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This study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.

Diagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.

According to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.

This study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

Firms are driven to ride on the digital wave in today’s open innovation ecosystem. This study aims to explore the effect of digital transformation (DT) on knowledge-intensive business services (KIBS) firms’ innovation ambidexterity, namely, radical versus incremental innovation, respectively. Meanwhile, the authors evaluated the moderating role of the complexity of R&D collaboration portfolio (i.e. organizational diversity and geographic diversity) in the above relationships.

Using a panel data set of 171 Chinese listed firms in the information and communications technology services industry from 2010 to 2018, the proposed hypotheses were empirically attested.

It is found that DT has a positive relationship with radical innovation and an inverted U-shaped relationship with incremental innovation. In terms of the R&D collaboration portfolio, organizational diversity positively moderates the relationships between DT and innovation ambidexterity, respectively. The geographic diversity weakens the inverted U-shaped effect of DT on incremental innovation; however, its moderating role in the link between DT and radical innovation is not empirically verified.

Extant scholars mainly addressed the interplay between KIBS firms and their manufacturing clients, while this study reveals the different consequences of DT on KIBS firms’ innovation ambidexterity to highlight the role of KIBS firms is an independent and essential innovator in a knowledge-driven economy. Notably, the findings contribute to knowledge management (KM) and R&D literature by confirming the diversity of the R&D collaboration portfolio is a critical KM strategy for KIBS firms to develop and promote external knowledge resources.

In recent years, environmental issues and resource depletion have posed significant challenges to firms and society. To address these environmental challenges, firms seek to build strategic alliances of green supply chain management (GSCM) with their supply chain partner. As the largest developing country in the Asia–Pacific region, China needs to take more responsibility for environmental protection, which requires more Chinese firms to participate in GSCM. Therefore, focusing on the issue of GSCM and innovation persistence in the context of an increasingly harsh ecological environment is essential.

To test the hypothesis, the authors perform an empirical analysis on a sample of 124 listed firms in China from 2014 to 2019. The results are robust to a battery of robustness analyses the authors performed to take care of endogeneity.

Empirical results indicate that GSCM can promote innovation persistence and both market environment turbulence and technology environment turbulence have a positive moderating effect on the relationship between the two. Mechanism tests show that GSCM can improve innovation efficiency, ensure innovation quality and alleviate financing constraints, thus promoting the innovation persistence of firms.

This study can provide a theoretical basis for the country to promote GSCM orientation, raise firms' awareness of the value of GSCM, convey the significance of GSCM to investors, influence firms' investment decisions and give experience to other developing countries.

The purpose of this study is to examine the moderating effect of two types of external funds in terms of loan and government subsidy on the relationship between R&D investment and firms' innovation performance in emerging markets, as well as the contingent role of firm leader's international experience associated with the effects of loan and government subsidy.

The authors tested the hypotheses using a longitudinal dataset of 716 high-tech firms of Zhongguancun Science Park (ZSP) in China during 2008–2014, covering detailed information on the operations, financial situation and R&D activities, patents, etc. The authors finally identified an unbalanced panel of 2,430 firm-year observations. Considering the dependent variable is the countable data and non-negative values, the negative binomial regression with fixed effects was adopted to test the hypotheses.

The results show that the more loans or government subsidies the firm receives, the weaker the positive effect of R&D investment on firms' innovation performance in emerging markets. Furthermore, the findings reveal that firm leaders' international experience can mitigate the negative moderating effect of government subsidies, but strengthen the negative moderating effect of loans.

The study provides new insights into how loans and government subsidies as external funds influence the effectiveness of R&D in enhancing innovation performance, and the findings highlight the fact that more external funds can reduce firm R&D efficiency. Moreover, the authors also enrich the resource orchestration theory by revealing the critical role of firm leaders' international experience in the decision-making of resource configuration to mitigate the inefficiency of high subsidies in emerging markets.

The Indian pharmaceutical industry currently faces multiple challenges, including rising costs and slowing export growth, which in turn have limited its ability to expand presence in global canvas. Given the nature of sectoral dynamics, a pharmaceutical firm must undertake huge investments in R&D to introduce product innovation, in turn enhancing market share and sustaining profit streams. The development of novel medicines, confirmed by the granting of patent rights, provides a pharma company edge over its competitors. In addition, presence of innovator firms within the industry invigorates the sectoral value chain and raises efficiency. Hence, it is important to analyze whether granting patent rights enhances the exports of pharmaceutical products in the Indian context.

The current study explored this question using a simultaneous-equation framework. Specifically, the authors use the methods developed by Davidson and MacKinnon (1993) and Greene (2003) to obtain heteroscedasticity-consistent estimates. The time-series properties of the data were further probed, and robust estimates were used to test the theory. Methods developed by Baltagi (1981) have been used further to refine the authors’ estimations.

After controlling for relevant variables, it is observed that granting of patents caused a significantly positive impact on pharmaceutical exports. Furthermore, the change in the patent administration regime had a significant impact on patent fillings, which further impacted their exportability. Compared to patents granted patents filed had a higher impact on pharmaceutical exports.

This study attempts to apply the framework developed by Goldstein and Khan (1978) with necessary modifications to suit the context of a developing country. The application of the 3SLS method to estimate the export supply equation for pharmaceutical products is a novel approach to the research question in general and to the Indian context in particular. System autocorrelation and heteroscedasticity tests were performed to refine the results further.

This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different types of inventors) on the formation of structural holes.

The authors collected 59,798 patents applied for and granted in the USA by 33 of the largest firms worldwide in the pharmaceutical industry between 1975 and 2014. A random-effects tobit model was used to test the hypotheses.

The inventors’ ability to acquire external knowledge contributes to the formation of structural holes. While inventors’ ability to provide broad knowledge positively affects the formation of structural holes, their ability to provide professional knowledge works otherwise. In addition, key inventors and industrious inventors are more likely to form structural holes than talents.

The results identify individual factors that affect the formation of structural holes and improve the understanding of structural hole theory. This study is unique in that most scholars have studied the consequences of structural hole formation rather than their antecedents. Studies on the origin of structural holes neglect the effect of inventors’ knowledge abilities and patenting output. By addressing this gap, this study contributes to a more comprehensive theoretical understanding of structural holes. The results can guide managers in managing structural holes in accordance with inventors’ knowledge abilities and patenting outputs, which optimize the allocation of network resources.

This paper aims to investigate the antecedents of recombinant innovation from the perspective of ego–network dynamics, and further disentangle whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under heterogeneous knowledge base.

This paper uses 1,801 patent data in China’s biotechnology field as a sample and adopts fixed effects regression model to examine the effects of ego–network dynamics on recombinant innovation and further uses the Wald tests to discern which ego–network dynamic is more conducive to recombinant innovation under heterogeneous knowledge base.

The empirical results indicate that ego–network dynamics have a positive impact on recombinant innovation. Specifically, for firms with high knowledge breadth and high knowledge depth as well as high knowledge breadth and low knowledge depth, ego–network stability is more conducive to recombinant innovation. By contrast, for firms with low knowledge breadth and high knowledge depth, recombinant innovation benefits more from ego–network expansion. As for firms with low knowledge breadth and low knowledge depth, both ego–network stability and ego–network expansion can promote recombinant innovation, while the effects are not significant.

This research may enlighten managers to choose suitable ego–network dynamics strategies for recombinant innovation based on their knowledge base.

This research not only contributes to the literature on recombinant innovation by revealing the impact of different ego–network dynamics on recombinant innovation but also contributes to network dynamics theory by exploring whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under a heterogeneous knowledge base.