Proposición y validación de un modelo teórico de satisfacción electrónica e intención de continuidad de uso de los servicios de streaming en Brasil
DOI:
https://doi.org/10.5007/2175-8077.2024.e73310Palabras clave:
Aceptación de la Tecnología, Satisfacción Electrónica, Intención de Continuidad de Uso, UTAUT2, Servicios de StreamingResumen
Objetivo: Proponer y probar un modelo teórico capaz de relacionar los factores que afectan la Satisfacción Electrónica y la Continuidad de Uso de los Servicios de Streaming entre los consumidores brasileños.
Metodología/enfoque: Se identificó el modelo UTAUT2 y otros factores que se agregaron al modelo como medio para identificar los antecedentes de Satisfacción Electrónica y Continuidad de Uso de los Servicios de Streaming. El modelo de investigación fue analizado con base en 389 respuestas válidas obtenidas a través de una encuesta. El análisis de los datos se realizó utilizando el software R y sus paquetes para Modelado de Ecuaciones Estructurales.
Originalidad/relevancia: Los Servicios de Streaming distribuyen contenido digital sin descargar. La literatura afirma que, con nuevas tecnologías, es esencial analizar factores comportamentales del consumidor.
Principales resultados: El modelo de investigación presentado explica el 83,1% de la variación en la Satisfacción Electrónica con los Servicios de Streaming y el 56,5% de la variación en la Continuidad de Uso.
Contribuciones teóricas: Los resultados amplían la teoría sobre los sistemas digitales de información y comunicación, explorando por primera vez la Satisfacción electrónica y el uso continuo del streaming en los negocios digitales.
Contribución a la gestión: Los gerentes que se enfocan en mejorar las expectativas de desempeño, facilitar las condiciones y la influencia social de los usuarios pueden aumentar significativamente la satisfacción electrónica y el uso continuo de los servicios de streaming.
Citas
Abu Salim, T., El Barachi, M., Onyia, O. P., & Mathew, S. S. (2021). Effects of smart city service channel- and user-characteristics on user satisfaction and continuance intention. Information Technology & People, 34(1), 147–177. https://doi.org/10.1108/ITP-06-2019-0300
Agarwal, R., & Karahanna, E. (2000). Time Flies When You’re Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage. MIS Quarterly, 24(4), 665. https://doi.org/10.2307/3250951
Agarwal, R., & Prasad, J. (1998). A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology. Information Systems Research, 9(2), 204–215. https://doi.org/10.1287/isre.9.2.204
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
Ajzen, I., & Fishbein, M. (1977). Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), 888–918. https://doi.org/10.1037/0033-2909.84.5.888
Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50(February 2019), 28–44. https://doi.org/10.1016/j.ijinfomgt.2019.04.008
Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100–110. https://doi.org/10.1016/j.techsoc.2018.06.007
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
Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology and Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063
Arun, M. T., Singh, S., Khan, S. J., Akram, M. U., & Chauhan, C. (2021). Just One More Episode : Exploring Consumer Motivations for Adoption of Streaming Services. Asia Pacific Journal of Information Systems, 31(1), 17–42. https://doi.org/10.14329/apjis.2021.31.1.17
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473. https://doi.org/10.1016/j.tele.2020.101473
Atkinson, N. L. (2007). Developing a Questionnaire to Measure Perceived Attributes of eHealth Innovations. American Journal of Health Behavior, 31(6), 612–621. https://doi.org/10.5993/AJHB.31.6.6
Atulkar, S. (2020). Brand trust and brand loyalty in mall shoppers. Marketing Intelligence & Planning, 38(5), 559–572. https://doi.org/10.1108/MIP-02-2019-0095
