Research Article
BibTex RIS Cite

Factors Affecting Consumers' Online Purchasing Attitudes Towards Ads Guided by Artificial Intelligence

Year 2024, , 373 - 400, 17.07.2024
https://doi.org/10.53791/imgelem.1482365

Abstract

The aim of this study is to try to explain the factors that are thought to affect consumers' attitudes towards online advertisements guided by artificial intelligence. In this context, by utilizing the TAM model, innovation value, trust and perceived risk variables were added to the research model developed to explain the attitudes of individuals towards online advertisements guided by artificial intelligence. Although it is observed that the trust and perceived risk factors added to the model do not have a significant effect on AI-directed ads, it is thought that the non-significance of the two proposed hypotheses may be due to the data set. Because the literature in which the research model was developed shows that the perceived risk factor has a negative effect on attitudes. In this current study, it was observed that perceived risk had a negative effect on attitudes (R²=-0.038, p≤ ,106) but the hypothesis test was not significant. Similarly, although it was observed that trust had a positive effect on attitudes (R²=0.050, p≤ ,117), the hypothesis test was not significant. On the other hand, perceived usefulness (R²=-0,407 p≤ ,05), perceived ease of use (R²=-0,507, p≤ ,05), perceived novelty (R²=-0,186, p≤ ,05) positively affect attitudes towards AI-directed advertisements.

Ethical Statement

Ethics Committee permission for this study was obtained from Yozgat Bozok University Social Sciences and Humanities Ethics Committee with the decision dated September 20, 2023 and Decision Number 06/04.

References

  • Aguirre, E., Mahr, D., Grewal, D. et al. (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. https://doi.org/10.1016/j.jretai.2014.09.005
  • Al Athmay, A. A. A. R. A. (2015). Demographic Factors as Determinants of e-Governance Adoption: A Field Study in the United Arab Emirates (UAE), Transforming Government: People, Process and Policy, 9(2), 159-180.
  • Al-Gasawneh, J., Alfityani, A., Al-Okdeh, S. et al. (2022). Avoiding Uncertainty by Measuring the İmpact of Perceived Risk on the Intention to Use Financial Artificial İntelligence Services, Uncertain Supply Chain Management, 10(4), 1427-1436.
  • Argan, M., Dinc, H., Kayac, S. et al. (2022). Artificial Intelligence (AI) in Advertising: Understanding and Schematizing the Behaviors of Social Media Users, Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 331-348. https://doi.org/10.14201/adcaij.28331
  • Basha, N. K., Aw, E. C. X. & Chuah, S. H. W. (2022). Are We So Over Smartwatches? Or Can Technology, Fashion, and Psychographic Attributes Sustain Smartwatch Usage?, Technology in Society, 69, 101952.
  • Campbell, C., Plangger, K., Sands, S. et al. (2022). Preparing For An Era of Deepfakes and AI-Generated Ads: A Framework for Understanding Responses to Manipulated Advertising, Journal of Advertising, 51(1), 22-38, DOI: 10.1080/00913367.2021.1909515
  • Cheng, J. M., Kao, L. L. & Lin, J. Y. C. (2004). An Investigation of the Diffusion of Online Games in Taiwan: An Application of Rogers’ Diffusion of Innovation Theory, Journal of American Academy of Business, 5(1/2), 439-445.
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13(3), 319.
  • Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts, International Journal of Man-Machine Studies, 38 (3), 475-487.
  • Demir, K. (2006). Rogers’ın Yeniliğin Yayılması Teorisi ve İnternetten Ders Kaydı, Kuram ve Uygulamada Eğitim Yönetimi Yaz, 47, 367-392.
  • Fornell, C., Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error, Journal of Marketing Research, 18, 39-50. https://doi.org/10.2307/3151312

Tüketı̇cı̇lerı̇n Yapay Zekâ Tarafından Yönlendı̇rı̇len Reklamlara Yönelı̇k Çevrı̇mı̇çı̇ Satın Alma Tutumlarını Etkı̇leyen Faktörler

