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Examining University Students’ Perception and Ad Viewing Behavior in Artificial Intelligence (AI) Influencer Marketing

Year 2025, Volume: 22 Issue: 4, 810 - 820

Can Saygıner

https://doi.org/10.26466/opusjsr.1706956

Abstract

The effectiveness of social media advertisements increasingly depends on their influence on consumer viewing behavior. This study explores how consumer perceptions—specifically informativeness, entertainment, credibility, economic contribution, and value deterioration—affect advertisement viewing behavior in the context of AI influencer marketing. Data were collected from 134 university students at public and private universities in Izmir through a structured questionnaire and analyzed using SMARTPLS 4.0 with a structural equation modeling approach. Results showed that informativeness and credibility significantly enhanced perceived entertainment, which in turn positively influenced advertisement viewing behavior. Additionally, economic contribution (representing innovation) had a direct and significant effect on viewing behavior. The model explained 37.3% of the variance in advertisement viewing behavior, demonstrating moderate explanatory power. These findings highlight the critical role of perceived entertainment and innovation in shaping engagement with AI influencer ads, offering valuable insights for marketers aiming to optimize their digital advertising strategies in the age of artificial intelligence.

Keywords

Social Media Advertising AI Influencers University Students’ Perception Advertisement Viewing Behavior Structural Equation Modeling

