Although the literature on university–industry links has begun to uncover the reasons for, and types of, collaboration between universities and businesses, it offers relatively little explanation of ways to reduce the barriers in these collaborations. This paper seeks to unpack the nature of the obstacles to collaborations between universities and industry, exploring influence of different mechanisms in lowering barriers related to the orientation of universities and to the transactions involved in working with university partners. Drawing on a large-scale survey and public records, this paper explores the effects of collaboration experience, breadth of interaction, and inter-organizational trust on lowering different types of barriers. The analysis shows that prior experience of collaborative research lowers orientation-related barriers and that greater levels of trust reduce both types of barriers studied. It also indicates that breadth of interaction diminishes the orientation-related, but increases transaction-related barriers. The paper explores the implications of these findings for policies aimed at facilitating university–industry collaboration.

Investigating the factors that diminish the barriers to university-industry collaboration

The role of digitalization on green economic growth: Does industrial structure optimization and green innovation matter?

In the context of sustainable development, countries around the world shed more light on green innovation in their environmental policies, and the digital economy may take a vital part in improving green innovation. Predicted on the panel data of 278 cities in China from 2011 to 2019, this research administrates the principal component analysis (PCA) to evaluate the advancement level of the urban digital economy and employs the number of urban green patent applications to represent green innovation level. Through the benchmark regression model, the mediating effect model, the spatial Durbin model, the dynamic threshold panel model, and the gradual difference-in-difference model, this paper explores the direct effect, indirect effect, spatial effect, nonlinear relationship, and policy effect of that digital economy has on green innovation. The development of the digital economy can improve green innovation levels in indirect ways, such as by boosting the degree of economic openness, optimizing the industrial structure, and expanding the market potential, and as economic openness, industrial structure, and market potential advance, the promotion intensity of digital economy on green innovation is becoming lower and lower. The development of green innovation has an obvious spatial spillover effect. Still, the enhancement of green innovation in more developed regions may inhibit green innovation in less developed regions due to talent flow and industrial transfer. Finally, the gradual difference-in-difference model founded on the ‘Broadband China’ pilot policy supplementarily verifies that digital economy enhancement can substantially advance urban green innovation. 

Digitalization and sustainable development: How could digital economy development improve green innovation in China?

Impact of the digital economy on high-quality urban economic development: Evidence from Chinese cities

Does industrial robot application promote green technology innovation in the manufacturing industry?

This paper measures the level of urban digital economy and high-quality green development in China, seeking to reveal the mechanisms and influences of the digital economy in a unified framework. The results demonstrate that the digital economy can directly drive high-quality green development, and industrial structure adjustment and green technology innovation are significant mediating mechanisms. Meanwhile, it has positive nonlinear effects on high-quality green development, but the marginal effects are clearly diminishing. Further study shows city-specific heterogeneity effects, and digital dividends in eastern cities, key urban agglomerations, and high-level cities are more fully released. Moreover, the digital economy can affect high-quality green development in neighboring areas through spatial spillover effects. The conclusions are robust after adopting instrumental variables and smart city construction as a quasi-natural experiment. The findings could provide decision-making references for policymakers and professionals in emerging economies to enhance green development. 

Innovation in emerging economies: Research on the digital economy driving high-quality green development

Purpose Innovation ambidexterity is crucial for fostering growth and gaining a competitive advantage in small and medium enterprises (SMEs). Previous research indicates that achieving a balance between exploration and exploitation is a multifaceted phenomenon occurring across various levels. This paper aims to examine the influence of individual, organizational and institutional factors on the ambidextrous innovation of Chinese niche leaders using a configurational perspective. Design/methodology/approach This study uses secondary data collected from 69 Chinese niche leaders in the new equipment manufacturing industry. The authors use fuzzy-set qualitative comparative analysis to investigate how owner openness, age, digitization, the formal institutional environment and the informal institutional environment jointly influence innovation ambidexterity. Findings By using fuzzy set analysis, this study categorizes combinations of interdependent factors that promote innovation ambidexterity. In particular, the authors pinpoint three configurations that foster high innovation ambidexterity and two configurations that lack such high levels of innovation ambidexterity. The analysis results suggest that innovation paradoxes in SMEs are linked to a nested system comprising leadership, organizational factors and the institutional environment. Originality/value This study elucidates the mechanism of innovation ambidexterity through a configurational perspective. This research proposes and validates a framework that enables SMEs to develop ambidextrous innovation capabilities, thereby integrating organizational ambidexterity theory and shedding light on the intricately complex nature of innovation ambidexterity. 

A configurational analysis of innovation ambidexterity: evidence from Chinese niche leaders

The dramatic change of economic environment triggers the more complicated complex cooperation among firms, governments, and research institutions. Actually, cooperation efficiency (CE) of some industry-university-research (IUR) knowledge innovation alliances has not achieved expected levels. Accordingly, this paper organizes an empirical analysis of 296 groups of China's IUR alliances and then investigates the effect of risk among stakeholders, operations process risk, and environmental risk on alliances' CE. Empirical results present that decreasing stakeholders' risk improves alliances' CE. Further, alliances' cooperative R&D mode, human capital, digestion and absorption capabilities of technology progress, degree of R&D output sharing by firms, firms' compliance for R&D funds input, and universities and research institutions' compliance for R&D activities all positively affect alliances' CE. Additionally, alliances' favorable external environmental improves such efficiency and further strengthen the effect of stakeholders' risk on this efficiency. Our findings will help participants of IUR alliance and policy-makers to enhance alliances' CE with the fall of actual risk they need to deal with, also providing a flexible way to establish an effective partner-selection mode.

The Effect of Operations Risk on Cooperation Efficiency of Industry-University-Research Knowledge Innovation Alliance in China

Evolutionary characteristics and proximity mechanism of intercity knowledge innovation networks in China

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Innovation in emerging economies: Research on the digital economy driving high-quality green development

A configurational analysis of innovation ambidexterity: evidence from Chinese niche leaders

The Effect of Operations Risk on Cooperation Efficiency of Industry-University-Research Knowledge Innovation Alliance in China

Evolutionary characteristics and proximity mechanism of intercity knowledge innovation networks in China