YENİLİKLERİN YAYILMASI TEORİSİ PERSPEKTİFİNDE SANAL ETKİLEYİCİLERİN TÜKETİCİ KABULÜ: ALGILANAN İNSANSILIĞIN ARACILIK ROLÜ

Öz

Dijital pazarlamanın yükselen aktörleri arasında yer alan sanal etkileyiciler, markaların tüketiciyle kurduğu iletişimde giderek daha önemli bir rol üstlenmektedir. Bu çalışma, Yeniliklerin Yayılması Teorisi (YYT) perspektifinden hareketle, sanal etkileyicilerin tüketici kabulünü açıklamayı ve özellikle algılanan insansılığın bu süreçteki aracılık rolünü ortaya koymayı amaçlamaktadır. Araştırma verileri, İstanbul’da yaşayan 572 katılımcıdan elde edilmiştir. Çok değişkenli yapılar arasındaki ilişkileri analiz edebilmek amacıyla Kısmi En Küçük Kareler Yapısal Eşitlik Modellemesi (PLS-SEM) kullanılmış; analizler SmartPLS 4 programı aracılığıyla gerçekleştirilmiştir. Aracı etkilerin test edilmesinde Hayes’in (2013) bootstrap-temelli aracılık prosedürü kullanılmıştır. Araştırma bulgularına göre, tüketiciler samimi buldukları sanal etkileyicileri daha insansı olarak değerlendirmekte; bu insansı algı da olumlu tutumlara ve dolayısıyla satın alma niyetine dönüşmektedir. Çalışma, sanal etkileyici tasarımında insani ve uyarlanabilir özelliklerin önemini vurgulayarak dijital pazarlama literatürüne katkı sağlamaktadır. Teorik bakış açıları antropomorfik ve ilişkilendirilebilir özelliklerin tüketici etkileşimini artırdığını vurgulamaktadır. Pratik çıkarımlar, pazarlamacıların tüketici tutumlarını güçlendirmek ve satın alma niyetlerini teşvik etmek için samimiyeti, uyum sağlama yeteneğini ve insani benzerliği sanal etkileyici stratejilerine entegre etmeleri gerektiğini göstermektedir.

Anahtar Kelimeler

• Sanal Etkileyiciler
• Algılanan İnsansılık
• Algılanan Samimiyet
• Yeniliklerin Yayılması Teorisi (YYT)
• Dijital Pazarlama

CONSUMER ACCEPTANCE OF VIRTUAL INFLUENCERS FROM THE PERSPECTIVE OF THE DIFFUSION OF INNOVATIONS THEORY: THE MEDIATING ROLE OF PERCEIVED HUMANNESS

Öz

Virtual influencers, as emerging actors in digital marketing, increasingly shape brand communication. Grounded in the Diffusion of Innovations Theory (DIT), this study investigates consumer acceptance of virtual influencers and explores the mediating role of perceived humanness in this process. Data were collected from 572 participants residing in Istanbul. The analysis employed Partial Least Squares Structural Equation Modeling (PLSSEM) through SmartPLS 4, while mediation effects were tested using Hayes’s (2013) bootstrap approach. According to research findings, consumers perceive virtual influencers they find sincere as more human-like, and this human-like perception turns into positive attitudes and, consequently, purchase intention. The study contributes to digital marketing literature by highlighting the importance of human-like, adaptable features in the design of virtual influencers. Theoretical insights emphasize that anthropomorphic and relatable attributes enhance consumer engagement. Practical implications suggest that marketers should integrate sincerity, adaptability, and human resemblance into virtual influencer strategies to strengthen consumer attitudes and foster purchase intentions.

