Respondent-Level Dataset for Robo-Advisor Adoption in China: Trust, Fiduciary Duty, Perceived Benefits, and Asset Allocation (N = 378)

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.

本数据集为支撑论文《智能投顾（Robo-Advisor）采用中的信任、受托责任与文化壁垒：来自中国受《个人信息保护法》（PIPL）监管的金融科技生态的证据》的实证框架而构建，属于面向受访者个体的数据集文件。该数据集对应一项覆盖378名中国投资者的调研，以单份问卷回复为单位进行组织。本数据集包含受访者标识、年龄与投资经历等基础信息，同时涵盖与论文所报告模型对应的构念层面变量，包括注意义务（Duty of Care）、忠实义务（Duty of Loyalty）、感知收益（Perceived Benefits）、信任（Trust）、感知易用性（Ease of Use）、数据安全（Data Security）、采用预期（Adoption Expectations）以及资产配置比例（Asset Allocation Ratio）。本数据集可用于实证结果复现、模型校验、稳健性检验以及个人学术研究。