# Exploring the Innovation Diffusion of Big Data Robo-Advisor
## 2 Literature Review
### Innovation Diffusion Theory  
Innovation diffusion theory is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. First put forward by [PERSON] in 2003, it theorizes and describes the dispersion process of innovation. Taking place within certain social systems, the innovative element uses a certain communication channel, and it takes a period of time. Starting with an incubation and maturing process, the diffusion would involve constituents' support by their involvement in development, sharing and consensus building. There are four elements of innovation diffusion, including the innovation itself, communication channels, time, and social systems. The communication process is shown in Figure 1 with five stages, including knowledge, persuasion, decision, implementation, and confirmation [7]. The characteristics of innovations, as perceived by individuals, help to explain their different rates of adoption. Relative advantage is the degree to which an innovation as better than the idea it supersedes; the greater the perceived relative advantage of an innovation, the more rapid its rate of adoption is going to be. Compatibility is the degree to which an innovation is perceived as being consistent with the existing values, past experiences, and needs of potential adopters. An idea that is not compatible with the prevalent values and norms of a social system will not be adopted as rapidly as an innovation that is compatible. Complexity is the degree to which an innovation is perceived as difficult to understand and use. In general, new ideas that are simpler to understand will be adopted more rapidly than innovations that require the adopter to develop new skills and understandings. Trialability is the degree to which an innovation may be experimented with on a limited basis. New ideas that can be tried on the installment plan will generally be adopted more quickly than innovations that are not divisible. Observability is the degree to which the results of innovation are visible to others. The easier it is for individuals to see the results of an innovation, the more quickly they are to adopt [7].  
Proceeding into the next stage is usually sequential, and time is needed in each stage for the new innovation to be accepted. If one of these steps cannot be satisfied, the process would discontinue, and the innovation cannot be diffused. An individual may also reject an innovation at any time during or after the adoption process. [PERSON] and [PERSON] (1989) emphasized that the subsequent stages are needed for market users' acceptance; otherwise, according to [PERSON] (1999), innovative non-proliferation would occur, as shown in Figure 2[15; 16].  
Big data robo-advisors are an innovative investment strategy that have recently emerged in the investment field, mainly utilizing big data AI forecasting models such as time series, decision trees, or neural networks to predict market ups and downs. This research will use the innovative diffusion theory, combined with the research results of previous scholars, and semi-structured expert interviews, to explore the diffusion of the new investment prediction model of big data robo-advisors.