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Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

The purpose of this paper is to analyse the development and evolution of industrial innovation ecosystems of Around-Tongji Knowledge Economy Circle from the three levels mentioned above, focusing on knowledge-producing populations, core populations and service-supporting populations, and to further develop this research framework by combining with the latest developments.

Based on the five-helix theory and economic census statistical data, this paper adopts geographic information system technology and examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji knowledge economy circle.

The knowledge product populations lead the development of industries in Around-Tongji Knowledge Economy Circle. It contributes political capital output for the government. It innovates community cooperation and governance mode, and it improves the natural ecological environment. In the face of the changes and challenges in the development environment, the future development must be recognised from the height of the iterative development of the interaction mode between university knowledge production and economic and social development.

Based on the five-helix theory and economic census statistical data, this paper examines the characteristics of the industrial innovation ecosystem and the synergistic evolution process in Around-Tongji Knowledge Economy Circle. It further expands the research framework used to develop a synergistic evolution model, which reveals the interactive and synergistic relationship among the populations and the evolution characteristics of the entire industrial innovation ecosystem. This paper also provides useful perspectives for the study of the industrial innovation ecosystem.

The relationship between industrial policy and exploratory innovation is imperfect.

The authors use Chinese high-tech enterprise identification policy (HTEP) as a natural experimental group to test policy impacts, spillover effects and mechanisms of action.

First, HTEP promotes exploratory innovation. In addition, HTEP has a greater impact on non-exploratory innovation. Second, HTEP has spillover effects in two phases: HTEP (2008) and the 2016 policy reform. HTEP affects exploratory innovation in nearby non-high-tech firms, and the policy effect decreases monotonically with increasing distance from the treatment group. Third, HTEP affects innovation capacity through financing constraints, technical personnel flow and knowledge flow, which explains not only policy effects but also spillover effects. Fourth, the analysis of policy heterogeneity shows that the 2016 policy reforms reinforce the positive effect of HTEP (2008). By deducting the effects of other policies, the HTEP effect is found to be less volatile. In terms of the continuity of policy identification, continuous uninterrupted identification has a crucial impact on the improvement of firms’ innovation capacity compared to repeated certification and certification expiration. Finally, HTEP has a crowding-out effect in state-owned enterprises and large firms’ innovation.

This paper contributes to the existing literature in several ways. First, the authors enrich the literature on industrial policy through exploratory innovation research. While previous studies have focused on R&D investment and patents (Dai and Wang, 2019), exploratory innovation helps firms break away from the inherent knowledge mindset and achieve sustainable innovation. Second, few studies have explored the characteristics of industrial policies. In this paper, the authors subdivide the sample into repeated certification, continuous certification and certification expiration according to high-tech enterprise identification. In addition, the authors compare the differences in policy implementation effects between the 2016 policy reform and the 2008 policy to provide new directions for business managers and policy makers. Third, innovation factors guided by industrial policies may cluster in specific regions, which in turn manifest externalities. This is when the policy spillover effect is worth considering. This paper fills a gap in the industrial policy literature by examining the spillover effects. Finally, this paper also explores the mechanisms of policy effects from three perspectives: financing constraints, technician mobility and knowledge mobility, which can affect not only the innovation of beneficiary firms directly but also indirectly the innovation of neighboring non-beneficiary firms.

Using the industrial data between 2000 and 2016, this study analysed the process of coupling and coordinated development of technological innovation and standardisation. Accordingly, the study considered the high-tech industry (five sub-sectors) in China as the research object.

Based on the summary of innovation and standardisation literature review, this study constructed a theoretical model of the influence of technological innovation and standardisation on industrial development from the perspective of the coupling system. Furthermore, the study employed multivariate linear regression analysis to explore coupling coordination relationships.

The study results revealed that high coupling coordination between technological innovation and standardisation is highly conducive to industrial development. Moreover, requirements for standardisation levels differ owing to different stages and characteristics in each segmented industry.

This study primarily contributes to the literature by using a bibliometrics tool to summarise related literature on innovation and standardisation and provides a new perspective of reviewing, and it also offers new evidence on the coupling coordination relationship between innovation and standardisation in the high-tech industry.

This paper aims to analyze the role and advantages of knowledge resources in the carbon emission reduction of the industrial chain, and how it can be used to promote the carbon emission reduction of the industrial chain, so that the industry can better achieve the saving of energy and the reduction of emission.

This paper argues that the traditional resource-plundering industrial chain production method can no longer meet the needs of sustainable development of the green and low-carbon industrial chain, and builds the coupling and coordination of knowledge technology innovation drive and industrial chain carbon emission reduction mechanism, in the four dimensions of industrial chain organization, government support, internet support and staff brainstorming, put forward suggestions for knowledge resources to drive carbon emission reduction in the industrial chain.

