An Exploratory Analysis Using Co-Authorship Network: Trends in Risk Behavior

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Author(s): Burçin Güçlü (Universitat Ramon LLull, Spain), Miguel Ángel Canela (Universidad de Navarra, Spain)and Inés Alegre (Universidad de Navarra, Spain)
Copyright: 2019
Pages: 35
Source title: Machine Learning Techniques for Improved Business Analytics
Source Author(s)/Editor(s): Dileep Kumar G. (Adama Science and Technology University, Ethiopia)
DOI: 10.4018/978-1-5225-3534-8.ch008

Keywords: Business Information Systems / Business Science Reference / Data Analysis & Statistics / Library & Information Science

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Abstract

Social network analysis has been widely used by organizational behavior researchers to stress the importance of the context, social connections, and social structure on human behavior. In the last decade, social network analysis has emerged as one of the most useful techniques for exploring online social networks, world wide web, e-mail traffic, and logistic operations. In this chapter, the authors present an application of social network analysis techniques for academic research. The authors choose Kahneman and Tversky's prospect theory as the focus of their analysis and, based on that, develop a co-authorship structure that depicts in a clear manner the key authors and/or the researchers that dominate and bridge different sub-fields in the field of management. The authors discuss the implications of this study for academic research and management discipline.

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An Exploratory Analysis Using Co-Authorship Network: Trends in Risk Behavior

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