大数据下基于多源信息融合的企业竞争对手评价模型研究

目的/意义]针对传统企业竞争对手评价研究中数据源单一和评价指标片面性的不足,文章率先提出了基于多源信息融合的竞争对手评价方法。方法/过程]基于顾客价值领先战略,从企业和消费者的视角出发,选取企业财务报表和电商平台上的消费者评论作为信息源。通过构建财务特征和情感特征,依托BP神经网络,分别建立基于财务特征和综合特征的竞争对手评价模型。结果/结论]采用仿真实验对提出的方法进行验证,证明基于综合特征建立的模型相比基于单一财务特征的模型更有效。该方法为大数据背景下的企业竞争对手评价提供了一种新的研究思路。

A Research on Enterprise Competitor Evaluation Model Based on Multi-source Information Fusion in Big Data Environment

Purpose/significance]Due to the singleness of data source and inadequacy of evaluation indexes in traditional enterprise competitor evaluation research,this paper firstly puts forward the competitor evaluation method based on multi-source information fusion.Method/process]Based on the strategy of customer value leadership,the financial statements and consumer reviews on the e-commerce platform are used as information sources from the perspective of enterprises and consumers.Then a comprehensive feature system is built by integrating financial features and emotional features.Subsequently,competitor evaluation models with financial features and comprehensive features are built based on BPNN respectively.Result/conclusion]The proposed method is validated by simulation experiments,which indicates that the model with comprehensive features outperforms the model with pure financial features.The proposed approach provides a new research idea for the evaluation of enterprise competitors in big data environment.