Method and system for evaluating logistics platform driver credit index based on big data

Abstract

The invention discloses a method and system for evaluating a logistics platform driver credit index based on big data. In the invention, a logistics driver credit system comprises a certificate acquisition system, a platform service system, an operation database system, a BI system and an authority management system, wherein the certificate acquisition system comprises mobile terminal equipment and certificate detection equipment; the operation database system comprise a data storage unit, a data backup unit and a data access unit; and the BI system is connected with a cloud storage system through an information verification and data transmission module. According to the invention, a valuable driver credit index is extracted by means of a big data analysis method and tool according to multi-dimensional long-period driver static and dynamic data accumulated by a logistics information platform for a long time, the efficiency and accuracy of logistics driver credit evaluation are improved, and thus the logistics industry is promoted to develop quickly and healthily.

Description

technical field [0001] The invention belongs to the field of logistics platform management and driver credit evaluation system, in particular to a method and system for evaluating the driver credit index of logistics platform based on big data. Background technique [0002] China's modern logistics industry has undergone nearly 30 years of market development, and now the main players in the logistics market are: [0003] 1. Cargo owners: including production, commerce, and e-commerce enterprises; [0004] 2. Logistics companies: including various third-party logistics companies, dedicated line less-than-truckload companies, and transportation companies. They provide logistics organization, management, and service activities. At present, logistics companies generally have multi-level subcontracting business; [0005] 3. Logistics information platform: an information technology company that mainly provides information matching, information services and value-added services fo...

AI Technical Summary

Problems solved by technology

[0020] 1. The method of on-site verification and observation: This method can only obtain relevant driver credit information with paper materials, but cannot obtain relevant information on driver service ability, service awareness and capital flow status; even if certain information is obtained through on-site observation and communication Perceptual knowledge, but without specific data support, it is not objective and scientific

[0021] 2. Learn from the units that the driver has served before: through the name and contact information of the unit that the driver has served before and left in the registration, and through telephone or email return visits, the existing problems are: First, individual drivers There are many service units, and the service units left by the drivers may be only a small number or good relationship units, so the driver credit information obtained is not comprehensive and untrue; The Chinese have a culture of not offending others, and generally do not say anything unfavorable to the subject of the investigation, so the driver’s credit information obtained in this way is not true and not representative

[0022] 3. Inquire about the credit status of drivers through the Internet or related credit information platforms and peer logistics information platforms: through Internet search engines, it is possible to inquire about the credit information of some drivers with "big crimes and heinous crimes", but on the one hand, Internet search engines are based on bidding ranking rules. It is too difficult to search for useful information among many information. On the other hand, it cannot be ruled out that relevant units or individuals maliciously exaggerate the driver's credit due to disputes; some credit information platforms can query some personal credit information, but more are based on the unit Legal person or consumer credit is of little significance to the driver's logistics credit investigation; in addition, other logistics information platform peers conduct credit investigation on the drivers registered on this platform. Membership is required to view and use it, and cross-platform data query and call are generally not supported

[0023] 4. Obtaining information through secret investigation and observation: secretly investigating and observing drivers can obtain some real service capabilities, service awareness or financial status of drivers, but for millions of drivers on the logistics information platform, this kind of The method is not feasible, the cost is high, and the cycle is long. It is not an economical and feasible method for driver credit evaluation

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