Evidence map›Paper›PMID 42039019›Full record

ArticleFrontiers in psychology2026

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

Wei Chang, Jingjing Yu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Wei ChangSchool of Finance, Shanghai Lixin University of Accounting and Finance, Shanghai, China.
Jingjing YuSchool of Finance, Capital University of Economics and Business, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: With the rapid development of intelligent investment advisory platforms, the interaction between algorithmic transparency and social influence in investment decision-making remains underexplored. Based on Self-Determination Theory, this study investigates how algorithmic transparency moderates the effect of social influence on investment decisions, with perceived autonomy as a proposed mediating mechanism. Methods: Two progressive online experiments were conducted (total Results: Social influence significantly increased investment intention (F(1,236) = 24.87, Discussion: Algorithmic transparency reduces investors' reliance on social information primarily by enhancing perceived autonomy. The effect is most pronounced among nonprofessional investors with low-to-moderate financial literacy. These findings offer empirical support for transparency-oriented fintech platform design and regulatory policy formulation.

Indexed as

algorithmic transparencyinvestment decisionperceived autonomyself-determination theorysocial influence

Identifiers

PMID42039019
PMCPMC13102815

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.