Research on Intelligent Narrative and Consumer Trust Construction in Short-Video E-Commerce
- DOI
- 10.2991/978-94-6239-640-1_31How to use a DOI?
- Keywords
- Short-Video E-Commerce; Intelligent Narrative; Consumer Trust; Human-AI Collaboration
- Abstract
Facing content homogenization and rising consumer ad tolerance in short-video e-commerce, Generative AI (AIGC) is shifting from a tool to a narrative paradigm reconstructor. This study explores how AIGC-driven intelligent narration affects consumer trust. Grounded in Human–AI Collaboration Theory and the Elaboration Likelihood Model, we propose a moderated mediation framework. Three features of intelligent narration—large-scale personalization, interactive plasticity, and process transparency—influence cognitive and affective trust via perceived authenticity, professional competence, and value identification. These paths are moderated by product type (search vs. experience goods) and AI disclosure status. Through theoretical deduction and multi-case analysis, we explain trust formation under human–AI collaboration. The study constructs an intelligent narration framework, reveals a dual-path trust mechanism and a “transparency paradox,” offering strategic insights for balancing innovation and trust.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yudong Chang PY - 2026 DA - 2026/04/20 TI - Research on Intelligent Narrative and Consumer Trust Construction in Short-Video E-Commerce BT - Proceedings of the 2026 5th International Conference on Big Data Economy and Digital Management (BDEDM 2026) PB - Atlantis Press SP - 328 EP - 337 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6239-640-1_31 DO - 10.2991/978-94-6239-640-1_31 ID - Chang2026 ER -