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In recent years, supply chain finance (SCF) is exploited to solve the financing difficulties of small- and medium-sized enterprises (SMEs). SME credit risk assessment is a critical part in the SCF system. The diffusion of SME credit risk may cause serious consequences, leading the whole supply chain finance system unstable and insecure. Compared with traditional credit risk assessment models, the supply chain relationship, credit condition of SME, and core enterprises should all be considered to rate SME credit risk in SCF. Traditional methods mix all indicators from different index systems. They cannot give a quantitative result on how these index systems work. Furthermore, traditional credit risk assessment models are heavily dependent on the number of annotated SME data. However, it is implausible to accumulate enough credit risky SMEs in advance. In this paper, we propose an adaptive heterogenous multiview graph learning method to tackle the small sample size problem for SMEs’ credit risk forecasting. Three graphs are constructed by using indicators from supply chain operation, SME financial indicator, and nonfinancial indicator individually. All the graphs are integrated in an adaptive manner, providing a quantitative explanation on how the three parts cooperate. The experimental analysis shows that the proposed method has good performance for determining whether SME is risky or nonrisky in SCF. From the perspective of SCF, SME financing ability is still the main factor to determine the credit risk of SME.

Green innovation for supply chain has attracted much academic attention. Yet, there is no adequate understanding of how spillover and cooperation can impact the enterprises’ green innovation decisions in the presence of free-rider. Besides, the dynamic impact of green innovation on emission is still lack of attention. We develop a differential game model that explicitly considers a supply chain with two types of manufacturers (i.e., green innovation and free-riding) to examine the dynamics of green innovation. The analysis reveals that under the noncooperation mode, the emissions and profits of free-riding manufacturers are found to be lower than that of innovating manufacturers, but technology spillovers will narrow the gap between them. Under the cooperation mode, there would be greater innovation efforts of green manufacturers and lesser efforts of green suppliers. Moreover, technology spillovers will have less impact on optimal decision changes. The profit of free-riding manufacturers is higher than that of innovating manufacturers, but the initial market power will affect the changes in their sales and profits. Meanwhile, cooperation will increase the total emission amount and long-term profits of the green supply chain, and technology spillovers of green manufacturers will help narrow the emission gap and broaden the profit gap, while that of the suppliers will have the opposite effect. The present study provides a new perspective for research on green innovation decisions for supply chain.

Effective safety supervision guarantees coal mine safety production. However, the traditional supervision mode in Chinese coal mines cannot fully realize the synergistic and complementary effects of elements (i.e., safety inspectors) of safety supervision system, which causes information-isolated island, application-isolated island, and resource-isolated island. To overcome these deficiencies and improve the efficiency of safety supervision, a synergistic and complementary safety supervision mode (SCSSM) was explored in this study. After the applicability analysis of the synergistic and complementary management idea, this study creatively introduced the proposed idea to the safety supervision in the coal mine. On the basis of the deficiencies of the existing safety supervision mode and the advantages of synergistic and complementary management, the SCSSM was then established and its definite operation method was also provided. Finally, the new safety supervision mode was applied in Xinwen Mining Group Xin Julong Co., Ltd. with definite implementation method and comparative analysis. Results show that the new safety supervision mode uses lesser safety supervision resources than the traditional one. Meanwhile, the checking and rectification efficiency of hidden dangers and the project qualified rate are improved. Moreover, the number of accidents is reduced, which has significant safety, economic, and social benefits. This study can realize the synergistic and complementary effects of elements of safety supervision to improve the level of coal mine safety supervision and has high value of popularization and application.

Coal mine safety is an important part of safety management for a risk society and the unsafe behaviors of coal miners are major sources of hidden dangers. A considerable number of studies on coal miners' unsafe behaviors have been done based on behavioral science. However, few studies have been conducted from the perspective of cognition. This study explored the cognitive mechanism of coal miners' unsafe behaviors and proposed corresponding intervention strategies. A conceptual model of coal miners' unsafe behaviors was constructed after the analysis on the cognitive failure mechanism of unsafe behaviors, and an empirical test was carried out in Zhaizhen coal mine of China. Results show the necessity of exploring the causes of coal miners' unsafe behaviors from the perspective of cognitive failure. Among all the identified causes, the combined influence of personal causes is the most profound and the degree of influence of environmental causes, organization management, and behavioral attributes are decreased in turn. Unsafe behaviors can be restrained by optimizing the employment mechanism, improving the level of mechanization of underground mining, arranging the job division and operation schedule reasonably, and improving safety training mechanism and safety culture. Moreover, the safety of coal miner' operation behaviors can be ensured by improving safety management capability of managers, strengthening site management and safety protection, and improving the safety management system and incentive mechanism. T his study provides significant reference for behavioral intervention to reduce coal miners' unsafe behaviors in an effort to avoid the unsafe factors in risk society. [ABSTRACT FROM AUTHOR]

In order to protect the national petroleum security, combining with the actual situation in China, this paper establishes evaluation index system of petroleum security in China under the background of international oil price fluctuation, determines supply, consumption, trade, geopolitics and ecology 5 basic indexes and 15 specific indexes, and applies the DHGF (the combination of Delphi method, analytic hierarchy process, gray clustering analysis method and fuzzy evaluating method) and entropy technology model to evaluate China's petroleum security situation from 1995 to 2016. The result of evaluation shows that petroleum security was in a "relative dangerous" state from 2000 to 2013 and returned to "general" from 2014 to 2016. It is a new trial on evaluation method of petroleum security to evaluate China's petroleum security situation by using the DHGF and entropy technology model, which provides a new research idea and method for petroleum security evaluation. [ABSTRACT FROM AUTHOR]