Search results

Currently, China’s manufacturing industry chain still faces the danger of chain breakage due to the persistent “lack of technology” issue. The definition and detection of key nodes in the industry chain are significant to the enhancement of the stability of the industry chain. Therefore, detecting the key nodes in the manufacturing industry chain is necessary.

A complex network based on the links amongst listed manufacturing enterprises is built, and the authors analyse the network’s basic characteristics and vulnerability, taking into account the impact of scientific and technological innovation on the stability of the industry chain.

It is found that the high structural characteristic of midstream nodes in the naval architecture and marine engineering equipment industry chain determines their importance to stability, and the key status of upstream nodes is reflected in the weakness of technological innovation. The upstream nodes should focus on improving their independent innovation and R&D capability, whilst the midstream nodes should maintain a close supply–demand cooperation relationship.

The key node detection model for industry chain stability is constructed by considering various factors from the perspective of network and technological innovation. Empirical study is conducted to verify effectiveness of proposed method.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

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.

In the context of a retailer with an international supply network, this paper develops theories of (a) how both stability and strong ties in an international supply network combine to yield a resource base that enables the development of flexible relationships with suppliers, (b) how stability and relationship flexibility in the international supply network of a retail reseller may in turn be driven both by the international diversity and by the density of the retailer’s supply network in a product category, and (c) how both the international diversity and the density of a retailer’s supply network may directly affect the likelihood of a retailer developing flexible relationships with its supplier. In doing so, this paper develops and presents six hypotheses and discusses some approaches to measurement of the underlying constructs and testing the hypothesized effects.

The authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the characteristics of a firm's whole network and ego-network in a transnational coopetition network influence network performance.

The authors analyzed the public news of the sample firms about the coopetition by structural content analysis to build the coopetition networks and access to data on the competitive actions of firms. Then, to measure the variables associated with the coopetition network, such as the structural hole, centrality and ego-network stability, the authors use UCINET 6 that is a widely used piece of software for social network analysis to establishing five undirected binary adjacency matrices.

The authors find that a firm's competitive aggressiveness mediates the relationship between a firm's whole network position and network performance that emphasizes the need for integrating competitive dynamics research and coopetition research and shows how valuable insights can be gained through such integration. And the interaction of structural hole and centrality impacts competitive aggressiveness and network performance, and the interaction is different under high and low ego-network stability. The integration of whole network and ego-network literature studies provides new insights into firm network literature.

In the process of cooperation, firms should consider whether they can occupy the structural hole and center as important indicators for partner selection. Too stable relationship will prevent firms from obtaining new resources. Firms should weigh the period of cooperation according to specific situation.

These results indicate that ego-network stability, as an important complementary characteristic of coopetition network, has a significant synergistic effect with structural holes and centrality on competitive aggressiveness and network performance. And these findings expand the current literature on the relationship between characteristics of network, competitive aggressiveness and network performance.

The purpose of this paper is to develop a methodology for the design of cellular neural networks with interconnection topologies optimized and suitable for spatially distributed implementation.

The authors perform combinatorial optimization on the neural network's topology to obtain a sparser network, in which the links between the components of the network that reside in different physical locations are minimized. The approach builds on existing computationally efficient tools for the design of cellular neural networks and uses the concept of the network's stability parameters to assess the performance of the network prior to testing.

It turns out that the sparser cellular neural networks thus produced exhibit performance that can be on par with that of networks with full connectivity, and that for implementations of modest size, communication delays are not that significant to affect the stability of the dynamical system.

The novelty of the proposed approach lies in the formulation of the combinatorial optimization problem in a way that trades‐off network performance for communication overhead, and the use of this method for the physical implementation of associative memories across different interconnected processors.

This study aims to analyze the dynamics of the institutional change and institutional stability undergone by strategic networks (SNs) in the pharmaceutical industry.

The authors performed a case study with four Brazilian SNs which followed different patterns of institutional change and institutional stability. Twenty network managers and network members from the pharmaceutical industry were interviewed, and documents were analyzed.

The results show how and why institutions changed or remained the same. More specifically, exogenous shocks can negatively impact the competitive environment influencing institutional change in SNs. Moreover, endogenous shocks may prevent institutional change and stimulate institutional stability. Continuous interaction between institutions and SNs is the key to institutional change, especially if public and private policies are considered a source of political institutions.

Research has highlighted the endogenous influence of SNs on firms in selecting their partners and arranging their positions in the SNs, but little attention has been paid to how SNs themselves respond to institutions or promote institutional change. This study explains how and why change fails at the network level, additionally pinpointing the main sources of the institutional change and inertia in SNs. As such, network members may use different strategies to stimulate institutional change or stability according to their interests.

By applying models of social and economic networks to financial institutions, the purpose of this paper is to address the issues of how policy makers can promote financial network stability and social efficiency.

The authors characterize the decentralized network formation of financial institutions in three stages through which institutions choose to become member banks connected to a central bank, bank-holding company subsidiaries or non-banks. Financial institutions choose one of the three roles in an endogenous process by considering the effects of sharing shocks among the members of the network. In the model, there is a social-welfare-maximizing government regulator at the center of the network.

The authors show that the stable equilibrium network is not always the efficient network, so the central authority must use policy instruments to ensure that the stable equilibrium network is as close as possible to the efficient network.

To obtain the theoretical results, the authors make assumptions about the utility function and risk aversion of a financial institution, as well as about the costs of network formation. These assumptions might need to be relaxed to bring the model closer to real-world institutions.

The results suggest that regulators must try to set their policy variables to make the efficient network as close as possible to the stable network.

The contribution is to incorporate concepts from social network theory into the modeling of financial networks. The results may be of use to regulators in maintaining the stability of the financial system.

This study aims to explore the effect of competitive aggressiveness on firm performance and the moderating effect of firm 2019s ego-network structures in the international coopetition network.

From the perspective of strong cooperation of the global automobile industry in recent years, this study uses the global automobile firms in Factiva database as samples to test hypotheses using the least squares dummy variable (LSDV) model.

This study finds that there is different relationship between the number and variety of competitive actions and firm performance. In addition, ego-network structures have different coefficients for the number and variety of competitive actions.

The conclusions provide theoretical support and policy suggestions for firms to develop effective competitive strategies according to ego-network structures in the international coopetition network.

This study draws on recent actor-network theory (ANT) literature to provide a nuanced understanding of the effect of time on activity networks in urban spaces. It investigates the role of time in multiplying these networks and producing urban change, which is limited in similar ANT-related research.

This ethnographic study of a cul-de-sac square within a housing project in the suburb of Dahiyat Al-Hussein in Amman, Jordan, documents the changes in its activity networks when comparing the 1990s with 2019. Data were collected through interviews and site observations covering the two time periods to investigate the different activities that occurred constantly over time, which reflect the temporal network stabilisation within the square.

The findings demonstrate the profound effect time has on the stability of activity networks related to playing, observing, walking, vending and their interrelations. Their overlaps and conflicts with each other and with other networks in the space were observed. Unpacking the stability of activity networks and their interrelations demonstrates the change in their actor relations and temporalities over time. This is significant in understanding urban change.

The study investigates the importance of time in recognising and extending the multiplicity of urban activities, which suggests new ways of understanding urban change. This exploration highlights new possibilities for creating more adaptable spaces according to residents' long-term needs.