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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.

The focus of industrial cluster innovation lies in the cooperation between enterprises and universities/scientific research institutes to make a theoretical breakthrough in the system and mechanism of industrial cluster network. Under the theoretical framework of cluster network, industrial structure can be optimized and upgraded, and enterprise benefit can be improved. Facing the increasing proliferation and multi-structured enterprise data, how to obtain potential and high-quality innovation features will determine the ability of industrial cluster network innovation, as well as the paper aims to discuss these issues.

Based on complex network theory and machine learning method, this paper constructs the structure of “three-layer coupling network” (TLCN), predicts the innovation features of industrial clusters and focuses on the theoretical basis of industrial cluster network innovation model. This paper comprehensively uses intelligent information processing technologies such as network parameters and neural network to predict and analyze the industrial cluster data.

From the analysis of the experimental results, the authors obtain five innovative features (policy strength, cooperation, research and development investment, centrality and geographical position) that help to improve the ability of industrial clusters, and give corresponding optimization strategy suggestions according to the result analysis.

Building a TLCN structure of industrial clusters. Exploring the innovation features of industrial clusters. Establishing the analysis paradigm of machine learning method to predict the innovation features of industrial clusters.

To maintain and enhance innovation performance, many firms nowadays look for resources from external sources such as strategic alliances and regional network embeddedness. While considering the important interdependencies among different alliances, research has established an alliance portfolio perspective. From an alliance portfolio perspective, firms can consciously configure the dimensions of their alliance portfolios such as partner characteristics, relational properties, or structural properties. However, within the context of alliance portfolio configuration, the role of regional networks has been largely overlooked. As most high-tech firms are regionally clustered, this is an important research gap. In addressing this gap, this study explores the link between regional network density, alliance portfolio configuration, and its contribution to firm innovation performance. We examine how regional network density and alliance partner diversity influences firm level innovation output. We also investigate the moderating effect of overall network partner status and partner diversity on the link between regional network density and innovation performance. Our empirical evidence is derived from a longitudinal quantitative study of 1,233 German biotechnology firms. We find that regional network density and alliance partner diversity has an inverted U-shape effect on firm level innovation performance. However, overall network status as well as alliance partner diversity negatively moderates the link between regional network density and innovation output. Thus, our study contributes to a better understanding of the link between regional networks, alliance portfolio configuration, and firm level innovation performance.

Collective reputation cognition is an enterprise's perception of the general rules of reputation evaluation, jointly formed by a network's collective members. It affects the choice of enterprises' innovation behavior and guides enterprises to occupy a dominant position in the innovation network, thus achieving high innovation performance. In this process, it is inseparable from the enterprise's good network competence. This study attempts to bring collective reputation cognition, network competence and innovation performance into the same framework and aims to explore the relationship among them and determine the influential roles of collective reputation perception and network capability on innovation performance.

This study uses 227 Chinese enterprises in the innovation network as samples and applies partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to explore the questions mentioned above.

The results verify the relationship among collective reputation cognition, network competence and innovation performance. Furthermore, the results yield five paths that lead to high innovation performance, such as “putting ability first” and “both fame and competence”, which are different combinations of collective reputation cognition and network competence.

Based on institutional theory, this study considers the network context and identifies “collective reputation cognition” as a key variable. Meanwhile, it opens the “black box” of the mechanism of reputation's influence on innovation performance and finds that the combined paths of collective reputation cognition and network competence achieve high performance in terms of innovation.

This paper investigates the roles and activities of the orchestrators of innovation networks constituted within cities. In this sense, the authors expected to contribute for research related to the roles and activities of the orchestrators of innovation networks constituted in the scope of cities given the large number and diversity of complex and multiple dimensions social actors (Castells & Borja, 1996; Reypens, Lievens & Blazevic, 2019).

The authors conducted an exploratory research with a single case study in depth. The case chosen for the paper is the case of Pacto Alegre. The case selection criterion was the relevance of the Pacto Alegre Case in the construction of an innovation network in the city of Porto Alegre, Rio Grande do Sul, Brazil. The Pacto Alegre network was proposed by the Alliance for Innovation (composed of the three main Universities in the city: UFRGS, PUCRS and UNISINOS) and by the Municipality of Porto Alegre. In addition to these actors, the network counts on financial and development institutions as sponsors, with media partners, with design partners, with an advisory board (composed of five professionals considered references in different themes) and composed by more than 100 companies, associations and institutions from different areas (Pacto Alegre, 2019). Data were collected from 09/20/2020 to 11/30/2020 through in-depth interviews, documentary research and non-participant observation.

In this research, the authors highlighted the city as a community that involves and integrates various actors, such as citizens and companies, to collaborative innovation activities. For this, they proposed a framework on innovation networks and network orchestration. In this direction, seven dimensions of the “orchestration of innovation networks” were assumed as a result of the combination of previous studies by Dhanaraj and Parke (2006), Hurmelinna-Laukkanen et al. (2011) and da Silva and Bitencourt (2019). In the sequence, different roles of orchestrators associated with the literature were adopted based on the work by Pikkarainen et al. (2017) and Nielsen and Gausdal (2017).

The authors’ results advance in relation to other fields by promoting the expansion of the “orchestration of innovation networks” model with the combination of distinct elements from the literature in a coherent whole (agenda setting, mobilization, network stabilization, creation and transfer of knowledge, innovation appropriability, coordination and co-creation) and in the validation of its applicability in the context of the innovation network studied. In addition, when relating different roles of orchestrators to the seven dimensions studied, it was realized that there is no linear and objective relationship between the dimensions and roles of the orchestrator, as in each dimension there may be more than one role being played in the orchestration.

Therefore, the findings suggest two theoretical contributions. First, the authors identified a role not discussed in the literature, here called the communicator. In the case analysis, the authors observed the communicator role through functions performed by a media partner of the innovation network and by a group of civil society engaged in the city's causes. Second, the authors indicated a new dimension of orchestration related to the management of communication in the innovation network and its externalities such as p. ex. civil and organized society, characteristic of an innovation network set up within a city.

Although several studies have proposed advances in the understanding of the orchestration of innovation networks (Dhanaraj & Parkhe, 2006; Ritala, Armila & Blomqvist, 2009; Nambisan & Sawhney, 2011; Hurmelinna-Laukkanen et al., 2011), the discussion on the topic is still a black box (Nilsen & Gausdal, 2017). More specifically, the authors identified a gap in the literature about the role and activities of actors in the city level. Few studies connected the regional dimension with the roles and activities of the orchestrators (Hurmelinna-Laukkanen et al., 2011; Pikkarainen et al., 2017), raising several challenges and opportunities to be considered by academics and managers.

The purpose of this paper is to study the organizational processes in co-creation with multiple stakeholders within the scope of innovation networks. It consists of analyzing the necessary adaptation of organizational processes and to structure a proposal of an integrated process.

This paper is a review article, an analysis of relevant articles in the areas of co-creation with multiple stakeholders, innovation networks, dynamic capabilities and organizational aspects linked to network organization which reflect on the main differences by relating them to the relevant literature.

Identification of related processes: Innovation development, knowledge integration/sharing, Co-evolution, Value Co-creation, Value Capture, Stakeholders capabilities, and elements of an integrated process in an innovation network.

Proposition of an integrated co-creation process with multiple stakeholders in an innovation network based on dynamic capabilities with the elements of literature and an analysis of the model variables. This process makes it possible, before reconfiguring the network itself, to create and to define the Project in an integrated manner. They also promote an evolution in the commitment, in the relationship and in the sharing of knowledge among the stakeholders and in the anticipation and evaluation by the stakeholders.

This study aims to present a theoretical analysis on the capabilities (at the organizational) and skills (at the individual level) of the hub organization (orchestrator) in an innovation network.

The authors conducted literature reviews on the orchestration of innovation networks; and networking capabilities.

This study presents a theoretical model and a research agenda.

In interorganizational relations, a central actor can stand out the role of intentionally creating, extracting and distributing value in the network, generating gains for all members. Literature recognizes this set of intentional and deliberate actions as the “orchestration” of resources in the network. Despite the increasing interest regarding the theme, the phases and specific capabilities for orchestration still lack further investigation.

Based on the perspective of technology supply chain, this study explores the effect of macroeconomic uncertainty regarding the spatiotemporal evolution of urban innovation networks to establish causality.

It collects patent trading data for 283 cities in China (2005–2017) and employs the spatial econometric model to investigate the causal relationship.

The regional transfer of advanced technology in China is rising sharply, and the innovation network based on patent trading is typically high-density, multi-direction and wide-spreading. Further, macroeconomic uncertainty has a negative effect on the scale of innovation flows and the absorptive capacity in eastern cities. However, it has no significant impact on the innovation network characteristics in developed cities. In contrast, macroeconomic uncertainty is detrimental for the absorptive capacity and node importance in inland and undeveloped cities.

As macroeconomic uncertainty increases, it is important to improve the quality of the urban innovation network with a better understanding of heterogeneity to promote further suitability innovation at the region-level.

This study highlights a clear and distinctive view that macroeconomic uncertainty not only directly affects the evolution of the urban innovation network but also indirectly affects the characteristics of other city nodes via the spatial spillover mechanism.