Study On Credit Rating System In Road Transportation Industry

Market economy is essentially credit economy, thus the economy reform going on in our country now calls for a correlative credit management. However, credit system construction is quite sluggish due to the obstacle caused by inertia of planned economy and affection of our traditional bargaining style. Besides, consciousness about credit among people in our country is generally weak, the leverage of credit on economy can not work normally, which leads to the ubiquitous phenomenon of credit-breaking, all the above forms an obstacle for economy development, both in speed and quality.In order to improve credit environment and ameliorate the national credit management, china has been devoting itself in credit system construction in recent years, not only makes up credit laws and regulations, but also advocates local governments and industry departments to take part in it. On this condition, the industry of road transportation has begun to introduce credit ratings into its administration system, from principle to method, expecting supplying support for social credit system construction, as well as finding out a new, better means to improve its administration, protect legal rights of proprietors and customers, most important of all, facilitate a healthy and strong traffic and transportation industry.Taking the structure and operation mode of social credit system as a reference, the article systematically studies credit demand and correlative environment in the industry, after a thorough analysis on the current condition of the industrial administration, the article sets the border and confirms content of the industry's credit rating system, then discusses its institutional backup, lines out headstreams of credit datum and its recording format, builds up an integrated credit rating model. To embody the model, the article obtains subjection functions using the statistical result from questionnaire, and offers detailed means to process the credit records and data to get values of indexes which act as the imput for the model.Finally the article imput sample data into the credit rationg model, result shows that the model fair works out ratings with a high efficiency given that credit data are adequately collected and processed.