Yuniawan, A, Hersugondo, H, Mas'ud, F, Latan, H and Renwick, DWS ORCID: https://orcid.org/0000-0001-6819-5746,
2025.
Determinants of artificial intelligence adoption in the financial services industry: understanding employees’ perspectives.
International Journal of Information Management Data Insights, 5 (2): 100371.
ISSN 2667-0968
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Abstract
This study examines the factors influencing AI adoption in Indonesia’s financial services sector, focusing on knowledge and awareness levels, perceived risks and benefits, self-confidence, and the moderating role of managerial support. Grounded in innovation diffusion theory (IDT), protection motivation theory (PMT), and self-determination theory (SDT), the study analyzes data from 489 employees using structural equation modeling with SmartPLS 4 software to test the hypotheses. The findings reveal that higher levels of knowledge and awareness, along with self-confidence, positively influence AI adoption intentions, while perceived risks and benefits exert a negative effect. Furthermore, managerial support moderates these relationships by enhancing the positive effects of knowledge and awareness levels and self-confidence, while mitigating the negative impact of perceived risks. These results emphasize the critical role of managerial support in promoting AI adoption and highlight the necessity of cultivating a supportive organizational culture and leadership to ensure successful AI integration.
Item Type: | Journal article |
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Publication Title: | International Journal of Information Management Data Insights |
Creators: | Yuniawan, A., Hersugondo, H., Mas'ud, F., Latan, H. and Renwick, D.W.S. |
Publisher: | Elsevier |
Date: | December 2025 |
Volume: | 5 |
Number: | 2 |
ISSN: | 2667-0968 |
Identifiers: | Number Type 2488703 Other |
Rights: | © 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Divisions: | Schools > Nottingham Business School |
Record created by: | Laura Borcherds |
Date Added: | 04 Sep 2025 08:10 |
Last Modified: | 04 Sep 2025 08:10 |
URI: | https://irep.ntu.ac.uk/id/eprint/54296 |
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