Author
Abstract
This study examines the relationships among emotional intelligence, artificial intelligence, and investment decisions within contemporary financial decision making. Drawing on data from 410 investors and applying structural equation modelling, the study tests whether emotional intelligence, captured through self-awareness, self-regulation, motivation, social awareness, and social skills, shapes investment decisions, and whether artificial intelligence mediates this relationship. The measurement model confirms strong loadings across all constructs, and the structural results show that each dimension of emotional intelligence, together with artificial intelligence, significantly predicts investment decisions, with artificial intelligence recording the strongest direct effect. Mediation analysis further indicates that artificial intelligence partially mediates the relationship between emotional intelligence and investment decisions, evidenced by both a significant direct effect of emotional intelligence and a significant indirect effect transmitted through artificial intelligence. These findings position artificial intelligence not as a replacement for human judgment but as a complementary mechanism that channels emotionally informed insight into more consistent investment behaviour. The study offers practical guidance for financial practitioners, technology developers, and policymakers seeking to integrate behavioural and algorithmic tools responsibly, while underscoring the continuing need for transparency and ethical oversight as artificial intelligence becomes more embedded in investment decision making.
Suggested Citation
Rachna Jain & Shikha Sharma, 2026.
"Is artificial intelligence a linking bridge between emotional intelligence and investment behaviour?,"
International Journal of Business and Management (IJBM), International Emerging Scholars Society (IESS), New Zealand, vol. 5(2), pages 671-689, August.
Handle:
RePEc:cwd:ijbmnz:v:5:y:2026:i:2:p:671-689
DOI: 10.56879/ijbm.v5i2.100
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cwd:ijbmnz:v:5:y:2026:i:2:p:671-689. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Cindy Liu (email available below). General contact details of provider: https://iessociety.org/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.