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15(2)2025

How playable advertisements affect Gen Z’s intention to download apps in Ho Chi Minh City


Author - Affiliation:
Long Cuu Hoang - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Hoan Phuc Ho - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Hung Xuan Dao - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Binh Gia Nguyen - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Giang Vu Chau Le - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Ha Nhu Ngoc Nguyen - University of Economics Ho Chi Minh City, Ho Chi Minh City , Vietnam
Corresponding author: Long Cuu Hoang - hoangcuulong@ueh.edu.vn
Submitted: 30-12-2023
Accepted: 21-04-2024
Published: 30-05-2024

Abstract
With the rapid growth of the Internet and portable devices such as smartphones and tablets, mobile advertisements have become a powerful, widely implemented marketing method. Having been popularly developed from 2014 - 2015, playable advertisements quickly gained intentions from advertisers, marketers, and app creators. However, due to the novelty of this advertising method, its effect on Gen Z audiences’ app-downloading intention in Ho Chi Minh City has not been examined yet. Therefore, this study aims to make further investigations into this topic by using the Theory of Reasoned Action (TRA), the Use and Gratification Theory (UGT) and the Theory of Planned Behavior (TPB). The research is conducted with a sample size of 342 respondents, and an online questionnaire is used to collect data from these research participants. The collected data is analyzed using Partial-Least-Squares Structural Equation Modeling (PLS-SEM), which subsequently indicates that these audiences’ attitudes, which are directly affected by their perceived value of the advertisements, are significantly associated with their intentions to download the advertised apps. Particularly, the respondents’ perceived value tends to be positively enhanced, which then stimulates an increase in their attitude towards the advertisements and consequently boosts their app-downloading intention once the credibility and entertainment of that advertisement are high, while the irritation is at a reasonably low level. A mediating effect of these Gen Z audiences’ attitudes in the relationship between advertising value and their app-downloading intentions is also found in this research. Overall, findings from this research are able to provide further understanding of which criteria affect the experience, perspectives, and responses of Gen Z audiences in Ho Chi Minh City when they interact with playable advertisements, which is insightful for advertisers, marketers, and app creators in applying the right advertising method into their mobile marketing strategies.

JEL codes
M37; O33; D84

Keywords
app download intention; Generation Z; Ho Chi Minh City (HCMC); playable advertisements; playable technology

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Cite this paper as:

Hoang, L. C., Ho, H. P., Dao, H. X., Nguyen, B. G., Le, G. V. C., & Nguyen, H. N. N. (2025). How playable advertisements affect Gen Z’s intention to download apps in Ho Chi Minh City. Ho Chi Minh City Open University Journal of Science – Economics and Business Administration, 15(2), 51-66. doi:10.46223/HCMCOUJS.econ.en.15.2.3154.2025


References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.


Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin82(2), Article 261.


Aydin, G., & Karamehmet, B. (2017). A comparative study on attitudes towards SMS advertising and mobile application advertising. International Journal of Mobile Communications15(5), 514-536.


Bauer, R. A. (1960). Consumer behavior as risk taking. Proceedings of the 43rd National Conference of the American Marketing Assocation, Chicago, Illinois. American Marketing Association.


Berlyne, D. E. (1970). Novelty, complexity, and hedonic value. Perception & Psychophysics, 8(5), 279-286.


Blumler, J. G., & Katz, E. (1974). The uses of mass communications: Current perspectives on gratifications research. Sage Annual Reviews of Communication Research Volume III.


BuildFire. (2024). 10 app categories that will dominate 2024 and beyond. https://buildfire.com/app-categories/


Buzeta, C., De Pelsmacker, P., & Dens, N. (2020). Motivations to use different social media types and their impact on Consumers’ Online Brand-Related Activities (COBRAs). Journal of Interactive Marketing, 52(1), 79-98.


Cacioppo, J. T., & Petty, R. E. (1989). Effects of message repetition on argument processing, recall, and persuasion. Basic and Applied Social Psychology, 10(1), 3-12.


Choi, H., & McMillan. (2008). Gearing up for mobile advertising: A cross-cultural examination of key factors that drive mobile messages home to consumers. Psychology and Marketing, 25(8), 4-5.


Cuillier, D., & Piotrowski, S. J. (2009). Internet information-seeking and its relation to support for access to government records. Government Information Quarterly, 26(3), 441-449.


Dimmick, J. W., Sikand, J., & Patterson, S. J. (1994). The gratifications of the household telephone: Sociability, instrumentality, and reassurance. Communication Research, 21(5), 643-663.


Ducoffe R. H. (1996). Advertising value and advertising on the web. Journal of Advertising Research, 36(5), 21-36.


