## 5 Discussion and Conclusions
It unfolds that most technologies are distributed in the southwest (extensive) and northeast (intensive) quadrants; that is, technologies with high/low concentration degree are often simultaneously characterized by high/low colocation, and supportive technologies are also substantial. The polarized distribution, somehow, differs from that in the U.S. where 60-70% technologies are extensive or distinctive with limited supportive technologies, implying the distribution is skewed to the left. Technologies in the northeast quadrant are usually intelligence intensive; e.g., digital communication, micro-structure, and nanotechnology, telecommunication, and computer technology etc. Those in the southwest quadrant classified as extensive technology are usually labor intensive such as basic materials chemistry, materials, metallurgy, and chemical engineering. Distinctive technologies in the northwest quadrants are very few, only optics, audio-visual technology, medical technology, and electrical machinery barely enter, in which enclosed knowledge flows are the main form. These three groups of technology have a high-high cluster in Suzhou, sometimes enlarge to Changzhou and Shanghai, neighboring low-high outliers in Jiaxing and Nantong. Supportive technologies falling into the southeast quadrant are often daily necessities such as food chemistry, furniture, machine tools, and handling, etc. This type has the largest high-high cluster without a high-low or low-high outlier. All four groups of technology have low-low clusters in the west, primarily in the less developed Anhui province. Highly concentrated technologies often mutually depend and have frequent flows of knowledge, whereby 'breakthroughs' are more likely to happen [45; 46]. However, intensive technologies such as micro-structure and nano-tech, basic communication process, analysis of biological materials, and IT methods for management are quite minimal in terms of quantity (Figure 6). The majority of applications belong to extensive and supportive technologies, which is relatively difficult to induce 'breakthroughs'. China's way towards innovative economy still requires efforts. Addressing RQ3, a regression analysis of these four types of technologies with cities is conducted. Findings verify the close association between economy and innovative outputs, as shown in the results that GDP (per capita), public expense, and actually utilized FDI are significantly related to the outputs of valid inventive patents, especially in extensive, distinctive, and supportive categories. However such an association does not always dominate urban-innovation relations; as in intensive category, the number of students in universities is most significantly associated with the outputs of valid inventive patents. The observation echoes the trend that the mutual reinforcement of economy and innovation is not as certain as usual and that the economy's overriding importance in innovation is declining [55; 56]. Moreover, in the relation between economy and innovation, economies of scale seem to matter more than economic efficiency per person, as GDP is more significantly related to innovative outputs than GDP per capita in the result. This is especially true for a distinctive technology on which influence of GDP per capita is negligible and for an intensive technology whose relation with GDP per capita is even negative and mainly relies on intensive talents. FDI ranks high in all four types of technologies, but distinctive technology seems to rely more on it as FDI represents the third significant factor associated with innovation. This implies that technology spillover from foreign areas still plays a role in China's innovation progress, especially for distinctive technology [61; 62]. The significance of public expense varied in different situations, depending on the marketization degree of a macro environment for public service provision and the intervention of local government. Population was once viewed as significant for technological innovation, but not the case in this research.