Influencing factor modeled examination on internet rural logistics talent innovation mechanism based on fuzzy comprehensive evaluation method.

Hui Zhan,Xin Zhang,Haiwen Wang,Dragan Pamucar

doi:10.1371/journal.pone.0246599

Abstract

In recent years, China's economic development has advanced by leaps and bounds, but the development of China's rural logistics system is still at its primary stage. Some remote areas with inconvenient transportation are still in a state of serious lack or even blank, and due to the high cost of rural logistics delivery services, the rural logistics business of the enterprise also has a profit problem, which limits the development of rural logistics talent innovation to some extent. The purpose of this paper is to study a new influencing factor model of the Internet rural logistics talent innovation mechanism. This paper innovatively proposes countermeasures to improve the innovation of e-commerce practitioners in rural areas. Through research, the author finds that the innovation of rural e-commerce application talents in China is generally low. The key point of the solution lies in how to improve the level of innovation in rural e-commerce application talents. According to the status quo, identify the factors that hinder the innovation and improvement of rural e-commerce application talents. Combined with the great environment of the development of rural e-commerce industry in China, the paper proposes to improve the countermeasures for improving the innovation of rural e-commerce application talents. Improve the current situation of rural e-commerce application talents mediocrity and promote the innovation of rural e-commerce application talents. Fundamentally promote agricultural development and the building of a new socialist countryside. This paper adopts the literature research method based on fuzzy comprehensive evaluation method, system analysis method and the combination of questionnaire survey and interview. Through big data and information science methods for data processing, using a company's Internet rural talent data set to simulate, the results It shows that with the method of this paper, the recognition rate reaches 98%, the speed increases obviously, and it is 20% faster than others.

Highlights

Logistics refers to the planning, implementation and management of raw materials, semi-finished products, finished products or related information from the origin of the goods to the place where the goods are consumed; meet the needs of customers at the lowest cost through transportation, storage and distribution
The key factors and inhibitors of success provide a sound basis for realizing the strategic potential of logistics and supply chain management
Co-investment by giants in the logistics industry, to create a three-dimensional ecological model of the logistics industry, using advanced Internet information technology to develop a set of information to get involved in the logistics industry practitioners The platform connects the main body of logistics demand, can be online transaction, settlement, supervision and evaluation; establishes urban logistics nodes offline, plays the role of collecting goods and distribution, utilizes social transportation capacity, builds national transportation network, promotes the overall development of logistics industry, and takes up the responsibility Promote the social responsibility of the reform and upgrading of the logistics industry

Summary

Introduction

Logistics refers to the planning, implementation and management of raw materials, semi-finished products, finished products or related information from the origin of the goods to the place where the goods are consumed; meet the needs of customers at the lowest cost through transportation, storage and distribution. Many countries are contracting providers of logistics to complement the internal distribution of public health systems. This reflects recent major outsourcing initiatives to address major gaps in transportation and logistics [1]. The key factors and inhibitors of success provide a sound basis for realizing the strategic potential of logistics and supply chain management. Big data analytics and the Internet of Things are supporting large logistics companies to improve driver safety, reduce operating costs and reduce environmental impact. This has implications for logistics companies in other parts of the world, where they may not be as widespread, but more widely used by drivers and society [3]. Other monetary and non-monetary factors should be considered, such as land, labor, investment incentives, and local government regulation [5]

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