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An Advertising Policy Model in Digital Marketing Using Eye Tracking | ||
| International Journal of Digital Content Management | ||
| دوره 7، شماره 12، فروردین 2026، صفحه 292-307 اصل مقاله (881.06 K) | ||
| نوع مقاله: Review Article | ||
| شناسه دیجیتال (DOI): 10.22054/dcm.2022.69257.1141 | ||
| نویسندگان | ||
| Seyed Hamid Mir Motahari1؛ Sina Nematizadeh* 2؛ Seyed Abbas Heydari3 | ||
| 1Ph.D. Candidate of Business Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| 2Assistance Professor, Department of Business Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| 3Associate Professor, Department of Business Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| چکیده | ||
| Purpose: This research aims to develop an advertising policy model in digital marketing based on eye tracking. Method: The research method is qualitative and based on grounded theory. Semi-structured interviews were used to collect information, and data analysis was performed using the Strauss and Corbin method and the paradigm model. Sampling was theoretical sampling using targeted (judgmental) techniques, based on which 15 interviews were conducted with managers and marketing and advertising experts. Findings: The findings of the research show that during the process of open, central and selective coding, the advertising policy model based on the use of eye tracking consists of Causal categories that include Advertising content, Quality of environmental advertising and Promotional features; contextual categories consist of advertising slogans, billboard elements, analysis of customer eye movements; intervening categories consist of online advertising, advertising costs, advertising through media and mass communication; Central categories that consist of environmental advertising status, development of advertising influence, effective advertising on customers' intentions; category of strategies includes advertising message attractions, evaluation of target environmental advertising selection process, advertising based on customers' taste; consequence category includes competitive advantage, currency innovation, Promotion of strategic marketing decisions. Conclusion: The study concludes that the eye tracking-based advertising policy model provides a comprehensive framework for enhancing advertising strategies. The model emphasizes the importance of considering various factors such as advertising content, consumer behavior, and contextual elements in developing effective advertising campaigns. The research highlights the potential of eye tracking in optimizing advertisements and gaining a competitive edge in the market. From a managerial perspective, the model offers actionable insights for marketers to improve customer engagement and increase advertising effectiveness by leveraging eye tracking data. It also suggests that advertisements should be tailored to consumer preferences and the context in which they are viewed. The study advocates for further research in this area to broaden the application of eye tracking technology in other marketing domains and service sectors. From an academic standpoint, this research contributes to the limited body of knowledge regarding environmental advertising and the use of eye tracking in marketing. It provides a foundation for future studies to explore the relationship between visual marketing and consumer behavior, offering insights that could foster innovative advertising strategies in the digital marketing field. | ||
| کلیدواژهها | ||
| Digital Marketing؛ Advertisement؛ Policy Model؛ Eye Tracking | ||
| مراجع | ||
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Casado-Aranda, L. A., Sánchez-Fernández, J., & Ibáñez-Zapata, J. Á. (2020). Evaluating communication effectiveness through eye tracking: Benefits, state of the art, and unresolved questions. International Journal of Business Communication, 23(2), 94-112.
Guitart, I. A., Hervet, G., & Hildebrand, D. (2018). Using eye-tracking to understand the impact of multitasking on memory for banner ads: The role of attention to the ad. International Journal of Advertising, 38(1), 154-170.
Hosp, B., Eivazi, S., Maurer, M., Fuhl, W., Geisler, D., & Kasneci, E. (2020). RemoteEye: An open-source high-speed remote eye tracker. Behavior Research Methods, 52(3), 1387-1401.
Javora, O., Hannemann, T., Volná, K., Děchtěrenko, F., Tetourová, T., Stárková, T., & Brom, C. (2020). Is contextual animation needed in multimedia learning games for children? An eye tracker study. Journal of Computer Assisted Learning, 37(2), 305-318.
Kong, S., Huang, Z., Scott, N., Zhang, Z. A., & Shen, Z. (2019). Web advertisement effectiveness evaluation: Attention and memory. Journal of Vacation Marketing, 25(1), 130-146.
Manhartsberger, M., & Zellhofer, N. (2005). Eye tracking in usability research: What users really see. In Usability Symposium (Vol. 198, No. 2, pp. 141-152).
Marois, A., Lafond, D., Vachon, F., Harvey, E. R., Martin, B., & Tremblay, S. (2020). Mobile real-time eye-tracking for gaze-aware security surveillance support systems. In International Conference on Intelligent Human Systems Integration (pp. 201-207). Springer, Cham.
Muñoz-Leiva, F., Hernández-Méndez, J., & Gómez-Carmona, D. (2019). Measuring advertising effectiveness in Travel 2.0 websites through eye-tracking technology. Physiology & Behavior, 200, 83-95.
Radach, R., Lemmer, S., Vorstius, C., Heller, D., & Radach, K. (2003). Eye movements in the processing of print advertisements. In The mind’s eye (pp. 609-632). North-Holland.
Wang, J. C., & Day, R. F. (2007). The effects of attention inertia on advertisements on the WWW. Computers in Human Behavior, 23(3), 1390-1407. | ||
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