Anahtar Kelimeler

• Virtual Influencer
• Perceived Humanness
• Perceived Sincerity
• Diffusion of Innovations (DIT)
• Digital Marketing

Kaynakça

1. Aaker, J. L. (1997). Dimensions of brand personality. Journal of Marketing Research, 34(3), 347–356.
2. Acar, C., & Ekizler, H. (2023). Sanal etkileyicilerin tüketici satın alma niyetine etkisi. Ege Stratejik Araştırmalar Dergisi, 14(1), 1–22.
3. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Sciences, 28(3), 557–582.
4. Airenti, G. (2018). The development of anthropomorphism in interaction: Intersubjectivity, imagination, and theory of mind. Frontiers in Psychology, 9, 2136.
5. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
6. Al-Ajam, A. S., & Nor, K. M. (2013). Internet banking adoption: Integrating technology acceptance model and trust. European Journal of Business and Management, 5(3), 207–215.
7. Alalwan, A. A. (2018). Investigating the impact of social media advertising features on customer purchase intention. International Journal of Information Management, 42, 65–77.
8. Allal-Chérif, O., Puertas, R., & Carracedo, P. (2024). Intelligent influencer marketing: How AI-powered virtual influencers outperform human influencers. Technological Forecasting and Social Change, 200, 123113.

