AEMPS

How Robo-Advisors Influence Green Bond Investment Behavior?

Author

Ruixian Liang * 1

1 Hwa Chong International School

Corresponding Author

Ruixian Liang

Keywords

robo-advisors, green bonds, investment behavior, transparency, reliability

Abstract

Green financing has become an essential way of ensuring sustainability globally, and the use of green bonds as the dominant financing instrument is essential in the implementation of sustainability in transportation, the environment, and the reduction of emissions. At the same time, the digital revolution in the financing sector has placed the use of artificial intelligence-driven robo-advisors at the forefront of financial decision-making among retail investors. This study investigates the relationship between robo-advisor attributes and individual investor behavior regarding the allocation of green bond investments, with the variables of transparency, reliability, trust, and frequency of use. With the research study adopting the quantitative research methodology and data from 401 participants, the study concludes with 70 participants, ensuring researchers assess the attributes as predictors of the proportion and amount of the entire green bond invested. The study concludes the findings as the variables of transparency and reliability being significant predictors of the allocation, while trust and frequency show no direct relationship.As a matter of influence on portfolio structure but less on the investment amount itself, that was respectively contributed to by investment experience and personal financial capabilities. Overall, the paper concludes that transparency and comprehensible recommendation logic, in combination with system reliability, is a crucial factor behind sustainable system adoption, while strategies on personalization were found to be most successful in the presence of clear information disclosure.

Citation

Ruixian Liang. How Robo-Advisors Influence Green Bond Investment Behavior?. AEMPS (2026) Vol. 266: 51-57. DOI: 10.54254/2754-1169/2026.LD32790.

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