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Innovation is the first driving force to lead development, how to improve manufacturing innovation performance has become a hot topic. Based on 47 listed companies in the computer, communication and other electronic equipment manufacturing industry in the A-share market, this paper adopted the Fuzzy set qualitative comparative analysis (fsQCA) to explore the influencing factors of technology, organization and environment on the innovation performance of manufacturing industry and the improvement path. The findings are as follows: (1) A single condition is not a necessary condition for high innovation performance in manufacturing industry, but government support plays a key role in improving innovation performance in manufacturing industry. (2) There are two improvement paths for high innovation performance in manufacturing industry, which are specifically explained as "technology-environment dual improvement path" and "technology-organization-environment collaborative improvement path". (3) The improvement of innovation performance in the manufacturing industry is the result of multiple factors, showing the characteristics of "all paths lead to the same destination". Different manufacturing enterprises have different paths to improve innovation performance based on their actual conditions. Based on these findings, this study may provide some implications for the effective improvement of manufacturing innovation performance. [ABSTRACT FROM AUTHOR]

In the context of the rapid development of the global digital economy, it is of great significance to explore the greening transformation of the manufacturing industry from the micro-perspective of enterprise digital development. This paper empirically examines the impact and mechanism of enterprise digital development on the greening transformation of the manufacturing industry using the 2010–2020 data of Chinese A-share listed companies in the manufacturing industry as a sample. The study shows that enterprise digital development can significantly promote the greening transformation of China's manufacturing industry, and this conclusion still holds after a series of robustness tests. Technological innovation and financing constraints are important mediating mechanisms. Further research found that the impact of enterprise digital development on the greening transformation of China's manufacturing industry has a positive nonlinear effect, and its marginal effect shows a weakening trend. Heterogeneity analysis shows that, from the perspective of micro characteristics, digital development is more able to promote the green transformation of state-owned and large enterprises. From a macro-regional perspective, digital development can better promote the green transformation of the manufacturing industry in eastern cities, key city clusters, and high-level cities. The findings of this paper can provide corresponding insights for "revitalizing the manufacturing industry", and also provide decision-making references for countries aiming to make the manufacturing industry bigger and stronger. [ABSTRACT FROM AUTHOR]

Enterprise financialization will block the equipment update and technological innovation of enterprises by crowding out the main business funds. The risks and benefits of supply chain concentration will affect the enterprise financialization. This paper selects the panel data of A-share listed companies in China from 2009 to 2021, and uses fixed effect regression to analyze the impact of supply chain concentration on enterprise financialization. The conclusions show: both suppliers and customers concentration significantly promote the financialization of enterprises, and this conclusion is still valid after a series of tests; This kind of financialization effect is heterogeneous in four aspects: the nature of property rights, the scale of enterprises, the intensity of industrial competition and the level of economic development in the region where the enterprises are located; the mechanism analysis show that customer concentration can affect enterprise financialization through upstream commercial credit, but supplier concentration cannot affect enterprise financialization through downstream commercial credit. [ABSTRACT FROM AUTHOR]

The logistics industry and the manufacturing industry are mutually productive factors and service objects, which determines that the two must develop cooperatively. In the increasingly fierce market competition, open collaborative innovation is more conducive to improving the level of linkage between the logistics industry and the manufacturing industry, and promoting industrial development. Based on the patent data of 284 prefecture-level cities in China from 2006 to 2020, this paper uses Gis spatial analysis, spatial Dubin model and other methods to analyze the collaborative innovation between the logistics industry and manufacturing industry. The results lead to several conclusions. (i) The overall collaborative innovation level is not high, and in terms of the evolution cycle, collaborative innovation has experienced three stages: embryo, rapid development and stable development. (ii) The spatial agglomeration characteristics of the collaborative innovation between the two industries are more and more obvious, and the Yangtze River Delta urban agglomeration and the middle reaches of the Yangtze River urban agglomeration play an important role in the collaborative innovation between the two industries. (iii) The hot spots of collaborative innovation between the two industries are concentrated in the eastern and northern coastal areas, while the cold spots are concentrated in the south of the northwest and southwest areas in the late stage of the study. (iiii) The positive influencing factors of local collaborative innovation between the two industries include economic development, scientific and technological level, government behavior, and employment, while the negative influencing factors include information technology level, and logistics infrastructure. Economic development has a negative spatial spillover effect on surrounding areas, while the spatial spillover effect of scientific and technological level is significantly positive. This article aims to explore the current situation and influencing factors of collaborative innovation between the two industries, with a view to proposing countermeasures and suggestions for improving the level of collaborative innovation between the two industries, and also providing new ideas for research on cross industry collaborative innovation. [ABSTRACT FROM AUTHOR]

