Acceptance of Generative AI in the Creative Industry: Examining the role of Brand Recognition and Trust in the AI adoption
Main Article Content
Abstract
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authorship: The list of authors signing must include only those people who have contributed intellectually to the development of the work. Collaboration in the collection of data is not, by itself, a sufficient criterion of authorship. "Retos" declines any responsibility for possible conflicts arising from the authorship of the works that are published.
Copyright: The Salesian Polytechnic University preserves the copyrights of the published articles, and favors and allows their reuse under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Ecuador license. They may be copied, used, disseminated, transmitted and publicly displayed, provided that: i) the authorship and the original source of their publication (journal, editorial and work URL) are cited; (Ii) are not used for commercial purposes; Iii) mention the existence and specifications of this license.
References
Abbasi, M., Vassilopoulou, P. y Stergioulas, L. (2017). Technology roadmap for the Creative Industries. Creative Industries Journal, 10, 40-58. https://doi.org/10.1080/17510694.2016.1247627
Alhwaiti, M. (2023). Acceptance of Artificial Intelligence application in the post-covid era and its impact on faculty members’ occupational well-being and teaching self-efficacy: a path analysis using the UTAUT 2 Model. Applied Artificial Intelligence, 37(1). https://doi.org/10.1080/08839514.2023.2175110
Anantrasirichai, N. y Bull, D. (2022). Artificial intelligence in the creative industries: A review. Artificial Intelligence Review, 55, 589-656. https://doi.org/10.1007/s10462-021-10039-7
Ameen, N., Tarhini, A., Reppel, A. y Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548. https://doi.org/10.1016/j.chb.2020.106548
Artechouse. (2023). World of AI Imagination. Artechouse. https://bit.ly/4aK2Hi3
Bagozzi, R. P. y Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
Bowden, J. L. H. (2014). The process of customer engagement: A conceptual framework. Journal of Marketing Theory and Practice, 17(1), 63-74. https://doi.org/10.2753/MTP1069-6679170105
Cabrera-Sánchez, J. P., Villarejo-Ramos, Á. F., Liébana-Cabanillas, F. y Shaikh, A. A. (2021). Identifying relevant segments of AI applications adopters: Expanding the UTAUT2’s variables. Telematics and Informatics, 58, 101529. https://doi.org/10.1016/j.tele.2020.101529
Caporusso, N. (2023). Generative artificial intelligence and the emergence of creative displacement anxiety. Research Directs in Psychology and Behavior, 3(1). https://doi.org/10.53520/rdpb2023.10795
Chatterjee, S., Chaudhuri, R., Vrontis, D., Thrassou, A. y Ghosh, S. K. (2021). Adoption of artificial intelligence-integrated CRM systems in agile organizations in India. Technological Forecasting and Social Change, 168, 120783. https://doi.org/10.1016/j.techfore.2021.120783
Chen, J. (2024). The Role of AI: speculative design in redefining artistic collaboration. Journal of Ecohumanism, 3(8), 2261-2272. https://doi.org/10.62754/joe.v3i8.4899
Chui, M., Hall, B., Mayhew, H. y Singla, A. (2022, December 6). The state of AI in 2022 and a half decade in review. McKinsey & Company. http://bit.ly/4hYSYrj
Chuyen, N. y Vinh, N. (2023). An empirical analysis of predictors of AI-powered design tool adoption. TEM Journal, 12(3), 1012-1021.https://doi.org/10.18421/tem123-28
De Almeida Pedro, E., Panizzon, M. y Weber, C. (2023). OHS Professionals AI adoption: A UTAUT Research in Brazilian Industry. 2023 15th IEEE International Conference on Industry Applications (INDUSCON), 850-857. https://doi.org/10.1109/INDUSCON58041.2023.10374850.
García, M. L. M. y Yábar, D. P. (2023). Impact of brand awareness on consumer loyalty. Scientific Journal of Applied Social and Clinical Science, 3(12), 2-9. https://doi.org/10.22533/at.ed.2163122307068
Hair, J. F., Hult, G. T. M., Ringle, C. y Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.
