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This study aims to explore the relationship between financing constraints and the innovation performance of Internet enterprises in the cross-border innovation cooperation network. The study also analyzes the moderating effect of the location of the cross-border innovation cooperation network.

The authors selected patent data, related transaction data and other data of A-share listed companies on Shanghai and Shenzhen stock exchanges from 2014 to 2019. The generalized moment estimation method of instrumental variables (IV-GMM) method was used to analyze the relationship between financing constraints and the innovation performance of Internet firms and the moderating effect of the cross-border innovation cooperation network location. The threshold value of the moderating effect of the network structure hole was calculated with the threshold model.

The empirical results show a significant inverted U-shaped relationship between financing constraints and the innovation performance in the cross-border innovation cooperation network of Internet enterprises. Network centrality positively moderates this relationship. There is a threshold for the adjustment effect of network-structural holes, and the adjustment intensity of structural holes changes before and after the threshold.

This study provides a new perspective for Internet firms in innovation cooperation networks to alleviate the negative impact of financing constraints on innovation performance. The inverted U-shaped relationship between financing constraints and the innovation performance of Internet enterprises is in two stages. The moderating range of network centrality and the structural hole besides the threshold of the moderating effect of a structural hole are detailed.

University–industry (UI) collaboration is essential for knowledge and technology exchange between higher education institutions and industries, enabling enterprises to accelerate innovation. However, few studies have investigated the collaborative innovation mechanism through which UI collaboration can enhance the accumulation of firms' intellectual capital (IC) and how this, in turn, affects their innovation-driven development.

Drawing from the knowledge management and collaborative innovation theory, this research proposes a theoretical framework of the inter-organization relationship between enterprises and universities to investigate the influence mechanism of UI collaboration, including academic engagement and commercialization, on corporate performance as well as the mediating role of IC by employing survey that covers 177 UI collaborations.

Empirical results show that human capital and relational capital fully mediate the relationship between academic engagement UI collaboration and corporate economic performance, while human capital partially mediates the relationship between commercialization UI collaboration and corporate economic performance. Additionally, structural capital and relational capital partially mediate the relationship between academic engagement and corporate innovation performance, while structural capital fully mediates the relationship between commercialization and corporate innovation performance.

This study empirically investigates how academic engagement and commercialization impact corporate performance (i.e. innovation dimension or economic dimension). It uncovers this relationship's underlying mechanism by documenting the IC's mediating impact.

The purpose of this paper is to study the influence mechanism of different levels of social capital (Structure holes–local network attributes and indirect ties–global network attributes) and organizational culture on the creativity of key inventors, and the role of organizational culture between social capital and creativity.

The paper tested the hypotheses with a sample of patent data accumulated from 46 firms in Chinese electronic information and automobile sectors. Negative binomial regression was used to explore the factors influencing the creativity of key inventors.

The paper discovers that structural holes are valuable social capital for the creativity of key inventors and very important in firms with a collective and conservative culture. Moreover, it also locates that key inventor are more creative in firms with an individualistic and competitive culture than those in firms with a collective and conservative culture.

This study emphasizes the influence of social capital on creativity and contributes to R&D management. It highlights structural holes are certainly important to key inventors in a collective and conservative culture, thus contradicting preceding studies that locate structural holes useful solely in an individualistic culture. This finding broadens our knowledge of the benefits of this network structure. Also, this debate challenges several basic views on structural holes currently.

Existing literature is limited in its ability to consider start-ups as a knowledge broker to trigger innovation in a supply chain ecosystem (SCE). In a traditional SCE, start-ups are relatively isolated, leading to structural holes that limit knowledge sharing among members. This paper aims to overcome that limitation and to build frameworks that help to illustrate the interaction between knowledge management and sharing, start-up innovation and an ecosystem from a supply chain perspective.

Following a qualitative approach, this study theorizes about the role of start-ups as knowledge brokers and the implications of knowledge management and sharing with members in an SCE concerning innovation. Conceptual analysis is used for examination, and this study uses a set of qualitative tactics to interpret and generate meaning from the existing literature.

