Article: Trust as a mechanism linking AI recommendation accuracy and investment performance among young investors in Indonesia Journal: International Journal of Electronic Finance (IJEF) 2026 Vol.15 No.5 pp.1 - 24 Abstract: The rapid adoption of AI-based investment recommendation systems has reshaped financial decision-making among Generation Z investors in emerging digital markets. The behavioural mechanism linking AI effectiveness to investment performance remains unclear. This study examines the effects of AI recommendation accuracy, investment goal orientation, technology readiness, and perceived risk on investment performance, with trust in AI recommendation as a mediating variable. Using a quantitative explanatory design and PLS-SEM analysis on 301 Generation Z investors, the findings show that AI recommendation accuracy is the strongest determinant of trust. Trust significantly enhances investment performance and mediates the relationship between perceived accuracy and performance. Investment goal orientation and technology readiness directly improve performance but are not fully mediated by trust, while perceived risk affects trust but not performance. These results extend the technology acceptance model by highlighting trust as a key behavioural mechanism linking AI system effectiveness to financial outcomes in emerging markets. Inderscience Publishers - linking academia, business and industry through research

Title: Trust as a mechanism linking AI recommendation accuracy and investment performance among young investors in Indonesia

Authors: Abdul Syukur; Fery Riyanto; Amron Amron; Febrianur Ibnu Fitroh Sukono Putra; Arry Maulana Syarif; Ahmad Rudi Yulianto

Addresses: Faculty of Economics and Business, Universitas Dian Nuswantoro, St. Imam Bonjol No. 207, Semarang City, 50131, Indonesia ' Faculty of Economics and Business, Universitas Dian Nuswantoro, St. Imam Bonjol No. 207, Semarang City, 50131, Indonesia ' Faculty of Economics and Business, Universitas Dian Nuswantoro, St. Imam Bonjol No. 207, Semarang City, 50131, Indonesia ' Faculty of Economics and Business, Universitas Dian Nuswantoro, St. Imam Bonjol No. 207, Semarang City, 50131, Indonesia ' Faculty of Computer Science, Universitas Dian Nuswantoro, St. Imam Bonjol No. 207, Semarang City, 50131, Indonesia ' Accounting Research Institute, Universiti Teknologi MARA, Level 12, Menara Sultan Abdul Aziz Shah, Shah Alam, Selangor, 40450, Malaysia

Abstract: The rapid adoption of AI-based investment recommendation systems has reshaped financial decision-making among Generation Z investors in emerging digital markets. The behavioural mechanism linking AI effectiveness to investment performance remains unclear. This study examines the effects of AI recommendation accuracy, investment goal orientation, technology readiness, and perceived risk on investment performance, with trust in AI recommendation as a mediating variable. Using a quantitative explanatory design and PLS-SEM analysis on 301 Generation Z investors, the findings show that AI recommendation accuracy is the strongest determinant of trust. Trust significantly enhances investment performance and mediates the relationship between perceived accuracy and performance. Investment goal orientation and technology readiness directly improve performance but are not fully mediated by trust, while perceived risk affects trust but not performance. These results extend the technology acceptance model by highlighting trust as a key behavioural mechanism linking AI system effectiveness to financial outcomes in emerging markets.

Keywords: trust in AI; investment performance; AI recommendation systems; Generation Z; Fintech adoption; Indonesia.

DOI: 10.1504/IJEF.2026.156551

International Journal of Electronic Finance, 2026 Vol.15 No.5, pp.1 - 24

Received: 24 Feb 2026
Accepted: 21 Aug 2026
Published online: 28 Sep 2026 *

Title: Trust as a mechanism linking AI recommendation accuracy and investment performance among young investors in Indonesia

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