Baabdullah, A. M. (2018). Consumer adoption of Mobile Social Network Games (M-SNGs) in Saudi Arabia: The role of social influence, hedonic motivation and trust. Technology in Society, 53, 91–102. https://doi.org/10.1016/j.techsoc.2018.01.004
Brislin, R. W. (1970). Back-Translation for Cross-Cultural Research. Journal of Cross-Cultural Psychology, 1(3), 185–216. https://doi.org/10.1177/135910457000100301
Brown, & Venkatesh. (2005). Model of Adoption of Technology in Households: A Baseline Model Test and Extension Incorporating Household Life Cycle. MIS Quarterly, 29(3), 399. https://doi.org/10.2307/25148690
Cardozo, É. A. A., Christino, J. M. M., & de Carvalho, A. C. P. (2023). Digital bank accounts and digital credit cards: extending UTAUT2 to FinTech’s services in Brazil. International Journal of Services and Operations Management, 44(2), 238. https://doi.org/10.1504/IJSOM.2023.129049
Cesareo, L., & Pastore, A. (2014). Consumers’ attitude and behavior towards online music piracy and subscription-based services. Journal of Consumer Marketing, 31(6/7), 515–525. https://doi.org/10.1108/JCM-07-2014-1070
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(July), 1–14. https://doi.org/10.3389/fpsyg.2019.01652
Chemingui, H., & Ben lallouna, H. (2013). Resistance, motivations, trust and intention to use mobile financial services. International Journal of Bank Marketing, 31(7), 574–592. https://doi.org/10.1108/IJBM-12-2012-0124
Chen, C. C., Leon, S., & Nakayama, M. (2018). Converting music streaming free users to paid subscribers: social influence or hedonic performance. International Journal of Electronic Business, 14(2), 128. https://doi.org/10.1504/IJEB.2018.094870
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study. Information Systems Research, 14(2), 189–217. https://doi.org/10.1287/isre.14.2.189.16018
Chong, A. Y.-L., Ooi, K.-B., Lin, B., & Bao, H. (2012). An empirical analysis of the determinants of 3G adoption in China. Computers in Human Behavior, 28(2), 360–369. https://doi.org/10.1016/j.chb.2011.10.005
Christino, J., Cardozo, E., Carrieri, A. D. P., Petrin, R., & Silva, J. (2020). Understanding the adoption of co-working spaces. International Journal of Services and Operations Management, 1(1), 1. https://doi.org/10.1504/IJSOM.2022.124286
Christino, J., Cardozo, É., Petrin, R., & Pinto, L. (2021). Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps. Review of Business Management, 23(1), 21–42. https://doi.org/10.7819/rbgn.v23i1.4095
Chu, C., & Lu, H. (2007). Factors influencing online music purchase intention in Taiwan. Internet Research, 17(2), 139–155. https://doi.org/10.1108/10662240710737004
Collis, Jill; Hussey, R. (2005). Pesquisa em Administração: um guia prático para alunos de graduação e pós-graduação (2a). BookBoon.
Contreras Pinochet, L. H., Diogo, G. T., Lopes, E. L., Herrero, E., & Bueno, R. L. P. (2019). Propensity of contracting loans services from FinTech’s in Brazil. International Journal of Bank Marketing, 37(5), 1190–1214. https://doi.org/10.1108/IJBM-07-2018-0174
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/10.1016/S0305-0483(98)00028-0
De Sousa, P. R., Cardozo, É. A. A., & Christino, J. M. M. (2023). Business intelligence and analytics systems adoption: determinants and impacts on organisational performance and competitive advantage from a developing country perspective. International Journal of Business Information Systems, 1(1), 1–38. https://doi.org/10.1504/IJBIS.2023.10057844
Dejonghe, W. (2015). Netflix and the new U(TAUT) : een studie naar de validatie van het UTAUT2-model in de context van Netflix met betrekking tot Vlaanderen [Universidad de Gante - Bélgica]. https://lib.ugent.be/fulltxt/RUG01/002/217/624/RUG01-002217624_2015_0001_AC.pdf
