Aplicabilidade da teoria unificada de aceitação e uso da tecnologia em serviços de streaming musical em jovens usuários
DOI:
https://doi.org/10.5585/remark.v18i1.4031Palavras-chave:
Transmissão de música, Aplicabilidade, UTAUT2, Pessoas jovens.Resumo
Objetivo: O objetivo deste estudo é analisar a aplicabilidade do modelo Unified Theory of Acceptance and use of Technology 2 (UTAUT2), desenvolvido por Venkatesh, Thong e Xu (2012), sobre aceitação e utilização de serviço de streaming musical por estudantes universitários.
Método: Assim, este estudo não se propõe a realizar uma replicação de pesquisa, mas sim a utilização de um modelo teórico consagrado. A pesquisa, do tipo survey, contemplou uma amostra final de 419 indivíduos, cujos dados foram analisados por meio da Modelagem de Equações Estruturais (MEE), com estimação por Partial Least Square (PLS), para verificar as relações diretas e indiretas do modelo original.
Resultados: A variável latente Condições Facilitadoras não se sustentou no modelo na fase de ajustamento, pois o perfil analisado demonstra facilidade e uso intuitivo no acesso a esse tipo de infraestrutura. Ademais, os resultados demonstraram que a maior parte do modelo é válida para o serviço de streaming musical, com exceção da Expectativa de Esforço para Intenção de Uso e Motivação Hedônica para Intenção de Uso.
Contribuições teóricas: Verificou-se que o construto Hábito é altamente relevante para o consumo desses serviços, possibilitando que as empresas busquem alternativas para a geração de maior motivação e engajamento com os aplicativos e sites que estimulem o consumidor.
Originalidade/Relevância: O uso do modelo UTAUT 2, para analisar o fenômeno da tecnologia streaming, é relevante para a compreensão dos seus efeitos.
Downloads
Referências
Aarts, H., Verplanken, B. & Knippenberg, A. V. (1998). Predicting behavior from actions in the past: repeated decision making or a matter of habit? Journal of Applied Social Psychology, v.28, Issue 15, 1355–1374, DOI: 10.1111/j.1559-1816.1998.tb01681.x
Ajzen, I. & Madden, T. J. (1986). Prediction of goal-directed behavior: attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 453–474, DOI: 10.1016/0022-1031(86)90045-4
Alazzam, M. B., Basari, S. H., Sibghatullah, A. S., Ramli, M. R., Jaber, M. M., & Naim, M. H. (2016). Pilot study of ehrs acceptance in jordan hospitals by utaut2. Journal of Theoretical and Applied Information Technology, v. 85, n. 3.
Anderson, K. C., Knight, D. K., Pookulangara, S., & Josiam, B. (2014). Influence of hedonic and utilitarian motivations on retailer loyalty and purchase intention: a facebook perspective. Journal of Retailing and Consumer Services, v. 21, n. 5, p. 773-779.
Bi, Z., Xu, D. L. & Wang, C. (2014). Internet of things for enterprise systems of modern manufacturing. IEEE Transactions on Industrial Informatics, 10, 1537–1546, DOI: 10.1109/TII.2014.2300338
Boksberger, P. E., & Melsen L. (2011). “Perceived value: a critical examination of definitions, concepts and measures for the service industry,” Journal of Services Marketing, 25(3), 229–240, ISSN: 0887-6045
Brown, S. A., Venkatesh, V. (1989). “Model of Adoption of Technology in the Household: A Baseline Model Test and F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, 13(3), 319–340, ISSN: 0276-778
Burkart, P. (2008). Trends in Digital Music Archiving. Information Society, 24(4), 246-250.
DOI:10.1080/01972240802191621
Burke, R. R. (2002). “Technology and the customer interface: what consumers want in the physical and virtual store,” Journal of the Academy of Marketing Science, 30(4), 411–432, DOI: 10.1177/009207002236914, ISSN 0092-0703
Capapé, E., & Ojer, T. (2012). Nuevos modelos de negocio en la distribución de contenidos audiovisuales: el caso de Netflix. Revista Comunicación, v.1, n. 10, p. 187-200. ISSN 1989-600X
Chin, W. W. (1994). PLS-Graph Manual, unpublished, University of Calgary.
