Research on the Impact of Executive Shareholding on New Investment in Enterprises Based on Multivariable Linear Regression Model

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Tác giả: Yi Cao, Mo Geng, Zhijun Li, Hongbiao Si, Wenyuan Sun, Lihua Tang, Ning Yan, Longda Zhang, Xulong Zhang, Shanyi Zhou

Ngôn ngữ: eng

Ký hiệu phân loại: 001.432 Historical method

Thông tin xuất bản: 2023

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 198220

 Based on principal-agent theory and optimal contract theory, companies use the method of increasing executives' shareholding to stimulate collaborative innovation. However, from the aspect of agency costs between management and shareholders (i.e. the first type) and between major shareholders and minority shareholders (i.e. the second type), the interests of management, shareholders and creditors will be unbalanced with the change of the marginal utility of executive equity incentives.In order to establish the correlation between the proportion of shares held by executives and investments in corporate innovation, we have chosen a range of publicly listed companies within China's A-share market as the focus of our study. Employing a multi-variable linear regression model, we aim to analyze this relationship thoroughly.The following models were developed: (1) the impact model of executive shareholding on corporate innovation investment
  (2) the impact model of executive shareholding on two types of agency costs
  (3)The model is employed to examine the mediating influence of the two categories of agency costs. Following both correlation and regression analyses, the findings confirm a meaningful and positive correlation between executives' shareholding and the augmentation of corporate innovation investments. Additionally, the results indicate that executive shareholding contributes to the reduction of the first type of agency cost, thereby fostering corporate innovation investment. However, simultaneously, it leads to an escalation in the second type of agency cost, thus impeding corporate innovation investment.Comment: Accepted by the 7th APWeb-WAIM International Joint Conference on Web and Big Data. (APWeb 2023)
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