Sadiyah, Luthfi Azmi (2026) Analisis Penerimaan Platform Live Streaming TikTok Menggunakan Model UTAUT2. Undergraduate thesis, UPN Veteran Jawa Timur.
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Abstract
The growing trend of live streaming commerce in Indonesia particularly through TikTok, has created a shopping ecosystem that integrates technology, entertainment, and social interaction. However, it also raises several challenges, such as SMEs’ economic dependency, transaction security risks, and complex consumer psychological dynamics related to promotional exposure and perceived fraud risk. This condition indicates that the acceptance of live streaming technology is influenced not only by technical aspects but also by psychological and social dimensions that have not been fully examined in a comprehensive manner. This study aims to analyze the factors influencing the acceptance and use of TikTok Live by applying the UTAUT2 model extended with Trust, Perceived Risk, Deal Proneness, and Consumer Innovativeness. This quantitative research employs SEM-PLS analysis with 403 valid respondents who are active TikTok users and have made purchases through TikTok Live. The results show that 10 out of 18 hypotheses are supported statistically, with Habit emerging as the most dominant predictor of Behavioral Intention and Usage Behavior, followed by Deal Proneness, Social Influence, Hedonic Motivation, and Consumer Innovativeness. Perceived Risk is found to have a very strong effect on Trust. Additionally, several variables do not directly influence behavior but operate indirectly through mediation via Behavioral Intention and Trust. Overall, the extended UTAUT2 model is proven to be relevant and effective in explaining the acceptance of TikTok Live streaming platforms in Indonesia, highlighting the important role of social, emotional, and habitual factors in shaping consumer behavior.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T58.6-58.62 Management Information Systems |
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| Divisions: | Faculty of Computer Science > Departemen of Information Systems | ||||||||||||
| Depositing User: | Luthfi Azmi Sa’diyah | ||||||||||||
| Date Deposited: | 26 May 2026 02:44 | ||||||||||||
| Last Modified: | 26 May 2026 08:18 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/52543 |
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