## 5 Discussion and Conclusions  
Drawn from data sources of patents applications from 2010 to 2018 from the CNIPA, this research pioneered filtering valid patent inventions and using the IPC code to explore one of China's most technological robust regions, the YRD, which enriches the discussion on technological composition and innovation factors at the city-region scale in the Chinese context. By visualizing the classification in a four-quadrants diagram based on the quantified concentration and colocation indicators, the study deepens our recognition on intra-city regional innovation patterns across technology fields and reflect on the quality dilemma. It is thus able to identify the technological component and relational urban factors of innovation in the YRD region across prefectural-level cities in line with the extensive, supportive, distinctive, and intensive technology groups, to generate new insights into technological innovation development. The YRD is usually viewed as a technopole for the national innovation system. This study has unfolded the heterogeneity of the tech space within this city region from two aspects: the spatial heterogeneity of different technological fields and the technological heterogeneity of different cities, to echo RQ1. Spatial heterogeneity of different technologies not only refers to an uneven distribution of a particular technology across different cities but also implies the divergent spatial concentration degree (measured by Gini coefficients) among the 35 technologies (see Table 2). In other words, the level of such unevenness varied across technologies and the variations, if compared by Gini coefficients, are substantial, ranging from 0.44 to 0.87. Inventions requiring the most cutting-edge technology such as micro-structure and nano-technology, digital communication, semiconductors, computer technology, etc., have the greatest values of Gini. Inventions in traditional manufacturing with much less demand for frontier knowledge have much lower values of Gini. This generally accords with the patterns found in metropolitan areas of the U.S. [16; 17], though the concentration degree is slightly lower than the latter. There were minor exceptions; for instance, food chemistry is extremely concentrated in the U.S. but very disperse in this study. From a broader perspective, however, unlike the U.S. where technological innovation is spread across the country and concentrated in dispersed urban clusters, China's innovation is spatially concentrated in the east coast, particularly the most populated city-regions [27]. Thus, concentration and colocation are highly overlapping and the vast majority of technological innovation borders one another, forming high mixed and heterogenous tech clusters. Further research on a country level comparison may help a more in-depth explanation. Technological heterogeneity of different cities points to the patterns of how different technologies colocate with one another. The top three principal components explain 92.62% of the variance in the data, which indicates a contrasting colocation pattern. The largest component is related to computer and communication with a hybrid combination of biochemistry, measurement, and semiconductor, etc. The second largest component is related to mechanical engineering, combined with gadget and chemistry. While these two components unravel a high degree of colocation of its combined technologies, the third significant component, with a much lower rate of variance explained, is almost solely related to food chemistry. The result suggests a different as well as similar colocation pattern of technology group compared with that found in metropolitan areas of the U.S. [16; 17]: technological components with a substantial mix of technologies from different fields identified in this research is more diverse than that in the U.S. but technology bundles in small areas is relatively unanimous. To probe RQ2, this research charts the relative position of the 35 technologies.