Díaz, A., Gómez, M., & Molina, A. (2017). A comparison of online and offline consumer behaviour: An empirical study on a cinema shopping context. Journal of Retailing and Consumer Services, 38(November 2016), 44–50. https://doi.org/10.1016/j.jretconser.2017.05.003
Dörr, J., Wagner, T., Benlian, A., & Hess, T. (2013). Music as a Service as an Alternative to Music Piracy? Business & Information Systems Engineering, 5(6), 383–396. https://doi.org/10.1007/s12599-013-0294-0
El Refae, G. A., Kaba, A., & Eletter, S. (2021). Distance learning during COVID-19 pandemic: satisfaction, opportunities and challenges as perceived by faculty members and students. Interactive Technology and Smart Education, 18(3), 298–318. https://doi.org/10.1108/ITSE-08-2020-0128
Farah, Z., Mohamad, F., Napitupulu, D., Nazuar, S., & Roza, L. (2021). Analyzing Indonesian Students’ Google Classroom Acceptance During COVID-19 Outbreak: Applying an Extended Unified Theory of Acceptance and Use of Technology Model. European Journal of Educational Research, 10(4), 1697–1710. https://doi.org/10.12973/eu-jer.10.4.1697
Farooq, M. S., Salam, M., Jaafar, N., Fayolle, A., Ayupp, K., Radovic-Markovic, M., & Sajid, A. (2017). Acceptance and use of lecture capture system (LCS) in executive business studies. Interactive Technology and Smart Education, 14(4), 329–348. https://doi.org/10.1108/ITSE-06-2016-0015
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312
Ganguly, B., Dash, S. B., Cyr, D., & Head, M. (2010). The effects of website design on purchase intention in online shopping: the mediating role of trust and the moderating role of culture. International Journal of Electronic Business, 8(4–5), 302–330.
Hagen, A. N. (2015). The Playlist Experience: Personal Playlists in Music Streaming Services. Popular Music and Society, 38(5), 625–645. https://doi.org/10.1080/03007766.2015.1021174
Hair, 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 (1st ed.). Springer International Publishing. https://doi.org/10.1007/978-3-030-80519-7
Hampton-Sosa, W. (2017). An exploration of essential factors that influence music streaming adoption and the intention to engage in digital piracy. International Journal of Electronic Commerce Studies, 8(1), 97–134. https://doi.org/10.7903/ijecs.1458
Hampton-Sosa, W. (2019). The Access Model for Music and the Effect of Modification, Trial, and Sharing Usage Rights on Streaming Adoption and Piracy. Journal of Theoretical and Applied Electronic Commerce Research, 14(3), 126–155. https://doi.org/10.4067/S0718-18762019000300108
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing (First, Vol. 20, pp. 277–319). Emerald Group Publishing Limited.
Ho Cheong, J., & Park, M. (2005). Mobile internet acceptance in Korea. Internet Research, 15(2), 125–140. https://doi.org/10.1108/10662240510590324
Hracs, B. J., & Webster, J. (2021). From selling songs to engineering experiences: exploring the competitive strategies of music streaming platforms. Journal of Cultural Economy, 14(2), 240–257. https://doi.org/10.1080/17530350.2020.1819374
Hsu, C.-L., & Lin, J. C.-C. (2016). Effect of perceived value and social influences on mobile app stickiness and in-app purchase intention. Technological Forecasting and Social Change, 108, 42–53. https://doi.org/10.1016/j.techfore.2016.04.012
IFPI. (2017). Global music report 2017. International Federation of the Phonographic Industry, 1–44.
IFPI, I. F. of the P. I. (2021). IFPI issues Global Music Report 2021. https://www.ifpi.org/ifpi-issues-annual-global-music-report-2021/
Indrawati, I., & Utama, K. P. (2018). Analyzing 4G Adoption in Indonesia Using a Modified Unified Theory of Acceptance and Use of Technology 2. 2018 6th International Conference on Information and Communication Technology (ICoICT), 98–102. https://doi.org/10.1109/ICoICT.2018.8528744
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer Trust in an Internet Store. Information Technology and Management, 1(1), 45–71.
Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43(April), 342–351. https://doi.org/10.1016/j.jretconser.2018.04.001
Kim, J., Nam, C., & Ryu, M. H. (2017). What do consumers prefer for music streaming services?: A comparative study between Korea and US. Telecommunications Policy, 41(4), 263–272. https://doi.org/10.1016/j.telpol.2017.01.008
Kirk, C. P., & Rifkin, L. S. (2020). I’ll trade you diamonds for toilet paper: Consumer reacting, coping and adapting behaviors in the COVID-19 pandemic. Journal of Business Research, 117(Sep), 124–131. https://doi.org/10.1016/j.jbusres.2020.05.028
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). Guilford publications.
Laato, S., Islam, A. K. M. N., Farooq, A., & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services, 57(November 2020), 102224. https://doi.org/10.1016/j.jretconser.2020.102224
Leong, L.-Y., Hew, T.-S., Ooi, K.-B., & Wei, J. (2020). Predicting mobile wallet resistance: A two-staged structural equation modeling-artificial neural network approach. International Journal of Information Management, 51, 102047. https://doi.org/10.1016/j.ijinfomgt.2019.102047
Li, Z., & Cheng, Y. (2014). From free to fee: exploring the antecedents of consumer intention to switch to paid online content. Journal of Electronic Commerce Research, 15(4), 281.
Liao, C., Palvia, P., & Lin, H.-N. (2006). The roles of habit and web site quality in e-commerce. International Journal of Information Management, 26(6), 469–483. https://doi.org/10.1016/j.ijinfomgt.2006.09.001
Lu, J. (2014). Are personal innovativeness and social influence critical to continue with mobile commerce? Internet Research, 24(2), 134–159. https://doi.org/10.1108/IntR-05-2012-0100
Muthen, B., & Kaplan, D. (1992). A comparison of some methodologies for the factor analysis of non-normal Likert variables: A note on the size of the model. British Journal of Mathematical and Statistical Psychology, 45(1), 19–30. https://doi.org/10.1111/j.2044-8317.1992.tb00975.x
Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34–47. https://doi.org/10.1016/j.tele.2015.05.006
Okumus, B., Ali, F., Bilgihan, A., & Ozturk, A. B. (2018). Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants. International Journal of Hospitality Management, 72, 67–77. https://doi.org/10.1016/j.ijhm.2018.01.001
Pavlou, A. P. (2003). Consumer Acceptance of Electronic Commerce : Integrating Trust and Risk with the Technology Acceptance Model Consumer Acceptance of Electronic Commerce : Integrating Trust and Risk with the Technology Acceptance Model. International Journal of Electronic Commerce ISSN:, 7(3), 101–134. https://doi.org/10.1.1.86.7139
Pinochet, L. H. C., Nunes, G. N., & Herrero, E. (2019). Applicability of the unified theory of acceptance and use of technology in music streaming services for young users. Revista Brasileira de Marketing, 18(1), 147–162. https://doi.org/10.5585/remark.v18i1.4031
Polites, & Karahanna. (2012). Shackled to the Status Quo: The Inhibiting Effects of Incumbent System Habit, Switching Costs, and Inertia on New System Acceptance. MIS Quarterly, 36(1), 21. https://doi.org/10.2307/41410404
Praveena, K., & Sam, T. (2014). Continuance Intention to Use Facebook: A Study of Perceived Enjoyment and TAM. Bonfring International Journal of Industrial Engineering and Management Science, 4(1), 24–29. https://doi.org/10.9756/BIJIEMS.4794
Ramírez-Correa, P. E., Mello, T. M., & Mariano, A. M. (2018). A aceitação da Netflix: um estudo utilizando equações estruturais. Revista Tecnologia e Sociedade, 14(30), 71–82.
Ramírez-Correa, P., Mariano-Mello, T., & Melo-Mariano, A. (2017). Factors explaining the acceptance OF netflix IN Brazil: the role moderator OF the experience. 14th CONTECSI - International Conference on Information Systems and Technology Management, May, 497–505. https://doi.org/10.5748/9788599693131-14CONTECSI/PS-4468
Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology acceptance model (TAM) and social media usage: an empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. https://doi.org/10.1108/JEIM-04-2012-0011
Raza, S. A., Qazi, W., Khan, K. A., & Salam, J. (2021). Social Isolation and Acceptance of the Learning Management System (LMS) in the time of COVID-19 Pandemic: An Expansion of the UTAUT Model. Journal of Educational Computing Research, 59(2), 183–208. https://doi.org/10.1177/0735633120960421
Rogers, E. M. (1995). The Diffusion of Innovations (T. F. Press (ed.); 4th ed.). The Free Press, Simon and Schuster.
