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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.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

This study aims to investigate whether there are disparities in research and development (R&D) internationalization between latecomers from economy-level technological disparities and firms with ownership-specific technological capability differences in the wind turbine industry.

Employing econometric analysis based on patent indicators, the authors examine the patent data assigned by the United States Patent and Trademark Office (USPTO) to the technologically advanced economy and the technologically emerging economy.

This study finds that latecomers from technologically advanced economies behave with no difference from early leaders in terms of international co-invention (INCO) but do show differences in another indicator – native ownership of foreign inventors (NOFIs). Additionally, latecomers from economy-level technological disparity show significant differences both in both INCO and NOFI. These results indicate that the latecomers from technologically advanced economies not only possess the nature of latecomers which motivates them to seek knowledge from foreign economies but also benefit from their advanced home base, thereby prompting them to internationalize and access cost-effective R&D resources. Moreover, the results demonstrate that latecomers from technologically emerging economies are more prone to engage in R&D internationalization to augment their own home base compared with firms from advanced economy.

This study extends the literature on R&D internationalization by introducing novel perspectives. It distinguishes some apparent distinctions of the tendency of R&D internationalization between latecomers under economy-level technological disparity as well as firms from ownership-specific technological capabilities differences. Additionally, this study disaggregates R&D internationalization into twin key dimensions: INCO and NOFI. These findings allow for a comprehensive understanding of the differences in the firm's R&D internationalization under economy-level technological disparities and ownership-specific technological differences. These findings offer valuable insights for decision-makers in navigating global innovation activities by highlighting the diverse economy-level technological advantages as well as ownership-specific advantages.

The study aims to test the success of university-industry (U-I) collaboration in terms of innovation process efficiency. Then, this study explores the moderating role of a set of organizational routines in the U-I relationship, which can help in overcoming the issues undermining the collaboration success.

The study is based on an international Open Innovation (OI) survey. The survey investigated the items to build the main variables of the conceptual framework, measured through seven-point Likert scales. Steps to ensure the reliability and validity of the variables were conducted. Then, hypotheses were tested with an ordinary least squares regression.

Results show that the higher the collaboration intensity (depth) with universities, the higher the innovation process efficiency. Furthermore, organizational routines aimed at improving firms' assimilation absorptive capacity further strengthen the positive effects of intensive collaboration on innovation process efficiency.

Findings indicate that R&D managers should strive to build deep collaborations with universities to enhance process efficiency and invest in the quality of these relationships. Managers should create and maintain an internal environment that further enhances the positive effects of intensive collaboration on innovation process efficiency.

The OI literature has not reached a shared view on the positive contribution of universities toward industrial firms' innovation performance. The study adopts a process-efficiency view, rarely used by other OI studies usually focused on output indicators; this study unpacks, respectively, the role of the intensity of collaboration and the organizational routines, thus disclosing the benefit of U-I collaboration on innovation efficiency.

Small and medium-sized enterprises (SMEs) are currently showing an increasingly open innovation (OI) approach. Public policies supporting the adoption of OI by SMEs are becoming a priority for policymakers. Therefore, the aim of this article is to contribute to the literature by mapping scholars' policy recommendations for implementing OI among SMEs.

The authors conducted a systematic review of the literature (SRL) on the topic to achieve this purpose. A total of 99 academic articles were selected from the Web of Science and Scopus databases to suggest the main scholars' policy recommendations to implement OI among SMEs.

Results indicated that scholars' policy recommendations for OI adoption in SMEs can be organized into: research and development (R&D), networking, collaboration, knowledge and intellectual property rights (IPR), ecosystem, managerial capabilities, funding and incentives and sustainability policies.

Only relevant articles about this topic have been included due to the reliance on the interpretations of the authors. The analysis of the literature revealed that the authors did not always distinguish policies dedicated to SMEs and those dedicated to large companies. Moreover, policies are not matched according to each OI dimensions (e.g. inbound, outbound and coupled OI).

The article uses a systematic literature review method that combines qualitative and quantitative analyses. This method contributes to theoretical development of OI policies dedicated, in particular to SMEs. This paper also provides policymakers and researchers with insights on the scope of OI policies that could support economic growth.

This study contributes to the literature on eco-innovation (EI) and the circular economy (CE) by providing insights into the factors of external knowledge absorption that facilitate the adoption of a subset of EIss called proactive-EIs. Proactive-EIs involve collaborations among multiple stakeholders, the use of technical knowledge and a greater level of investment than other innovations. In this study, the environmental actions taken by small and medium-sized enterprises (SMEs) in resource-intensive sectors in the European Union (EU) were observed, and elements related to the national context were compared.

