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Repositorio de la Red Internacional de Investigadores en Competitividad

Innovación tecnológica e IA

Vol. 19 (2025): La IA y el futuro digital construyendo el camino hacia un mundo sostenible y competitivo 978-84-10470-93-4

La información y la facilidad de uso del comercio social: antecedente de intención de compra

Enviado
octubre 29, 2025
Publicado
2025-11-06

Resumen

Las redes sociales han creado un nuevo modelo de negocios denominado comercio social que involucra la participación de los consumidores en las transacciones comerciales en Internet. El objetivo de esta investigación es determinar la influencia de la información (calidad y comunicación) en la facilidad de uso en las plataformas de comercio social como antecedente de intención de compra por parte del consumidor. Para alcanzar la meta, se aplica un cuestionario a 182 consumidores habituales de comercio social y con base en el Modelado de Ecuaciones Estructurales, se realiza el análisis inferencial. Las principales aportaciones al conocimiento: la calidad de la información es un factor esencial que permite percibir la facilidad con la que se opera una plataforma tecnológica de comercio social a través de Internet, que, a su vez, esa facilidad de uso se manifiesta como un elemento determinante en la intención de compra por parte de los consumidores.

Citas

  1. Bugshan, H., & Attar, R. (2020). Social commerce information sharing and their impact on consumers. Technological Forecasting & Social Change, 153, 119875. Doi:10.1016/j.techfore.2019.119875
  2. Cheng, X., Gu, Y., & Shen, J. (2019). An integrated view of particularized trust in social commerce: An empirical investigation. International Journal of Information Management, 45, 1-12. Doi:10.1016/j.ijinfomgt.2018.10.014
  3. Chin, W. (1998). The partial least squares approach to structural equation modelling. En G. Marcoulides (Eds), Modern Methods for Business Research (pp. 295–336). Lawrence Erlbaum.
  4. Chin, 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), 189e217
  5. Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. Doi:10.2307/249008
  6. Dixon, S. (2023). Number of global social network users 2017-2027. https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/
  7. Dwivedi, Y.K. et al. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. Doi:10.1016/j.ijinfomgt.2020.102168
  8. Fu, J.R., Lua, I-W., Chenb, J., & Farn, C.K. (2020). Investigating consumers’ online social shopping intention: An information processing perspective. International Journal of Information Management, 54, 102189. Doi:10.1016/j.ijinfomgt.2020.102189
  9. Ghahtarani, A., Sheikhmohammady, M., & Rostami, M. (2020). The impact of social capital and social interaction on customers’purchase intention, considering knowledge sharing in socialcommerce context. Journal of Innovation & Knowledge, 5, 190–198. Doi:10.1016/j.jik.2019.08.004
  10. Hair, J., Hult, T., Ringle, C., Sarstedt, M., Castillo, J., Cepeda, G., & Roldán, J. (2019). Manual de Partial Least Squares Structral Equation Modeling (PLS-SEM). SAGE Publishing, España
  11. Hu, X., Huang, Q., Zhong, X., Davison, R.M., & Zhao, D. (2016). The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention. International Journal of Information Management, 36(6), 1218-1230. Doi:10.1016/j.ijinfomgt.2016.08.005
  12. Huang, Z., & Benyoucef, M. (2017). The effects of social commerce design on consumer purchase decision-making: An empirical study. Electronic Commerce Research and Applications, 25, 40–58. Doi:10.1016/j.elerap.2017.08.003
  13. Hyun, H., Thavisay, T., & Lee, S.H. (2022). Enhancing the role of flow experience in social media usage and its impact on shopping. Journal of Retailing and Consumer Services, 65, 102492. Doi:10.1016/j.jretconser.2021.102492
  14. Jiang, G., Liu, F., Liu, W., Liu, S., Chen, Y. & Xu, D. (2021). Effects of information quality on information adoption on social media review platforms: moderating role of perceived risk. Data Science and Management, 1(1), 13–22. https://doi.org/10.1016/j.dsm.2021.02.004
  15. Kang, M.Y., & Park, B. (2018). Sustainable corporate social media marketing based on message structural features: Firm size plays a significant role as a moderator. Sustainability, 10(4), 1167. Doi:10.3390/su10041167
  16. Kaur, P., Dhir, A., N., Sahu, G., & Almotairi, M. (2020). An innovation resistance theory perspective on mobile payment solutions Puneet. Journal of Retailing and Consumer Services, 55, 102059. Doi:10.1016/j.jretconser.2020.102059