This study develops two frameworks to provide insight into how start-ups can trigger innovation as knowledge brokers in an SCE. The first framework shows how start-ups, and their knowledge base, influence supply chain members and the overall ecosystem, highlighting the isolated function of start-ups and the issue of structural holes in a traditional SCE. The authors propose a model that illustrates how structural holes can be bridged within an SCE, thereby demonstrating how start-ups redefine the ecosystem architecture according to their knowledge broker position in the SCE.

By expanding insight into the concepts of how start-ups can trigger innovation as knowledge brokers in an SCE, this paper extends the so-far neglected area of start-ups and knowledge brokers. This study clarifies the conceptual and theoretical components and processes in an SCE and links the different roles of start-ups as knowledge brokers to the respective supply chain members to better understand the implications on the entire SCE.

This research is an empirical study that addresses whether knowledge resources impact on, or do not impact on, innovation development and if this impact is mediated by dynamic capabilities in the medical tourism sector in Mashhad city, Iran.

A quantitative research methodology was applied and questionnaires were used for data collection in this study. A total of 108 questionnaires were collected of which 102 questionnaires were valid. Data were analyzed using structural equation modelling technique.

Empirical evidence obtained from the study reveals that the dynamic capability of learning plays a significant role in transforming knowledge resources into innovation in the medical tourism sector. The mediating role of coordinating capability in the relationship between explicit and tacit knowledge and innovation is considerable and it influences human capital, as well. Sensing capability also exhibits some degree of a mediating role; however, integrating capability is not influential and its role in transforming explicit knowledge to innovation is rejected.

Most studies on innovation in medical tourism focused on market and its typology, and neglected the role of knowledge resources and dynamic capabilities. The current study bridges this gap and thus contributes to the scientific literature.

Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation.

Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses.

The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs.

This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

This study aims to reveal the contribution mechanism of various types of intrafirm networks formed among inventors to firms’ searching for new knowledge. This study also intends to show how this mechanism is influenced by the geographic dispersion of inventors and the external alliance of firms.

This study develops an analytical framework building on social network theory to explain the collective search among inventors within the firm. The authors validate the hypotheses using the data from 316 publicly traded biotechnology firms in the USA.

As demonstrated by the findings, intrafirm network clustering facilitates the search for new knowledge. The geographic dispersion of inventors’ location has a negative moderating effect on this relation, whereas the number of alliance partners has a positive moderating effect on this relation. By contrast, the search for new knowledge is hampered by the intrafirm network average path length. The geographic dispersion of inventors positively moderates this relation, whereas a firm’s alliance partner number negatively moderates this relation.

To the best of the authors’ knowledge, this study is the first to examine the joint effect of intrafirm networks, inventors’ geographic locations and external alliances on the new knowledge-searching process. This study points out that new knowledge acquired through inventors’ geographic locations and alliance partners is internalized efficiently according to different types of internal networks.

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

Industrialization is a major contributor to pollution and the worsening of some social problems. A change in this context would help in a new industrial model aiming at a viable and sustainable manufacturing system. This research aims to verify the state of the art of sustainability within the industrial production process through a systematic literature review, verifying the main characteristics in relation to industrial sustainability that the literature demonstrates.

The development of the research took place in three stages: a survey of articles with Journal Citation Reports (JCR), the construction of the database and descriptive analysis and text mining analyses of social networks and content. The survey took place through academically endorsed research platforms, totaling a total of 352 scientific articles, which included 18 quality management tools and worked with at least one sustainability indicator (financial, social and environmental).

Lean manufacturing, integrated management system and Six Sigma were the most cited quality tools, and articles containing the three indicators were found more frequently. It was found that most authors treated sustainability only as an environmental contribution. Knowledge of the organization's structural and management issues is essential for implementing sustainability and production process improvement.

This work is the first to develop a systematic analysis regarding the use of sustainability implementation in the industrial production process, considering a wide scope of production process tools, guiding on the characteristics of sustainability relating to the main critical success factors (CSFs), motivations, difficulties and benefits that lead industries in different parts of the world to implement sustainability.