The national innovation system (NIS) perspective was adopted using a multilevel framework to assess the determinants of proactive-EIs among SMEs in the EU. The framework involves three levels: micro- (environmental awareness), meso- (external collaboration and intra-industry agglomeration) and macro- (economic complexity, trade openness and government research and development [R&D]). The survey data of 6,188 SMEs in resource-intensive sectors were analysed using a binary logistic regression.

The results showed that public awareness, economic complexity and public sector R&D positively influenced SMEs' adoption of proactive-EIs, whereas external collaboration and sectoral agglomeration negatively influenced adoption.

Among the existing empirical studies on EI, areas related to external knowledge-based innovations and systematic assessments of heterogeneity among EU member states remain underexplored. This study contributed to the literature by assessing the conditions surrounding external knowledge absorption. The findings contribute to the green entrepreneurship literature in the context of developed economies and offer insights for managers and policymakers seeking to promote EIs.

The authors contribute to the literature on leadership by investigating how characteristics of principal investigators (PIs) affect innovation performance, and how collaborative and non-collaborative projects moderate this relationship within the context of inter-organisational research projects.

The authors analysed panel data from the National Science and Technology Information Service on 171 research projects within a biomedical and regenerative medicines programme overseen by the Korea Health Industry Development Institute. The authors used a hierarchical regression model, based on the ordinary least squares method, to examine the relationship between PI characteristics and performance, considering both quantity and quality.

The results show that the characteristics of PIs have diverse effects on the quantity and quality of innovation performance. Gender diversity within PIs negatively affects the quality of innovation performance, while the capacity of PIs positively influences it. Moreover, the degree of PI’s engagement is positively associated with the quantity of innovation performance but does not have a significant relationship with the quality of performance. In terms of moderating effects, collaborative projects with multiple leaders seem less reliant on PI capacity than non-collaborative projects led by a single leader, in terms of innovation performance.

The results contribute significantly to the literature on innovation management by examining the role of leadership in collaborative environments to enhance innovation performance, addressing the need for empirical evidence in this area. Analyses of PI characteristics in government R&D management can lead to improved team performance, more efficient processes and effective resource allocation, ultimately fostering innovation.

The paper proposes an answer to one of the most important questions in corporate innovation management: what mechanisms of technological diversification exist within multinational companies? It is ascertained that research and development (R&D) intra-firm co-invention or co-patenting is one of those mechanisms. Co-invention implies knowledge-sharing, which should lead to unique combinations of knowledge and expertise and hence technological diversification of patent applications.

This paper offers a novel conceptual framework exploring the relationship between patents’ technological diversification and a detailed classification of different forms of international co-invention. Based on the case of Siemens’ Patent Cooperation Treaty (PCT) applications, the revealed technological advantage (RTA) index is utilized to measure the extent of the technological diversification of patent output.

The results show that patent applications generated by subsidiaries in advanced economies in cooperation with other subsidiaries feature unique technological areas that deviate from the company's overall technological specializations. These results provide a strong argument in favor of inter-subsidiary or horizontal co-patenting as a mechanism of new knowledge creation.

On the conceptual level, the results accentuate inter-subsidiary patenting being an important mechanism of knowledge meta-integration boosting technological diversification. The obvious limitation of this paper lies in exploring a single company case, which restricts the generalizability of our findings. Due to the dynamic nature of technological change, the author’s dataset also suffers from a lack of temporal external validity. Future research can expand the scope in both regards in applying our co-invention mode typology.

Based on the results, to diversify knowledge portfolio, companies should strengthen the co-patenting effort and reinforce horizontal (inter-subsidiary) R&D collaborations.

To the author’s knowledge, this is the first time when such a nuanced typology of co-invention modes is being utilized to understand the effect of different co-invention categories on knowledge diversification.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

The purpose of this paper is to investigate the impact of two dimensions of technological relatedness, namely technological similarity and complementarity, on collaborative performance, plus the mediating role of collaboration network stickiness and the moderating role of partner expertise and geographical distance in interfirm collaboration contexts.

This study takes Chinese Scientific and Technological Achievements (STA) of inter-firm collaboration in five high-tech fields in 2010–2020 as the sample and uses OLS regression to test the hypothesis.

Technological similarity and complementarity positively affect collaborative performance. Partner expertise negatively moderates the relationship between similarity, complementarity and collaborative performance. Geographical distance positively moderates the relationship between similarity and collaborative performance while negatively moderates that between complementarity and collaborative performance. Collaboration network stickiness partly mediates the relationship between similarity and collaborative performance.

This study expands literature on inter-firm collaboration, especially research on the antecedents of collaborative performance. Moreover, this study not only compensates for lack of empirical analysis in partner selection research, but also utilizes second-hand data to enhance the objectivity of analysis. Additionally, we enrich the research on the moderating role of partner expertise and geographical distance as well as the mediating role of collaboration network stickiness.