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As sustainable performance has a central role in the small and medium enterprises (SMEs) performance literature, this study aims to examine the influence of networking capabilities in enhancing sustainable performance through knowledge workers’ productivity and digital innovation. It also examines the sequential mediating role of knowledge workers’ productivity and digital innovation on networking capabilities and SMEs’ sustainable performance relationship.

Data were collected from 308 knowledge workers in the information technology sector and analyzed using the Hayes Process Macro bootstrapping method to test the proposed hypotheses.

Results indicate that knowledge workers’ productivity and digital innovation individually and sequentially mediate the relationship between networking capabilities and SME’s sustainable (economic and environmental) performance, surprisingly, they do not act as a mediator between networking capability and SME’s social performance. SMEs should prioritize investments in the professional development of their knowledge workers through training and skill enhancement programs. This investment equips knowledge workers with the tools to effectively use the knowledge and resources acquired through networking. Thus, knowledge workers may improve performance by using these resources to tackle challenges.

Although this research focused on this specific context, it is prudent to acknowledge that additional factors may also exert influence on sustainable performance within SMEs, factors that managers may consider when making decisions. Methodologically, the cross-sectional design of this research poses a potential limitation, as it does not allow for the complete elimination of endogeneity concerns. However, it is worth noting that scholars have endorsed the use of cross-sectional data in cases where management researchers aim to expand beyond well-documented and longitudinal data sets.

This research offers practical recommendations for SMEs to improve their sustainable performance through networking. SMEs should seek partnerships with complementary knowledge to improve operations and for other performance-oriented benefits.

This study adds significantly to the literature on sustainable SME performance by studying the interdependent effects of networking capabilities. It also represents the individual and sequential mediation mechanism that links networking capabilities to SME success through knowledge worker productivity and digital innovation.

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.

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 paper aims to explain the unwillingness to exchange export knowledge by members of exporters’ networks and provides potential solutions to this problem.

This study uses data from a survey of 301 members of a French exporter’s network to test a set of hypotheses with partial least squares structural equation modeling.

Network participants’ export experience and age have a negative influence on their willingness to exchange knowledge. However, positive attitudes toward the network (perception of network quality, commitment) can mitigate those negative links.

Network members’ unwillingness to exchange knowledge represents a major challenge that threatens the existence of knowledge networks. The findings suggest solutions to this issue for network managers.

This study views knowledge exchange in a network as a risky behavior. It explains why members do not participate in networks. The model shows how contrary forces work and interact to deter or foster knowledge exchange.

The purpose of this paper is to examine the information flows, in terms of content and process, underpinning the sharing of knowledge by managers and owners. Such an examination reveals similarities and differences that will influence the generation and dissemination of knowledge used in tourism business operations and contribute to innovation.

This paper examines information flows within the theoretical and methodological framework of social network analysis. The findings were derived from a quantitative study of tourism managers and owners of a tourism hub in South-West England.

The main finding was that network structure characteristics determine the flow of information within owners’ and managers’ social networks. The owners of smaller businesses received information from several sources and, therefore, had fewer structural constraints and reported larger structural holes. In comparison, the managers had more brokerage opportunities to disseminate the information within their social networks.

This paper highlights knowledge sharing between tourism business managers and owners in an open network structure. First, an open network structure builds innovation through the provision of nonredundant information. This is determined through the effective size of structural holes and the dissemination of information through brokerage roles. Second, the knowledge capability of a destination is built up through the social networking of managers and owners. The generation and dissemination of knowledge in a tourism destination are facilitated by the social networking activities of managers and owners.

Managers and owners of tourism businesses require knowledge through information to assist with innovative business practices. The practical implication of this is that the social networks of managers and owners have different network characteristics, and that these differences result in consequences for the innovation of business practices. Another practical implication relates to the importance of managers in knowledge dissemination based on having several brokerage roles in the tourism destination.

These findings are important because an understanding of social networks and the flow of information is one of the keys to determining the influences on knowledge sharing within tourism destination knowledge networks of owners or managers and their potential contributions to innovation.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

Despite the significance of knowledge sharing for competitive advantage in networked businesses like franchising systems, there is a lack of comprehensive understanding regarding the strategic value of knowledge sharing in the context of franchising. In particular, the specific contribution of information and communication technologies (ICTs) in facilitating interorganizational knowledge exchange among franchising members remains inadequately understood, particularly in emerging economies. Therefore, this study aims to explore the mechanisms involved in the knowledge-sharing process facilitated by a virtual learning environment (VLE) within franchising networks and examine the role of VLEs in facilitating knowledge.

