近十年以来我国快递行业蓬勃发展,快递业务量从91.9亿件到1105.8亿件,但是由于快递企业在我国的发展历史不长,快递企业也面临着丢失、延误、损毁等方面信用问题。本文从快递企业信用出发,利用在线评论数据爬取结合行业标准以及文献资料建立初步信用评价指标体系,再通过主成分分析法依靠模型数据得到最终的快递企业信用评价指标体系,其次,基于诱导密度算子构建静态信用评价模型,再结合TOPSIS-GRA法建立快递企业动态信用评价模型,以实现对快递企业信用风险的度量,进而促进快递企业改善信用问题,以此带动快递行业高质量发展。In the past decade, China’s express delivery industry has flourished, with the volume of express delivery services increasing from 9.19 billion to 110.58 billion. However, due to the short development history of express delivery companies in China, they also face credit problems such as loss, delay, and damage. This article starts from the credit of express delivery enterprises, uses online comment data crawling combined with industry standards and literature to establish a preliminary credit evaluation index system, and then uses principal component analysis to rely on model data to obtain the final credit evaluation index system of express delivery enterprises. Secondly, based on the induced density operator, a static credit evaluation model is constructed, and then combined with TOPSIS-GRA method to establish a dynamic credit evaluation model of express delivery enterprises, in order to measure the credit risk of express delivery companies, and then promote the improvement of credit problems of express delivery companies, this will drive the high-quality development of the express delivery industry.
