家庭金融决策在财富积累与风险管理中起着关键作用,但复杂的金融市场和信息过载问题使许多家庭难以做出最优的投资选择。智能投顾作为一种基于自动化和数据驱动的金融科技工具,为家庭金融决策提供了有效的辅助。然而,信任机制与认知负...家庭金融决策在财富积累与风险管理中起着关键作用,但复杂的金融市场和信息过载问题使许多家庭难以做出最优的投资选择。智能投顾作为一种基于自动化和数据驱动的金融科技工具,为家庭金融决策提供了有效的辅助。然而,信任机制与认知负荷的管理成为影响智能投顾应用效果的核心因素。本研究以行为金融学和心理学理论为基础,构建了智能投顾对家庭金融决策影响的综合模型,重点分析智能投顾通过降低认知负荷与增强用户信任提升资产配置效率的路径机制。通过两阶段实验和多层次回归分析,研究验证了智能投顾在高信息复杂度情境下显著减轻认知负荷的作用,并发现信任度在智能投顾对决策效率的影响中具有显著的调节效应。实证结果表明,智能投顾不仅通过简化信息处理降低了决策负担,还通过增强用户对建议的信任,提高了资产配置效率。基于研究结果,本文进一步提出了智能投顾设计与普惠金融应用的政策建议,特别针对低金融素养家庭,提出了提升透明度与信任度的具体对策。Household financial decision-making plays a critical role in wealth accumulation and risk management. However, the complexity of financial markets and information overload make it challenging for many families to make optimal investment choices. Robo-advisors, as a data-driven and automated financial technology tool, provide effective support for household financial decision-making. Nevertheless, the management of trust mechanisms and cognitive load has emerged as a crucial factor influencing the effectiveness of robo-advisors. This study, grounded in behavioral finance and psychology theories, develops a comprehensive model to explore how robo-advisors enhance asset allocation efficiency by reducing cognitive load and strengthening user trust. Through a two-stage experiment and multilevel regression analysis, the research confirms the significant role of robo-advisors in alleviating cognitive load under high information complexity scenarios and identifies trust as a key moderator in the impact of robo-advisors on decision efficiency. Empirical results indicate that robo-advisors not only reduce decision-making burdens by simplifying information processing but also enhance asset allocation efficiency by increasing user trust in their recommendations. Based on these findings, this study provides policy recommendations for the design of robo-advisors and their application in inclusive finance, with specific measures to improve trust and transparency for households with low financial literacy.展开更多
文摘家庭金融决策在财富积累与风险管理中起着关键作用,但复杂的金融市场和信息过载问题使许多家庭难以做出最优的投资选择。智能投顾作为一种基于自动化和数据驱动的金融科技工具,为家庭金融决策提供了有效的辅助。然而,信任机制与认知负荷的管理成为影响智能投顾应用效果的核心因素。本研究以行为金融学和心理学理论为基础,构建了智能投顾对家庭金融决策影响的综合模型,重点分析智能投顾通过降低认知负荷与增强用户信任提升资产配置效率的路径机制。通过两阶段实验和多层次回归分析,研究验证了智能投顾在高信息复杂度情境下显著减轻认知负荷的作用,并发现信任度在智能投顾对决策效率的影响中具有显著的调节效应。实证结果表明,智能投顾不仅通过简化信息处理降低了决策负担,还通过增强用户对建议的信任,提高了资产配置效率。基于研究结果,本文进一步提出了智能投顾设计与普惠金融应用的政策建议,特别针对低金融素养家庭,提出了提升透明度与信任度的具体对策。Household financial decision-making plays a critical role in wealth accumulation and risk management. However, the complexity of financial markets and information overload make it challenging for many families to make optimal investment choices. Robo-advisors, as a data-driven and automated financial technology tool, provide effective support for household financial decision-making. Nevertheless, the management of trust mechanisms and cognitive load has emerged as a crucial factor influencing the effectiveness of robo-advisors. This study, grounded in behavioral finance and psychology theories, develops a comprehensive model to explore how robo-advisors enhance asset allocation efficiency by reducing cognitive load and strengthening user trust. Through a two-stage experiment and multilevel regression analysis, the research confirms the significant role of robo-advisors in alleviating cognitive load under high information complexity scenarios and identifies trust as a key moderator in the impact of robo-advisors on decision efficiency. Empirical results indicate that robo-advisors not only reduce decision-making burdens by simplifying information processing but also enhance asset allocation efficiency by increasing user trust in their recommendations. Based on these findings, this study provides policy recommendations for the design of robo-advisors and their application in inclusive finance, with specific measures to improve trust and transparency for households with low financial literacy.