9. Arli, D., & Bakpayev, M. (2023). Exploring the role of innovation attributes on mobile payment adoption. Journal of Consumer Marketing, 40(7), 826–841.
10. Arsenyan, J., & Mirowska, A. (2021). Almost human? A comparative case study on the social media presence of virtual influencers. International Journal of Human-Computer Studies, 155, Article 102694.
11. Atkinson, R. K., Mayer, R. E., & Merrill, M. M. (2005). Fostering social agency in multimedia learning: Examining the impact of an animated agent's voice. Contemporary Educational Psychology, 30(1), 117–139.
12. Barari, M., Ross, M., & Azad Moghddam, H. (2025). Virtual influencers’ anthropomorphism, consumer engagement and/or well-being. Journal of Consumer Marketing, 42(5), 673–688.
13. Belanche, D., Casaló, L. V., & Flavián, M. (2024). Human versus virtual influences, a comparative study. Journal of Business Research, 173, 114493.
14. Block, E., & Lovegrove, R. (2021). Discordant storytelling, ‘honest fakery’, identity peddling: How uncanny CGI characters are jamming public relations and influencer practices. Public Relations Inquiry, 10(3), 265–293.
15. Byun, K. J., & Ahn, S. J. (2023). A systematic review of virtual influencers: Similarities and differences between human and virtual influencers in interactive advertising. Journal of Interactive Advertising, 23(4), 293-306.
16. Chae, J. (2022). Who makes a better influencer? Comparing real and virtual influencers on Instagram. Computers in Human Behavior, 128, 107129.
17. Ciechanowski, L., Przegalinska, A., Magnuski, M., & Gloor, P. (2019). In the shades of the uncanny valley: An experimental study of human–chatbot interaction. Future Generation Computer Systems, 92, 539–548.
18. Cochran, W. G. (1977). Sampling techniques (3rd ed.). Wiley.
19. Cowan, K., & Little, M. (2019). Artificial intelligence in marketing: Examining the impact of AI agents on customer engagement. Journal of Marketing Management, 35(7–8), 645–661.
20. Da Silva Oliveira, A. B., & Chimenti, P. (2021). “Humanized robots”: A proposition of categories to understand virtual influencers. Australasian Journal of Information Systems, 25, 1–15.
21. Dabiran, E., Farivar, S., Wang, F., & Grant, G. (2024). Virtually human: Anthropomorphism in virtual influencer marketing. Journal of Retailing and Consumer Services, 79, 103797.
22. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319–340.
23. De Brito Silva, M. J., de Oliveira Ramos Delfino, L., Alves Cerqueira, K., & de Oliveira Campos, P. (2022). Avatar marketing: A study on the engagement and authenticity of virtual influencers on Instagram. Social Network Analysis and Mining, 12(1), 130.
24. Duffett, R. G. (2015). Facebook advertising’s influence on intention-to-purchase and purchase amongst Millennials. Internet Research, 25(4), 498–526.
25. Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: a three-factor theory of anthropomorphism. Psychological review, 114(4), 864.
26. Erdoğan, H., & Özcan, B. M. (2020). Influencer pazarlaması kullanımının tüketicilerin satın alma niyetine etkisi. İşletme Araştırmaları Dergisi, 12(4), 3813–3827.
27. Eyel, C. Ş., & Şen, B. (2020). Influencer pazarlama ve tüketicilerin influencer’lara yönelik tutumlarının satın alma niyeti üzerindeki etkisi. Atlas Sosyal Bilimler Dergisi, 1(5), 7–29.
28. Fishbein, M. (1963). An investigation of the relationships between beliefs about an object and the attitude toward that object. Human Relations, 16, 233–240.
29. Fishbein, M., & Ajzen, I. (1974). Attitudes toward objects as predictors of single and multiple behavioral criteria. Psychological Review, 81, 59–74.
30. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
31. Garip, S., & İnceli, P. (2021). Yeniliklerin yayılımı bağlamında Instagram’da yapay zeka ürünü sanal etkileyenin takipçiler tarafından kabulüne yönelik bir inceleme. Erciyes İletişim Dergisi, 8(2), 959-980.
32. Gentsch, P. (2019). AI in marketing, sales and service: How marketers without a data science degree can use AI, big data and bots. Palgrave Macmillan.
33. Gerlich, M. (2023). The power of virtual influencers: Impact on consumer behaviour and attitudes in the age of AI. Administrative Sciences, 13(8), 178.
34. Ghazali, A. S., Ham, J., Barakova, E., & Markopoulos, P. (2018). The influence of social cues in persuasive social robots on psychological reactance and compliance. Computers in Human Behavior, 87, 58-65.
35. Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in human behavior, 97, 304-316.
36. Gong, L., & Nass, C. (2007). When a talking-face computer agent is half-human and half-humanoid: Human identity and consistency preference. Human Communication Research, 33(2), 163–193.
37. Gray, H. M., Gray, K., & Wegner, D. M. (2007). Dimensions of mind perception. Science, 315(5812), 619.
