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By analyzing microblog texts, a visual early warning research of college net loans is conducted in this paper to effectively reduce the negative impact of illegal Internet loans (abbreviated as "net loans") on college students' lives. Two calculation models are proposed in our research: One is the Identification Model of Risk Degree (IMRD) based on the security level of microblog texts about net loans. The other is the Calculation Model of Relationship Closeness (CMRC) based on three dimensions: user's relevant relationship, interaction strength, and interest similarity. IMRD is used to identify the risk of microblog net loan texts, and determine whether to early warn or not. CMRC is utilized to acquire a net loan communication map by describing the closeness level between net loan microblog publishers and their followers, and analyzing the possibility of retweeting. A visual monitoring and early warning platform is constructed based on these two models. With this platform, further spread of net loan information can be prevented by analyzing the graph and cutting off key nodes in time. The early warning mechanism of this research can effectively alleviate the negative influence of illegal net loans.

Price decision is studied in a risk-averse retailer-dominated dual-channel supply chain, which consisting of one manufacturers and one retailer with both off-line and on-line channels. Firstly, two mean-variance models in centralized and decentralized supply chain are established. Secondly, the optimal solutions under the two decision modes are compared and analyzed. The results shows that the price of dual-channel of retailer decreased with the increase of retailers’ risk- aversion coefficient and the standard deviation of the fluctuation of market demand, while the wholesale price changes is on the contrary; in addition, when the market demand is greater than a certain value, the prices of dual channel are correspondingly higher in decentralized supply chain than in centralized supply chain, and vice versa. In addition, when the retailer’s risk aversion is in a certain interval, the expected utility of the whole supply chain is greater in centralized supply chain than in decentralized decision, and vice versa. Finally, a numerical example is given to verify the above conclusions.

In recent years, rural Internet finance has gradually risen, effectively solving the financing needs of farmers. This paper takes Python crawling data of online lending platform as a sample, and uses multiple regression model to research the influencing factors of farmers' lending efficiency in rural Internet financial market. The results show that in the rural Internet financial market, the gender and annual interest rate of farmers will affect the efficiency of lending, while the age and income of farmers have no significant correlation with the efficiency of lending. In addition, in order to promote the orderly development of rural Internet finance, this paper puts forward relevant suggestions from the perspective of the government, Internet lending platform and other subjects.

Agriculture is a basic industry that supports the construction and development of the national economy and plays an important role in promoting rural revitalization. And in the current post-COVID-19 era, agricultural SMEs have difficulty in obtaining the favours of financial institutions in normal lending due to their weak credit guarantee capabilities and high credit management costs. Difficulty in financing has become a bottleneck problem that plagues the development of enterprises and restricts the development of agricultural modernization. How to evaluate and control its credit risk is not only a major way to solve the financing difficulties of agricultural SMEs, but also the basis for the stable development of supply chain financial services. This paper analyzes three typical financing modes of agricultural SMEs from the perspective of supply chain finance, and takes the agricultural SMEs in the New OTC Market as an example to construct a Logistic model, and uses factor analysis to effectively predict the credit risk of supply chain finance. The results show that the operational efficiency factors, growth factors and related core corporate profitability of agricultural SMEs financing enterprises significantly affect their credit risk. After testing, the model is highly accurate in predicting the financing risks of agricultural SMEs.

In order to improve the overall level and long-term development of YTO Express, according to the development strategy and planning of YTO Express logistics, this paper puts forward the construction of Hub-and-Spoke air logistics transport network with core hub airport, and optimizes YTO Express transport network. Firstly, the cluster analysis function of SPSS is used to divide the region of the air node, and then the center of gravity method is used to select the regional hub point, and the core hub airport and the regional hub airport are determined, so as to design the final transport network, which is conducive to the sustainable development of YTO Express, and improve the proportion of YTO Express in the air field.

Based on a ground review of the literature on safety culture, the paper analyzed the forming process of main stream enterprise safety culture and developed a general framework distinguishing three dimensions which enterprise safety culture identification could be studied. The framework described safety culture identification process from three aspects as individual level, group level and organizational level. The results showed that the identification of enterprise safety culture was the key link which makes mainstream enterprise safety culture translated into strong enterprise safety culture.

As a novel population-based optimization algorithm, Teaching-Learning based Optimization (TLBO) possesses the advantages of single tuned parameter and global fast coarse search capability, at the same time it risks being trapped in local optima for function optimization due to premature convergence. In this paper, a TLBO-based memetic algorithm, namely TLBO-SPSA, is proposed, in which simultaneous perturbation stochastic approximation (SPSA) is incorporated into the canonical TLBO to enhance its local search capability and balance the global exploration and local exploitation as well. Numerical results on six well-known benchmark problems and comparisons with the state-of-the-art algorithms, e.g., conventional TLBO, I-TLBO, LGMS-FFO, IFFO, show that the proposed TLBO-SPSA outperforms the other algorithms in terms of the accuracy and convergence rate, especially the superior performance and robustness for solving higher dimensional problems.

Using game theory, the paper discusses the collusion between the contractor and supervisor as well as the action of owner. According to the judgment of the probability which the supervisor accepts the contract's bribe, the owner gives his strategy. So supervisor judges the owner's conduct to decide how to do. And then contractor makes the decision whether bribe or not. Therefore, all the strategies of players are discussed.

Based on the game theory, the paper discusses the collusion between contractor and supervisor in construction claims. By creating a three-person game model, the paper analyzes the strategies of the entire three partners. There is no pure strategy Nash equilibrium, so they should select their strategies by chance according mixed strategy Nash equilibrium. Furthermore, the paper suggests government how to reduce the likelihood of collusion.