  17. Kitirattarkarn, G.P., Tao, W., & Sunny, W.H.T. (2021). Intended audience and valence of electronic word-of-mouth on social media: a study of Dutch consumers. Internet Research, 31(3), 990-1017. Doi:10.1108/INTR-03-2020-0133
  18. Kudeshia, C., & Kumar, A. (2017). Social eWOM: does it affect the brand attitude and purchase intention of brands? Management Research Review, 40(3), 310-330. Doi:10.1108/MRR-07-2015-0161
  19. Lankton, N.K., & McKnight, D.H. (2011). What does it mean to trust Facebook? Examining technology and interpersonal trust beliefs. The DATA BASE for Advancesin Information Systems, 42(2), 32e54. Doi:10.1145/1989098.1989101
  20. Le, L.H., & Ha, Q.A. (2021). Effects of negative reviews and managerial responses on consumer attitude and subsequent purchase behavior: An experimental design. Computers in Human Behavior, 124, 106912. Doi:10.1016/j.chb.2021.106912
  21. Li, Y., Wu, R., & Li, D. (2020). The influence of subjective characteristics of social network sites on consumers’ word-of-mouth sharing. Online Information Review, 44(5), 977-994. Doi:10.1108/OIR-09-2018-0263
  22. Liang, T., Ho,Y., Li, Y., & Turban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69–90. Doi:10.2753/JEC1086-4415160204
  23. Molinillo, S., Aguilar-Illescas, R., Anaya-Sánchez, R., & Liébana-Cabanillas, R. (2021). Social commerce website design, perceived value and loyalty behavior intentions: The moderating roles of gender, age and frequency of use. Journal of Retailing and Consumer Services, 63, 102404. Doi:10.1016/j.jretconser.2020.102404
  24. PowerReviews (2018). The Ever-Growing Power of Reviews. https://www.powerreviews.com/blog/the-ever-growing-power-of-reviews/
  25. Rahman, F.B., Hafiz, M., Zahari, M.S., & Jipiu, L.B. (2023). Social commerce adoption: a study on consumer’s online purchase behaviour of perishable pastry products. British Food Journal, 125(1), 318-344, Doi:10.1108/BFJ-07-2021-0796
  26. Ringle, C.M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4. Oststeinbek: SmartPLS GmbH. http://www.smartpls.com
  27. Ringle, M., Sarstedt, M., Sinkovics, N., & Sinkovics, R. (2023). A perspective on using partial least squares structural equation modelling in data articles. Data in Brief, 48, 109074. Doi:10.1016/j.dib.2023.109074
  28. Rondán-Cataluña, F.J., Arenas-Gaitán, J., & Ramírez-Correa, P. (2015). Travel buying behavior in social network site users: to buy online vs. Offline. Journal of Theoretical and Applied Electronic Commerce Research, 10(1), 49-62. Doi:10.4067/S0718-18762015000100005
  29. Ryu, S. & Park, J. (2020). The effects of benefit-driven commitment on usage of social media for shopping and positive word-of-mouth. Journal of Retailing and Consumer Services, 55, 102094. https://doi.org/10.1016/j.jretconser.2020.102094
  30. Sembada, A.Y., & Koay, K.Y. (2021). How perceived behavioral control affects trust to purchase in social media stores. Journal of Business Research, 130, 574–582.
  31. Doi:10.1016/j.jbusres.2019.09.028
  32. Trehan, D., & Sharma, R. (2021). Assessing advertisement quality on C2C social commerce platforms: an information quality approach using text mining. Online Information Review, 45(1), 46-64. Doi:10.1108/OIR-07-2020-0320
  33. Ureña, R., Chiclana, F., Carrasco R.A., & Herrera-Viedma, E. (2019). Leveraging users’ trust and reputation in social networks. Procedia Computer Science, 162, 955–962. Doi:10.1016/j.procs.2019.12.073
  34. Wang, Y., & Herrando, C. (2019). Does privacy assurance on social commerce sites matter to millennials? International Journal of Information Management, 44, 164–177. Doi:10.1016/j.ijinfomgt.2018.10.016
  35. Weitzl, W., & Hutzinger, C. (2017). The effects of marketer- and advocate-initiated online service recovery responses on silent bystanders. Journal of Business Research, 80, 164-175. Doi:10.1016/j.jbusres.2017.04.020
  36. Yang, X. (2022). Consumers’ purchase intentions in social commerce: the role of social psychological distance, perceived value, and perceived cognitive effort. Information Technology & People, 35(8), 330-348. Doi:10.1108/ITP-02-2022-0091
  37. Zhao, Y., Wang, L., Tang, H., & Zhang, Y. (2020). Electronic word-of-mouth and consumer purchase intentions in social ecommerce. Electronic Commerce Research and Applications, 41, 100980. Doi:10.1016/j.elerap.2020.100980

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