Does transparency matter? The moderating effect of algorithm transparency on social influence in investment decisions

Area of Science:

• Behavioral Economics
• Fintech
• Investment Decision-Making

Background:

• Intelligent investment platforms are growing.
• The interplay of algorithmic transparency and social influence on investment choices is understudied.
• Self-Determination Theory provides a framework for understanding autonomy in decision-making.

Purpose of the Study:

• To investigate how algorithmic transparency moderates social influence on investment decisions.
• To examine the mediating role of perceived autonomy in this relationship.
• To explore the implications for fintech platform design and regulation.

Main Methods:

• Two online experiments with 400 participants.
• Study 1: 2x2 between-subjects design (Social Information x Algorithm Transparency).
• Study 2: Measured perceived autonomy as a mediator; analyzed using ANOVA and Hayes' PROCESS macro.

Main Results:

• Social influence significantly increased investment intention.
• Algorithmic transparency negatively moderated social influence, reducing its impact by ~34.7% under high transparency.
• Perceived autonomy partially mediated this moderating effect (34.8% mediation).

Conclusions:

• Algorithmic transparency enhances perceived autonomy, lessening reliance on social information in investment decisions.
• The effect is strongest for nonprofessional investors with limited financial literacy.
• Findings support transparency in fintech design and policy.