Abstract
Hierarchical decision models (HDMs) have been used widely in industrial and academic fields. The world of research in HDM is shrinking due to the connectivity of collaborative relationships between researchers. For new research to become widely known and for collaboration to be done in HDMs, we want to identify and connect the clusters of the researchers and the central member of the clusters. We use the social network analysis method to analyze the network of HDM researchers connected by coauthorship in the selected papers. We find out the important researchers with highest degree centralities and publication frequencies and the key researchers among the top 8 components. We act as the “information gatekeeper” by connecting the identified researchers so that the average distance between the vertices is eliminated significantly and thus construct a smaller world in the research realm about HDMs.
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