Anuncios comprables en redes sociales móviles: alta personalización y preocupación por la privacidad

  • Jorge Serrano-Malebrán Universidad Católica del Norte
  • Jorge Arenas-Gaitán Universidad de Sevilla


El presente estudio explora la evaluación de los consumidores de los anuncios comprables de marcas de moda en la aplicación móvil de Facebook. Para esta cumplir con este objetivo, se prueba un modelo conceptual que propone relaciones que pueden influir en las intenciones de los consumidores a comprar a través anuncios comprables. Específicamente este estudio examina las relaciones entre la personalización de los anuncios comprables, la preocupación por la privacidad, la percepción de utilidad y la intención de comprar a través de este nuevo formato de anuncio en redes sociales móviles. Se aplicó un cuestionario a usuarios redes sociales móviles, logrando una muestra de 486 encuestados para su análisis mediante el enfoque de modelado de ecuaciones estructurales. Los resultados muestran que la personalización de los anuncios tiene un efecto sobre la preocupación por la privacidad, la percepción de utilidad y la intención de compra. No se encontró una relación estadísticamente significativa en la relación de la preocupación por la privacidad con la utilidad percibida y la intención de compra.


La descarga de datos todavía no está disponible.


Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49.
Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social Media in Marketing: A Review and Analysis of the Existing Literature. Telematics and Informatics, (May).
Bakar, M. S. A., & Bidin, R. (2014). Technology Acceptance and Purchase Intention towards Movie Mobile Advertising among Youth in Malaysia. Procedia - Social and Behavioral Sciences, 130, 558–567.
Ben, I., Al-neama, N., & Kerbache, L. (2018). Investigating the drivers for social commerce in social media platforms : Importance of trust , social support and the platform perceived usage. Journal of Retailing and Consumer Services, 41(September 2017), 11–19.
Bleier, A., & Eisenbeiss, M. (2015). The Importance of Trust for Personalized Online Advertising. Journal of Retailing, 91(3), 390–409.
Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online Behavioral Advertising: A Literature Review and Research Agenda. Journal of Advertising, 46(3), 363–376.
Celebi, S. I. (2015). How do motives affect attitudes and behaviors toward internet advertising and Facebook advertising? Computers in Human Behavior, 51(PA), 312–324.
Chae, H., & Ko, E. (2016). Customer social participation in the social networking services and its impact upon the customer equity of global fashion brands. Journal of Business Research, 69(9), 3804–3812.
Chin, W. (1998). The Partial Least Squares Approach for Structural Equation Modeling. In Marcoulides, G.A. (Ed.), Modern Methods for Business Research (pp. 295–336).
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.
eMarketer. (2017). Facebook Leads Competitors for Last-Click Social Commerce. Retrieved April 20, 2018, from
Enwereuzor, I. K. (2017). Capturing consumers’ experiences of unsolicited mobile advertising. Telematics and Informatics, 34(7), 948–960.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.
Gao, S., & Zang, Z. (2016). An empirical examination of users’ adoption of mobile advertising in China. Information Development, 32(2), 203–215.
Gibreel, O., AlOtaibi, D. A., & Altmann, J. (2018). Social commerce development in emerging markets. Electronic Commerce Research and Applications, 27, 152–162.
Goodwin, D. (2016). Businesses Can Now Sell In Facebook Messenger. Retrieved October 18, 2018, from
Gudergan, S. P., Ringle, C. M., Wende, S., & Will, A. (2008). Confirmatory tetrad analysis in PLS path modeling. Journal of Business Research, 61(12), 1238–1249.
Hansen, J. M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197–206.
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research : updated guidelines.
Hew, J. J., Lee, V. H., Ooi, K. B., & Lin, B. (2016). Mobile social commerce: The booster for brand loyalty? Computers in Human Behavior, 59, 142–154.
Jung, A.-R. (2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309.
Kim, Y. J., & Han, J. (2014). Why smartphone advertising attracts customers: A model of Web advertising, flow, and personalization. Computers in Human Behavior, 33, 256–269.
