CONSUMER TRUST IN ARTIFICIAL INTELLIGENCE: A SYSTEMATIC LITERATURE REVIEW USING PRISMA GUIDELINES
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F25%3A63593158" target="_blank" >RIV/70883521:28120/25:63593158 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
CONSUMER TRUST IN ARTIFICIAL INTELLIGENCE: A SYSTEMATIC LITERATURE REVIEW USING PRISMA GUIDELINES
Original language description
This systematic literature review examines how consumer trust in artificial intelligence (AI) is conceptualized, measured and influenced in marketing contexts. Using PRISMA 2020 guidelines, 64 empirical studies published between 2017 and 2024 in ABS-ranked journals were analyzed. The findings highlight that trust is a key driver of AI adoption, satisfaction and engagement, especially in e-commerce, banking and social media marketing. Most studies define trust through cognitive dimensions such as competence and reliability, while emotional or relational aspects are less frequently addressed. Trust is commonly measured using self-reported Likert scales, with little use of behavioral or longitudinal data. Influencing factors include AI design attributes, user characteristics and contextual elements like brand reputation. The review identifies a lack of unified theoretical models and limited research on affective trust, generative AI and underrepresented user groups, offering clear directions for future research.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
50204 - Business and management
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Conference Proceedings DOKBAT 2025 21st International Bata Conference for Ph.D. Students and Young Researchers
ISBN
978-80-7678-372-0
ISSN
—
e-ISSN
—
Number of pages
16
Pages from-to
215-230
Publisher name
Academia Centrum UTB ve Zlíně
Place of publication
Zlín
Event location
Zlín
Event date
Sep 9, 2025
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—