References

  • Chan, K. W., Septianto, F., Kwon, J., & Kamal, R. S. (2023). Color effects on AI influencers’ product recommendations. European Journal of Marketing, 57(9), 2290-2315. https://doi.org/-10.1108/ejm-03-2022-0185
  • Chen, X., & Ryoo, J. (2025). Advancing AI in healthcare through professional training: Insights from Chinese practitioners. Scientia. Technology, Science and Society, 2(1), 95-110. https://doi.org/10.59324/stss.2025.2(1).08
  • Choi, M., Choi, Y., & Lee, H. (2023). Gen Z travelers in the Instagram marketplace: Trust, influencer type, post type, and purchase intention. Journal of Hospitality & Tourism Research, 48(6), 1020-1034. https://doi.org/10.1177/-10963480231180938
  • Chu, C., Chiang, I., Tsai, K., & Tung, Y. (2023). Exploring the effects of personalized advertising on social network sites. Journal of Social Media Marketing, 1(2), 38-54. https://doi.org/10.-33422/jsmm.v1i2.1051
  • Faisal, A., Adzharuddin, N. A., & Yusof, R. N. R. (2024). The nexus between advertising and trust: Conceptual review in the context of halal food, Malaysia. International Journal of Academic Research in Business and Social Sciences, 14(1), 600-620. https://doi.org/10.-6007/ijarbss/v14-i1/19718
  • George, B. & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196. https://doi.org/10.3390-/admsci13090196
  • Giang, N. T. P., Duy, N B. P., Anh, N. H. T., Giang, D. N. T., Triet, D. M., & Tan, T. D. (2025). Factors influencing the intention to use artificial intelligence for online advertising on social networks. Multidisciplinary Science Journal, 7(8), 2025416. https://doi.org/10.31893/multiscience.2025416
  • Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modelling. Sage Publications Inc.
  • Huang, Q., Qu, H., & Li, P. (2022). The influence of virtual idol characteristics on consumers’ clothing purchase intention. Sustainability, 14(14), 8964. https://doi.org/10.3390/su-14148964
  • Jawaid, S. A., & Qureshi, J. (2024). How artificial intelligence and machine learning can impact market design. Advances in Urban Regional Development and Planning, 1(1), 1-8. https://doi.org/10.20944/preprints202402.-0011.v1
  • Kelling, A. S., Wilson, M. L., Martin, A. L., Barker, S., & Mallavarapu, S. (2024). Exploring best practices in constructing dog adoption advertisements. Society & Animals (published online ahead of print 2024). https://doi.org-/10.1163/15685306-bja10192
  • Kim, E., Kim, D., Zihang, E., & Shoenberger, H. (2023). The next hype in social media advertising: Examining virtual influencers’ brand endorsement effectiveness. Frontiers in Psychology, 14, 1089051. https://doi.org/10.3389-/fpsyg.2023.1089051
  • Kim, J., Giroux, M., & Lee, J. C. (2021). When do you trust AI? The effect of number presentation detail on consumer trust and acceptance of AI recommendations. Psychology & Marketing, 38(7), 1140-1155. https://doi.org/-10.1002/mar.21498
  • Knödler, L. & Rudeloff, C. (2024). Look who’s talking now: The effects of pre-recorded and AI-generated synthetic brand voices on brand anthropomorphism and brand equity. Journal of Creative Communications, 19(3), 295-311. https://doi.org/10.1177/09732586241253651
  • Li, B. and Nan, Y. (2023). Real versus virtual celebrity endorsement: Presentation of online product information and consumer attitudes toward digital products. Marketing Intelligence & Planning, 42(2), 304-328. https://doi.org/10.-1108/mip-06-2023-0288
  • MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. https://doi. org/10.1037/1082-989X.1.2.130
  • Miyake, E. (2022). I am a virtual girl from Tokyo: Virtual influencers, digital-orientalism and the (im)materiality of race and gender. Journal of Consumer Culture, 23(1), 209-228. https://doi.org/10.1177/14695405221117195
  • Pitardi, V. & Marriott, H. R (2021). Alexa, she's not human but… Unveiling the drivers of consumers' trust in voice‐based artificial intelligence. Psychology & Marketing, 38(4), 626-642. https://doi.org/10.1002/mar.21457
  • Sands, S., Campbell, C. L, Plangger, K., & Ferraro, C. (2022). Unreal influence: Leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721-1747. https://doi.org/10.-1108/ejm-12-2019-0949
  • Sands, S., Demsar, V., Ferraro, C., Campbell, C., & Cohen, E. (2024). Inauthentic inclusion: Exploring how intention to use AI‐generated diverse models can backfire. Psychology & Marketing, 41(6), 1396-1413. https://doi.org/10.-1002/mar.21987
  • Soti, R. (2022). The impact of advertising on consumer behavior. World Journal of Advanced Research and Reviews, 14(3), 706-711. https://doi.org/-10.30574/wjarr.2022.14.3.0577
  • Stright, A., Sloan, G., Code, M. N., Gorman, M., Moss, R., & McSweeney, M. B. (2025). A preliminary investigation into the use of AI‐generated food images in a survey asking about consumer perception of appeal, naturalness, healthiness, and willingness to consume. Journal of Sensory Studies, 40(1), 1-9. https://doi.org/10.1111/joss.70015
  • Tauheed, J., Shabbir, A., & Pervez, M. (2024). Exploring the role of artificial intelligence in digital marketing strategies. Journal of Business Communication & Technology, 54-65. https://doi.org/10.56632/bct.2024.3105
  • Wang, W., & Li, G. (2021). A theoretical analysis of the pricing and advertising strategies with Lévy-Walking consumers. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2129-2150. https://doi.org/10.3390/-jtaer16060119
  • Wang, X., Zhu, H., Jiang, D., Xia, S., & Xiao, C. (2023). “Facilitators” vs “Substitutes”: The influence of artificial intelligence products’ image on consumer evaluation. Nankai Business Review International, 14(1), 177-193. https://doi.org/-10.1108/nbri-05-2022-0051
  • Wang, Y., Sun, S., Lei, W., & Toncar, M. (2009). Examining beliefs and attitudes toward online advertising among Chinese consumers. Direct Marketing: An International Journal, 3(1), 52-66. https://doi.org/10.1108/17505930910945732
  • Wortel, C., Vanwesenbeeck, I., & Tomas, F. (2024). Made with artificial intelligence: The effect of artificial intelligence disclosures in instagram advertisements on consumer attitudes. Emerging Media, 2(3), 547-570. https://doi.org/10.1177/27523543241292096
  • Wu, C-W. & Monfort, A. (2022). Role of artificial intelligence in marketing strategies and performance. Psychology & Marketing, 40(3), 484-496. https://doi.org/10.1002/mar.21737
  • Xu, Y., Tat, H. H., & Sade, A. B. (2024). A literature analysis on the relationship between AI influencers’ perceived credibility and purchase intention: Product-endorser fit with the brand as a moderator. International Journal of Academic Research in Business and Social Sciences, 14(3), 370-382. https://doi.org/10.6007-/ijarbss/v14-i3/21092
  • Yazdani, A., & Darbani, S. (2023). The impact of AI on trends, design, and consumer behavior. AI and Tech in Behavioral and Social Sciences, 1(4), 4-10. https://doi.org/10.61838/kman.aitech.-1.4.2
  • Yim, A., Cui, A. P., & Walsh, M. (2023). The role of cuteness on consumer attachment to artificial intelligence agents. Journal of Research in Interactive Marketing, 18(1), 127-141. https://doi.org/10.1108/jrim-02-2023-0046
  • Zhang, Y., Zhu, J., Chen, H., & Jiang, Y. (2024). Enhancing trust and empathy in marketing: Strategic AI and human influencer selection for optimized content persuasion. Journal of Consumer Behaviour, 24(2), 866-885. https://doi.org/10.1002/cb.2423
  • Zhang, Z., Fort J. M., & Mateu, L. G. (2024). Decoding emotional responses to AI-generated architectural imagery. Frontiers in Psychology, 15: 1348083. https://doi.org/10.3389/fpsyg.2024.-1348083

Yapay Zekâ (YZ) Influencer Pazarlamasında Üniversite Öğrencilerinin Algısı ve Reklam İzleme Davranışının İncelenmesi

Year 2025, Volume: 22 Issue: 4, 810 - 820

Can Saygıner

https://doi.org/10.26466/opusjsr.1706956

Abstract

Sosyal medya reklamlarının etkinliği, giderek artan bir şekilde tüketici izleme davranışlarını etkileme düzeyine bağlı hâle gelmektedir. Bu çalışma, tüketici algılarının—özellikle bilgilendiricilik, eğlence, güvenilirlik, ekonomik katkı ve değer yozlaşması—yapay zekâ tabanlı influencer pazarlaması bağlamında reklam izleme davranışı üzerindeki etkilerini incelemektedir. Veriler, İzmir’deki devlet ve özel üniversitelerinde öğrenim gören 134 üniversite öğrencisinden yapılandırılmış bir anket aracılığıyla toplanmış ve SMARTPLS 4.0 kullanılarak yapısal eşitlik modelleme yöntemiyle analiz edilmiştir. Bulgular, bilgilendiricilik ve güvenilirliğin algılanan eğlence düzeyini anlamlı şekilde artırdığını ve eğlencenin reklam izleme davranışı üzerinde pozitif bir etkisi olduğunu ortaya koymuştur. Ayrıca, ekonomik katkı (yenilik katkısını temsilen) reklam izleme davranışını doğrudan ve anlamlı biçimde etkilemiştir. Model, reklam izleme davranışındaki varyansın %37,3’ünü açıklamış ve orta düzeyde bir açıklayıcılık sunmuştur. Bu bulgular, yapay zekâ influencer reklamlarında algılanan eğlence ve yenilik katkısının, tüketici etkileşimini şekillendirmedeki kritik rolünü vurgulamakta ve dijital reklam stratejilerini optimize etmek isteyen pazarlamacılar için değerli içgörüler sunmaktadır.

Keywords

Sosyal Medya Reklamcılığı Yapay Zekâ Influencer’ları Üniversite Öğrencilerinin Algısı Reklam İzleme Davranışı Yapısal Eşitlik Modellemesi