Haghirian, P., Madlberger, M., & Tanuskova, A. (2005). Increasing advertising value of mobile marketing-an empirical study of antecedents. In Proceedings of the 38th annual Hawaii international conference on system sciences (pp. 32c-32c). IEEE.


Haq, Z. U. (2009). E-mail advertising: A study of consumer attitude toward e-mail advertising among Indian users. Journal of Retail & Leisure Property8(3), 207-223.


Hu, X., & Wise, K. (2021). How playable advertisements influence consumer attitude: Exploring the mediation effects of perceived control and freedom threat. Journal of Research in Interactive Marketing, 15(2), 295-315.


Interactive Advertising Bureau. (2019). Playable advertisements for brands: An IAB playbook www.iab.com/insights/playable-advertisements-for-brands-playbook/


Kaur, P., Dhir, A., Chen, S., Malibari, A., & Almotairi, M. (2020). Why do people purchase virtual goods? A Uses and Gratification (U&G) theory perspective. Telematics and Informatics53, Article 101376.


Lin, C. A. (2006). Predicting satellite radio adoption via listening motives, activity, and format preference. Journal of Broadcasting & Electronic Media, 50(1), 140-159.


Lin, T. T., & Bautista, J. R. (2018). Content-related factors influence perceived value of location-based mobile advertising. Journal of Computer Information Systems, 60(2), 184-193.


Liu, C. L. E., Sinkovics, R. R., Pezderka, N., & Haghirian, P. (2012). Determinants of consumer perceptions toward mobile advertising - A comparison between Japan and Austria. Journal of Interactive Marketing, 26(1), 21-32.


MacKenzie, S. B., & Lutz, R. J. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing53(2), 48-65.


Malki, M., & Shaqrah, A. (2019). Analysis of gamification elements to explore misinformation sharing based on U&G theory: A software engineering perspective. International Journal of Software Engineering & Applications (IJSEA), 10(4).


Miltgen, C. L., Cases, A. S., & Russell, C. A. (2019). Consumers’ responses to Facebook advertising across PCs and mobile phones: A model for assessing the drivers of approach and avoidance of Facebook advertisements. Journal of Advertising Research, 59(4), 414-432.


Okazaki, S., Katsukura, A., & Nishiyama, M. (2007). How mobile advertising works: The role of trust in improving attitudes and recall. Journal of Advertising Research, 47(2), 165-178.


Panda, S., & Pandey, S. C. (2017). Binge watching and college students: Motivations and outcomes. Young Consumers, 18(4), 425-438.


Rialti, R., Filieri, R., Zollo, L., Bazi, S., & Ciappei, C. (2022). Assessing the relationship between gamified advertising and in-app purchases: A consumers’ benefits-based perspective. International Journal of Advertising, 41(5), 868-891.


Scharl, A., Dickinger, A., & Murphy, J. (2005). Diffusion and success factors of mobile marketing. Electronic Commerce Research and Applications4(2), 159-173.


Schmidt, S., & Eisend, M. (2015). Advertising repetition: A meta-analysis on effective frequency in advertising. Journal of Advertising, 44(4), 415-428.


Shavitt, S., Lowrey, P., & Haefner, J. (1998). Public attitudes towards advertising: More favourable than you might think. Journal of Advertising Research, 38(4), 7-22.


Sigurdsson, V., Menon, R. V., Hallgrímsson, A. G., Larsen, N. M., & Fagerstrøm, A. (2018). Factors affecting attitudes and behavioral intentions toward in-app mobile advertisements. Journal of Promotion Management, 24(5), 694-714.


Sreejesh, S., Ghosh, T., & Dwivedi, Y. K. (2021). Moving beyond the content: The role of contextual cues in the effectiveness of gamification of advertising. Journal of Business Research, 132, 88-101.


Taylor, D. G., Lewin, J. E., & Strutton, D. (2011). Friends, fans, and followers: Do ads work on social networks? How gender and age shape receptivity. Journal of Advertising Research51(1), 258-275.


Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science46(2), 186-204.


Watson, C., McCarthy, J., & Rowley, J. (2013). Consumer attitudes towards mobile marketing in the smart phone era. International Journal of Information Management33(5), 840-849.


Wut, E., Ng, P., Leung, K. S. W., & Lee, D. (2021), Do gamified elements affect young people’s use behavior on consumption-related mobile applications? Young Consumers, 22(3), 368-386.


Xu, D. J. (2006). The influence of personalization in affecting consumer attitude toward mobile advertising in China. The Journal of Computer Information Systems, 47(2), 9-21.


Xu, D. J., Liao, S. S., & Li, Q. (2008). Combining empirical experimentation and modeling techniques: A design research approach for personalized mobile advertising applications. Decision Support Systems, 44(3), 710-724.



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