Sadana, M., & Sharma, D. (2021). How over-the-top (OTT) platforms engage young consumers over traditional pay television service? An analysis of changing consumer preferences and gamification. Young Consumers, 22(3), 348–367. https://doi.org/10.1108/YC-10-2020-1231
Samat, M. F., Awang, N. A., Hussin, S. N. A., & Mat Nawi, F. A. (2020). Online Distance Learning Amidst Covid-19 Pandemic Among University Students. Asian Journal of University Education, 16(3), 220. https://doi.org/10.24191/ajue.v16i3.9787
Santosa, A. D., Taufik, N., Prabowo, F. H. E., & Rahmawati, M. (2021). Continuance intention of baby boomer and X generation as new users of digital payment during COVID-19 pandemic using UTAUT2. Journal of Financial Services Marketing, 26(4), 259–273. https://doi.org/10.1057/s41264-021-00104-1
Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of Business Research, 117(Jun), 280–283. https://doi.org/10.1016/j.jbusres.2020.05.059
Sitar‐Tăut, D. (2021). Mobile learning acceptance in social distancing during the COVID-19 outbreak: the mediation effect of hedonic motivation. Human Behavior and Emerging Technologies, 3(3), 366–378. https://doi.org/10.1002/hbe2.261
Slade, E. L., Williams, M. D., & Dwivedi, Y. K. (2013). Delivered by Ingenta to : Guest User. The Marketing Review, 13(2). https://doi.org/10.1166/mex.2014.1172
Soares, J. L., Christino, J. M. M., Gosling, M. D. S., Vera, L. A. R., & Cardozo, É. A. A. (2020). Acceptance and use of e-hailing technology: a study of Uber based on the UTAUT2 model. International Journal of Business Information Systems, 34(4), 512–535. https://doi.org/10.1504/ijbis.2020.109019
Souza, K. N. de, Damacena, C., & Régio Brambilla, F. (2023). Aceitação e prontidão para uso de tecnologia em micro e pequenos negócios: atitudes e comportamentos na pandemia de Covid-19. Revista de Ciências Da Administração, 25(65). https://doi.org/10.5007/2175-8077.2023.e86990
Spilker, H. S., Ask, K., & Hansen, M. (2020). The new practices and infrastructures of participation: how the popularity of Twitch.tv challenges old and new ideas about television viewing. Information, Communication & Society, 23(4), 605–620. https://doi.org/10.1080/1369118X.2018.1529193
Statista. (2019a). Music Streaming - Worldwide - Statista Market Forecast. Digital Global Overview Report.
Statista. (2019b). Video Streaming (SVoD) - Worldwide - Statista Market Forecast. Global Digital Report 2019.
Sun, J., & Chi, T. (2018). Key factors influencing the adoption of apparel mobile commerce: an empirical study of Chinese consumers. The Journal of The Textile Institute, 109(6), 785–797. https://doi.org/10.1080/00405000.2017.1371828
Suoranta, M. (2003). Adoption of Mobile Banking in Finland. In Jyvaskyla Studies in Business and Economics.
