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

Contenido principal del artículo

Fábio Corrêa
Dárlinton Barbosa Feres Carvalho
Vinícius Figueiredo de Faria
João Victor Boechat Gomide

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.