Data · dataset · 2026
Ethical Responsibility and AI-Driven Transparency in TikTok Live Commerce: A Systematic Literature Review
Listed in Teesside University Research Data Repository
TikTok Live Commerce has transformed digital marketing practices by integrating live broadcasting, social commerce, and artificial intelligence (AI)-based recommendation systems.
Description
The use of AI in content distribution and product promotion raises various ethical challenges related to algorithm transparency, platform accountability, consumer protection, and risk disclosure of circulating product information. This study aims to analyze the relationship between ethical responsibility, AI-based transparency, platform governance, and consumer behavior in the TikTok Live Commerce ecosystem.
The method used is a Systematic Literature Review (SLR) by adapting the PRISMA 2020 guidelines. Data were obtained from scientific articles indexed in Scopus, Web of Science, ScienceDirect, SpringerLink, Emerald Insight, Taylor & Francis, and Google Scholar published in the period 2020–2026. The results of the study identified five main themes, namely algorithm transparency and accountability, influencer and affiliate ethical responsibility, product information and consumer vulnerability, consumer trust and protection, and platform governance and AI ethical regulation.
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The research findings indicate that algorithm transparency, ethical marketing communications, and accountable platform governance play a crucial role in building consumer trust and increasing willingness to participate in live commerce activities. This research contributes to the growing literature on AI ethics, platform governance, and consumer trust in TikTok live commerce. These findings can also serve as a reference for MSMEs, digital platforms, regulators, and researchers in developing more transparent, accountable, ethical, and consumer-protection-oriented social commerce practices.
Links
Where it is published
- DOI doi.org/10.17632/s63wbk2jwb.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Artificial intelligence · Computer Science & AI · Earth & Environmental Science
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/s63wbk2jwb.1 | 15 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |