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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.

This study aims to examine the effect of supplier supply network (SSN) resources on buyer–supplier collaborative product innovation. The existing relevant studies from the network perspective are focused more horizontally on the mobilization of the firm’s entire supplier network resources and less vertically on the utilization of the individual supplier's supply network resources. Therefore, this paper takes a contingency perspective, regards the buyer as the receiver of a supplier’s supply network resources and, based on the theoretical motivation–opportunity–ability framework, explores the important motivation and ability factors that may weaken or enhance the product innovation value of the network resources.

This paper develops a new research model that assesses how the innovation utilization effectiveness of SSN resources is contingent on a buyer’s perception of the SSN effects and relative absorptive capacity on the SSN. A large sample questionnaire is designed and collected from 300 Chinese high-tech manufacturing firms and their suppliers. An empirical test is carried out in which multiple regression analysis is applied to 246 valid sample data.

The results show that SSN resources can significantly enhance buyer–supplier collaborative product innovation; however, the innovation utilization effectiveness is limited by the buyer’s relative absorptive capacity for the SSN and perception of the SSN effects. Specifically, if a buyer perceives that a greater innovation effect of a supplier’s supply network is correlated with an improved relative position in the SSN or with higher network structural equivalence and network cognitive congruence between the buyer and the supplier on the SSN, then the buyer will be more motivated and capable of transforming the SSN resources into actual product innovation value.

The research results provide useful guidance for firms to effectively mobilize their SSN resources to tap into the supplier innovation value for a sustainable competitive advantage.

This paper extends the research on supplier innovation value to the SSN field. Through linking dyadic and network levels of analysis, this paper reveals the value and uniqueness of product innovation utilization of a specific supplier’s supply network resources in the buyer–supplier relationship and provides a new research perspective for future studies on related issues.

This study aims to explore the influence of a region’s network location characteristics and indirect connections on its innovation capability. The aim is to assist regions in different network locations to use innovation resources to improve their innovation capabilities more efficiently.

This paper represents the Chinese regional innovation network using the gravity model. A theoretical framework is developed to explore the relationships between a region’s innovation capability and its network location. Hypotheses are tested using hierarchical regressions.

First, this paper finds that a region’s network centrality can promote its innovation capability. Second, a structural hole can positively adjust the relationship between a region’s centrality and innovation capability. Third, a region’s indirect connections can inhibit its innovation capability while exhibiting a U-shaped relationship in moderating centrality and innovation capability.

This study uses a multi-index system to construct an innovation network covering 29 regions in China. This network represents the innovation cooperation and overall situation of innovation in China. The paper is one of the first attempts at investigating the relationship between regional network locations and innovation capability. It is also the first attempt at testing the influence of indirect connections on a region’s innovation capability. The findings provide a new perspective on the factors influencing regional innovation capacity and a new way for regions to improve their innovation capability.

Previous studies examined the effect of inter-organizational collaboration relationships on organizational innovation. However, most focused on the configuration of the network from the static network perspective, and few examined the influence of network structure stability on an organization's exploratory innovation from the ego-network perspective. This study addresses this research gap by focusing on ego-network stability and its effect on an organization's exploratory innovation.

The empirical setting is the smartphone collaboration network from 2004 to 2017. We selected one-site schemes and panel data of patents from the Derwent Innovation Database. A negative binomial model with fixed effects was used to test our hypotheses.

The regression results show that an organization's ego-network stability has an inverted-U-shaped relationship with its exploratory innovation. Global cohesion of the focal organization's knowledge network moderates the process in such a way that when it is at a high level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability. However, local cohesion moderates in such a way that, at a low level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability.

This study highlights the importance of ego-network stability and its effect on the focal organization's exploratory innovation. It contributes to the literature on the relationship between ego-network stability and exploratory innovation by investigating the moderating role of global cohesion and local cohesion in knowledge networks.

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.

The experience of successful firms has proven that one of the most important ways to promote co-learning and create successful networked innovations is the proper application of inter-organizational knowledge mechanisms. This study aims to use a resource-action-performance framework to open the black box on the relationship between networking capability and innovation performance. The research population embraces companies in the Iranian automotive industry.

Due to the latent nature of the variables studied, the required data are collected through a web-based cross-sectional survey. First, the content validity of the measurement tool is evaluated by experts. Then, a pre-test is conducted to assess the reliability of the measurement tool. All data are gathered by the Iranian Vehicle Manufacturers Association (IVMA) and Iranian Auto Parts Manufacturers Association (IAPMA) samples. The power analysis method and G*Power software are used to determine the sample size. Moreover, SmartPLS 3 and IBM SPSS 25 software are used for data analysis of the conceptual model and relating hypotheses.

The results of this study indicated that the relationships between networking capability, inter-organizational knowledge mechanisms and inter-organizational learning result in a self-reinforcing loop, with a marked impact on firm innovation performance.

Since there is little understanding of the interdependencies of networking capability, inter-organizational knowledge mechanisms, co-learning and their effect on firm innovation performance, most previous research studies have focused on only one or two of the above-mentioned variables. Thus, their cumulative effect has not examined yet. Looking at inter-organizational relationships from a network perspective and knowledge-based view (KBV), and to consider the simultaneous effect of knowledge mechanisms and learning as intermediary actions alongside, to consider the performance effect of the capability-building process, are the main advantages of this research.

This paper aims to shed light on how offshore wind park business networks can orchestrate dynamic capabilities to enable innovation for the competitive advantage of renewable offshore wind energy.

The research is based on a qualitative multiple-case study of operation and maintenance activities in offshore wind parks, starting in June 2014 with a pilot qualitative case study and the main qualitative multiple-case research conducted via in-depth interviews with 20 enterprises. The preliminary findings were presented for the qualitative triangulation of comments in a seminar in May 2015.

The findings explain the need for collaboration across the business network through the use of an open innovation platform for orchestrating dynamic signature capabilities in combination with ordinary capabilities. Both locally distributed leadership and central leadership in knowledge creation are necessary ingredients. The model developed from the research findings shows the need to change the competitive advantage criteria within business networks to VRIS (valuable, rare, imitable, substitutable) in contrast to the traditional criteria for individual enterprises of VRIN (valuable, rare, imperfectly imitable, non-substitutable).

The research is focused on offshore wind park business networks, and therefore, the generalizability of this qualitative case study to other contexts can be limited. Further research is thus needed to verify the findings.

A three-fold contribution is made to the understanding of the integrated combination of orchestrating dynamic capabilities in the offshore wind energy sector. Business networks, academia and policy bodies are given a model for enacting the competitive advantage of renewable offshore wind energy for the benefit of society.

This paper aims to identify the influence of innovation network and technological learning on innovation performance of high-tech cluster enterprises.

Using a questionnaire, data are collected from Dalian High-tech Industrial park in China. In addition, structural equation model is used to identify the influence of innovation network and technological learning on the innovation performance of high-tech cluster enterprise.

The findings of this study show that the centrality of network location and the strength of the network relationship have a direct positive effect on technology acquisition, technology digestion and technology exploit of high-tech cluster enterprises. Meanwhile, technology acquisition has a direct positive effect on technology digestion, technology digestion has a direct positive effect technology exploit, and technology exploit has a direct positive effect innovation performance of high-tech cluster enterprises.

To improve innovation performance, high-tech cluster enterprises should not only nurture and optimize innovation networks but also improve technological learning ability.

This paper empirically supports the significant influence of innovation network and technological learning on innovation performance. While the results provide guidance for researchers and practitioners, it also adds value to innovation-related research.