Editor-in-chief

Prof. Paul Sudnik

Munich University of Applied Sciences, Germany

As the Editor-in-Chief of IJSSH, I invite you to contribute your scholarly work to our esteemed publication. The journal publishes papers which focus on the advanced researches in the field of all aspects of social science and humanity. I'll endeavour to make this journal grow better and hopefully it will become a recognized journal among researchers and scholars in related fields.

Home > Archive > 2026 > Volume 16, Number 1, 2026
Chaochu Xiang 1,* and Sili Jian 2, Xinxin Liu 2
1. Visual Communication Design Department, Academy of Fine Arts and Design, Chengdu University, Chengdu, Sichuan, China
2. Digital Media Design, Academy of Fine Arts and Design, Chengdu University, Chengdu, Sichuan, China
Email: xiangchaochu@cdu.edu.cn (C.X.); 1169623226@qq.com (S.J.); 1570859930@qq.com (X.L.)
*Corresponding author

Analysis of Viewing Behavioral Intention towards Chinese Animation within the Context of the AIGC Animation Industry

IJSSH 2026 Vol.16(1): 43-50
doi: 10.18178/ijssh.2026.16.1.1277

Manuscript received December 8, 2025; accepted January 12, 2026, published March 26, 2026.

Abstract— This quantitative study investigated the Behavioral Intention (BI) of audiences to view Chinese animations within the context of the Artificial Intelligence (AI) Generated Content (AIGC) animation industry, alongside identifying the pivotal determinants exerting a significant influence upon it. The study assessed specific determinants, namely AI Based Screenwriting (ABS), AI Based Design Quality (ABDQ), Broadcast System (BS), Linkage System (LS), Social Influence (SI), and Attitude (ATT), to ascertain whether and in what manner they impacted the target audiences’ behavioral intention. Quantitative surveys were administered to the target audience, and statistical analytical methods were employed to examine 498 valid responses. A stratified random sampling technique was adopted for this investigation. To assess the causal relationships among the factors considered, Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were utilized. The statistical analysis revealed that all proposed hypotheses were supported, with Attitude (ATT) exerting the most substantial direct effect on behavioral intention. Every hypothesis was consequently validated, thereby fulfilling the research objectives. It is posited that these findings will offer valuable insights for the advancement of the Chinese animation industry in the era of AIGC.

Keywords— Artificial Intelligence Generated Content (AIGC), Chinese animation, animation industry, behavioral intention

Cite: Chaochu Xiang, Sili Jian, and Xinxin Liu, " Analysis of Viewing Behavioral Intention towards Chinese Animation within the Context of the AIGC Animation Industry," International Journal of Social Science and Humanity, vol. 16, no. 1, pp. 43-50, 2026.


Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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