Otto-von-Guericke-Universität Magdeburg

 
 
 
 
 
 
 
 

Social network analysis of PLS-SEM research

12.04.2018 - We’re happy to announce that the paper “Methodological research on partial least squares structural equation modeling (PLS-SEM): An analysis based on social network approaches“ has been accepted for publication in Internet Research, a leading journal in the Information Systems field. Authored by Gohar F. Khan (The University of Waikato), Marko Sarstedt, Wen-Lung-Shiau (Ming Chuan University), Joe F. Hair (University of South Alabama), Christian M. Ringle (Hamburg University of Technology), and Martin P. Fritze (University of Cologne), we explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. We analyze the structures of author, institution, country, and co-citation networks, and disclose trending schemes in the field. Based on bibliometric data downloaded from the Web of Science, we apply various social network analysis and visualization tools to examine the structure of knowledge networks of the PLS-SEM domain. Specifically, we investigate the PLS-SEM knowledge network by analyzing 84 methodological studies published in 39 journals by 145 authors from 106 institutions. We find that specific authors dominate the network, whereas most authors work in isolated groups, loosely connected to the network’s focal authors. Besides presenting the results of a country level analysis, our research also identifies journals that play a key role in disseminating knowledge in the network. Finally, a burst detection analysis indicates that method comparisons and extensions, for example, to estimate common factor model data or to leverage PLS-SEM’s predictive capabilities, feature prominently in recent research.
Letzte Änderung: 12.04.2018 - Ansprechpartner: Webmaster