Representation and effectiveness based on big data analytics: optimizing the construction of leadership team structures

Abstract

Abstract The optimization of leadership team structure is the research object of this paper, and the regression model in big data analysis is explored as the research method. Neighboring sample information is introduced through the network structure diagram, the regression model with neighboring sample information is constructed, the corresponding estimation method of regression coefficients is proposed, and the proof of the error bounds of the proposed estimation is given. Finally, the method is applied to analyze the results after optimizing the corporate leadership team structure. It includes regression analysis of the non-heterogeneous, heterogeneous, and overall structures of the leadership team and examines the moderating effect of salary heterogeneity on the results. The results show that the number of applications for invention patents and the number of authorized patents in the enterprise reaches 3 times to 5 times the number before the change, respectively, and in the regression analysis of the heterogeneous structure of the leadership team on the development of the enterprise R 2 =0.134, F value=2.186, which indicates that the heterogeneity of the years of working experience has a very significant positive effect on the development of the enterprise.