This paper holds that the use of knowledge resource advantages can better help industrial chain enterprises to carry out technological innovation, knowledge resource digital platform construction, knowledge resource overflow and transfer, application and management of network information technology, so as to reduce carbon emission in industrial chain.

This paper contributes to the discussion about the high-quality implementation of the revitalization strategy of the industrial chain and also deepens research on the knowledge resource-driven carbon emission reduction of the industrial chain. Further, this paper enriches the role of knowledge resources in the industrial industry, and the theoretical results support the advantages of knowledge resource in the field of chain carbon emission reduction.

The research question is how can a company implement a circular innovation in a supply network context? Leveraging the main conceptual and interpretative models of the industrial marketing and purchasing thinking, this study aims to investigate the interplay between the process of circular innovation development and the changes in the structure and dynamics of the supply network in which innovation takes place.

This research applies a case study design focusing on participant interaction dynamics. The case relates to an industrial company producing an innovative coating solution for compostable packaging. The data used to develop the case study came from multiple sources but primarily from semistructured interviews that cover the implementation of the circular innovation and the configuration of the circular network.

The dynamics of interconnected relationships can configure a circular network that interconnects business and non business actors through vertical, horizontal and heterogeneous relationships. The network configuration is supported by the new mobilizer actor that facilitates the sharing of circular knowledge within the circular network, together with the sharing of a market orientation and entrepreneurial orientation within the supply network, through the educational learning path.

This paper aims to contribute to a new understanding of how circular innovation can be developed, adopted and diffused. In a network, when circular innovation takes place, the focal issue is not the new product or technology in itself but how such innovation is developed and implemented by and through the reconfiguration of the business and non-business relationships into circular network.

This paper aims to provide a comprehensive view of the different competition-based approaches that policymakers can exploit to foster external knowledge search and their positioning among innovation policy measures. A growing number of companies have implemented initiatives to access external knowledge to increase their innovativeness, consistently with the open innovation paradigm. Competition-based approaches have received increasing attention by the private sector as a way to access external knowledge. However, despite their potential role as innovation policy measures, a limited attention has been devoted so far to investigate them from the policymakers’ perspective.

To this aim, a two-stage empirical analysis has been carried out to develop a taxonomy of competition-based approaches. The first stage leveraged a multiple case study methodology including a sample of 20 competition-based approaches, while the second one leveraged interviews with Italian and European key informants.

This paper proposes a novel taxonomy including eight competition-based approaches, which differ among each other in terms of policy strategy, scope breadth and output required. Moreover, this paper enriches a well-established taxonomy of innovation policy instruments with the identified competition-based approaches.

This study contributes to the current debate on innovation policy by providing a taxonomy that includes eight competition-based approaches that can be exploited by policymakers to foster external knowledge search as well as their positioning among the innovation policy instruments. The taxonomy will hopefully support policymakers in identifying of the most suitable instruments in the light of their policy strategy and objectives.

This paper aims to empirically investigate the impact of the carbon intensity constraint policy (CICP) on green innovation.

This study takes the implementation of the CICP as a quasi-natural experiment and uses a quasi–difference-in-difference method to investigate the impact of the CICP on firm green innovation from a microeconomic perspective.

The CICP significantly limits the quality of firms’ green innovation. Among the range of green patents, the CICP distorts only patents related to CO₂ emissions. The inhibitory effect is more pronounced in non-state-owned enterprises and heavily polluting firms. R&D investment and green investor are identified as the main mechanism.

These findings provide evidence for the influence of the CICP on firm green innovation, which can guide policymakers in China and other emerging economies that prioritize carbon intensity constraint targets and the improvement of relevant auxiliary measures.

Governments and firms should have a comprehensive understanding of environmental policies and corporate behavior and need to mitigate the negative impact through a combination of measures.

This study contributes to the literature by providing additional empirical evidence regarding the two opposing sides of the ongoing debate on the positive or negative effects of CICP. It also provides new evidence on the policy effect of the CICP on firm green innovation, together with its mechanisms and heterogeneous influences.

This chapter describes practical lessons for leading transformational innovation in industrial firms. These lessons result from theory-building empirical research based on published studies and the authors’ personal observations. These latter are the results of interviews with over 100 senior managers. The research also discriminates between the capabilities for leading core, adjacent and transformational innovations. In practice, each form requires different leadership and skills to ensure success. In the past, firms that use this approach have been described as ambidextrous. However, this oversimplifies the situation rather than considering the continuum of innovation approaches within a firm necessary to ensure long-term sustainability. This is because firms must innovate long-term, deliver ongoing core innovation in their existing portfolio, and evolve their value propositions and business models through adjacent innovation.