References

  • Chan, K. W., Septianto, F., Kwon, J., & Kamal, R. S. (2023). Color effects on AI influencers’ product recommendations. European Journal of Marketing, 57(9), 2290-2315. https://doi.org/-10.1108/ejm-03-2022-0185
  • Chen, X., & Ryoo, J. (2025). Advancing AI in healthcare through professional training: Insights from Chinese practitioners. Scientia. Technology, Science and Society, 2(1), 95-110. https://doi.org/10.59324/stss.2025.2(1).08
  • Choi, M., Choi, Y., & Lee, H. (2023). Gen Z travelers in the Instagram marketplace: Trust, influencer type, post type, and purchase intention. Journal of Hospitality & Tourism Research, 48(6), 1020-1034. https://doi.org/10.1177/-10963480231180938
  • Chu, C., Chiang, I., Tsai, K., & Tung, Y. (2023). Exploring the effects of personalized advertising on social network sites. Journal of Social Media Marketing, 1(2), 38-54. https://doi.org/10.-33422/jsmm.v1i2.1051
  • Faisal, A., Adzharuddin, N. A., & Yusof, R. N. R. (2024). The nexus between advertising and trust: Conceptual review in the context of halal food, Malaysia. International Journal of Academic Research in Business and Social Sciences, 14(1), 600-620. https://doi.org/10.-6007/ijarbss/v14-i1/19718
  • George, B. & Wooden, O. (2023). Managing the strategic transformation of higher education through artificial intelligence. Administrative Sciences, 13(9), 196. https://doi.org/10.3390-/admsci13090196
  • Giang, N. T. P., Duy, N B. P., Anh, N. H. T., Giang, D. N. T., Triet, D. M., & Tan, T. D. (2025). Factors influencing the intention to use artificial intelligence for online advertising on social networks. Multidisciplinary Science Journal, 7(8), 2025416. https://doi.org/10.31893/multiscience.2025416
  • Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modelling. Sage Publications Inc.
  • Huang, Q., Qu, H., & Li, P. (2022). The influence of virtual idol characteristics on consumers’ clothing purchase intention. Sustainability, 14(14), 8964. https://doi.org/10.3390/su-14148964
  • Jawaid, S. A., & Qureshi, J. (2024). How artificial intelligence and machine learning can impact market design. Advances in Urban Regional Development and Planning, 1(1), 1-8. https://doi.org/10.20944/preprints202402.-0011.v1
  • Kelling, A. S., Wilson, M. L., Martin, A. L., Barker, S., & Mallavarapu, S. (2024). Exploring best practices in constructing dog adoption advertisements. Society & Animals (published online ahead of print 2024). https://doi.org-/10.1163/15685306-bja10192
  • Kim, E., Kim, D., Zihang, E., & Shoenberger, H. (2023). The next hype in social media advertising: Examining virtual influencers’ brand endorsement effectiveness. Frontiers in Psychology, 14, 1089051. https://doi.org/10.3389-/fpsyg.2023.1089051
  • Kim, J., Giroux, M., & Lee, J. C. (2021). When do you trust AI? The effect of number presentation detail on consumer trust and acceptance of AI recommendations. Psychology & Marketing, 38(7), 1140-1155. https://doi.org/-10.1002/mar.21498
  • Knödler, L. & Rudeloff, C. (2024). Look who’s talking now: The effects of pre-recorded and AI-generated synthetic brand voices on brand anthropomorphism and brand equity. Journal of Creative Communications, 19(3), 295-311. https://doi.org/10.1177/09732586241253651
  • Li, B. and Nan, Y. (2023). Real versus virtual celebrity endorsement: Presentation of online product information and consumer attitudes toward digital products. Marketing Intelligence & Planning, 42(2), 304-328. https://doi.org/10.-1108/mip-06-2023-0288
  • MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130-149. https://doi. org/10.1037/1082-989X.1.2.130
  • Miyake, E. (2022). I am a virtual girl from Tokyo: Virtual influencers, digital-orientalism and the (im)materiality of race and gender. Journal of Consumer Culture, 23(1), 209-228. https://doi.org/10.1177/14695405221117195
  • Pitardi, V. & Marriott, H. R (2021). Alexa, she's not human but… Unveiling the drivers of consumers' trust in voice‐based artificial intelligence. Psychology & Marketing, 38(4), 626-642. https://doi.org/10.1002/mar.21457
  • Sands, S., Campbell, C. L, Plangger, K., & Ferraro, C. (2022). Unreal influence: Leveraging AI in influencer marketing. European Journal of Marketing, 56(6), 1721-1747. https://doi.org/10.-1108/ejm-12-2019-0949
