Data · dataset · 2026
Consumer Trust and AI Technological Characteristics in E-Commerce Platform Usage Intention: An Extension of TAM and TRA
Listed in ScienceDB
Integrating the Technology Acceptance Model (TAM) and the Theory of Reasoned Action (TRA), this study investigates the micro-mechanisms through which consumers translate subjective norm (SN) and technological cognition into usage intention (UI) within AI-driven e-commerce contexts.
Description
Based on a quota sample of 896 e-commerce platform users in Taiwan, the conceptual framework was tested using covariance-based structural equation modeling (CB-SEM) and conditional process analysis.
The empirical results indicate that perceived usefulness (PU) and perceived ease of use (PEOU) significantly and positively affect UI. Notably, consumer trust (CT) constitutes the most potent direct driver and core mediating pathway, successfully internalizing external SN and instrumental beliefs. Conversely, AI transparency (AIT), AI personalization (AIP), and AI interactivity (AII) function not as direct antecedents, but as critical contextual cues that significantly moderate the transmission efficiency from technological cognition to UI.
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These findings clarify the "cognitive–psychological–behavioral" boundary conditions in smart retailing, providing theoretical foundations for trustworthy AI governance and precision retail design.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.22918 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Computed tomography 50% · Human-centred computing 72%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.22918 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4608 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:ct | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (50%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |