## 6 Longitudinal Comparison of ICT Factors between 2015 and 2020  
A comparison was performed between 2015 ICT/internet levels and the same variable set in 2020, both drawing from the China Yearbook series. A paired sample \(t\) test was conducted to compare the overall ICT change of Chinese provinces during the designated five years. As seen in Table 6, all of the dependent variables had a significant increase, except for the number of websites per 100 enterprises, indicating that most dimensions of ICT had kept developing in China from 2015 to 2020. The growth, however, may not be even across the Chinese provinces. Accordingly, a regression analysis of the change in ICT factors was carried out, and the results are summarized in Table 7.  
As expected, most of the 2015 ICT dependent variables significantly influenced the changes during the five-year period. Provinces with higher penetration rates for mobile internet, broadband subscribers, and mobile phones experienced smaller growth in the five years subsequent to 2015. This suggests a saturation of the market for these ICT uses. Similarly, the inequality of ICT infrastructure lessened, as evidenced by the negative coefficient of capacity of mobile phone exchange, domain names, and websites of enterprises. On the other hand, gaps in income from ICT services, intensity of mobile internet usage, and e-commerce continued to increase among Chinese provinces. In addition to the 2015 ICT dependent variables, the most dominant independent variable is college degree or above, which positively affects the growth in digital infrastructure, IT services, and ICT use, suggesting the sustained development in ICT is highly dependent on the education attainment of the population. The second influential indicator is the unemployment rate. The higher the unemployment rate, the slower the development in digital infrastructure, IT services, and e-commerce, which is in line with our expectation. However, the unemployment rate had a positive relationship with the mobile phone adoption rate. This might be because although fewer unemployed people would obtain company-subsidized mobile phones for daily use, personal uses, such as job searching, are still in demand. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Paired Differences**} & \multirow{2}{*}{**t**} & \multirow{2}{*}{**df**} \\ \cline{2-2} \cline{4-5}  & **Mean** & & & **Std Deviation** \\ \hline All lengths of optical cable lines (km), per capita & 0.02 & 0.01 & 12.40 & 30 \\ \hline Base stations of mobile phones (10,000), per capita & 0.04 & 0.01 & 14.44 & 30 \\ \hline Mobile internet subscribers per capita & 0.26 & 0.10 & 13.90 & 30 \\ \hline All broadband subscribers to internet (10,000 subscribers), per capita & 0.16 & 0.04 & 22.97 & 30 \\ \hline Flow accessed to mobile internet (10,000 GB) per capita & 0.01 & 0.003 & 25.30 & 30 \\ \hline Penetration rate of mobile phones (set/100 persons) & 21.41 & 11.54 & 10.32 & 30 \\ \hline Income from related software business (CNY 100,000), per capita & 0.03 & 0.09 & 2.09 & 29 1  \\ \hline Income from IT services (CNY 100,000), per capita & 0.03 & 0.07 & 2.19 & 29 1  \\ \hline Sales through e-commerce (CNY 1 million), per capita & 0.01 & 0.01 & 2.85 & 30 \\ \hline Purchases through e-commerce (CNY 1 million), per capita & 0.004 & 0.01 & 3.27 & 30 \\ \hline Enterprise with e-commerce transactions (\%) & 1.17 & 2.15 & 3.03 & 30 \\ \hline Computers used per 100 persons in enterprise & 10.55 & 4.10 & 14.33 & 30 \\ \hline Websites per 100 enterprises (unit) & \(-9.16\) & 6.42 & \(-7.95\) & 30 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Paired \(t\) test of changes in ICT and internet determinants, 2015–2020. Compared to the prior discussion, the impact of innovation and knowledge production had mixed impacts on ICT changes. Expenditure on science and technology boosted mobile internet penetration and knowledge production in books; electronic publications facilitated the growth in ICT infrastructure and e-commerce.