Ko, H.-C. (2018). Social Desire or Commercial Desire? The Factors Driving Social Sharing and Shopping Intentions on Social Commerce Platforms. Electronic Commerce Research and Applications, 28, 1–15.
Lal, P. (2017). Analyzing determinants influencing an individual׳s intention to use social commerce website. Future Business Journal, 3(1), 70–85.
Lee, J., & Hong, I. B. (2016). Predicting positive user responses to social media advertising: The roles of emotional appeal, informativeness, and creativity. International Journal of Information Management, 36(3), 360–373.
Li, C. Y. (2017). How social commerce constructs influence customers’ social shopping intention? An empirical study of a social commerce website. Technological Forecasting and Social Change, (129), 0–1.
Liang, T., & Turban, E. (2011). Introduction to the special issue social commerce: A research framework for social commerce. International Journal of Electronic Commerce, 16(2), 5–14.
Lin, C. A., & Kim, T. (2016). Predicting user response to sponsored advertising on social media via the technology acceptance model. Computers in Human Behavior, 64, 710–718.
Lin, X., Li, Y., & Wang, X. (2015). Social commerce research: Definition, research themes and the trends. International Journal of Information Management.
McDonald, A. M., & Cranor, L. F. (2010). Americans’ attitudes about internet behavioral advertising practices. Proceedings of the 9th Annual ACM Workshop on Privacy in the Electronic Society - WPES ’10, 63.
Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37(January), 8–22.
Okazaki, S., & Mendez, F. (2012). Exploring convenience in mobile commerce: Moderating effects of gender. Computers in Human Behavior, 29(3), 1234–1242.
Oleynikova, E., & Zorkin, Y. (2016). Social Commerce as a Driver of Sustainable Development of the Information Economy of the City. Procedia Engineering, 165, 1556–1562.
Prasarnphanich, P., & Wagner, C. (2009). The role of Wiki Technology and Alturism in Colaborative Knowldege Creation, 49(4), 33–41. Retrieved from
Ringle, C. M., Wende, S., & Becker, J. M. (2015). “SmartPLS 3.” Boenningstedt: SmartPLS GmbH. Retrieved from
Scuotto, V., Del Giudice, M., Peruta, M. R. della, & Tarba, S. (2017). The performance implications of leveraging internal innovation through social media networks: An empirical verification of the smart fashion industry. Technological Forecasting and Social Change.
Shaouf, A., Lu, K., & Li, X. (2016). The effect of web advertising visual design on online purchase intention: An examination across gender. Computers in Human Behavior, 60, 622–634.
Statista. (2017). Statistics and facts about social networks. Retrieved October 18, 2018, from
Statista. (2018). Most popular social networks worldwide as of April 2018, ranked by number of active users (in millions). Retrieved May 9, 2018, from
Streukens, S., & Leroi-Werelds, S. (2016). Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Management Journal, 34(6), 618–632.
SUBTEL. (2016). Séptima Encuesta de Acceso, Usos y Usuarios de Internet.
Tam, K. Y., & Ho, S. Y. (2006). Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly, 30(4), 865–890. Retrieved from
Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119–134.
Wang, Y., & Hajli, M. N. (2014). Co-creation in branding through social commerce: The role of social support, relationship quality and privacy concerns. 20th Americas Conference on Information Systems, AMCIS 2014, (August), 1–16. Retrieved from
White, T. B., Zahay, D. L., Thorbjørnsen, H., & Shavitt, S. (2008). Getting too personal: Reactance to highly personalized email solicitations. Marketing Letters, 19(1), 39–50.
Wright, R. T., Campbell, D. E., Thatcher, J. B., & Roberts, N. (2012). Operationalizing multidimensional constructs in Structural Equation Modeling: Recommendations for IS research. Communications of the Association for Information Systems, 30(23), 367–412.
Yadav, M., & Rahman, Z. (2017). Measuring consumer perception of social media marketing activities in e-commerce industry: Scale development & validation. Telematics and Informatics.
Cómo citar
Serrano-Malebrán, J., & Arenas-Gaitán, J. (2019). Anuncios comprables en redes sociales móviles: alta personalización y preocupación por la privacidad. GECONTEC: Revista Internacional De Gestión Del Conocimiento Y La Tecnología, 7(2), 66-79. Recuperado a partir de