The phenomenon of animated characters: A Generation Z perspective
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Abstract
This study delves into the factors contributing to the popularity of animated characters among Generation Z viewers, a generation deeply immersed in the digital transformation of entertainment and media. To unravel the allure of animated characters for Generation Z, this research explores their emotional resonance, educational significance, and cultural relevance. The research objectives encompass examining Generation Z viewers' affinity for animated characters, utilizing a quantitative cross-sectional methodology. A sample was selected via convenience sampling, targeting animated movie enthusiasts aged 15 to 26, who participated in an online questionnaire. The study's findings were gathered through a rigorously quality-checked questionnaire, ensuring that the measurement models for both variables, character appearance and character attributes met good quality criteria. This achievement can be attributed to the rigorous development process, which ensured content validity. The results depict a sample predominantly comprised of female university students with a pronounced penchant for animated-style movies. Their preferences lean toward 3D animation and cartoons, particularly favoring animated films segmented into parts or episodes (spin-offs). In evaluating the characters' popularity based on appearance, male characters with endearing features, long hairstyles, superhuman abilities, and contemporary attire garnered the highest favor. Furthermore, when considering character roles, Generation Z respondents displayed a preference for main characters endowed with distinct labels, unique powers, and cheerful, sociable personalities. Characters with significant wealth also piqued their interest.
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References
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173
Bassiouni, D. H., & Hackley, C. (2014). 'Generation Z' children's adaptation to digital consumer culture: A critical literature review. Journal of Customer Behaviour, 13(2), 113–133. https://doi.org/10.1362/147539214X14024779483591
Bedekar, M., & Joshi, P. (2020). Cartoon films and their impact on children’s mentality. Research Review: International Journal of Multidisciplinary, 5(6), 13–18. https://doi.org/10.31305/rrijm.2020.v05.i06.003
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Sage Publications.
Çınar, D., & Kurt, H. (2019). Development of animation attitude scale (AAS): Validity and reliability study. Journal of Computer and Education Research, 7(14), 558–574. https://doi.org/10.18009/jcer.617943
DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). Sage Publications.
Digital Economy Promotion Agency (Depa). (2023). Big opportunities and challenges to drive the digital economy of the Gen Z era. https://www.depa.or.th/en/article-view/article4-2563 [in Thai]
Fuller, F. R. (2021). The atomic bomb: Reflections in Japanese manga and animated. International Journal of Social Science and Humanities Research, 9(2), 56–128.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications.
Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Ingard, A. (2023a). Principle, theories, and practices: Structural equation modeling (2nd ed). Chulalongkorn University Press. [in Thai]
Ingard, A. (2023b). Statistics for research design. Silpakorn University. [in Thai]
Kline, R. B. (1998). Principles and practice of structural equation modeling. The Guilford Press.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
Oh, W.-O., Song, D., Han, J., Park, M. Y., & Park, I. T. (2021). The hospital safety scale for kids: Development of a new measurement tool for hospitalized children. Journal of Child Health Care, 25(1), 146–160. https://doi.org/10.1177/1367493520913768
Roscoe, J. T. (1975). Fundamental research statistics for the behavioral sciences. Holt, Rinehart and Winston.
Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling (2nd ed.). Lawrence Erlbaum Associates.
Tirakoat, S. (2021). The study of educational game design components by factors analysis of player’s perception. Journal of Graduate Studies Valaya Alongkorn Rajabhat University, 15(3), 222–234. [in Thai]