Investigation of individual investors' acceptance of artificial intelligence use in financial investment decisions: The case of ChatGPT
Computers in Human Behavior Reports, cilt.23, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 23
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.chbr.2026.101223
- Dergi Adı: Computers in Human Behavior Reports
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
- Anahtar Kelimeler: ChatGPT, Financial investment decisions, Generative artificial intelligence, UTAUT
- Karadeniz Teknik Üniversitesi Adresli: Evet
Özet
This study investigates the factors influencing financial investors' acceptance of ChatGPT, a generative artificial intelligence tool, within the context of financial decision-making. Specifically, it examines the effects of performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness on individual investors’ behavioral intention to use ChatGPT. Focusing on understanding the acceptance and usage of ChatGPT among individual investors, the research uses the unified theory of acceptance and use of technology (UTAUT) as the guiding framework. Four important constructs of UTAUT (performance expectancy, effort expectancy, social influence, and facilitating conditions) and personal innovativeness, which is an important variable in the adoption of new technologies, were investigated to understand their impact on individual investors' intentions. A total of 450 individual investors who are active investors in Türkiye participated in the study. The data was evaluated using confirmatory factor analysis and structural equation modeling techniques. The maximum likelihood estimation method was used to test the model. The main findings show that facilitating conditions (0.654) impacted behavioral intention the most. Performance expectancy (0.356) and social influence (0.206) had an impact on behavioral intention. Conversely, the positive effect of effort expectancy and personal innovativeness on behavioral intention was not supported. Interestingly, effort expectancy showed a significant negative relationship with behavioral intention, while personal innovativeness was not a significant predictor, suggesting that ease of use and innovativeness may have played a different role in high-stakes financial contexts than in other ChatGPT adoption settings. The results increase our understanding of technology acceptance in the context of AI tools, and these inputs are important for formulating strategies that promote the effective incorporation of ChatGPT into financial investment decisions. It also underlines the need for wider adoption of artificial intelligence tools in financial investment decisions to improve the investment performance of individual investors. Although this study is limited to a sample, it is expected that the effects of ChatGPT-like technologies on financial investment decisions will be the source of further research due to their potential.