# Exploring the Innovation Diffusion of Big Data Robo-Advisor
## 4 Discussion  
From the previous research, it was found that the prediction effect of neural networks was better than other models [1, 2], so this study takes the neural network-like prediction model as the subject of discussion. While earlier studies tended to use mean absolute error (MAE) to show the correctness of predictions of neural network-like models [2], recent studies have used the accuracy ratio as the correctness of predictions, so for the sake of research consistency, we used recent research literature data as a standard. This study summarizes the big data stock market forecasts of scholars such as [PERSON] and [PERSON] (2016), [PERSON] et al. (2018), [PERSON] et al. (2020), [PERSON] and [PERSON] (2020), and [PERSON] et al. (2021), as shown in Table 1[10; 11; 12; 13; 14]. According to the summary, the accuracy of the prediction models of these scholars ranged from 52% to 97%, with the prediction results of the models varying significantly. Investors would like the higher accuracy ratio of the investment forecast model, and the prediction results should be more consistent, otherwise the reliability of the model will be reduced. Table 1 shows the accuracy ratio of the research model of various scholars. In addition to the empirical results of scholars such as [PERSON] and [PERSON] (2020) and [PERSON] et al. (2021) with higher accuracy rates (above 70%), the accuracy rates from other researchers were less than 70%, and the prediction accuracy rates of the different methods and different markets were inconsistent [13, 14]. The results indicate that the accuracy of the stock selection prediction model of recent AI neural networks has indeed improved, but the prediction results are not stable. Therefore, it is impossible to obtain a broad and consistent prediction accuracy rate, which can convince external investors and promote this innovation. The stock price prediction model is used in the actual stock selection operation of the stock market. Next, semi-structured interviews were conducted with representatives of various asset management companies (such as fund companies) by enquiring whether the mutual funds managed by their companies use neural networks as investment models whilst asking them to provide related supporting sales data. After interviews with the business representatives from 21 fund companies (with a total of 551 funds in portfolios under these managers), only one of the respondents (4.76%) said that he/she was not previously aware of the big data forecasting model. Therefore, from [PERSON]'s proposed communication channels of innovation diffusion theory, this interviewee in the first stage (\"knowledge\") did not have a further understanding of this big data prediction model. Twenty respondents (95.24%) said their fund companies did not use the big data forecasting model as a stock selection model. This means that respondents were aware of the big data forecasting model, but it was not used an investment stock selection model for the funds to which they belonged. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Author** & **Research Model** & **Accuracy** \\ \hline \multirow{3}{*}{[PERSON] and [PERSON] (2016)} & MLP & 52.10\% \\  & CNN & 53.60\% \\  & RNN & 52.20\% \\ \hline [PERSON] et al. (2018) & LSTM & 57.00\% \\ \hline \multirow{3}{*}{[PERSON] et al. (2020)} & RCNK & 66.26\% \\  & RCNK-T & 59.44\% \\  & RCNK-S & 63.25\% \\  & CNK & 65.61\% \\ \hline Ding and Qin (2020) & LSTM & 78.79\% \\  & DRNN & 97.37\% \\ \hline \multirow{3}{*}{[PERSON] et al. (2021)} & CNN & 78.00\% \\  & LSTM & 77.00\% \\ \cline{1-1}  & CNN+LSTM & 80.00\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of Neural Network Prediction Models. This also implies that in [PERSON]'s proposed communication channels model, respondents were in the first stage, \"knowledge\"--they already knew the big data forecasting model. However, for the second stage--\"persuasion\"--the respondents were not persuaded to use the big data forecasting model as the fund's investment stock selection model.