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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.

As foreign direct investment (FDI) plays an important role in economic globalization. This paper examines the structural features of the global FDI network based on FDI flows data and changes in the position of countries within the network.

In order to study the structural characteristics of the global FDI network and the status and changes of countries in the global FDI network, the authors build the investment network and apply the QAP (Quadratic Assignment Procedure) analysis to examine the evolutionary characteristics of the network and its influencing factors.

The global FDI network becomes more interconnected and has a clear “core-periphery” structure. The network connections and volumes have increased dramatically and most countries spread their assets across multiple countries, while only a handful of countries have concentrated investments. The topological structure of the global FDI network has changed noticeably, although this process has been slow and stable and countries in the core position have remained largely intact. The authors find that trade relations between countries, geographic distance and differences in economic size, income levels and institutional environments all have a significant impact on the global FDI network.

Although we find some valuable results, some aspects need further investigation. For example, how a country uses the investment network to boost its economy and how the different industries in the investment network change over time. It is important to get the industry-level details to understand the impact of the global investment network from a government's perspective.

FDI affects the distribution of international capital and contributes to the development of the global economy. Therefore, it is important to study the characteristics of the global FDI network and its development patterns. With more understanding about the network as well as its evolutionary pattern, the government can possibly carry out some policies to promote direct investments as well as economic development.

All countries should actively engage in international direct investments and strengthen their economic ties. At the same time, they can put more emphasis on inward or outward FDI based on their own level of economic development to better establish the circulation channel for domestic and international capital.

This paper examines foreign direct investments through the lens of a global network. In contrast to traditional bilateral studies, this paper focuses on the network structure and evolution, reflecting the dynamics of the entire direct investment system as well as the changing positions of participating countries.

The purpose of this paper is to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network, the status and roles of each province in China’s inter-regional innovation correlation network and the influencing factors of China’s inter-regional innovation correlation effect.

Based on the patent data of 30 provinces (autonomous regions and municipalities) in China from 1991 to 2017, social network analysis was used to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network and the status and roles of each province in China’s inter-regional innovation correlation network. Furthermore, the QAP method was used to find out the influencing factors of China’s inter-regional innovation correlation effect.

China’s inter-regional innovation correlation is becoming increasingly close and inter-regional innovation correlation network is becoming increasingly stable. Jiangsu, Zhejiang, Beijing, Shanghai, Guangdong and other eastern coastal provinces are at the core in the inter-regional innovation correlation network, while the western regions are marginal actors. China’s regional innovation development territory can be divided into four blocks, namely, “bidirectional spillover block,” “net spillover block,” “main beneficial block” and “net beneficial block,” and gradient transfer mechanism is obvious between the blocks. The geographical adjacency and similarity in regional industrial structure, urbanization level and government attention degree have significant positive effect on China’s inter-regional innovation correlation effects.

This paper only uses patent application as a measure of regional innovation level to analyze inter-regional innovation correlation effect. Meanwhile, this paper carries out an empirical study only from the provincial level and not from the city level.

This paper provides the practical basis for further promoting the coordinated development of regional innovation and promoting the construction of regional innovation systems with different characteristics.

This paper contributes to understand the status and role of each province in inter-regional innovation correlation network. Meanwhile, this paper also helps to understand the influence of the proximity and external environmental factors on inter-regional innovation correlation effect.

The purpose of this paper is to illustrate the use of Social Network Analysis (SNA) to map information and knowledge flow in six virtual project teams with members of diverse cultures in private and public sector companies in different sectors.

Due to the area of research, the authors supplemented the in‐depth interviews with an embedded SNA questionnaire and two stage analysis.

The SNA findings demonstrated that network ties are useful predictors of how information and knowledge flows in virtual project teams and can be better indicators than formal project structures. assessment of participants' prestige, activity and influence and their generic formal team functions, thus leadership, member and support roles.

SNA does not yield information about causal factors, context or history of the team contributing to the current team relationships.

SNA as a method in this study delivers information on diverse members' influence, prestige and specific team member‐related brokerage roles. It highlights what boundary‐crossing knowledge sharing activities they engage in and maps the knowledge and information flows between members of the virtual project teams within the companies.

The multi‐method research design represents a sound approach to target knowledge management in virtual project environments in international contexts.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

The purpose of this paper is to study whether the use of a shared study space played a role in shaping graduate students’ social networks by exploring how the copresence in space was related to the structure of friendship and advice networks. The authors first proposed two concepts of spatial copresence: measured spatial-temporal copresence and perceived copresence. The authors then examined the role of copresence through a case study of a shared study space occupied by 27 graduate students in the same department.

Copresence relations were first constructed through a six-month room access history data set and self-reported data to examine whether measured spatial-temporal copresence was consistent with perceived copresence. Friendship and advice network relations were then analyzed with copresence, social media connections, class project collaboration relations and social homophily (nationality, gender, cohort) through quadratic assignment procedure (QAP) and MQAP analysis.

The authors found that students who used the shared study space more often reported more friendship and advice ties. The perceived copresence and the measured spatial-temporal copresence were highly correlated. Copresence relations, as measured by survey and room access history, were both significantly correlated with advice relation, which was associated with perceived social support.

