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Dyadic multi-dimensionality informs the variation that exists within and between network ties and suggests that ties are not all the same and not all equally strategic. This chapter presents a model of dyadic evolution grounded in dyadic multi-dimensionality and framed within actor-level, dyadic-level, endogenous, and exogenous contexts. These contexts generate both strategic catalysts that motivate network action and bounded agency that may constrain such network action. Assuming the need to navigate within bounded agency, the model highlights three strategic processes that demonstrate how dyadic multi-dimensionality underlies the evolution of strategic network ties.

In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks.

This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence.

The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout.

The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed.

Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.

The purpose of this paper is to provide an overview of the available insights regarding interorganizational network evolution. The research questions being addressed are as follows: What is the nature of interorganizational network evolution? And what causes interorganizational network evolution? The review hence focuses on the nature of interorganizational network evolution (at the ego-network level and whole-network level) and the causes of interorganizational network evolution (firm-related causes and environmental causes). This paper highlights relevant gaps in the existing literature on interorganizational network evolution while outlining a research agenda by identifying key research questions and issues requiring further scholarly contributions to stimulate research in this field.

An extensive review of scholarly peer-reviewed English language journal articles was conducted in the subject areas of economics, sociology, business and management (including entrepreneurship) while excluding articles in the domain areas of computer science that dealt with computer networks and the health field that addressed neural networks to obtain articles on interorganizational network evolution for the period 1970-2019. Various journal databases such as EBSCO, ScienceDirect (Elsevier), Emerald, JSTOR and ABI/INFORM and Ebook Central on ProQuest were used to extract relevant articles using specific keywords.

To better understand this phenomenon of interorganizational network evolution, there is a need for future studies to focus on the less researched areas such as the “nature of evolution” of EINR1, EINR3 and EINR4 and the “causes of evolution” of FRC3, FRC5, FRC7 and FRC8. Further, over the years, in comparison to the evolution of interorganizational network relationships (EINR), fewer works have considered the evolution of overall interorganizational network structure (EINS). The research studies on environmental causes (EC) have been less in number in comparison to firm related causes (FRC), and this could be an area for further research. Also, studies on interorganizational network evolution have not examined the impact of FRC1 on EINR 3 and only a few studies have examined the impact of FRC1 on EINR1 and EINR4. Less attention has been given to the impact of FRC2 on EINR1, EINR3, EINR4 and EINS. Additionally, the impact of FRC3 on EINR1, EINR3 and EINS needs more in-depth examination. The impact of FRC4 on EINR4; FRC5 on EINR1, EINR2 and EINR4; FRC6 on EINR1 and EINS; and FRC7 and FRC8 on all forms of “nature of interorganizational network evolution” requires more research work. Finally, the impact of EC on EINR3 and EINR4 is also a less researched stream in the literature needing more scholarly contribution to better understand the phenomenon under consideration in this study. Some of the least explored theoretical lenses and relevant questions that can be addressed using these lenses to advance research on network evolution have also been discussed.

The main contribution of this paper is that it provides a comprehensive literature review, collating the dispersed knowledge on interorganizational network evolution – nature of evolution and causes of evolution, identifying areas that require further research attention for the development of this domain.

Mobile peer‐to‐peer communications is an essential phase in the evolution of mobile communications technologies, motivating this research which aims to focus on how established industry stakeholders and new entrants can adapt themselves to the new situation.

Based on existing literature, the authors identified three distinctive evolution paths for mobile peer‐to‐peer communications and developed an analysis framework for their comparison. The authors validated the analysis by conducting a questionnaire study among domain experts, and analyzed its results using statistical analysis.

Internet‐driven evolution has high value proposition, is profitable and has subscription fees as an important revenue model. Telecom‐driven evolution creates value, leverages markets, leverages competence, is likely to encounter regulatory intervention and benefits all customer segments. Proprietary evolution has a successful revenue model, results in alliances of competitors and is competence‐enhancing to mobile device vendors.

Future work consists mainly of analyzing quantitatively the implications of the new technologies when they become readily available and evaluating the value analysis framework in other applicable cases.

Internet‐driven evolution enables new business opportunities to independent service operators and equipment vendors by enabling opportunities in profiting from sales of advanced devices and networks. Telecom‐driven evolution benefits mostly incumbent mobile network operators. Proprietary evolution enables limited competition against incumbent actors by independent service operators.

This study is one of the first journal publications on mobile peer‐to‐peer communications from a holistic techno‐economic point of view, beneficial to both academics and practitioners.

Clarifying the risk evolution mechanism of housing construction for work-safety management is essential. Existing studies have inadequately discussed the risk-accumulation process in housing construction. Therefore, this study aimed to use the complex network theory and risk allocation mechanisms to explore the evolution of risk factors.

The authors analysed a database of housing construction accidents in China from 2015 to 2020 to identify risk factors. Moreover, the causal relationship between risk factors was determined through a systematic analysis of the logical sequence of risk factors. A complex network was used to construct a risk network for housing construction accidents (RNHCA).

The risk matrix method was used to define the factor risk threshold, and a risk value was assigned based on the correlation between risk factors. This contributes to the examination of the evolution mechanism of risk networks in the process of risk factor transmission. The case verification results show that the RNHCA quantitative assessment model can better evaluate the system risk status of housing construction accidents. Furthermore, this model can identify the key risk factors and risk chains with high risk in the evolution of the risk network.

