scholarly journals Social Network Analysis and the Study of University Industry Relations

Author(s):  
Fernando Cabrita Romero

The aim of this chapter is to give an overview of the use of social network analysis in the study of university industry relations. The structure of networks can be analyzed through the lens of social network analysis. This methodological approach is briefly described, and its fundamental concepts are presented. The chapter reviews the applications of this approach on the study of university industry relations. Different structures in the relations may result in different innovation outcomes, and the use of SNA may be particularly useful to understand differential outcomes. This chapter is based on a review of available literature on the topics. The chapter aims at systematizing the information and knowledge related to the application of SNA on university industry networks, highlighting the main research pathways, the main conclusions, and pointing to possible future research questions.

Author(s):  
Fernando Cabrita Romero

The aim of this work is to give an overview of the use of social network analysis in the study of university industry relations. The structure of networks can be analysed through the lens of Social Network Analysis. This methodological approach is briefly described and its fundamental concepts are presented. The paper reviews the applications of this approach on the study of university industry relations. Different structures in the relations may result in different innovation outcomes, and the use of SNA may be particularly useful to understand differential outcomes. This work is based on a review of available literature on the topics. The paper aims at systematizing the information and knowledge related to the application of SNA on university industry networks, highlighting the main research pathways, the main conclusions and pointing possible future research questions.


2011 ◽  
Vol 474-476 ◽  
pp. 1007-1011
Author(s):  
Bing Wu ◽  
Jun Ge ◽  
Wen Xia Xu

This study is a productivity review on the literature gleaned from SSCI, SCIE databases concerning social network analysis in knowledge management research. The result indicates that the number of related literature is still growing especially in recent two years. The main research development country is the United States, then England and German, and from the analysis of the subject area, Information Science & Library Science is the most popular subject. Concerning source title, Knowledge Management Research & Practice is in the priority. Moreover the research focuses on this topic are mainly in close relationship with knowledge network. Typical references were analyzed in detail, including limitations and future research.


2015 ◽  
Vol 19 (01) ◽  
pp. 1550013 ◽  
Author(s):  
MIGUEL LINHARES PINHEIRO ◽  
CÂNDIDA LUCAS ◽  
JOSÉ CARLOS PINHO

Purpose: This work tests the use of social network analysis (SNA) as a new methodological approach to better understand university–industry (U–I) relationships in the context of research and development (R&D) cooperation networks for innovation. Methodology: Following a thorough review of the literature on U–I links from the last two decades, focusing on methodologies, SNA was applied to data on work relationships, obtained through a survey of the participants from University and Industry, engaged on a FP7 project. Findings: SNA is suggested as a useful and relevant tool to understand and examine U–I R&D cooperation at both personal and organizational levels. In support of this statement, several examples and an empirical illustration are provided. The assessment of the processes underlying the establishment and maintenance of U–I relationships within R&D cooperation with SNA suggested that interpersonal relationships are crucial for the establishment of successful cooperative activities. Unlike other tools, SNA allows the recognition of preferential relationships between institutions, and reveals asymmetries from within the U–I R&D network. Originality/value: This paper addresses the interactional dynamics embedded in U–I links. Most studies regarding U–I links focus on describing the downstream processes associated with technology transfer and commercialization. This study applies SNA to understand the ex ante establishment and maintenance of U–I relationships within R&D cooperation. The high volatility of these relationships, in view of the importance of the expected outcomes, justifies the need to understand the fundamentals of successful cooperation.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy

PurposeApplications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.Design/methodology/approach95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.FindingsA significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.Originality/valueCloser collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.


Author(s):  
Eun-Joo Kim ◽  
Ji-Young Lim ◽  
Geun-Myun Kim ◽  
Seong-Kwang Kim

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.


Author(s):  
Maria Isabel Escalona-Fernandez ◽  
Antonio Pulgarin-Guerrero ◽  
Ely Francina Tannuri de Oliveira ◽  
Maria Cláudia Cabrini Gracio

This paper analyses the scientific collaboration network formed by the Brazilian universities that investigate in dentistry area. The constructed network is based on the published documents in the Scopus (Elsevier) database covering a period of 10 (ten) years. It is used social network analysis as the best methodological approach to visualize the capacity for collaboration, dissemination and transmission of new knowledge among universities. Cohesion and density of the collaboration network is analyzed, as well as the centrality of the universities as key-actors and the occurrence of subgroups within the network. Data were analyzed using the software UCINET and NetDraw. The number of documents published by each university was used as an indicator of its scientific production.


Author(s):  
Mohana Shanmugam ◽  
Yusmadi Yah Jusoh ◽  
Rozi Nor Haizan Nor ◽  
Marzanah A. Jabar

The social network surge has become a mainstream subject of academic study in a myriad of disciplines. This chapter posits the social network literature by highlighting the terminologies of social networks and details the types of tools and methodologies used in prior studies. The list is supplemented by identifying the research gaps for future research of interest to both academics and practitioners. Additionally, the case of Facebook is used to study the elements of a social network analysis. This chapter also highlights past validated models with regards to social networks which are deemed significant for online social network studies. Furthermore, this chapter seeks to enlighten our knowledge on social network analysis and tap into the social network capabilities.


Author(s):  
Lucio Biggiero

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.


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