Hair, J. F., Risher, J. J., Sarstedt, M. y Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Handayani, W. P. P. (2023). The UTAUT implementation model in defining the behavioral intention of mobile banking users. Jurnal Manajemen Bisnis, 14(2), 25-39. https://doi.org/10.18196/mb.v14i2.18649
Hatzius, J., Briggs, J., Kodnani, D., Pierdomenico, G. y Goldman Sachs & Co. LLC. (2023). The potentially large effects of artificial intelligence on economic growth (By Goldman Sachs & Co. LLC). https://bit.ly/3ElOOKX
Hem, L. E., De Chernatony, L. e Iversen, N. M. (2003). Factors influencing successful brand extensions. Journal of Marketing Management, 19(7-8), 781-806. https://doi.org/10.1362/026725703322498109
Hess, J. y Story, J. (2005). Trust‐based commitment: Multidimensional consumer‐brand relationships. Journal of Consumer Marketing, 22(6), 313-322. https://doi.org/10.1108/07363760510623902
Izza, A. M., Ardiansyah, M. N., Barkah, F. y Romdonny, J. (2024). Synergistic effects of content marketing and influencers marketing on the formation of brand awareness and purchase interest of TikTok Shop users (Cirebon City case study). International Journal of Social Service and Research, 4(5), 1339-1347. https://doi.org/10.46799/ijssr.v4i05.781
Jiang, J., Ma, J., Huang, X., Zhou, J. y Chen, T. (2024). Extend UTAUT2 model to analyze user behavior of China Construction Bank Mobile App. SAGE Open, 14(4). https://doi.org/10.1177/21582440241287070
Kathuria, S., Bansal, H. y Balhara, S. (2018). Impact of Brand Recognition on Consumer Attraction: A Study of Telecom Sector. Researchers World, Journal of Arts Science & Commerce, 9(1), 57-63. https://doi.org/10.18843/rwjasc/v9i1/07
Maican, C., Sumedrea, S., Tecău, A., Nichifor, E., Chițu, I., Lixăndroiu, R. y Brătucu, G. (2023). Factors influencing the behavioural intention to use AI-generated images in business. Journal of Organizational and End User Computing. https://doi.org/10.4018/joeuc.330019
Menon, D. y Shilpa, K. (2023). Chatting with ChatGPT: Analyzing the factors influencing users’ intention to use OpenAI’s ChatGPT using the UTAUT model. Heliyon, 9(11). https://doi.org/10.1016/j.heliyon.2023.e20962
Rios, R. E. y Riquelme, H. (2010). Sources of brand equity for online companies. Journal of Research in Interactive Marketing, 4(3), 214-240. https://doi.org/10.1108/17505931011070587
Roets, C. R. Q., Bevan-Dye, A. L. y Viljoen, W. P. (2014). Influence of social image and brand trust on mobile phone brand equity amongst African Generation Y students. Mediterranean Journal of Social Sciences, 5(21), 75-84. https://doi.org/10.5901/mjss.2014.v5n21p75
Rubio, N., Oubiña, J. y Villaseñor, N. (2014). Brand awareness–Brand quality inference and consumers’ risk perception in store brands of food products. Food Quality and Preference, 32, 289-298. https://doi.org/10.1016/j.foodqual.2013.09.006
Sanchez, T. (2023). Examining the text-to-image community of practice: Why and how do people prompt generative AIs? Creativity and Cognition. https://doi.org/10.1145/3591196.359305
Sanmukhiya, C. (2020). A PLS –SEM approach to the UTAUT model: the case of Mauritius. Annals of Social Sciences & Management Studies, 6(1). https://doi.org/10.19080/asm.2020.06.555677
Sasmita, J. y Mohd Suki, N. (2015). Young consumers’ insights on brand equity: Effects of brand association, brand loyalty, brand awareness, and brand image. International Journal of Retail & Distribution Management, 43(3), 276-292. https://doi.org/10.1108/IJRDM-02-2014-0024
Smith, C. (2022, December 22). The unreal exhibition showcases AI-handling talents of 'prompt writers'. trend hunter. http://bit.ly/3EgCX0S
Soper, D. S. (2024). A-priori sample size calculator for structural equation models [Software]. https://bit.ly/4hPigrm
Upadhyay, N., Upadhyay, S. y Dwivedi, Y. K. (2022). Theorizing artificial intelligence acceptance and digital entrepreneurship model. International Journal of Entrepreneurial Behaviour & Research, 28(5), 1138-1166. http://dx.doi.org/10.1108/IJEBR-01-2021-0052
Venkatesh, V., Morris, M., Davis, G. B. y Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. y Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Vinchon, F., Lubart, T., Bartolotta, S., Gironnay, V., Botella, M., Bourgeois-Bougrine, S., Burkhardt, J., Bonnardel, N., Corazza, G. E., Glăveanu, V., Hanson, M. H., Ivcevic, Z., Karwowski, M., Kaufman, J. C., Okada, T., Reiter‐Palmon, R. y Gaggioli, A. (2023). Artificial intelligence and creativity: A manifesto for collaboration. The Journal of Creative Behavior, 57(4), 472-484. https://doi.org/10.1002/jocb.597
Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., Anandkumar, A., Bergen, K., Gomes, C. P., Ho, S., Kohli, P., Lasenby, J., Leskovec, J., Liu, T., Manrai, A. y Zitnik, M. (2023). Scientific discovery in the age of artificial intelligence. Nature, 620(7972), 47-60. https://doi.org/10.1038/s41586-023-06221-2
Wang, H., Wei, J. y Yu, C. (2008). Global brand equity model: Combining customer-based with product-market outcome approaches. Journal of Product & Brand Management, 17(5), 305-316. https://doi.org/10.1108/10610420810896068
Westland, J. C. (2010). Lower bounds on sample size in structural equation modeling. Electronic Commerce Research and Applications, 9(6), 476-487. https://doi.org/10.1016/j.elerap.2010.07.003
Yin, M., Han, B., Ryu, S. y Min, H. (2023). Acceptance of generative AI in the creative industry: Examining the role of AI anxiety in the UTAUT2 model. In Lecture Notes in Computer Science, 14059, 288-310. https://doi.org/10.1007/978-3-031-48057-7_18
Zhang, W. (2020). A study on the user acceptance model of artificial intelligence music based on UTAUT. Journal of the Korea Society of Computer and Information, 25(1), 25-33.https://doi.org/10.9708/jksci.2020.25.06.025