que los predictores de las versiones originales sean inadecuados, sino que, según la tecnología y el punto de vista del investigador, se aprovechan mejor con ajustes. En segundo lugar, dado el resultado anterior, se concluye que el Modelo de Aceptación de Tecnología es teóricamente robusto; de lo contrario, no se producirían adaptaciones y ampliaciones. La tercera conclusión surge de las anteriores y se establece a partir de una reflexión: ¿se exige una actualización, denominada Modelo 4 de Aceptación de Tecnología? Entendemos que ¡no! Dado que se encontraron 401 adaptaciones y 198 extensiones, la propuesta de una estructura más no acabaría con las diferentes perspectivas de predictores a incluir en futuras investigaciones.

Descargas

Los datos de descargas todavía no están disponibles.

Detalles del artículo

Cómo citar
Corrêa, F., Carvalho, D. B. F., Figueiredo de Faria, V., & Boechat Gomide, J. V. (2025). Estudio sobre la necesidad de un nuevo Modelo de Aceptación de Tecnología. Revista De Ciencia Y Tecnología, 44(1), 85–96. https://doi.org/10.36995/j.recyt.2025.44.009
Sección
Notas Técnicas
Recibido 2024-05-07
Aceptado 2025-05-13
Publicado 2025-11-20

Citas

Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13,3:319–340.

Venkatesh, V., & Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 462:186–204.

Venkatesh, V. & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 392:273–315.

Villa, E.J.E., Marín, V.I., & Salinas, J. (2021). Research Skills for Information Management: Uses of Mobile Devices in Research Training. Education Sciences, 11:749–760.

Knox, L., Gemine, R., Rees, S., Bowen, S., Groom, P., Taylor, D., & Lewis, K. (2021). Using the Technology Acceptance Model to conceptualise experiences of the usability and acceptability of a self-management app (COPD. Pal®) for Chronic Obstructive Pulmonary Disease. Health and technology, 11,1:111–117.

Silva, G., Mendes Filho, L., & Marques Júnior, S. (2022). Intenção de usar criptomoedas por gestores de empreendimentos turísticos: uma abordagem utilizando o Technology Acceptance Model (TAM). Revista Brasileira de Pesquisa em Turismo, 16:1–15.

Adji, H.I., & Taufik, T.A. (2022). Analysis of the adoption and commercialization of XYZ app using TRL, CRL, TRI2 and TAM2. In: The 5th International Conference on Management of Technology, Innovation, and Project, 1–9.

Kusumastuti, R., Touriano, D., Rosita, S., & Fatricia, R. S. (2022). Effectiveness of accrual basis accounting system in state budget and treasury system in TAM 3 framework. Journal of Islamic Accounting and Finance Research, 4:1, 97–130.

Al-Dokhny, A., Drwish, A., Alyoussef, I., & Al-Abdullatif, A. (2021). Students’ intentions to use distance education platforms: An investigation into expanding the technology acceptance model through social cognitive theory. Electronics, 10,23:2992–3015.

Zhang, X., Tlili, A., Shubeck, K., Hu, X., Huang, R., & Zhu, L. (2021). Teachers’ adoption of an open and interactive e-book for teaching K-12 students Artificial Intelligence: a mixed methods inquiry. Smart Learning Environments, 8,1:1-20.

Garcia, S.F.A., Bottaro, H.Z., da Silva, D.D.S., & Galli, L.C.D.L.A. (2020). O impacto da facilidade de uso percebida na adoção do Instagram. In: XXIII Seminários em Administração, SemeAd, 1–15.

Marikyan, D., & Papagiannidis, S. (2022) Technology Acceptance Model: A review. In Papagiannidis, S. (Ed), TheoryHub Book. http://open.ncl.ac.uk

Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021). The extended Unified Theory of Acceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation. International Journal of Information Management, 57, 102269.

Fishbein,M, & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: an Introduction to Theory and Research.

Davis, F.D., Bagozzi, R.P., & Warshaw, P.R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management Science, 35,8:982–1003.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84,2:191–215.

Moore, G.C.I., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Inform. Systems Res, 2:192–222.

Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating perceived behavioral control, computer anxiety and enjoyment into the technology acceptance model. Information Systems Research, 11:342–365.

Bardin, L. (1977). Análise de Conteúdo.