Taylor, S. (2021). Campus dining goes mobile: Intentions of college students to adopt a mobile food-ordering app. Journal of Foodservice Business Research, 24(2), 121–139. https://doi.org/10.1080/15378020.2020.1814087
Troise, C., O’Driscoll, A., Tani, M., & Prisco, A. (2020). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664–683. https://doi.org/10.1108/BFJ-05-2020-0418
Venkatesh, V., Morris, M. G., Davis, Davis, Davis, G. B., Davis, F. D., Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J., & 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
Venkatesh, V., Thong, J., Xu, X., Thong, & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157. https://doi.org/10.2307/41410412
Verma, S., & Gustafsson, A. (2020). Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. Journal of Business Research, 118, 253–261. https://doi.org/10.1016/j.jbusres.2020.06.057
Vlassis, A. (2021). European Union and online platforms in global audiovisual politics and economy: Once Upon a Time in America ? International Communication Gazette, 83(6), 593–615. https://doi.org/10.1177/1748048520918496
Wang, Y.-S., Tseng, T. H., Wang, W.-T., Shih, Y.-W., & Chan, P.-Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002
Xu, F., & Du, J. T. (2018). Factors influencing users’ satisfaction and loyalty to digital libraries in Chinese universities. Computers in Human Behavior, 83, 64–72. https://doi.org/10.1016/j.chb.2018.01.029
Yang, H., & Lee, H. (2018). Exploring user acceptance of streaming media devices: an extended perspective of flow theory. Information Systems and E-Business Management, 16(1), 1–27. https://doi.org/10.1007/s10257-017-0339-x
Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: An empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129–142. https://doi.org/10.1016/j.chb.2011.08.019
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150–162. https://doi.org/10.1016/j.jretconser.2016.12.013
Yoon, C. (2011). Theory of Planned Behavior and Ethics Theory in Digital Piracy: An Integrated Model. Journal of Business Ethics, 100(3), 405–417. https://doi.org/10.1007/s10551-010-0687-7
Zanetta, L. D., Hakim, M. P., Gastaldi, G. B., Seabra, L. M. J., Rolim, P. M., Nascimento, L. G. P., Medeiros, C. O., & da Cunha, D. T. (2021). The use of food delivery apps during the COVID-19 pandemic in Brazil: The role of solidarity, perceived risk, and regional aspects. Food Research International, 149(November), 110671. https://doi.org/10.1016/j.foodres.2021.110671
Zhao, Y., & Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91, 102683. https://doi.org/10.1016/j.ijhm.2020.102683
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2024 Revista de Ciências da Administração
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
El autor deberá garantizar:
- que exista pleno consenso entre todos los coautores para aprobar la versión final del documento y su envío para publicación.
que su trabajo es original, y si se utilizó trabajo y/o palabras de otras personas, estos fueron debidamente reconocidos.
El plagio en todas sus formas constituye un comportamiento editorial poco ético y es inaceptable. RCA se reserva el derecho de utilizar software o cualquier otro método de detección de plagio.
Todos los envíos recibidos para evaluación en la revista RCA pasan por la identificación de plagio y autoplagio. El plagio identificado en los manuscritos durante el proceso de evaluación dará lugar al archivo del envío. Si se identifica plagio en un manuscrito publicado en la revista, el Editor Jefe realizará una investigación preliminar y, de ser necesario, se retractará.
Los autores otorgan a RCA los derechos exclusivos de primera publicación, estando la obra licenciada simultáneamente bajo la Licencia Creative Commons (CC BY) 4.0 Internacional.
Los autores están autorizados a celebrar contratos adicionales por separado, para la distribución no exclusiva de la versión del trabajo publicado en esta revista (por ejemplo, publicación en un repositorio institucional, en un sitio web personal, publicación de una traducción o como capítulo de un libro), con reconocimiento de autoría y publicación inicial en esta revista.
Esta licencia permite a cualquier usuario tener derecho a:
Compartir: copiar, descargar, imprimir o redistribuir el material en cualquier medio o formato.
Adapte: remezcle, transforme y cree a partir del material para cualquier propósito, incluso comercial.
Bajo los siguientes términos:
Atribución: debe dar el crédito apropiado (citar y hacer referencia), proporcionar un enlace a la licencia e indicar si se realizaron cambios. Debe hacerlo bajo cualquier circunstancia razonable, pero de ninguna manera que sugiera que el licenciante lo respalda a usted o su uso.
Sin restricciones adicionales: no puede aplicar términos legales ni medidas tecnológicas que restrinjan legalmente a otros hacer algo que la licencia permite.