2019 International Conference on Economic Management and Model Engineering (ICEMME)最新文献_第4页

The Formation Mechanism of SMEs' Credit Risk Under Supply Chain Finance Based on Game Theory 基于博弈论的供应链金融下中小企业信用风险形成机制

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00080

Hao Du, H. Kuang, Xin Zhang

{"title":"The Formation Mechanism of SMEs' Credit Risk Under Supply Chain Finance Based on Game Theory","authors":"Hao Du, H. Kuang, Xin Zhang","doi":"10.1109/ICEMME49371.2019.00080","DOIUrl":"https://doi.org/10.1109/ICEMME49371.2019.00080","url":null,"abstract":"Small and medium-sized enterprises (SMEs) that have difficulty in financing are the weak link in the supply chain. In recent years, with the development of the supply chain management concept and financial institutions business, the supply chain financial model emerges as the times require. It not only helps SMEs in the supply chain to finance, but assists the core enterprises to expand their business scope and obtain value-added profits, which has become an effective way to solve the financing difficulty of SMEs. This paper in the supply chain studies the formation mechanism of credit risk of SMEs by using the game model. The paper obtains the factors that affect the credit risk through the balanced income of banks and core enterprises in the game model and analyzes the behavior decision-making and the probability of occurrence of credit risk of SMEs and banks via using the revenue function. And it reveals the formation mechanism of credit risk of SMEs and makes up for the existing research on the formation mechanism of credit risk without SMEs in the supply chain finance. Eventually, combined with the specific results of the game model, it puts forward practical suggestions for the participants of the supply chain finance to reduce the credit risk and promote the win-win of the participation of the supply chain finance. Eventually, combined with the specific results of the game model, it puts forward practical suggestions for the participants of the supply chain finance to reduce the credit risk and promote the win-win of the participation of the supply chain finance.","PeriodicalId":122910,"journal":{"name":"2019 International Conference on Economic Management and Model Engineering (ICEMME)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127799313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Internet Plus, Inclusive Finance and Inclusive Growth: Impact Mechanisms and Empirical Evidence 互联网+、普惠金融与普惠增长:影响机制与实证

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00130

Li Zhang, Fang Zou, Min Fan, Daifen Chen, Shuang Huang

引用次数: 0

Research on Evaluation of Urban Talent Gathering Ability - Taking Shenzhen City as an Example 城市人才集聚能力评价研究——以深圳市为例

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00129

Kai Guo, Y. Lv

{"title":"Research on Evaluation of Urban Talent Gathering Ability - Taking Shenzhen City as an Example","authors":"Kai Guo, Y. Lv","doi":"10.1109/ICEMME49371.2019.00129","DOIUrl":"https://doi.org/10.1109/ICEMME49371.2019.00129","url":null,"abstract":"Human resources have gradually become the strategic resources and core competitiveness of regional development, making methods to improve the ability of urban talent gathering a research highlight. The first step of quantitative research on the urban talent gathering ability is to build an evaluation index system. This paper first analyzed the influencing factors of urban talent gathering, including several first-level indicators, such as economic development, urban construction and urban environment, education and medical service, living conditions and career platform, as well as 27 secondary indicators used to assemble Shenzhen talents. Then it aggregated the ability evaluation index system. The principal component analysis method was used to empirically evaluate the talent gathering ability of Shenzhen. The results showed that Shenzhen's indicators, such as per capita GDP, public library collection, number of foreign-funded enterprises, annual average wage level and patent authorization, have a positive impact on the city's talent pooling ability. Finally, specific measures were proposed to enhance its talent pooling. of ability. This research can provide theoretical support and a decision-making basis for the enhancement of the talent pooling ability of Shenzhen.","PeriodicalId":122910,"journal":{"name":"2019 International Conference on Economic Management and Model Engineering (ICEMME)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130711482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Novel Quantitative Stock Selection Model Based on Support Vector Regression 一种新的基于支持向量回归的定量股票选择模型