Accident investigation reports need to be classified and processed to analyse the evolution law of risk networks under different scales of construction project, such as high-rise buildings, middle-rise buildings, and low-rise buildings.

This study clarified the risk evolution process of complex systems in housing construction and provided a new method for analysing accidents.

This study clarifies the risk value allocation of risk factors in the transmission process and reveals the process of risk factor evolution in housing construction. This study explains the individual risk factors that form a systemic risk through the transmission chain. Moreover, this paper clarified the transformation relationship between system risk and accidents. The paper also provided a new perspective for risk analysis.

The paper aims to provide a methodology by which organisational knowledge can be extracted and visualised dynamically over time, providing a glimpse into the knowledge evolution processes that occur within organisations.

Recursive analysis of email interactions is offered as a case to account for the knowledge structure evolution related to the different programs of international non-governmental organization (INGO). Several methods are used: analysis of the network expansion to see whether the process is random or uniform is performed, visualisation of the network configuration changes throughout studied time period; and the statistical examination of network formation.

The results of the presented study indicate that content structure of electronic knowledge networks exhibits hierarchical and centralised tendencies. The social network analysis results suggest that INGO exhibits non-hierarchical and decentralized structure of the individuals contributing to the discussion lists.

By providing the means to carry out network evolution analysis of content structure dynamics and social interactions, the presented work provides a means for probabilistically modelling patterns of organisational knowledge evolution.

The approach allows the exploration of the dynamics of tacit to explicit knowledge, from individual to the group and from informal groups to the whole organisation.

By displaying the large collection of the key phrases that reflected the evolution of the organisational knowledge structure over the time, organisational emails are placed in meaningful context explaining the language of the organisation and context of knowledge structure evolution.

Concerning that limited explanation exists examining the function of corporate governance in trust processing within entrepreneurial network development, the purpose of this paper is to explore trust evolution and the role of corporate governance in an entrepreneurial network.

This paper makes an innovative exploration based on the case study of NVC Lighting Holding Limited.

It proposes that in the initial period of network relationship which is based on entrepreneur’s individual social network and embodies sole social network embeddness, entrepreneurial network relies more on affective trust than contractual trust. When stepping into extending period of network relationship which reflects separate embeddedness of social and market network, however, entrepreneurial network has an equal reliance on both affective trust and contractual trust. With further development, when ushering in the phase of maturity which undergoes superimposing embeddedness of both social and market network, entrepreneur network inclines to rely more heavily on affective trust than contractual trust. During the whole process, it can be found that the reliance of entrepreneurial network on trust has the tendency to transfer from affective trust to contractual trust. Furthermore, decreasing of equity ratio of founders and strengthening of controlling right heterogeneity in the corporate governance have facilitated the transfer process and the entrepreneurs’ authority has restraining effect on the evolution of the process.

Through case study, this paper presents the trust evolution process in different stages of entrepreneurial network. Another important theoretic contribution of this paper is that it reveals the function of corporate governance in trust processing within entrepreneurial network development.

In the evolution process of building construction accidents, there are key nodes of risk change. This paper aims to quickly identify the key nodes and quantitatively assess the node risk. Furthermore, it is essential to propose risk accumulation assessment method of building construction.

Authors analyzed 419 accidents investigation reports on building construction. In total, 39 risk factors were identified by accidents analysis. These risk factors were combined with 245 risk evolution chains. Based on those, Gephi software was used to draw the risk evolution network model for building construction. Topological parameters were applied to interpret the risk evolution network characteristic.

Combining complex network with risk matrix, the standard of quantitative classification of node risk level is formulated. After quantitative analysis of node risk, 7 items of medium-risk node, 3 items of high-risk node and 2 items of higher-risk nodes are determined. The application results show that the system risk of the project is 44.67%, which is the high risk level. It can reflect the actual safety conditions of the project in a more comprehensive way.

This paper determined the level of node risk only using the node degree and risk matrix. In future research, more node topological parameters that could be applied to node risk, such as clustering coefficients, mesoscopic numbers, centrality, PageRank, etc.

This article can quantitatively assess the risk accumulation of building construction. It would help safety managers could clarify the system risk status. Moreover, it also contributes to reveal the correspondence between risk accumulation and accident evolution.

This study comprehensively considers the likelihood, consequences and correlation to assess node risk. Based on this, single-node risk and system risk assessment methods of building construction systems were proposed. It provided a promising method and idea for the risk accumulation assessment method of building construction. Moreover, evolution process of node risk is explained from the perspective of risk accumulation.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

This chapter aims to identify the main determinants that define the architectural properties of network emergence and significantly influence the dynamics underlying network evolution in time. The identification and analysis of these determinants, as well as the dynamic processes tied to them, allows to appreciate the competitive bases and consequences of network morphology. To this purpose, using a complex systems perspective as an integrative conceptual approach, we represent networks as complex dynamic systems of knowledge and capabilities. We perform a comparative in-depth analysis of the processes underlying the emergence and evolution of STMicroelectronic's global network and of Toyota's supplier network in the US so as to allow an elucidatory empirical assessment of the theoretical representation elaborated in the article.