This study uses a multiple-case study approach involving 24 franchisees and the franchisor within a Brazilian franchising network operating in the furniture market to examine the role played by a VLE.

The results of the study reveal that the introduction of a VLE has played a significant role in fostering enhancements in the knowledge-sharing process among the franchisor and franchisees in the network. Moreover, the results indicate that VLEs play a significant role in overcoming geographical obstacles, thereby enabling efficient knowledge sharing between franchisees and franchisors operating in extensive territorial contexts. Finally, findings indicate that intracommercial competition acts as a prominent barrier, leading to low levels of cooperation and knowledge-sharing intent among franchisees within the network.

This study contributes to the existing knowledge by enhancing the understanding of how ICTs can facilitate knowledge sharing in organizations operating within franchising systems. Furthermore, this paper advances the comprehension of the role of networking franchising configuration and governance in supporting organizational improvements. Additional actionable insights are provided.

This paper aims to seek answers to the question: What are the relevant factors that allow not-for-profit innovation networks to successfully transition new technologies from proof-of-concept to commercialisation?

This question is examined using the knowledge-based view and network orchestration theory. Data are collected from 35 interviews with managers and engineers working within seven centres that comprise the High Value Manufacturing Catapult (HVMC). These centres constitute a not-for-profit innovation network where suppliers, customers and competitors collaborate to help transition new technologies across the “Valley of Death” (the gap between establishing a proof of concept and commercialisation).

Network orchestration theory suggests that a hub firm facilitates the exchange of knowledge amongst network members (knowledge mobility), to enable these members to profit from innovation (innovation appropriability). The hub firm ensures positive network growth, and also allows for the entry and exit of network members (network stability). This study of not-for-profit innovation networks suggests the role of a network orchestrator is to help ensure that intellectual property becomes a public resource that enhances the productivity of the domestic economy. The authors observed how network stability was achieved by the HVMC's seven centres employing a loosely-coupled hybrid network configuration. This configuration however ensured that new technology development teams, comprised of suppliers, customers and competitors, remained tightly-coupled to enable co-development of innovative technologies. Matching internal technical and sectoral expertise with complementary experience from network members allowed knowledge to flow across organisational boundaries and throughout the network. Matrix organisational structures and distributed decision-making authority created opportunities for knowledge integration to occur. Actively moving individuals and teams between centres also helped to diffuse knowledge to network members, while regular meetings between senior management ensured network coordination and removed resource redundancies.

The study contributes to knowledge-based theory by moving beyond existing understanding of knowledge integration in firms, and identified how knowledge is exchanged and aggregated within not-for-profit innovation networks. The findings contribute to network orchestration theory by challenging the notion that network orchestrators should enact and enforce appropriability regimes (patents, licences, copyrights) to allow members to profit from innovations. Instead, the authors find that not-for-profit innovation networks can overcome the frictions that appropriability regimes often create when exchanging knowledge during new technology development. This is achieved by pre-defining the terms of network membership/partnership and setting out clear pathways for innovation scaling, which embodies newly generated intellectual property as a public resource. The findings inform a framework that is useful for policy makers, academics and managers interested in using not-for-profit networks to transition new technologies across the Valley of Death.

This study aims to investigate how international entrepreneurial firms (IEFs) successfully commercialise innovative products/services internationally. In doing so, the authors examined the role played by the international dynamic marketing capability (IDMC) in the relationship between explorative and exploitative innovation and commercialisation. In addition, the authors also evaluated how the breadth and depth of international networks facilitate IEFs in upholding the effects of the IDMC to influence commercialisation.

To test the research model, structural equation modelling is used based on time-lagged survey data drawn from 201 Malaysian IEFs. To validate the results, additional robustness tests and endogeneity analyses have been performed.

The findings show that the IDMC positively mediates the relationship between explorative and exploitative innovation and commercialisation. Furthermore, the finding exhibits that the effects of the IDMC on commercialisation are positively moderated by the breadth and depth of international networks.

Given the fragmented and general nature of the extant marketing research on the IDMC, the study contributes to the international marketing literature by providing rich and nuanced pertinent knowledge. This study advances dynamic capability theory in relation to IEFs by establishing the IDMC as a functional capability suited to enable them to successfully commercialise the products/services resulting from explorative and exploitative innovation.

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.