基于BP神经网络的民营上市企业治理模式识别与选择。

Jie Wang, Zhenjin Li, Yidan Chen, Zhi-qiang Zhou, Shun Li
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引用次数: 0

摘要

本文对民营上市企业的治理模式进行了探索,将民营上市企业分为小型、中型和大型三类。民营上市企业的治理模式根据股权资本治理和人力资本治理两种不同的管理强度可分为9类。运用BP神经网络模型识别民营上市企业治理模式的9类。本文分析了民营上市公司在不同规模下治理模式的演变,并对不同的治理模式进行了分析。因此,中小、大型民营上市公司分别选择了“强股权弱人力”、“适度股权适度人力”和“弱股权适度人力”的治理模式。本文比较分析了不同规模下治理模式的治理效率。结果表明,“适度公平,适度人力”是三个规模最有效的管理模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition and Selection of Governance Modes of Private Listed Enterprises Based on BP Neural Network.
Exploring the governance modes of private listed enterprises, this paper divides private listed enterprises into categories of small, medium and large. The governance modes of private listed enterprises can be divided into 9 categories according to two different management intensities of equity capital governance and manpower capital governance. The 9 categories of governance modes of private listed enterprises are identified by using the BP neural network mode. This paper analyses the evolution of private listed companies’ governance modes at different scales and analyses various governance modes. Therefore, small, medium and large private listed companies choose the “strong equity and weak manpower”, “moderate equity and moderate manpower” and “weak equity and moderate manpower” governance modes, respectively. This paper comparatively analyses the governance efficiency of governance modes at different scales. The results show that “moderate equity and moderate manpower” is the most effective management mode for all three scales.
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