38. Guthrie, S. (2020). Virtual influencers: More human than humans. In Influencer marketing (pp. 271–285). Routledge.
39. Hair Jr, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110.
40. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P. ve Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature.
41. Hair, J. F., Hult, G. T., Ringle, C. M. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (Pls-Sem) (2. nd Ed.) Los Angeles: Sage Publication.
42. Hayes, A. (2013). Introduction to mediaton, moderation and conditional process analysis: A regression-based approach. New York: The Guildford Press.
43. Hermann, E. (2022). Anthropomorphized artificial intelligence, attachment, and consumer behavior. Marketing Letters, 33(1), 157-162.
44. Hewapathirana, I. U., & Perera, N. (2024). Navigating the age of AI influence: A systematic literature review of trust, engagement, efficacy and ethical concerns of virtual influencers in social media.
45. Hildebrandt, F., Lichtenberg, S., Brendel, A. B., & Landmann, E. (2023). Who’s bad? The influence of perceived humanness on users’ intention to complain about conversational agent errors to others. ICIS 2023 Proceedings, 11, 1–17.
46. Hlee, S., Park, J., Park, H., Koo, C., & Chang, Y. (2023). Understanding customer's meaningful engagement with AI-powered service robots. Information Technology & People, 36(3), 1020-1047.
47. Ho, C. C., & MacDorman, K. F. (2017). Measuring the uncanny valley effect: Refinements to indices for perceived humanness, attractiveness, and eeriness. International Journal of Social Robotics, 9(1), 129–139.
48. Hofeditz, Lennart; Nissen, Anika; Schütte, Reinhard; and Mirbabaie, Milad. (2022). "Trust Me, I’m an Influencer! - A Comparison of Perceived Trust in Human and Virtual Influencers". ECIS 2022 Research-in-Progress Papers. 27.
49. Horton, D., & Richard Wohl, R. (1956). Mass communication and para-social interaction: Observations on intimacy at a distance. Psychiatry, 19(3), 215–229.
50. Isyanto, P., Sapitri, R. G., & Sinaga, O. (2020). Micro influencers marketing and brand image to purchase intention of cosmetic products Focallure. Systematic Reviews in Pharmacy, 11(1), 601–605.
51. Jang, H. (2022). The impact of the humanness of AI influencers on the success of influencer marketing (Master’s thesis). University of Texas at Austin.
52. Jang, I., Kim, J., & Park, I. (2025). When AI takes your call: Investigating the impact of conversational styles on customer service agents’ affective delivery. Telematics and Informatics, 102277.
53. Jin, S. V. (2020). Humanizing artificial intelligence interactions: The impact of anthropomorphism on consumer responses to AI influencers. Journal of Interactive Marketing, 49, 27–40.
54. Jin, S. V., & Viswanathan, V. (2025). “Threatened and empty selves following AI-based virtual influencers”: Comparison between followers and non-followers of virtual influencers in AI-driven digital marketing. AI & Society, 40(1), 117–131.
55. Kanchanatanee, K., Suwanno, N., & Jarernvongrayab, A. (2014). Effects of attitude toward using, perceived usefulness, perceived ease of use and perceived compatibility on intention to use e-marketing. Journal of Management Research, 6(3), 1.
56. Khan, L., & Asim, J. (2025). Impact of social media influencers on purchase intention. Research Journal of Psychology, 3(1), 151–165.
57. Köse, Ş. G. (2025). Sanal etkileyicilerin yükselişi: Tüketici tutumları üzerine keşfedici bir araştırma. Alanya Akademik Bakış, 9(1), 324–339.
58. Kosnina, R., Hasanb, H., & Ahmadc, I. (2019). Perceived knowledge, anxiety and relative advantage as antecedence of attitude towards gold dinar acceptance. International Journal of Innovation, Creativity and Change, 6(3), 33-54.
59. Laszkiewicz, A., & Kalinska‐Kula, M. (2023). Virtual influencers as an emerging marketing theory: A systematic literature review. International Journal of Consumer Studies, 47(6), 2479-2494.
60. Lee, H., & Yi, Y. (2025). Humans vs. service robots as social actors in persuasion settings. Journal of Service Research, 28(1), 150–167.
61. Lee, J. A., & Eastin, M. S. (2020). I like what she’s #endorsing: The impact of female social media influencers’ perceived sincerity, consumer envy, and product type. Journal of Interactive Advertising, 20(1), 76–91.
62. Lee, J., & Park, H. (2023). Perceived warmth and competence of AI agents: Effects on trust and interaction intentions. Journal of Business Research, 154, 113316.
63. Li, C., & Huang, F. (2024). The impact of virtual streamer anthropomorphism on consumer purchase intention: Cognitive trust as a mediator. Behavioral Sciences, 14(12), 1228.
64. Li, Y., Hou, R., & Tan, R. (2024). How customers respond to chatbot anthropomorphism: The mediating roles of perceived humanness and perceived persuasiveness. European Journal of Marketing, 58(12), 2757–2790.
