## 4 Data Analysis and Discussion of Results
### Results and Discussion  
Configuration 1 (FUND*TAL*IMP*-RES) indicates that the research funds and the government importance degree jointly exert influence on this path, and that technical talent play an auxiliary role. Therefore, this path is named the technology-driven path under the government's supervision. This path can explain about 27.6% of intelligent coal mine construction cases, of which about 25.6% can only be explained by this path. Configuration 2 (FUND*IMP*DEM) indicates that in addition to the research funds and the government importance degree, the national demonstration has also become a core condition, and this path can be called the path jointly driven by three prongs. This path can explain about 19.8% of the intelligent coal mine construction cases, and about 19.8% of the cases can only be explained by this path. Configuration 3 (-FUND*-TAL*IMP*DEM*-RES) indicates that the national demonstration plays a core role, supplemented by the government importance degree, and this path can be called the policy-driven path under the resource priority. This path can explain about 17.7% of the intelligent coal mine construction cases, and about 15.6% of the cases can only be explained by this path. Based on the analysis results, three configuration paths for the intelligent and efficient construction of coal mines in China are summarized, and the three types of configuration \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{3}{*}{**Conditional Variables**} & \multirow{3}{*}{**Configuration**} & \multicolumn{2}{c}{**Technology-Driven**} & \multirow{3}{*}{**Jointly Driven by**} & \multirow{3}{*}{**Policy-Driven under**} \\  & & & **overnment’s** & & **Three Prongs** \\  & & & **Supervision** & \\ \cline{3-5}  & & & **Configuration 1** & **Configuration 2** & **Configuration 3** \\ \hline Technology & FUND & & & & \(\otimes\) \\  & TAL & \(\bullet\) & & & \(\otimes\) \\ Organization & IMP & & & & \(\bullet\) \\ Environment & DEM & & & & \\ Resources & RES & \(\otimes\) & & & \(\otimes\) \\  & Consistency & 0.9412 & 1 & 0.9286 \\  & Original coverage rate & 0.2764 & 0.1982 & 0.1773 \\  & Unique coverage rate & 0.2555 & 0.1982 & 0.1564 \\  & Overall consistency & & 0.9679 & \\  & Overall coverage rate & & 0.6309 & \\ \hline \hline \end{tabular} Note. \(\bullet\) indicates that the core conditions exist and have a great impact on the outcome variables; \(\bullet\) indicates that the auxiliary conditions exist and have little impact on the outcome variables; \(\otimes\) indicates the absence of the core conditions.  
\end{table} 
Table 4: Configuration analysis of the effect of the construction of intelligent coal mines. paths are described in detail by selecting cases with outstanding explanatory effects for each configuration (Figure 2). (1) Technology-driven path under the government's supervision  
This path type is reflected in Configuration 1, with Shandong Province as a typical representative. source endowment may be one of the factors limiting the further development and growth of smart coal mines in such regions. (2) Path jointly driven by three prongs  
The path jointly driven by three prongs is reflected in Configuration 2 and is typified by Shanxi Province. Although it is located in the central plains, where the science and technology are not outstanding, its R & D funds are quite advantageous for the inland, and one of the reasons for this is that it is based on the featured coal industry. Since 2017, the 5G Intelligent Mine Alliance was established by the Global Headquarters of Huawei Coal Mine Corps, China Mobile, and their partners, and some local enterprises (such as Jingying Link and Keda Automation Control) are deeply engaged in the field of intelligent coal mines and have continued their efforts to again make Shanxi the focus of the national coal industry, consolidating and strengthening the foundation of scientific research and innovation.