## 5 Data Processing and Results
### Determination of Comprehensive Evaluation Index for Technological Innovation  
In this section, we report the comprehensive evaluation index for the technological innovation subsystem. The complete calculated indices for all 30 regions in years 2002-2023 for dataset \(O\) is provided in Appendix B, Table A3. The complete indices for the reference dataset \(R\) are provided in Appendix B, Table A5. First, we provide an overview of the indices for all 30 regions in 2002, 2012, and 2023, for the technological innovation subsystem calculated using dataset \(O\) in Figure 7.  
To show the evolution of the indices over the years, we show two regions, Beijing, which consistently has the highest index, and Qinghai, which has the lowest index among all regions, in Figure 8. As can be seen, the general trend for both regions is that the development level (as indicated by the index) is increasing over time, with the exception of occasional slight drops (from 2002 to 2003 for Beijing) or stagnancy (from 2010 to 2011 for Beijing; from 2004 to 2005 and from 2014 to 2015 for Qinghai). For readers who are not familiar with China, it is necessary to provide some explanation regarding as to why Qinghai consistently has the lowest index and Beijing consistently has the highest index. Unlike many developed countries, regions in China may have huge differences in their development levels due to historical governmental policies, locations,  
Figure 7: Comprehensive evaluation indices for the technological innovation subsystem for all 30 regions in China in 2002, 2012, and 2023 calculated using dataset \(O\). natural and human resources. We contrast the two regions from four dimensions that could impact their development levels:  
* Economic and financial infrastructure: Beijing is the capital of China with a large concentration of financial institutions, including international financial headquarters. Qinghai, on the other hand, is located in the far western region of China and much less economically developed with very limited financial infrastructure. * Technological development: Beijing is home to many top universities in China, and as such, Beijing is leading in patent filings and technology startups. In contrast, Qinghai does not have a top university and lacks the high-tech industrial base. * Government policy and investment: Being the capital of China, Beijing receives substantial central government funding and policy support. The support for Qinghai is limited to renewable energy projects. * Human capital and talent pool: Due to the special location and the rich opportunities, Beijing attracts top-tier latent from across China. Beijing also has the best talent pool in China due to its top universities. In contrast, Qinghai faces significant challenges in attracting and retaining skilled workers due to the lack of opportunities and possibly harsh weather. Qinghai also lacks a talent pool. As can be seen in Figure 9, the development levels across different regions appear rather similar when we use the set of seven predictors proposed in [3]. What is also odd is that Henan has the highest index value in 2002, and Hubei has the highest index value in 2023. The calculated distribution of the indices clearly fail to match the reality in China. Beijing, the capital city of China, has a concentration of the best higher educational institutions in China. As such, Beijing should be expected to have the highest technological innovation index. Henan and Hubei are nowhere near the level of Beijing. This demonstrates that the choice of the set of predictors is very important to deriving the development levels of each subsystem.