@article{ART003367439},
author={Kim Se Hyeon and Kim Seung In},
title={Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction},
journal={Industry Promotion Research},
issn={2466-1139},
year={2026},
volume={11},
number={3},
pages={51-61},
doi={10.21186/IPR.2026.11.3.051}
TY - JOUR
AU - Kim Se Hyeon
AU - Kim Seung In
TI - Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction
JO - Industry Promotion Research
PY - 2026
VL - 11
IS - 3
PB - Industrial Promotion Institute
SP - 51
EP - 61
SN - 2466-1139
AB - This study examined how AI recommendation explanation types (no explanation, quantitative, qualitative, and contextual) affect recommendation acceptance intention through a serial mediation path (perceived transparency → algorithm trust → information satisfaction → acceptance intention), as well as the moderating effect of algorithmic literacy, using a four-group between-subjects randomized controlled experiment with 459 OTT users. The explanation groups reported significantly higher perceived transparency and information satisfaction than the control group. With no significant direct effects and only the indirect paths originating from transparency reaching significance, full mediation with transparency as the entry point was confirmed, whereas algorithmic literacy exhibited no moderating effect. This study contributes by extending the Expectation-Confirmation Model (ECM-IT) to the context of OTT recommendation explanations, identifying perceived transparency as the entry point of the serial mediation, and proposing transparency-centered UX design principles.
KW - UX;OTT;AI Recommendation Explanation;Personalization Algorithm;Algorithm Literacy
DO - 10.21186/IPR.2026.11.3.051
ER -
Kim Se Hyeon and Kim Seung In. (2026). Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction. Industry Promotion Research, 11(3), 51-61.
Kim Se Hyeon and Kim Seung In. 2026, "Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction", Industry Promotion Research, vol.11, no.3 pp.51-61. Available from: doi:10.21186/IPR.2026.11.3.051
Kim Se Hyeon, Kim Seung In "Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction" Industry Promotion Research 11.3 pp.51-61 (2026) : 51.
Kim Se Hyeon, Kim Seung In. Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction. 2026; 11(3), 51-61. Available from: doi:10.21186/IPR.2026.11.3.051
Kim Se Hyeon and Kim Seung In. "Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction" Industry Promotion Research 11, no.3 (2026) : 51-61.doi: 10.21186/IPR.2026.11.3.051
Kim Se Hyeon; Kim Seung In. Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction. Industry Promotion Research, 11(3), 51-61. doi: 10.21186/IPR.2026.11.3.051
Kim Se Hyeon; Kim Seung In. Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction. Industry Promotion Research. 2026; 11(3) 51-61. doi: 10.21186/IPR.2026.11.3.051
Kim Se Hyeon, Kim Seung In. Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction. 2026; 11(3), 51-61. Available from: doi:10.21186/IPR.2026.11.3.051
Kim Se Hyeon and Kim Seung In. "Analysis of OTT User’s Recommendation Acceptance Process by AI Recommendation Types: The Serial Mediating Effects of Perceived Transparency, Algorithm Trust, and Information Satisfaction" Industry Promotion Research 11, no.3 (2026) : 51-61.doi: 10.21186/IPR.2026.11.3.051
