The rise of robo-advisors signifies a transformative shift in various industries, highlighting their pivotal role in fostering innovation and efficiency. Leveraging the adaptability of the Technology Adoption Model (TAM), this study integrates social influence, facilitating conditions, and user trust to analyze consumer behavior towards robo-advisors. Contrary to expectations, the study challenges conventional wisdom by revealing that the perceived ease of use significantly impacts user perceptions, prompting a reconsideration of the support for perceived usefulness. Recommendations include incorporating collaborative features and enhancing user-friendly designs, recognizing the importance of simplicity and usability. The study identifies challenges in user trust effectiveness, urging future research on trust relationships and the development of confidence-building plans. Providing critical managerial insights, the research guides effective marketing strategies, ensuring alignment with evolving user perceptions for the successful adoption of robo-advisors.
Top1. Introduction
The escalating adoption of robo-advisors across diverse sectors is indicative of a transformative paradigm shift, underscoring their pivotal role in reshaping and optimizing processes across a multitude of industries. The advent of AI-powered diagnosis and treatment algorithms marks the onset of a transformative era in patient care. The educational landscape has undergone a seismic shift with the introduction of adaptive learning platforms, while the shopping experience has been revolutionized by the proliferation of intelligent recommendation engines. Concurrently, production lines have witnessed enhanced efficiency and adaptability through the seamless integration of robotic process automation. These automated systems meticulously analyze large volumes of data to optimize outcomes and elevate customer satisfaction levels (Seyhan & Carini, 2019). The swift expansion of robo-advisors, automated investment platforms offering tailored advice and portfolio management, has further reshaped the terrain. Notably, the data underscores the escalating influence of robo-advisors on consumer behavior. A staggering 40% of millennials express interest in leveraging robo-advisors, according to a 2022 Fidelity Investments study (Fidelity Investments, 2022). Additionally, research from Charles Schwab in 2021 reveals that 33% of investors under 40 are already utilizing robo-advisors (Charles Schwab, 2021). Projections indicate that the global robo-advisor market is poised to reach $1.2 trillion by 2023 (Aite-Novarica, 2020). These compelling statistics underscore the rising prominence of robo-advisors as a formidable force in the financial services landscape. Anticipating an upward trajectory, the utilization of robo-advisors is expected to surge as more consumers become cognizant of their manifold advantages, encompassing lower fees, round-the-clock accessibility, and personalized investing plans (The Financial Times, 2023).
As numerous studies have consistently demonstrated, many favourable aspects exist to using robo-advisors and taking a role. Customers are more likely to utilize robo-advisors if they think they can assist them in reaching their objectives (Barber & O'Donohoe, 2016). Some elements impacting this view are cheaper costs from financial advisors, access to various markets, and guidance on personal investments (Huang & Lin, 2021). Additionally, studies demonstrate a favourable correlation between robo-advisor acceptance and user-friendliness (Li & Rao, 2020). Clients are more likely to accept robo-advisors if they are simple, easy to use, and accessible across multiple platforms (e.g., mobile apps and web interfaces) (Wang and Chen, 2017). Recruitment process. Provide direct guidance and build strong relationships with customers (Cooper et al., 2014). Research shows that hiring robo-advisors can have an impact on adoption decisions. According to a study by Chen and Wang (2019), customers who have a positive perception of robo-advisors and see them as trustworthy, innovative, and trustworthy will be more helpful! Research shows that risk tolerance and self-esteem influence robo-advisor adoption. Increased self-awareness will help users evaluate the pros and cons of using robo advisors and decide how to use them (Li and Rao, 2021). Research shows that health and demographic factors such as age, education and income level will have an impact on robo-advisors (Huang and Zhang, 2022). Li and Wu (2021) claim that the young, the wealthy, and the educated will accept new technologies such as robo-advisors! Both marketplace and robo-advisor policies will have an impact on adoption.