Chong. A.Y.-L (2013). “Mobile commerce usage activities: the roles of demographic and motivation variables,” Technological Forecasting and Social Change, 80(7), 1350–1359, DOI: 10.1016/j.techfore.2012.12.011
Davis, F. D. (1989). “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information” MIS Quarterly, Vol. 13, No. 3 (Sep. 1989), pp. 319-340, DOI: 10.2307/249008
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). “Effects of price, brand, and store information on buyers’ product evaluations,” Journal of Marketing Research, 28, 307–319, DOI: 10.2307/3172866
Financial Time: “How streaming saved the music industry” 2017 https://www.ft.com/content/cd99b95e-d8ba-11e6-944b-e7eb37a6aa8e?mhq5j=e2 Acessado em: 08/06/2017
Fornell, C., Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50, DOI: 10.2307/3151312
Gupta, A.; Dogra, N.; George, B. (2018). What determines tourist adoption of smartphone apps? An analysis based on the UTAUT-2 framework. Journal of Hospitality and Tourism Technology, Vol. 9 Issue: 1, pp.50-64, DOI: 10.1108/JHTT-02-2017-0013
Giovanis, A. N., Tomaras, P., & Zondiros D. (2013). “Suppliers logistics service quality performance and its effect on retailers’ behavioral intentions”, Procedia-Social and Behavioral Sciences, 73, 302–309, DOI: 10.1016/j.sbspro.2013.02.056
Hair, J. R., Black, W. C., Babin, B. J., Anderson, R. E. & Tatham, R. L. (2006). Multivariate Data Analysis. 6ª Ed. Upper Saddle River, NJ: Pearson Prentice Hall, ISBN: 9780138132309
Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications. DOI: 10.1080/1743727X.2015.1005806
Helkkula, Aapeli. (2016). Consumers’ Intentions to Subscribe to Music Streaming Services (title of thesis – master’s degree). Aalto University, P.O. BOX 11000, 00076, 2016. p. 1-50.
Hermann, L. A. (2012). A convergência midiática e as mudanças comportamentais no consumo do mercado de nicho: Netflix e a “desmaterialização” dos produtos. Animus Revista Interamericana de Comunicação Midiática, v. 11, n. 22, 2012.
Herrero, A., Martín, H. S., & Salmones, M. M. G. (2017). Explaining the adoption of social networks sites for sharing user generated content: A revision of the UTAUT2. Computers in Human Behavior, v. 71, p. 209-217, DOI: 10.1016/j.chb.2017.02.007
IFPI (International Federation of the Phonographic Industry) (2016). “Consumer Research e http://www.ifpi.org/facts-and-stats.php
Jeng, D. J.-F. & Tzeng, G. -H (2012). “Social influence on the use of clinical decision support systems: revisiting the unified theoryof acceptance and use of technology by the fuzzy DEMATELtechnique,” Computers and Industrial Engineering, vol. 62(3), 819–828, DOI: 10.1016/j.cie.2011.12.016
Kim, H.-W., Chan H. C., & Gupta S. (2007). “Value-based adoption of mobile internet: an empirical investigation,” Decision Support Systems, 43(1), 111–126, DOI:10.1016/j.dss.2005.05.009
Kit, A. K. L. (2014). UTAUT2 influencing the behavioural intention to adopt mobile applications. Tese (Doutorado). University Tunku Abdul Rahman.
Lee, C. (2013). Streaming media service based on fuzzy similarity in wireless mobile networks. Journal of Supercomputing, 65(1), 86-105. DOI: 10.1007/s11227-012-0778-6
Li, S., Xu, D. L. & Zhao, S. (2015). The internet of things: a survey. Information Systems Frontiers, 17, 243–259, DOI: 10.1007/s10796-014-9492-7
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). “How habit limits the predictive power of intention: the case of information systems continuance,” MIS Quarterly: Management Information Systems, 31(4), 705–737, DOI: 10.2307/25148817
Loureiro, S. M. C.; Cavallero, L.; Miranda, F. J. (2018). Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth. Journal of Retailing and Consumer Services, v. 41, p. 131-141.
Madigan, R., Louw, T., Dziennus, M., Graindorge, T., Ortega, E., Graindorge, M., & Merat, N. (2016). Acceptance of automated road transport systems (ARTS): an adaptation of the UTAUT model. Transportation Research Procedia, v. 14, p. 2217-2226.