Technology accumulation plays a vital role in research and development (R&D) activities. This paper used technology accumulation as the threshold variable to construct a dynamic panel threshold model to explore the technology accumulation threshold effect of independent R&D on innovation performance of China's pharmaceutical manufacturing industry over the period 1995~2019. The results show that the independent R&D of China's pharmaceutical manufacturing industry had a significant promotion effect on innovation performance. However, it is constrained by the level of technology accumulation, showing a significant double threshold effect of technology accumulation. A moderate level of technology accumulation was more conducive to independent R&D to drive innovation performance, while lower or higher technology accumulation will weaken independent R&D promotion on innovation performance. This study provided insights for policymakers and managers in making effective innovation strategies. [ABSTRACT FROM AUTHOR]

Background: In November 2015, China launched a pilot program for its Drug Marketing Authorization Holder (MAH) system, aiming to integrate production and research and development resources to spur drug innovation. While many scholars have examined the theoretical relationship between the MAH system and pharmaceutical manufacturing innovation, empirical studies have been scarce. Methods: This study uses inter-provincial panel data on China's pharmaceutical manufacturing industry from 2009 to 2019, along with synthetic control methods, to offer a robust analysis of the impact of the MAH paradigm on innovation quality in pilot provinces. We treat the 2015 MAH system implementation in ten provinces as a natural experiment and account for the mediating effects of R&D investments, allowing us to discern the underlying mechanisms. Results: Our findings demonstrate a significant positive effect of China's MAH system on innovation quality in the pharmaceutical manufacturing industry. Specifically, the system is most effective in Jiangsu, Guangdong, and Shandong provinces. We also identify R&D investments as playing a mediating role in facilitating the favorable impact of the MAH system on innovation quality. Conclusion: Our study highlights the crucial importance of the MAH system in promoting innovation quality in China's pharmaceutical manufacturing industry, providing vital empirical support for its adoption and further enhancement. This research also offers practical insights for policymakers and R&D decision-makers in the pharmaceutical sector. [ABSTRACT FROM AUTHOR]

Enterprises acquire heterogeneous knowledge through external knowledge search and adapt to the change of external environment, which is of great significance to enterprise breakthrough innovation. This paper takes the innovation ecosystem as the boundary of the research paradigm. Based on innovation ecosystem theory, knowledge management theory and enterprise innovation theory, this paper constructs a moderated mediation model of the enterprise knowledge search, knowledge integration and breakthrough innovation under the characteristics of innovation ecosystem network. This model is tested on the survey data of 344 technology enterprise and manufacturing industries including R&D departments in the Beijing-Tianjin-Hebei region. The research results show that: knowledge integration plays part of the intermediary role between knowledge search and enterprise breakthrough innovation; the larger the network scale, the stronger the network connection, the stronger the intermediary role of knowledge integration on the relationship between knowledge search and enterprise breakthrough innovation. The research results reveal the important role of the innovation ecosystem in enterprise breakthrough innovation. At the same time, the research on knowledge search and enterprise breakthrough innovation should consider the network characteristics of innovation ecosystem and the ability of enterprise knowledge integration. [ABSTRACT FROM AUTHOR]

