Digital Finance and Green Technology Innovation: Understanding the Factors Influencing Adoption and use of Robo-Advisor Based on Mixed Structure Model

Robo-advisory services are increasingly being used in the financial investment sector, while they also play an important role in popularizing the application of green digital finance. Nevertheless, research into their adoption and use has rarely been considered from the customer perspective. This study proposes a unified model that integrates the Technology Acceptance Model (TAM) and the Task-Technology Fit (TTF) model to investigate the intention to use Robo-advisor services with 732 clients with experience in using Robo-advisor services. The results show that perceived usefulness, perceived ease of use and perceived risk significantly influence customer attitudes towards using Robo-advisor services. In addition, the relative advantages and information transparency of Robo-advisor services significantly affect the perceived usefulness and perceived risk, respectively. This paper contributes to the consumer research of Robo-advisor services and provides management implications for Fin-tech and green technology innovation.