Measuring Risks of Confirming Warehouse Financing from the Third Party Logistics Perspective

Zhixin Wang,Yue Wang

doi:10.3390/su11236573

Abstract

Confirmation warehouse financing is an important model in supply chain finance. This type of financing has special characteristics due to the existence of the reverse repurchase link, and it increases the risk commitment of the core enterprise at a certain level. Previous research on supply chain financial risk mostly settled in ‘all-industry, multi-model’, ignoring the special risks of single mode. To supplement the vacancies in the current research, the special risks of supply chain finance should be identified under a single model. On this basis, a measurement index system for confirmation warehouse financing risk is created. The article uses a Back Propagation (BP) neural network to build a Third Party Logistics (3PL) perspective of the risk measurement model for confirmation warehouse financing. The said network is combined with the 24 sets of actual cases from ZY Logistics. MATLAB is used to train the sample data. Results show that the absolute errors—0.042998, −0.011102, 0.020514 and 0.039448—between the training value and the predicted value are smaller than the preset error value. Among the 24 cases, high-risk businesses reached 41.7%, whereas low-risk businesses only accounted for 29.2%. The ZY enterprise confirms that warehouse financial business risk is high, and this situation should be revised. Research shows that the risk measurement indicator system has good risk prediction ability. This study establishes and verifies the rationality of the risk measurement index system and provides a reliable reference for 3PL risk aversion in supply chain finance.

Highlights

In China, small- and medium-sized enterprises (SMEs) have become an important part of its national economy and are the most important component of the modern market economy
Results show that the Kaiser Meyer Olkin (KMO) values of the indicators are greater than 0.6, which indicates the validity of the indicators
Validity, and factor analyses of the indicators in the four dimensions, we find that many risk factors of the initially established risk measurement index system are characterized by low reliability and low correlation

Summary

Introduction

In China, small- and medium-sized enterprises (SMEs) have become an important part of its national economy and are the most important component of the modern market economy. According to the National Small and Medium Enterprises Development Report released by the State Administration for Industry and Commerce in 2018, the report states that as of the end of 2017, the number of SMEs included in the directory of China’s small and micro enterprises (SMEs) has reached 73.281 million by the end of 2017. The vast majority of SMEs are the basic forces for promoting employment, improving livelihood, stabilizing society, developing the economy, and promoting innovation. SMEs are the largest and most dynamic enterprise group in the urban economy, yet money is the blood of business development. Problems in financing restrict the development of SMEs

Results

Discussion

Conclusion