This study contributes to the debate about whether “space” continues to play significant roles in graduate students’ social networks in the context of flexible learning environments. The results also reveal new directions for research methods in studying spatial proximity in flexible settings.

The governance of information technology outsourcing (ITO) has been identified as an essential determinant for ITO success. Prior studies have shed light on effective governance structures in different organizational contexts. This study aims to advance this prior knowledge by exploring how interpersonal networks, as an important aspect of such context, reflect and influence ITO governance.

A single case study was conducted from a vendor’s perspective in an ITO dyad. Social network analysis was leveraged to reveal the interpersonal networks, with whole-network analysis on 24 team members in an ITO vendor company. In addition, open-ended interviews with six selected team members were utilized to identify the perceived governance structure.

The findings of this study suggest certain features of interpersonal networks, i.e. network density and cross-network comparison, can reflect governance structure in multiple aspects. Meanwhile, the authors also argue that interpersonal networks can influence the form of governance structure.

As a single case study, the context of the research site cannot be ignored in the inference of findings. To increase the confidence for further generalization, future empirical studies are needed especially in contrasting sites, such as ITO relations based on network governance.

This study associates intra-organizational characteristics of the vendor to the inter-organizational governance structure of the ITO relationship. It also provides an innovative methodology for both researchers and practitioners to assess ITO governance structure.

Focusing on the sociological clarification based on structural pluralism, this study explores the degree to which social media users who comment on the news posts of local newspapers use uncivil remarks and words that reflect their moral foundations.

This computer-assisted data collection produces three types of datasets that include numerous social media comments. To explore the association between moral foundations and incivility, both quadratic association procedure (QAP) and multiple regression QAP (MRQAP) are implemented.

The findings suggest that social media users who comment on the news posts of urban-located newspapers tend to use more uncivil words compared to social media users who comment on the news posts of suburban and rural-based newspapers. Individuals who comment on the news posts of urban-based newspapers tend to show a wider range of moral foundation spectrums than those who comment on the posts of rural and suburban newspapers. Lastly, there are significant associations between moral-vice components and incivility in response to urban- and suburban-located newspapers' social media posts.

The employed bag-of-words may not completely capture incivility given that social media users can use nuanced and metaphoric terms instead of explicitly uncivil terms. Even though this study systematically selected local newspapers' social media accounts, the contextual factors of other newspapers in politically slanted communities could be different.

The findings of this study provide meaningful and practical implications for journalists and news reporters. The inherent rudeness and aggressiveness of social media users can drive them to use uncivil and moral-harm words against a particular person or group.

Under the circumstance that fake news and politically slanted news content are widely distributed in the United States, social media users may easily express negative emotions toward news stories or the journalists who post the stories.

Structural pluralism particularly specializes in explaining why and how the contextual factors of news stories differ depending on community complexity. Building on the reasoning of structural pluralism in the social media context, this study investigates the degree to which social media users who comment on the news posts of local newspapers employ uncivil remarks and moral foundation words.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2020-0522.

In large organizations, space planning relies on workgroup leaders to indicate spatial adjacency preferences. However, many factors affect workgroups’ adjacency preferences, and it is not clear how the choices are made. This paper aims to explore whether the adjacency preferences are influenced by the collaboration relationship or constrained by the organizational structure.

The authors studied a large company’s spatial adjacency planning with an in-depth analysis of its formal organizational structure and collaboration network. A sample of 183 managers was surveyed regarding groups with whom they want to be spatially adjacent and groups with whom they mostly interact. The data enabled us to test three structural factors related to adjacency preference: department affiliation, workgroup’s prestige and collaboration relation. The authors used the quadratic assignment procedure analysis to examine the correlations between network matrices.

The results suggest that department affiliation and collaboration relations are significantly correlated to adjacency preferences. The authors did not find evidence supporting the notion that a workgroup’s prestige affects the preference. Among the three factors, collaboration relation best predicts the preference, which echoes Pena et al.’s (1977) argument that space planners should look into how groups function, rather than merely following the organizational chart.

To the best of the authors’ knowledge, this research was the first to explore the choice of spatially adjacent workgroup through a detailed network analysis of the formal structure, work collaboration relations and other group-level characteristics. The findings have noteworthy cross-disciplinary implications, given that spatial proximity can be taken as a human resource management strategy to facilitate the overall interactions between workgroups.

Studies of gang violence typically use police reports to investigate the structure of gang conflict, but overreliance on a singular data source could impede crime control efforts. Extending networked criminology, this study aims to explore what court records reveal about the directionality of gang conflicts.

Controlling for the presence of a civil gang injunction (CGI), the authors use multivariate quadratic assignment procedure regression models to disentangle factors thought to account for structural patterns of gang violence mapped from 933 prosecutions involving 307 gangs associated with violent conflict affecting the City of Los Angeles (1998–2013). Specifically, the authors compare competitive advantage to the explanatory power of turf proximity.

One measure of turf proximity outperforms all other explanatory factors – gangs with turf centrally positioned in a turf adjacency matrix are significantly more likely to launch attacks, be victimized and exhibit the highest levels of imbalance in their violent involvements. Regarding competitive advantage, the number of cliques and level of internal conflict are significant. Finally, being subject to a CGI is associated with initiating violence.

Court cases offer a feasible alternative to police data when investigating patterns of intergroup street gang violence.