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http://dx.doi.org/10.5351/KJAS.2022.35.4.527

Statistical ERGM analysis for consulting company network data  

Park, Yejin (Department of Statistics, Duksung Women's University)
Um, Jungmin (Department of Statistics, Duksung Women's University)
Hong, Subeen (Department of Statistics, Duksung Women's University)
Han, Yujin (Department of Statistics, Duksung Women's University)
Kim, Jaehee (Department of Statistics, Duksung Women's University)
Publication Information
The Korean Journal of Applied Statistics / v.35, no.4, 2022 , pp. 527-541 More about this Journal
Abstract
A company is a social group of many individuals that work together to obtain better results, and it is an organization that pursues common goals such as profit. As a result, forming networks among members, as well as individual communication abilities, is critical. The purpose of this research was to determine what factors influence the creation of employee advice relationships. Using the ERGM(Exponential Random Graph Model) approach, we looked at the network data of 44 individuals from consulting firms with offices in the United States and Europe. The significance of structural network factors like connectivity was first discovered. Second, the gender factor had the most significant main influence on the likelihood of adopting each other's advice. Third, geographical homogeneity resulted in higher link probabilities than major impacts of gender. This research looked at ways to make a company's network more efficient and active.
Keywords
company network; ERGM; network data; reciprocity; transitivity;
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