## 3 Research Methods and Data Construction
### Variable Measuring  
The condition variables and outcome variables are measured (Table 1). Condition variables: 1 Research funds (FUND). The R & D fund of industrial enterprises above the designated size in the mining industry in each province in 2020 is used as the measurement index for research funds, and data from the yearbooks are collected directly to provide initial values for subsequent data calibration; 2 Technical talent (TAL). The IT industry employees of each province in 2020 is adopted as the measurement index for technical talent, and data from the yearbooks are collected directly to provide initial values for subsequent data calibration; 3 Government importance degree (IMP). The number of occurrences of \"intelligent construction/promotion of coal mines\" in the work reports, documents, and policies of provincial governments from 2019 to 2021 is adopted. The value is 0 for no occurrence, 0.33 for one year, 0.67 for two years, and 1 for all three years; 4 National demonstration (DEM). \"The list of the first batch of intelligent demonstration coal mines in China\" is adopted as the standard to screen the coal mines in various provinces and regions, and the results of the statistics list are used directly as initial values for subsequent data calibration; 5 Basic resource support (RES). The raw coal output from 2019 to 2021 is adopted. If the raw coal output increases for three consecutive years, the value is 1, and otherwise it is 0. Outcome variable: effect of coal mine intelligent construction (ECM). According to the development goals of intelligent mines, the comprehensive realization of intelligent working faces will be taken as the main achievement goal by 2025, and intelligent mining is one of the core systems of intelligent coal mines [20]. Therefore, the completion of intelligent working faces in coal mines is selected as the measurement index of its construction effect to investigate the complex causal relationship behind the intelligent and efficient construction of coal mines at this stage. The specific indicator data are from the work reports of the provincial people's governments, the Bureau of Energy, and other official websites, as well as official information on the Internet. Hence, the value of the provinces and regions where \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Variable Type** & **Measurement Index** & **Data Source** \\ \hline \multirow{8}{*}{Technology} & \multirow{4}{*}{\begin{tabular}{c} Research funds \\ (FUND) \\ \end{tabular} } & The R \& D fund of industrial enterprises above the designated size in the mining industry & China City Statistical Yearbook \\ \cline{2-4}  & & \begin{tabular}{c} Technical talent \\ (TAL) \\ \end{tabular} & The number of IT industry employees & China City Statistical Yearbook \\ \cline{2-4}  & & \begin{tabular}{c} Government \\ importance degree \\ (IMP) \\ \end{tabular} & \begin{tabular}{c} The government work \\ reports and “intelligent coal mine” \\ construction \\ \end{tabular} & Official government website \\ \cline{2-4}  & & \begin{tabular}{c} National \\ demonstration \\ (DEM) \\ \end{tabular} & \begin{tabular}{c} The number of local \\ mines enrolled in “The \\ list of the first batch of intelligent \\ demonstration coal \\ mines in China\" \\ \end{tabular} & Official government website \\ \cline{2-4}  & & \begin{tabular}{c} Basic resource support \\ (RES) \\ \end{tabular} & \begin{tabular}{c} Continuous increase in \\ raw coal production in \\ 2019–2021 \\ \end{tabular} & \
\begin{tabular}{c} China City Statistical \\ Yearbook, China \\ Energy Statistical \\ Yearbook \\ \end{tabular} \\ \hline \multirow{2}{*}{Outcome variable} & \multirow{2}{*}{
\begin{tabular}{c} Effect of coal mine intelligent construction \\ (ECM) \\ \end{tabular} } & The completion of intelligent working faces in coal mines & Official government website, official information on the Internet \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Variable settings and data sources.