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Trabajo presentado al 7th Biennial International Conference on University, Industry & Government Linkages celebrado en Glasgow (UK) del 17 al 19 de Junio de 2009. ; In recent years, considerable attention has been paid to the effectiveness of knowledge transfer processes between academia and industry. Although there is growing evidence that the characteristics of individual researchers are important when explaining cases of successful transfer, few studies have taken the individual researcher as their unit of analysis. This study aims to use social network theory techniques to gain a better insight into knowledge transfer processes. In particular, we study how the characteristics of ties among individuals, and the interdisciplinary and pervasiveness of research affects the diversity of knowledge transfer activities. To this end, we conduct an empirical study among researchers in the field of nanotechnology. This sector is chosen for its interdisciplinarity and its expected pervasiveness. Data was collected using a survey conducted in Spain and in The Netherlands, allowing us to correct for some environmental and context effects. ; This research has been partially supported by a grant from the Spanish National Research Plan (Project ref.: SEJ2005-05923/EDUC) ; Peer reviewed

The COVID-19 pandemic is a global health problem that has given the greatest challenge for humanity today. This paper discusses the social changes that have taken place on social network density after COVID-19 hit the world. The social network density discussed is based on Social Network Theory according to the current situation that has hit Malaysia. The methods used are based on document analysis and case analysis from official documents issued by the government. The analysis revealed that the COVID-19 pandemic has had a devastating impact on human health, social and economic. However, seen from the standpoint of social networks, the COVID-19 pandemic has led to the emergence of densities in social networks due to increased informal sector involvement in the formation of social networks. This means that, as the number of social networks is formed, the density of social network will increased as defined by Social Network Theory.

What are organizations? Where do they come from? How are they transformed and adapted to new situations? In the digital age and in the global network society, traditional theories of the organization can no longer answer these questions. Based on actor-network theory, this book explains organizations as flexible, open networks in which both human and non-human actors enter into socio-technical assemblies by constantly negotiating and re-negotiating programs of action. Organizations are not macro social structures or autonomous systems operating behind the backs of individuals. Instead, they are scalable actor-networks guided by network norms of connectivity, flow, communication, participation, authenticity, and flexibility.

What are organizations? Where do they come from? How are they transformed and adapted to new situations? In the digital age and in the global network society, traditional theories of the organization can no longer answer these questions. Based on actor-network theory, this book explains organizations as flexible, open networks in which both human and non-human actors enter into socio-technical assemblies by constantly negotiating and re-negotiating programs of action. Organizations are not macro social structures or autonomous systems operating behind the backs of individuals. Instead, they are scalable actor-networks guided by network norms of connectivity, flow, communication, participation, authenticity, and flexibility.

The purpose of this primer is to provide executives with an overview of social network research as it relates to individual, group, and organizational learning; innovation; and performance. Too often, when social networks are mentioned, managers think of Internet sites such as LinkedIn, Facebook, or MySpace. While social networking Web sites are part of the landscape of social network research, they are the tip of the iceberg in terms of what we know about social networks and the benefits of managing network structure. Chapter 1 identifies the key conceptual underpinnings of social network theory and social network analysis. Chapter 2 relates how social network theory predicts individual promotion and resource acquisition, while chapter 3 helps you understand and develop tactics for making your social network useful. Chapter 4 extends this work to show how the fruits of team collaboration are dependent on social network characteristics. Chapter 5 looks at social networks through a strategic lens, drawing on examples from Procter & Gamble (the connect and develop model), McKinsey (social networks as invisible organizational structure), and Accenture (innovation in a flat world). Finally, Chapter 6 identifies some of the key ethical issues accompanying social network analysis.

Risk perceptions have, to a great extent, been studied exclusively as individual cognitive mechanisms in which individuals collect, process, and form perceptions as atomized units unconnected to a social system. These individual‐level theories do not, however, help explain how perception of risk may vary between communities or within a single community. One alternative approach is based on a network theory of contagion. This approach, emerging largely from organizational and community social network studies, suggests that it is the relational aspects of individuals and the resulting networks and self‐organizing systems that influence individual perceptions and build "groups or communities of like‐minded" individuals. These social units, it is argued, behave as attitude, knowledge, or behavioral structures. The study reported in this article tests one aspect of this theoretical perspective. The central hypothesis proposes the existence of risk perception networks—relational groupings of individuals who share, and perhaps create, similar risk perceptions. To test this idea, data were collected from individuals involved in a community environmental conflict over a hazardous waste site cleanup. The statistical analysis used a matrix of relational social linkages to compare with a matrix of individual risk perceptions. The analysis confirmed the hypothesis suggesting that social linkages in communities may play an important role in focusing risk perceptions.