  • Sands, S., Demsar, V., Ferraro, C., Campbell, C., & Cohen, E. (2024). Inauthentic inclusion: Exploring how intention to use AI‐generated diverse models can backfire. Psychology & Marketing, 41(6), 1396-1413. https://doi.org/10.-1002/mar.21987
  • Soti, R. (2022). The impact of advertising on consumer behavior. World Journal of Advanced Research and Reviews, 14(3), 706-711. https://doi.org/-10.30574/wjarr.2022.14.3.0577
  • Stright, A., Sloan, G., Code, M. N., Gorman, M., Moss, R., & McSweeney, M. B. (2025). A preliminary investigation into the use of AI‐generated food images in a survey asking about consumer perception of appeal, naturalness, healthiness, and willingness to consume. Journal of Sensory Studies, 40(1), 1-9. https://doi.org/10.1111/joss.70015
  • Tauheed, J., Shabbir, A., & Pervez, M. (2024). Exploring the role of artificial intelligence in digital marketing strategies. Journal of Business Communication & Technology, 54-65. https://doi.org/10.56632/bct.2024.3105
  • Wang, W., & Li, G. (2021). A theoretical analysis of the pricing and advertising strategies with Lévy-Walking consumers. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2129-2150. https://doi.org/10.3390/-jtaer16060119
  • Wang, X., Zhu, H., Jiang, D., Xia, S., & Xiao, C. (2023). “Facilitators” vs “Substitutes”: The influence of artificial intelligence products’ image on consumer evaluation. Nankai Business Review International, 14(1), 177-193. https://doi.org/-10.1108/nbri-05-2022-0051
  • Wang, Y., Sun, S., Lei, W., & Toncar, M. (2009). Examining beliefs and attitudes toward online advertising among Chinese consumers. Direct Marketing: An International Journal, 3(1), 52-66. https://doi.org/10.1108/17505930910945732
  • Wortel, C., Vanwesenbeeck, I., & Tomas, F. (2024). Made with artificial intelligence: The effect of artificial intelligence disclosures in instagram advertisements on consumer attitudes. Emerging Media, 2(3), 547-570. https://doi.org/10.1177/27523543241292096
  • Wu, C-W. & Monfort, A. (2022). Role of artificial intelligence in marketing strategies and performance. Psychology & Marketing, 40(3), 484-496. https://doi.org/10.1002/mar.21737
  • Xu, Y., Tat, H. H., & Sade, A. B. (2024). A literature analysis on the relationship between AI influencers’ perceived credibility and purchase intention: Product-endorser fit with the brand as a moderator. International Journal of Academic Research in Business and Social Sciences, 14(3), 370-382. https://doi.org/10.6007-/ijarbss/v14-i3/21092
  • Yazdani, A., & Darbani, S. (2023). The impact of AI on trends, design, and consumer behavior. AI and Tech in Behavioral and Social Sciences, 1(4), 4-10. https://doi.org/10.61838/kman.aitech.-1.4.2
  • Yim, A., Cui, A. P., & Walsh, M. (2023). The role of cuteness on consumer attachment to artificial intelligence agents. Journal of Research in Interactive Marketing, 18(1), 127-141. https://doi.org/10.1108/jrim-02-2023-0046
  • Zhang, Y., Zhu, J., Chen, H., & Jiang, Y. (2024). Enhancing trust and empathy in marketing: Strategic AI and human influencer selection for optimized content persuasion. Journal of Consumer Behaviour, 24(2), 866-885. https://doi.org/10.1002/cb.2423
  • Zhang, Z., Fort J. M., & Mateu, L. G. (2024). Decoding emotional responses to AI-generated architectural imagery. Frontiers in Psychology, 15: 1348083. https://doi.org/10.3389/fpsyg.2024.-1348083
There are 33 citations in total.

Details

Primary Language English
Subjects Communication Technology and Digital Media Studies, Internet, Social Media Studies
Journal Section Research Articles
Authors

Can Saygıner 0000-0002-1680-392X

Early Pub Date August 3, 2025
Publication Date
Submission Date May 26, 2025
Acceptance Date August 3, 2025
Published in Issue Year 2025 Volume: 22 Issue: 4

Cite

APA Saygıner, C. (2025). Examining University Students’ Perception and Ad Viewing Behavior in Artificial Intelligence (AI) Influencer Marketing. OPUS Journal of Society Research, 22(4), 810-820. https://doi.org/10.26466/opusjsr.1706956
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