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When AI Delivers Earnings: Experimental Dataset on Digital Spokespersons, AI-Authored Financial Disclosure, Trust, and Investment Allocation (2×2 Investor Experiment)

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NIAID Data Ecosystem2026-05-10 收录
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https://data.mendeley.com/datasets/yb7rmbdxjy
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This dataset contains participant-level responses from a randomized 2×2 behavioral experiment examining how AI-mediated financial communication affects investor perceptions and investment decisions. The experiment investigates how communicator type (human executive vs. digital avatar) and disclosure of content authorship (management-authored and compliance-reviewed vs. AI-authored with limited human review) jointly influence perceived accountability, trust in financial communication, and capital allocation behavior. Participants viewed a standardized approximately 75-second earnings update video for a simulated publicly listed company, Aurevia Technologies Inc. The financial content, script, and visual information presented in the video were held constant across experimental conditions. Only the communication interface (human executive or digital avatar) and the disclosure regarding the origin of the message content varied across participants. After viewing the video, participants completed a structured questionnaire measuring manipulation checks, perceptions of accountability and governance, trust and credibility toward the earnings communication, and an incentivized-style allocation decision in which respondents allocated a hypothetical $10,000 investment between Aurevia stock and a risk-free asset. The dataset includes demographic variables, investment background information, risk tolerance measures, baseline attitudes toward AI in financial decision contexts, and multiple Likert-scale measures of trust, credibility, and accountability perceptions. The primary behavioral outcome variable records the amount allocated to Aurevia stock. Additional variables include manipulation-check indicators and exclusion flags used for robustness and data-cleaning procedures. The data support reproducible statistical analyses of the main and interaction effects of AI-mediated communication and AI-authored financial disclosure on investor trust and allocation behavior.
创建时间:
2026-03-05
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