The increasing prominence of urban scaling laws highlights the importance of a systematic understanding of the variational scaling rates for different economic activities. In this article, we utilize several datasets to provide the first systematic investigation of the urban scaling of manufacturing industries in China. Most existing literature assumes that the divergence in urban scaling can be explained by returns to agglomeration, with a few exceptions instead highlighting the role of knowledge complexity or a mixture of both. Our main purpose in this paper is to explain the inter-sector variation of urban scaling rates. In doing this, we provide a clearer approach to demonstrating the relations between urban scaling, returns to agglomeration, and knowledge complexity. Our findings are twofold. First, after uncovering the scaling rates (denoted as urban concentration) and returns to agglomeration (denoted as urban productivity) for each sub-manufacturing sector, we prove that, rather than being a positive predictor, returns to agglomeration is slightly negatively associated with urban scaling rates. This finding reveals that urban concentration of manufacturing may not simply be a natural consequence driven by the maximization of performance. We also show that this result of the manufacturing system contrasts with what would be found in other pure knowledge systems such as patents. Secondly, we measure the complexity for each sector and demonstrate that the variation of urban concentration can be largely explained by their complexity, consistent with the knowledge complexity perspective. Specifically, complex manufacturing sectors are found to concentrate more in large cities than less complex sectors in China. This result provides support for the view that the growth of complex activities hinges more on diversity than on efficiency. The findings above can greatly reduce the current level of ambiguity associated with urban scaling, returns to agglomeration and complexity, and have important policy implications for urban planners, highlighting the significance of a more balanced and diversified configuration of urban productive activities for the growth of innovation economy. [ABSTRACT FROM AUTHOR]

The innovative performance of manufacturing and service companies can be impacted by the existing relationship between open innovation (OI) and the generation of confidentiality agreements (NDAs) as a tool for the protection of intellectual property. Based on the analysis of a cross-sectional sample of 6,798 industrial companies (2019–2020) and 9,304 companies in the service sector (2017–2019) that are part of the directory of the National Administrative Department of Statistics (DANE) in its Technological Innovation and Development Survey (EDIT and EDITS), it can be suggested that the interaction of these two variables (OI and NDAs) generate positive effects for the manufacturing industry but negative ones for the service sector. It could be deduced that the positive effect is due to the greater tradition of OI in the manufacturing industry and the negative effect to the caution that the service sector presents when collaborating with external actors. [ABSTRACT FROM AUTHOR]

Based on the social network theory, this study utilizes knowledge absorption capacity as the mediating variable and technology turbulence as the moderating variable; furthermore, it focuses on China's intelligent manufacturing industry data to explore the effect of the intelligent manufacturing enterprise innovation network on technology innovation performance and the regulating mechanism of technology turbulence. Based on the patent data obtained from Derwent Database (survey period: 2016–2020), the empirical analysis indicates the following: (1) Network relationship, network location, and network density are significantly and positively correlated with technology innovation performance; however, network size exerts no significant effect on technology innovation performance. (2) Network relationship strength, network location, and network density exert significantly positive effects on the two dimensions of knowledge absorption capacity, namely the In-degree and the Out-degree. Network size exerts no significant effect on knowledge absorption capacity. (3) Knowledge absorption capacity exerts a partial mediating effect on the relationship between innovation network and technology innovation performance. (4) The three dimensions of innovation network that exert a significant effect on technology innovation performance are positively correlated with the interaction terms of technology turbulence, which indicates that the interaction terms, namely innovation network and technology turbulence, exert a positive impact on technology innovation performance through knowledge absorption capacity, and that the moderating effect of technology turbulence exerts a role through knowledge absorption capacity. Finally, this study postulates implementations and policy proposals for enhancing the innovation performance of intelligent manufacturing enterprises. [ABSTRACT FROM AUTHOR]

It is important for China to break the "low-end lock" of the manufacturing value chain worldwide by revealing how digital trade promotes and reallocates the export technology complexity of the manufacturing industry. Panel data for 30 provinces in China from 2011 to 2020 were employed to measure the digital trade development and export technology complexity of the manufacturing industry. Benchmark regression, intermediary effect regression, panel threshold and other models were used to test the promotion and reallocation of digital trade on the export technology complexity of the manufacturing industry. The findings are as follows: (1) Digital trade promotes the export technology complexity of the manufacturing industry, with significant regional heterogeneity (eastern, central and western regions), and the most obvious promotion in technology-intensive manufacturing. (2) Technological innovation and human capital play a reallocation role in the process of digital trade, affecting the technological complexity of manufacturing exports, with mediating effects of 14.19% and 8.61%, respectively. (3) Digital trade promotes and reallocates the export technology complexity of the manufacturing industry through industrial structure upgrading, and a nonlinear relationship was found. These results provide empirical support and a decision-making basis for digital trade in promoting the export technology complexity of the manufacturing industry. The development of digital trade should be encouraged; the differential development of digital trade in the eastern, central, and western regions should be boosted; importance should be attached to the intermediary incentive role of technological innovation and human capital; and the upgrading of the industrial structure should be promoted scientifically. [ABSTRACT FROM AUTHOR]