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Journal of Information and Optimization Sciences cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Examining trust, transparency and AI adoption on LinkedIn : Evidence from an extended UTAUT framework

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pp. 3425–3433Vol. 47Issue 9-BSeptember 2026DOI: 10.47974/JIOS-2439XML
Received:
01 Jun 2026
Published Online:
30 Sep 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2439
Pages:
3425–3433

Abstract

This study examines how artificial intelligence (AI) features on LinkedIn—job matching, connection recommendations, and career suggestions—shape user satisfaction and engagement. Extending the Unified Theory of Acceptance and Use of Technology (UTAUT), we surveyed 300 active users, including HR professionals, job seekers, students, and recruiters. Perceived usefulness and accuracy positively predicted satisfaction and engagement, while transparency raised trust and privacy concerns lowered it. Trust partially mediated the usefulness–satisfaction link, and transparency strengthened that link. Recruiters rated AI effectiveness higher than general users did. The findings underscore the need for ethical, transparent AI integration in professional networking.

Keywords

Subject Classifications

68T0768T0591D3068T0190B50

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