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Robo-Advisor Adoption and Influences of Innovation Attributes, Trust, and Image
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DOI：10.3390/fintech5010011.png)
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Abstract
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Robo-advisors are evolving fintech solutions that ask potential clients about their investment purpose and time horizon and then offer investment strategies to reach different goals. This study aims to build on prior research and gain insights into the influence of innovation attributes (relative advantage, complexity, compatibility, and observability), perceived trust, and image regarding robo-advisor adoption by applying and extending the Diffusion of Innovation (DOI) theory. Data were collected using a cross-sectional survey approach. A total of 187 valid responses were obtained from an online participant recruitment website based in the United States and analysed using the partial least squares approach. The findings indicate that relative advantage and attitude influence an individual's intention to adopt a robo-advisor, while all innovation attributes, perceived trust, and image of a robo-advisor influence an individual's attitude towards it. By extending the DOI framework, this research advances understanding of its applicability to robo-advisor adoption. This study contributes to the literature by clarifying the influences on robo-advisor adoption and their relationships. From a practical standpoint, the findings and measures could help wealth management companies improve their promotional campaigns and technical design.
Keywords:
diffusion of innovation
robo-advisor
fintech
artificial intelligence
partial least squares
C83
M15
O33
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