Year 2024, , 373 - 400, 17.07.2024
https://doi.org/10.53791/imgelem.1482365

Abstract

Bu çalışmanın amacı yapay zekânın yönlendirdiği çevrimiçi reklamlara ilişkin tüketicilerin satın almaya yönelik tutumlarını etkilediği düşünülen faktörleri açıklamaya çalışmaktır. Bu kapsamda TAM modelinden yararlanılarak, geliştirilen araştırma modeline, yenilik değeri, güven ve algılanan risk değişkenleri eklenerek, bireylerin yapay zekânın yönlendirdiği çevrimiçi reklamlara yönelik tutumları açıklanmaya çalışılmıştır. Modele eklenen güven ve algılanan risk faktörlerinin yapay zekânın yönlendirdiği reklamlara yönelik anlamlı bir etkisinin olmadığı gözlemlense de önerilen iki hipotezin anlamlı olmamasının veri seti kaynaklı olabileceği düşünülmektedir. Çünkü araştırma modelinin geliştirildiği literatür algılanan risk faktörünün tutumlar etkisi üzerinde negatif yönde etkisi olduğunu göstermektedir. Bu mevcut çalışmada da algılanan riskin tutumlar üzerinde negatif bir etkisi olduğu (R²=-0,038, p≤ ,106) ancak hipotez testinin anlamlı çıkmadığı görülmüştür. Yine benzer şekilde güvenin tutumlar üzerinde pozitif bir etkisi olduğu görülse de (R²=0,050, p≤ ,117) hipotez testinin anlamlı çıkmadığı gözlenmiştir. Bu karşın algılanan kullanışlılık (R²=-0,407 p≤ ,05), algılanan kullanım kolaylığı (R²=-0,507, p≤ ,05) ve algılanan yenilik değerlerinin (R²=-0,186, p≤ ,05) yapay zekânın yönlendirdiği reklamlara yönelik tutumları pozitif yönde etkilediği görülmüştür.

Ethical Statement

Bu çalışmanın etik kurul başvuru sonucu olumludur ve Yozgat Bozok Üniversitesinin 20 Eylül 2023 ve 06/04 numaralı kararı ile belgelenmiştir.

References

  • Aguirre, E., Mahr, D., Grewal, D. et al. (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. https://doi.org/10.1016/j.jretai.2014.09.005
  • Al Athmay, A. A. A. R. A. (2015). Demographic Factors as Determinants of e-Governance Adoption: A Field Study in the United Arab Emirates (UAE), Transforming Government: People, Process and Policy, 9(2), 159-180.
  • Al-Gasawneh, J., Alfityani, A., Al-Okdeh, S. et al. (2022). Avoiding Uncertainty by Measuring the İmpact of Perceived Risk on the Intention to Use Financial Artificial İntelligence Services, Uncertain Supply Chain Management, 10(4), 1427-1436.
  • Argan, M., Dinc, H., Kayac, S. et al. (2022). Artificial Intelligence (AI) in Advertising: Understanding and Schematizing the Behaviors of Social Media Users, Advances in Distributed Computing and Artificial Intelligence Journal, 11(3), 331-348. https://doi.org/10.14201/adcaij.28331
  • Basha, N. K., Aw, E. C. X. & Chuah, S. H. W. (2022). Are We So Over Smartwatches? Or Can Technology, Fashion, and Psychographic Attributes Sustain Smartwatch Usage?, Technology in Society, 69, 101952.
  • Campbell, C., Plangger, K., Sands, S. et al. (2022). Preparing For An Era of Deepfakes and AI-Generated Ads: A Framework for Understanding Responses to Manipulated Advertising, Journal of Advertising, 51(1), 22-38, DOI: 10.1080/00913367.2021.1909515
  • Cheng, J. M., Kao, L. L. & Lin, J. Y. C. (2004). An Investigation of the Diffusion of Online Games in Taiwan: An Application of Rogers’ Diffusion of Innovation Theory, Journal of American Academy of Business, 5(1/2), 439-445.
  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, 13(3), 319.
  • Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts, International Journal of Man-Machine Studies, 38 (3), 475-487.
  • Demir, K. (2006). Rogers’ın Yeniliğin Yayılması Teorisi ve İnternetten Ders Kaydı, Kuram ve Uygulamada Eğitim Yönetimi Yaz, 47, 367-392.
  • Fornell, C., Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error, Journal of Marketing Research, 18, 39-50. https://doi.org/10.2307/3151312
There are 11 citations in total.

Details

Primary Language English
Subjects Communication Sociology, Quantitative Methods in Sociology
Journal Section Articles
Authors

Simge Aksu 0000-0002-1818-0455

Betül Çepni Şener 0000-0002-1894-6799

Publication Date July 17, 2024
Submission Date May 11, 2024
Acceptance Date June 12, 2024
Published in Issue Year 2024

Cite

APA Aksu, S., & Çepni Şener, B. (2024). Factors Affecting Consumers’ Online Purchasing Attitudes Towards Ads Guided by Artificial Intelligence. İmgelem(14), 373-400. https://doi.org/10.53791/imgelem.1482365

cc-by-nc_1.png

This work licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Please click here to contact the publisher.