## 2 Methodology  
### IDEMATEL Method  
#### 2.1.1 Establish a Set of System Influencing Factors  
By entering the research-related keywords in the Web of Science database and the Science Direct database to search for the literature, we can understand the current research hotspots and research status in the academic community. After in-depth reading, the indicators were initially screened, and the indicators that appeared frequently in the research were summarized. A two-round questionnaire survey method was used to determine the research-related indicators. First, several experts engaged in related research were invited to \"merge\", \"delete\", and \"supplement\" in the form of a questionnaire, and the expert semantics were informatized. Then, the second round of questionnaires was designed based on the feedback results of the first round of questionnaires, and experts were invited to score using a Likert five-level scale. Finally, the reliability and validity of the questionnaire scoring results were tested to screen indicators and establish a set of influencing factors. The scoring results of the second round of questionnaires play a vital role in establishing a reasonable and credible set of influencing factors. Therefore, it is necessary to test the reliability and validity of the questionnaire data. The reliability of a questionnaire is a key factor in measuring the quality of questionnaire data. It refers to the reliability of the measurement results, that is, the reliability of the questionnaire data. All factors that may interact between the selected and the unselected are fully considered. This study uses [PERSON]'s alpha (\(\alpha\)) to verify and uses Formula (1) to calculate the reliability of all indicators. If the reliability coefficients of all indicators are greater than 0.7, the results indicate that the reliability of the questionnaire is good. The reliability range and reference standard of [PERSON]'s alpha are shown in Table 1[27]. \[\alpha=\frac{g}{g-1}\Bigg{(}1-\frac{\sum_{i=1}^{g}\sigma_{i}^{2}}{\sigma_{total }^{2}}\Bigg{)} \tag{1}\]  
\(g\) is the number of indicators in the questionnaire, \(\sigma_{total}^{2}\) is the variance of the questionnaire data, and \(\sigma_{i}^{2}\) is the method of collecting data for the \(i\)-th question. The validity analysis of questionnaire data can be tested by calculating Kendall's coefficient of concordance, asymptotic significance, and coefficient of variation (\(CV\)). [PERSON]'s coefficient of concordance can measure the consistency level and distribution dispersion of expert scoring data. It tests the coordination of experts' opinions on the importance of evaluation indicators. The [PERSON] coefficient \(p\) value is between 0 and 1. The larger the value, the higher the consistency of expert opinions. It can be calculated using Formula (2). \[P=\frac{12}{m^{2}(n^{3}-n)}\sum_{i=1}^{n}\bigg{(}L_{i}-\frac{m(n+1)}{2}\bigg{)}^ {2} \tag{2}\] \begin{table}
\begin{tabular}{c c} \hline
**Reliability Range** & **Reference Standards** \\ \hline
0.9 \(\leq\) [PERSON]’s alpha. & Very high intrinsic credibility, credible \\
0.8 \(\leq\) [PERSON]’s alpha \(<\) 0.9 & High intrinsic credibility and trustworthiness \\
0.7 \(\leq\) [PERSON]’s alpha \(<\) 0.8 & Intrinsic credibility is acceptable and reliable \\
0.6 \(\leq\) [PERSON]’s alpha \(<\) 0.7 & The scale has some problems, but it is of reference value and reliable \\ [PERSON]’s alpha \(<\) 0.6 & The scale has big problems and needs to be redesigned \\ \hline \end{tabular}
\end{table} 
Table 1: Reliability range and reference standard of [PERSON]’s alpha. \(m\) and \(n\) represent the number of experts and indicators, respectively, and \(L_{i}\) represents the sum of the orders of the \(i\)-th indicator. The asymptotic significance of the questionnaire results can reflect that the experts' judgment on the suitability of the indicators in the questionnaire has passed the consistency test.