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Market integration is an important tool for China's regionally coordinated economic development. At the same time, China is implementing an innovation-driven development strategy. Therefore, the way the market integration affects regional innovation is of great significance to analyze this problem. The panel data of 27 cities in the Yangtze River Delta region in China with the highest degree of economic integration from 2009 to 2018 are used to investigate the impact of market integration (MI) on regional innovation (RI). The main findings are as follows: the first-order lag term of RI is significantly positive, and RI has certain path dependence. In this regard, MI has a positive impact on RI and promotes RI. The estimated coefficient of MI is significantly positive and has a positive impact on RI and promotes RI. This provides a reference for promoting RI through MI. The contributions of the paper are threefold: (1) This paper examines the impact of MI on RI to provide policy implications for the coordinated development of innovation between regions. (2) The relative price method is adopted to measure the MI, which covers 16 kinds of commodities, covering a wider range than does the traditional method. (3) This paper uses the generalized method of moments (GMM) to test the effect of MI on RI for the first time. [ABSTRACT FROM AUTHOR]

The governments need beforehand to perceive the innovative relationship risk because they are one of the innovation subjects in those industry collaborative innovation alliances. However, it is difficult for innovation subjects to quantify the risks for industry collaborative innovation alliances due to the complexity, nonlinear, and dynamic condition. This paper firstly constructs an ordered logistic model, uses the following as independent variables: the collaborative degree, the ratio of science technology expenditure to GDP, the ratio of education expenditure to GDP, the ratio of finances to GDP, and uses the levels of risk as the dependent variable. Then, this paper uses the panel data of 30 provinces in China (Hainan is not included) from 2010 to 2018 to fit the model. Based on the fitting results, the research has gained the relationship risk prewarning model in industry collaborative innovation alliances by using the collaborative degree as an independent variable. The governments at all levels can use this relationship risk prewarning model to percept risk levels and reckon the corresponding probability which exists in industry collaborative innovation alliances. Furthermore, there are regional influences existing in the prewarning relationship risk levels in industry collaborative alliances. The east and middle areas have significant regional influence, but it does not exist among west areas and others. The governments at all levels may consider the regional differences. [ABSTRACT FROM AUTHOR]

With the growth and development of Construction 4.0, new technologies such as BIM, Big Data, and the Internet of Things are commonly used. These digital technologies play a critical role in fostering firm innovation and also have a major impact on firm performance. Based on panel data of 33 listed construction firms in China's construction industry from 2015 to 2020, this paper uses regression analysis and mediation analysis methods to empirically examine the relationship between Construction 4.0, technological innovation capabilities, and firm performance. The results demonstrate that Construction 4.0 has a significant positive promotional effect on the firm performance, while technological innovation capabilities mediate between Construction 4.0 and the firm performance. Based on these findings, it is suggested that construction firms should pay attention to the new technologies brought by Construction 4.0, increase investment in research and development, actively cultivate technological innovation capabilities, and build technological innovation networks, so as to promote digital transformation of construction firms. [ABSTRACT FROM AUTHOR]

Considering time lag and accumulation of inputs and outputs, this paper adopts the superefficiency data envelopment analysis (DEA) model to study the technological innovation efficiency of high patent-intensive industries using panel data from 2007 to 2017. Given the characteristics and the actual circumstances of the industries, the innovation process is divided into two stages, and an input-output indicator system is established. The results show that the overall innovation efficiency level of high patent-intensive industries in China is increasing. However, the R&D achievements in technology are not quickly applied or sufficiently transformed. [ABSTRACT FROM AUTHOR]