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00094

Jingyi Dai, Jingwei Zhou

{"title":"A Novel Quantitative Stock Selection Model Based on Support Vector Regression","authors":"Jingyi Dai, Jingwei Zhou","doi":"10.1109/ICEMME49371.2019.00094","DOIUrl":"https://doi.org/10.1109/ICEMME49371.2019.00094","url":null,"abstract":"Facing the huge challenges brought by changing market environment, the academic community is constantly looking for factors and combinations that can obtain excess returns on basis of traditional multi-factor stock selection model. Compared with the traditional linear multi-factor model, the machine learning algorithm can capture the more granular market signal by the nonlinear expression of the factor. To mine the stock factor data and optimize the stock selection model, this paper uses the equal weight linear model, machine learning support vector machine and linear regression algorithm for factor analysis. Based on the theory of SVM machine learning algorithm and multi-factor stock selection, this paper establishes and solves the SVR stock market forecasting model by characterizing the data. Then, we give and analyze examples after combining relevant data. The results show that the factors such as PB, PE, ROE, NetProfitGrowRate, OperatingRevenue-GrowRate, EPS and NegMktValue are outstanding. After putting excellent factors into the SVR model, the return rate of the stock portfolio is far greater than that of the traditional equal weight linear model, which indicates that the stock selection model using the machine learning algorithm has higher returns and stable results. This paper provides some guidance for decision makers to formulate stock picking strategies by mining stock factor data.","PeriodicalId":122910,"journal":{"name":"2019 International Conference on Economic Management and Model Engineering (ICEMME)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116637934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Evaluation of Operational Efficiency in International Disaster Public Welfare Organizations 国际灾害公益组织运作效率评价

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00028

Guoqu Deng, Shiqiang Liu, Li Li, Chu-shi Deng

{"title":"The Evaluation of Operational Efficiency in International Disaster Public Welfare Organizations","authors":"Guoqu Deng, Shiqiang Liu, Li Li, Chu-shi Deng","doi":"10.1109/ICEMME49371.2019.00028","DOIUrl":"https://doi.org/10.1109/ICEMME49371.2019.00028","url":null,"abstract":"The mission of the public welfare organizations is generally oriented to the public and based on morality. Serving as a key means to solve the problem in the non-profit organization agency, efficiency evaluation is also the premise and the foundation of accountability. Based on the data from 2010 to 2017, this paper analyzes the operational efficiency of four international disaster public welfare organizations (including GFDRR, UNISDR, OCHA, and ICRC). Given the characteristics of organizations, we extracted nine indexes of operational efficiency evaluation both in financial and non-financial aspects, and analyzed them by using the factor analysis method. The results show that the resource acquisition ability of the public welfare organization has a great influence on the operation of the organization. Additionally, the effective disclosure of the use of financial funds and the effectiveness of public welfare activities can promote public satisfaction. The beneficiary group size of the public welfare organization has a positive correlation with the management costs and staff costs.","PeriodicalId":122910,"journal":{"name":"2019 International Conference on Economic Management and Model Engineering (ICEMME)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116922621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction of Multidimensional Poverty Model for Urban Youth 城市青年多维贫困模型的构建

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00049

Chen Chen

引用次数: 0

Research on the Impact of Equity Incentive to Executives and Types of Incentive on Firm Performance 高管股权激励及激励类型对企业绩效的影响研究

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00114

Xiang-hong Que, Weitong Ren

引用次数: 0

Analysis on the Integrated Transportation Efficiency of China's Province 中国省际综合交通效率分析

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00045

Xin Zhang

引用次数: 0

Cluster Analysis of Teaching Knowledge Points of "Statistics" in Medical Colleges Base on Student-Centered 基于以学生为中心的医学院校《统计学》教学知识点聚类分析

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00097

Dan Chen, Bo Su, Song-nian Hu

{"title":"Cluster Analysis of Teaching Knowledge Points of \"Statistics\" in Medical Colleges Base on Student-Centered","authors":"Dan Chen, Bo Su, Song-nian Hu","doi":"10.1109/ICEMME49371.2019.00097","DOIUrl":"https://doi.org/10.1109/ICEMME49371.2019.00097","url":null,"abstract":"Objective: The purpose of this paper is to construct a statistical knowledge point learning system based on two dimensions: difficulty level and learning resource type. Methods: This study aimed to investigate the students who completed the statistics course in middle school hospitals, and used the clustering and two-step clustering method in the SPSS software to cluster the results. Results: This study obtained two results of the knowledge point learning system: First, the clustering results based on the difficulty level analysis, which can be used to summarize the difficulties and difficulties in the statistical teaching process from the perspective of students; Second, the results of different learning resource types clustering knowledge points, which shows that the extracurricular teaching resources of statistics and the learning effect played at this stage is not obvious. Conclusion: The statistical learning process cannot be carried out solely by teachers. It requires students, teachers and schools to work together. Whether there are different types of colleges and universities in the distribution of statistical knowledge points, structural differences between different provinces and different provinces, and the fairness of extracurricular teaching resources between them in the university category, whether there is a significant difference between the provinces, will be Future research directions.","PeriodicalId":122910,"journal":{"name":"2019 International Conference on Economic Management and Model Engineering (ICEMME)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127687479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Optimal Portfolio of Financial Investment Based on Genetic Algorithm 基于遗传算法的金融投资最优组合研究

2019 International Conference on Economic Management and Model Engineering (ICEMME) Pub Date : 2019-12-01 DOI: 10.1109/ICEMME49371.2019.00104

Bahao Li

引用次数: 1