Respondent-Level Dataset for Robo-Advisor Adoption in China: Trust, Fiduciary Duty, Perceived Benefits, and Asset Allocation (N = 378)
Description
This dataset contains a respondent-level file created to support the empirical structure of the paper Trust, Fiduciary Duty, and Cultural Barriers in Robo-Advisor Adoption: Evidence from China’s PIPL-Regulated Fintech Ecosystem. It represents a study’s survey size of 378 Chinese investors and is organized at the individual-response level. The file includes respondent identifiers, age, and investment experience, together with construct-level variables reflecting the model reported in the paper: Duty of Care, Duty of Loyalty, Perceived Benefits, Trust, Ease of Use, Data Security, Adoption Expectations, and Asset Allocation Ratio. This file is intended for replication support, model checking, robustness exploration, and personal research use.
Files
Steps to reproduce
1. Administer the structured questionnaire to Chinese investors through Sojump.com using quota sampling across age and investment-experience groups. 2. Screen responses for completeness and consistency, then retain only valid cases. In the paper, 492 responses were collected and 378 valid responses were kept for analysis. 3. Code demographic variables, including Age and Investment Experience. 4. Code the survey items for the core constructs on the study scale: Duty of Care, Duty of Loyalty, Perceived Benefits, Trust, Ease of Use, Data Security, and Adoption Expectations. 5. If multiple items are used for a construct, reverse-code where needed and compute composite scores as the mean of the relevant items. 6. Record Asset Allocation Ratio from the respondent’s reported willingness to allocate assets to robo-advisors. 7. Check reliability of the multi-item constructs using Cronbach’s alpha and confirm that reliability is acceptable before model estimation. 8. Estimate the regression models for H1–H4 using the composite variables, including the interaction terms for the moderation tests. 9. Run the SEM/path model in JASP to test the integrated framework linking fiduciary duty, perceived benefits, trust, adoption expectations, and asset allocation. 10. Compare the resulting coefficients, explained variance, and fit indices with those reported in the paper to confirm consistency of the reproduced dataset and analysis.
Institutions
- Ca' Foscari University of VeniceVeneto, Venice