65. Lin, Q., Li, Y., Li, L., & Yu, X. (2025). Anthropomorphism effect of virtual influencers on purchase intention in social commerce: A presence perspective. Social Behavior and Personality: an international journal, 53(2), 1-10.
66. Liu, Y., Yang, D., Chang, D., Jiang, P., Pan, Y., & Liu, Z. (2025). The effects of robot anthropomorphic characteristics on employees’ anti-robot sabotage. Scientific Reports, 15(1), 22064.
67. Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58–73.
68. Lou, C., Kiew, S. T. J., Chen, T., Lee, T. Y. M., Ong, J. E. C., & Phua, Z. (2023). Authentically fake? How consumers respond to the influence of virtual influencers. Journal of Advertising, 52(4), 540–557.
69. Lu, L., McDonald, C., Kelleher, T., Lee, S., Chung, Y. J., Mueller, S., & Yue, C. A. (2022). Measuring consumer perceived humanness of online organizational agents. Computers in Human Behavior, 128, 107092.
70. Malhotra, G., & Ramalingam, M. (2025). Perceived anthropomorphism and purchase intention using artificial intelligence technology: Examining the moderated effect of trust. Journal of Enterprise Information Management, 38(2), 401–423.
71. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.
72. Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [From the original 1970 article]. IEEE Robotics & Automation Magazine, 19(2), 98–100
73. Moustakas, E., Lamba, N., Mahmoud, D., & Ranganathan, C. (2020, June). Blurring lines between fiction and reality: Perspectives of experts on marketing effectiveness of virtual influencers. In 2020 international conference on cyber security and protection of digital services (cyber security) (pp. 1-6). IEEE.
74. Mrad, M., Ramadan, Z., Tóth, Z., Nasr, L., & Karimi, S. (2025). Virtual influencers versus real connections: Exploring the phenomenon of virtual influencers. Journal of Advertising, 54(1), 1–19.
75. Munnukka, J., Talvitie-Lamberg, K., & Maity, D. (2022). Anthropomorphism and social presence in human–virtual service assistant interactions: The role of dialog length and attitudes. Computers in Human Behavior, 135, 107343.
76. Na, Y., Kim, Y., & Lee, D. (2024). Investigating the effect of self-congruity on attitudes toward virtual influencers: Mediating the effect of emotional attachment. International Journal of Human–Computer Interaction, 40(18), 5534–5547.
77. Napoli, J., Dickinson, S. J., Beverland, M. B., & Farrelly, F. (2014). Measuring consumer-based brand authenticity. Journal of Business Research, 67(6), 1090-1098.
78. Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103.
79. Ohanian, R. (1990). Construction and validation of a scale to measure celebrity endorsers' perceived expertise, trustworthiness, and attractiveness. Journal of Advertising, 19(3), 39–52.
80. Premkumar, G., Ramamurthy, K., & Nilakanta, S. (1994). Implementation of electronic data interchange: An innovation diffusion perspective. Journal of Management Information Systems, 11(2), 157–186.
81. Pushparaj, P., & Kushwaha, B. P. (2023). A Systematic Literature Review of Virtual Influencers in Marketing Using Bibliometric Analysis. Available at SSRN 4593307.
82. Rao Hill, S., & Troshani, I. (2024). Chatbot anthropomorphism, social presence, uncanniness and brand attitude effects. Journal of Computer Information Systems, 1-17.
83. Rizzo, G. L. C., Berger, J., & Villarroel, F. (2023). What drives virtual influencer's impact? arXiv preprint. (Available at: https://arxiv.org/pdf/2301.09874
84. Rogers, E. M. (2002). Diffusion of preventive innovations. Addictive Behaviors, 27(6), 989–993.
85. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
86. Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In T. L. Hecht, S. J. Ribeau, & J. C. Weaver (Eds.), An integrated approach to communication theory and research (pp. 432–448). Routledge.
87. Rossi, C., & Rivetti, F. (2023, May). Virtual influencer marketing: Is it effective in engaging younger generations? In Proceedings of the 10th European Conference on Social Media (ECSM) (Vol. 10).
88. Schiffman, L. G., & Wisenblit, J. (2019). Consumer behavior (12th ed.). Pearson.
89. Schuetzler, R. M., Grimes, G. M., & Scott Giboney, J. (2020). The impact of chatbot conversational skill on engagement and perceived humanness. Journal of Management Information Systems, 37(3), 875–900.
90. Seeger, A. M., Pfeiffer, J., & Heinzl, A. (2021). Designing anthropomorphic conversational agents: Development and empirical evaluation of a design framework. Information Systems Journal, 31(1), 107–145.
91. Shang, S. S., Wu, Y. L., & Sie, Y. J. (2017). Generating consumer resonance for purchase intention on social network sites. Computers in Human Behavior, 69, 18–28.