Dresch, A, Lacerda, D. P., & Antunes Jr., J. A. V. (2020). Design Science Research: Método de Pesquisa para Avanço da Ciência e Tecnologia.

Falagalas, M.E., Pitsouni, E.I., Malietzis, G.A., & Pappas, G. (2008). Comparison of PubMed, Scopus, web of science, and Google scholar: strengths and weaknesses. The FASEB journal, 22,2:338–342.

Faria, V.F., Corrêa, F., Lima, P.P., Santos Jr, Z., & Dutra, F. G.C. (2022). Propósitos para mensuração do Capital Intelectual. Fronteiras de Representação do Conhecimento, 1:105–112.

Estrada Villa, E. J., Marín, V. I., & Salinas, J. (2021). Research skills for information management: Uses of mobile devices in research training. Education Sciences, 11(11), 749.

D’Souza, D.J., Joshi, H.G., & Prabhu, R. (2021). Assessment of Consumers Acceptance of E-Commerce to Purchase Geographical Indication Based Crop Using Technology Acceptance Model (TAM). Agris On-line Papers in Economics and Informatics, 13,3:25–33.

Oliveira Jr, E., Zorzo, A.F., & Neu, C.V. (2020). Towards a conceptual model for promoting digital forensics experiments. Forensic Science International: Digital Investigation, 35:1–15.

Saadatzi, M.N., Logsdon, M.C., Abubakar, S., Das, S., Jankoski, P., Mitchell, H., Chlebowy, D., & Popa, D.O. (2020). Acceptability of using a robotic nursing assistant in health care environments: experimental pilot study. Journal of medical Internet research, 22,11:1–7.

Al-Maroof, R.A.S., & Al-Emran, M. (2018). Students acceptance of google classroom: An exploratory study using PLS-SEM approach. International Journal of Emerging Technologies in Learning, 13,6:112–123.

Caffaro, F., Cremasco, M.M., Roccato, M., & Cavallo, E. (2020). Drivers of farmers’ intention to adopt technological innovations in Italy: The role of information sources, perceived usefulness, and perceived ease of use. Journal of Rural Studies, 76:264–271.

Michels, M., Hobe, C.F.V., Ahlefeld, P.J.W.V., & Musshoff, O. (2021). The adoption of drones in German agriculture: a structural equation model. Precision Agriculture, 22,6: 1728–1748.

Bhardwaj, A.K., Garg, A., & Gajpal, Y. (2021). Determinants of Blockchain Technology Adoption in Supply Chains by Small and Medium Enterprises (SMEs) in India. Mathematical Problems in Engineering, 2021:1–14.

Jaiswal, D., Kaushal, V., Kant, R., & Singh, P.K. (2021). Consumer adoption intention for electric vehicles: Insights and evidence from Indian sustainable transportation. Technological Forecasting and Social Change, 173:1–13.

Martins M., & Costa, C. (2021). Are the Portuguese ready for the future of tourism? A technology acceptance model application for the use of robots in tourism. Journal of Tourism and Development, 36,2:39–54.

Al-Maroof, R.S., Alhumaid, K., Alhamad, A.Q., Aburayya, A., & Salloum, S. (2021). User acceptance of smart watch for medical purposes: an empirical study. Future Internet, 13,5:1–19.

Kim, A.J., Yang, J., Jang, Y., & Baek, J.S. (2021). Acceptance of an Informational Antituberculosis Chatbot Among Korean Adults: Mixed Methods Research. JMIR mHealth and uHealth, 9,11:1–17.

Bauerová, R., & Klepek, M. (2018). Technology acceptance as a determinant of online grocery shopping adoption. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 66,3:737–746.

Nadeem, M.A., Liu, Z., Pitafi, A.H., Younis, A., & Xu, Y. (2021). Investigating the adoption factors of cryptocurrencies—a case of bitcoin: empirical evidence from China. SAGE open, 11,1:1–15

Mohammed, A.H., Mousa, A.H., Almeyali, N.M., & Nasir, I.S. (2021). M2CIM-DSS: A Model for Measuring Continuance Intention in Decision Support Systems. Indonesian Journal of Electrical Engineering and Informatics, 9-3:756–765.

Contador de visualizaciones: Resumen : 0 vistas.