基于BP神经网的我国制造业企业绩效评价体系——以上市白色家电制造企业为例

以上市白色家电制造企业为例,从盈利能力、适应能力、偿债能力和发展能力4个方面共选取了26个指标进行相关性分析,最终筛选确定了18个具有代表性的指标,构建上市白色家电制造企业的绩效评价体系。其中利用信息熵理论对指标权重进行确定,并计算出期望绩效值,再利用BP神经网络技术构建了绩效评价模型,训练以及模拟仿真样本白色家电制造企业的绩效,结果验证所构建的评价模型具有良好的泛化能力,可以有效地对上市白色家电制造企业进行评价。

The Performance Evaluation System of Chinese Manufacturing Enterprises Based on the BP Neural Network:Taking the Listed White Household Electrical Appliance Enterprises as an example

Although China is gradually strengthening the status of the entity of real economy in the market economy, there remains many obstacles in the development of the real economy, especially manufacturing enterprises. Therefore, it is urgent to strengthen the performance evaluation of manufacturing enterprises and improve their long-term development ability. Hence, this paper takes the listed white household electrical appliance manufacturing enterprises as an example, selects 26 indicators from four aspects of performance influencing factors, and finally determines 18 representative indicators to construct the performance evaluation system of the listed white household electrical appliance manufacturing enterprises. Besides, information entropy theory is applied to calculate the index weight and to evaluate the performance value of expectation. Then, using the BP neural network technique to build the model of performance evaluation system, training and simulating the network with the data from the listed white household electrical appliance enterprises. The result shows that the evaluation model is of good generalization, and it can effective evaluate the performance of the listed white household electrical appliance enterprises. This would lay a foundation for the followed performance evaluation of the manufacturing industry.