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The allocation of innovation-related elements is influenced by intangible elements such as technological information, which affects knowledge capital, human capital, and material element investment, resulting in the stochastic change of technological innovation efficiency. The endogenous change in technological information in element investment reduces friction, lowers costs, improves efficiency, and gradually reduces the deviation between knowledge capital investment and technological innovation efficiency. In terms of small knowledge capital investment characterized by the low demand for technological information and a single source, it is easier to make more-accurate predictions, so the stochastic change in technological innovation efficiency tends to be gentle. The endogenous change in technological information continuously increases the proportion of replacing other elements with knowledge capital investment, and the efficiency of technological innovation improves steadily. Under the condition of unchanged investment in other elements, there is a great difference in the duration of technological information between the simultaneous selection and the successive selection of knowledge capital investment. When one-time instantaneous information and continuous complete information are respectively acquired, the stochastic variation of technological innovation efficiency is obvious. On the basis of the technological innovation data of 287 listed companies in eight industries, this paper compares and analyzes the measurement results of GMM and OLS to verify the above findings.

Reasonable spatial system distribution is the prerequisite for the optimization of resource and spatial allocation and the coordinated development of the regional economy. Therefore, correctly identifying the impact of different types of spatial structures on scientific and technological innovation is an important way to promote the rational layout of regional spatial structures and enhance the strength of regional scientific and technological innovation. Based on the theory of regional spatial structure and panel data of 26 provinces and autonomous regions in China from 2005 to 2019, this paper tested the impact of regional spatial structure on innovation efficiency and gap by constructing the regional spatial structure index, the innovation efficiency index, and the innovation gap index. The research results show that: First, the agglomeration effect produced by a single-center spatial structure is conducive to improving the efficiency of scientific and technological innovation, whereas the spillover effect generated by a multi-center spatial structure is more favorable for narrowing the gap in scientific and technological innovation. Second, the single-center spatial structure is more suitable for provinces and cities in the western region with relatively low levels of economic development, whereas the multi-center spatial structure is more beneficial to the achievement of innovative and high-quality development in the eastern region. Third, the moderating effect analysis shows that with an increase in cultural diversity and inter-city distance, the partial effects of the single-center spatial structure on innovation efficiency present an “N” shape and an “inverted-U” shape, respectively, whereas the partial effects of the multi-center spatial structure on the innovation gap exhibit “inverted-U” shapes. This research not only provides theoretical support for the impact of regional spatial structure on innovation efficiency and gap but also offers empirical evidence for future regional development path choices.

Discussing the technological innovation efficiency of big data enterprises and carrying out in-depth research on big data enterprises will help to accurately evaluate the development status of big data industry and guide the development of big data industry. This paper uses DEA-BCC model to evaluate the technological innovation efficiency of 21 big data enterprises. It is found that the technological innovation efficiency of big data enterprises is better. The average values of technological efficiency, pure technological efficiency and scale efficiency are 0.587, 0.772 and 0.750, respectively. The technological efficiency of big data enterprises is lower, and the individual differences are larger. At the same time, the research shows that there are 15 big data enterprises need to further expand the scale, and then improve production efficiency.

In China, with the deepening of the reform of industrial structures, the improvement of technological innovation has become a key issue. This is not only related to whether the strategic development of Chinese science and technology can be achieved, but also whether the Chinese economy and high-quality human capital can develop sustainably. Based on the theoretical boundary of sustainable development&mdash, free transfer of information&mdash, we see that sticky wages are the embodiment of information dissemination. Under the dual effects of profit-seeking behavior and information barriers, the relationship between the sticky wages of technological innovation talents (TIT), as the most profitable labor force, and technological innovation efficiency (TIE) has become more complex, and so far we still have a limited understanding of it. We explore this issue in an empirical study by using a two-stage chain Data Envelopment Analysis (DEA) of TIE followed by modifying the wages of TIT, finally, we build a collaborative evolution model with spatial effects on a large dataset (from 2007 to 2016). The results show that the overall Chinese TIE is relatively low, and in the central and western regions the TIE has been seriously reversed, there are also divergences in the TIE at different stages in the regions we focus on. As the output of technological innovation, except for initial results (such as patents), the more important value is whether it has an ability to transform the initial results into production, and the core of it is whether it can match the market environment and technology transfer system (for example, market mechanism, transformation incentive mechanism, and institutional mechanism). So, considering these aspects, the central and west of China are obviously insufficient, while the east has obvious advantages, this can also explain the results of spatial diffusion, namely, in the eastern region it is higher than in other areas, but the gap between them is gradually narrowing, lastly, from the perspective of synergy, the wage stickiness of TIT in the central region is larger than that of the eastern and western regions, and the evolutionary relationship in the former is &ldquo, extruding&rdquo, while in the latter it is &ldquo, cooperative.&rdquo, Mainly due to the popularity of the eastern innovation network and the initial state of the west, the barriers of information transmission are relatively low, while the central part is undergoing economic transformation, so its extreme demand for TIT has pushed up the cost of information transmission.