92. Sirgy, M. J. (1985). Using self-congruity and ideal congruity to predict purchase motivation. Journal of Business Research, 13(3), 195–206.
93. Söderlund, M., & Oikarinen, E. L. (2021). Service encounters with virtual agents: An examination of perceived humanness as a source of customer satisfaction. European Journal of Marketing, 55(13), 94–121.
94. Sorosrungruang, T., Ameen, N., & Hackley, C. (2024). How real is real enough? Unveiling the diverse power of generative AI‐enabled virtual influencers and the dynamics of human responses. Psychology & Marketing, 41(12), 3124-3143.
95. Svenningsson, N., & Faraon, M. (2019, December). Artificial intelligence in conversational agents: A study of factors related to perceived humanness in chatbots. In Proceedings of the 2019 2nd Artificial Intelligence and Cloud Computing Conference (pp. 151–161).
96. Terzis, V. ve Economides, A. A. (2011). The acceptance and use of computer based assessment. Computers & Education, 56(4), 1032-1044.
97. Thomas, V. L., & Fowler, K. (2021). Close encounters of the AI kind: Use of AI influencers as brand endorsers. Journal of Advertising, 50(1), 11–25.
98. Tiwari, A., Kumar, A., Kant, R., & Jaiswal, D. (2024). Impact of fashion influencers on consumers' purchase intentions. Journal of Fashion Marketing and Management, 28(2), 209–225.
99. Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on engineering management, (1), 28-45.
100. Tsai, W. H. S., & Men, L. R. (2017). Social CEOs: The effects of CEOs’ communication styles and parasocial interaction on social networking sites. New Media & Society, 19(11), 1848–1867.
101. Van der Heide, B., & Lim, Y. (2018). On the conditional cues of social presence. Communication Monographs, 85(2), 230–250.
102. van Deventer, M., de Klerk, N., & Dye, A. B. (2018). Influence of Perceıved Ease of Use and Perceived Relative Advantage On Generation Y Students’attitudes Towards and Usage Behavıour of Mobıle Bankıng in South Afrıca. International Journal of eBusiness and eGovernment Studies, 10(1), 18-33.
103. Veerbeek, E. M. (2024). The Effects of the Type of Influencer (Human vs Virtual) on Source Credibility, Emotional Connection, and Purchase Intention in Fashion Advertising: The Moderating Role of Brand Awareness.Lou
104. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.
105. Waytz, A., Cacioppo, J., & Epley, N. (2010). Who sees human? The stability and importance of individual differences in anthropomorphism. Perspectives on psychological science, 5(3), 219-232.
106. Westerman, D., Edwards, A. P., Edwards, C., Luo, Z., & Spence, P. R. (2020). I-It, I-Thou, I-Robot: The perceived humanness of AI in human-machine communication. Communication Studies, 71(3), 393–408.
107. Willemsen, L. M., Withuis, I., Brom, M., & Boerman, S. C. (2025). How does persuasion knowledge differ between humanlike virtual influencers and human influencers? International Journal of Advertising, 44(1), 109–130.
108. Wong, J., & Wong, A. (2025). Consumer resistance to service robots: A stressor-based perspective on engagement and wellbeing. Journal of Consumer Marketing, 42(1), 56–71.
109. Xu, Y., Wang, R., & Qin, J. (2025). Examining the influence of avatar distinctiveness on consumers’ purchase intention: An empirical study. Journal of Data, Information and Management, 1–16.
110. Yang, J., Chuenterawong, P., Lee, H., Tian, Y., & Chock, T. M. (2023). Human versus virtual influencer: The effect of humanness and interactivity on persuasive CSR messaging. Journal of Interactive Advertising, 23(3), 275-292.
111. Yu, Q., & Lan, X. (2024). Exploring the impact of anthropomorphism in role-playing AI chatbots on media dependency: A case study of Xuanhe AI. arXiv preprint. arXiv:2411.17157.
112. Yuen, K. F., Cai, L., Qi, G., & Wang, X. (2021). Factors influencing autonomous vehicle adoption: An application of the model and innovation diffusion theory. Technology Analysis & Strategic Management, 33(5), 505–519.
113. Yunus, M. (2014). Diffusion of innovation, consumer attitudes and intentions to use mobile banking. In Information and knowledge management (Vol. 4, No. 10, pp. 12-18).
114. Zhafira, A. K., Purba, C. A. F., Asteriani, D., & Soesilo, P. K. (2022). The effect of social media influencer's perceived sincerity and perceived similarity on consumers' attitude and purchase intention. Journal of Research in Business, Economics, and Education, 4(1), 22–32.
115. Zhang, Y., & Wang, S. (2023). The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types. Journal of Retailing and Consumer Services, 74, 103432.
116. Zhou, S., Wang, F., Zhang, Q., & Li, Y. (2021). Avatar design in virtual commerce: The role of self-congruity and perceived value. Journal of Retailing and Consumer Services, 58, 102338.