Magni, M., Taylor, M. S. & Venkatesh V. (2010). “To play or not to play”: a cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology,” International Journal of Human Computer Studies, 68(9), 572–588, DOI: 10.1016/j.ijhcs.2010.03.004
Malhotra, N. K. (2014). Essentials of Marketing Research: A Hands-On Orientation. Prentice Hall, 1Edition, January 20, ISBN-13: 978-0137066735
Mishra, A., Maheswarappa, S. S., Maity, M., & Samu, S. (2017). Adolescent's eWOM intentions: An investigation into the roles of peers, the Internet and gender. Journal of Business Research. 86, 394-405, DOI: 10.1016/j.jbusres.2017.04.005
Neufeld, D. J.; Dong, L.; Higgins, C. (2007). Charismatic Leadership and User Acceptance of Information Technology. European Journal of Information Systems, 16(4), 494-510, DOI: 10.1057/palgrave.ejis.3000682
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press, ISBN-13: 978-0743222099
Ryan, R. M. & Deci, E. L. (2000). “Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being,” American Psychologist, 55(1), 68–78, DOI: 10.1037110003-066X.55.1.68
Silva, G. A. Alves da., & Hamza, K. M. (2017). Comportamento do consumidor de streaming de vídeo sob a ótica da extensão da teoria unificada de aceitação e uso da tecnologia. EnANPAD 2017, São Paulo/SP – 01 a 04 de Outubro.
Singh, M., Matsui, Y. (2018). How Long Tail and Trust Affect Online Shopping Behavior: An Extension to UTAUT2 Framework. Pacific Asia Journal of the Association for Systems, v. 9, n. 4.
Soltani, I. & Gharbi, J. (2008). “Determinants and consequences of the website perceived value”, Journal of Internet Banking and Commerce 13(1):1-13
Tandon, U., Kiran, R., & Sah, A. N. (2016). Understanding online shopping adoption in India: unified theory of acceptance and use of technology 2 (UTAUT2) with perceived risk application. Service Science, v. 8, n. 4, p. 420-437.
Tarhini, A., El-Masri, M., Ali, M. & Serrano, A. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon: A structural equation modeling approach. Information Technology & People, v. 29, n. 4, p. 830-849.
Teo, T. S. H., Lim. V. K. G & Lai. R. Y. C. (1999). “Intrinsic and extrinsic motivation in Internet usage,” Omega, 27(1), 25–37, DOI: 10.1016/S0305-0483(98)00028-0
The Guardian Web Wise: What is a streaming. (2012). http://www.bbc.co.uk/webwise/guides/about-streaming Acessado em: 08/06/2017
Thompson, R. L., C. A. Higgins C. A., Howell. J. M. (1991). “Personal computing: toward a conceptual model of utilization,” MIS Quarterly, 15(1), 125–143, DOI: 10.2307/249443
Venkatesh, V.; Morris, M.; Davis, G.; Davis D. (2003). “User acceptance of information technology: toward a unified view”. MIS Quarterly, 27(3), 425-478, DOI: 10.2307/30036540
Venkatesh, V., Thong, J. Y. L., Xu, X. (March 2012). “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology”. MIS Quarterly, 36(1), 157-178, ISSN:0276-7783
Vrijens, J. (2013). Online streaming: De redding van de muziekindustrie? (master’s degree), Communicatiewetenschappen.
Whitmore, A., Agarwal, A. & Xu, L. D. (2015). The internet of things - a survey of topics and trends. Information Systems Frontiers, 17, 261–274, DOI:10.1007/s10796-014-9489-2
Xu, B., Xu, D. L., Cai, H., Xie, C., Hu, J. & Bu, F. (2014). Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Transactions on Industrial Informatics, 10, 1578–1586, DOI: 10.1109/TII.2014.2306382
Zeithaml, V. A. (1988). “Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence,” The Journal of Marketing, 52(3), 2–22, DOI: 10.2307/1251446
Zhao L., Lu, Y., Zhang, L. & Chau, P. Y. K. (2012). “Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: an empirical test of a multidimensional model,” Decision Support Systems, 52(3), 645–656, DOI: 10.1016/j.dss.2011.10.022
Zhou, T. & Lu, Y. (2011). “Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience,” Computers in Human Behavior, 27(2), 883–889, DOI: 10.1016/j.chb.2010.11.013
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2019 Revista Brasileira de Marketing – Remark
Este trabalho está licenciado sob uma licença Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.