[Objective] This research proposes a selection scheme for the big data application to monitor the Internet financial platforms, which is verified by the real world cases. [Methods] First, we adopted a big data model to integrate multi-source heterogeneous data from the Solarbao platform. Second, we utilized the CHAID decision tree to summarize multi-dimensional monitoring indicators based on analysis of each project’s investment risks. Finally, we employed the R-Q factor analysis method to extract the key investment risks. [Results] We got 8 indicators to track the investment risks, which could be identified by the other 10 indicators for the photovoltaic projects. [Limitations] More research needs to be done with indicators of the R-Q factor analysis, which also requires a dynamic update mechanism. [Conclusions] The proposed scheme could help investors assess the risks of individual projects and then select the appropriate ones. It will also support the risk management work of the regulatory agencies.
杨旸,林辉,胡广伟. 面向光伏项目投资风险的大数据监测指标甄选研究*——以Solarbao平台为例[J]. 现代图书情报技术, 2016, 32(11): 11-19.
Yang Yang,Lin Hui,Hu Guangwei. Detecting Investment Risks of Photovoltaic Projects with Big Data: Case Study of Solarbao.com. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2016.11.02.
Scholtens B.Finance as a Driver of Corporate Social Responsibility[J]. Journal of Business Ethics, 2006, 68(1): 19-33.
Climent F, Soriano P.Green and Good? The Investment Performance of US Environmental Mutual Funds[J]. Journal of Business Ethics, 2011, 103(2): 275-287.
Graham A, Maher J J, Northcut W D.Environmental Liability Information and Bond Ratings[J]. Journal of Accounting Auditing & Finance, 2001, 16(2): 93-116.
Thomas S, Repetto R, Dias D.Integrated Environmental and Financial Performance Metrics for Investment Analysis and Portfolio Management[J]. Corporate Governance: An International Review, 2007, 15(3): 421-426.
Pope D G, Sydnor J R, What’s in a Picture? Evidence of Discrimination from Prosper.com[J]. Journal of Human Resources, 2008, 46(1): 53-92.
Duarte J, Siegel S, Young L.Trust and Credit: The Role of Appearance in Peer-to-Peer Lending[J]. Review of Financial Studies, 2012, 25(8): 2455-2484.
(Zhang Lichao, Fang Junming, Tang Qinneng.Research on Risk Identification in the Early Warning of Industry Competitive Intelligence: A Case Study of Photovoltaic Power Generation Industry in China[J]. Information Studies: Theory & Application, 2011, 34(10): 52-55.)
白洋. 面向大数据的电力设备状态监测信息聚合研究[D]. 昆明: 昆明理工大学, 2014.
(Bai Yang.Research on Data Aggregation of Power Equipment Condition Monitoring Based on Big Data [D]. Kunming: Kunming University of Science and Technology, 2014. )
(Sun Xiaoling, Zhao Yuxiang, Zhu Qinghua.Analyzing the Demand of Online Product Review System’s Features Using Kano Model: An Empirical Study of Chinese Online Shops[J]. New Technology of Library and Information Service, 2013(6): 76-84.)
Wang C H.Incorporating Customer Satisfaction into the Decision-Making Process of Product Configuration: A Fuzzy Kano Perspective[J]. International Journal of Production Research, 2013(22): 6651-6662.
Nagamachi M.Kansei Engineering: A New Ergonomic Consumer-Oriented Technology for Product Development[J]. International Journal of Industrial Ergonomics, 1995, 15(1): 3-11.
(Cheng Tiexin, Guo Tao, Qi Xin.Application of Decision Tree Classification Model in Risk Early Warning of Engineering Project Evaluation[J]. Journal of Applied Statistics and Management, 2010, 29(1): 122-128.)
Dey P K.Project Risk Management Using Multiple Criteria Decision Making Technique and Decision Tree Analysis: A Case Study of Indian Oil Refinery[J]. Production Planning & Control, 2012, 35(3): 1-19.
Walden J, Smith J P, Dackombe R V.The Use of Simultaneous R-Q Mode Factor Analysis as a Tool for Assisting Interpretation of Mineral Magnetic Data[J]. Mathematical Geology, 1992, 24(3): 227-247.
Murtagh F.The Correspondence Analysis Platform for Uncovering Deep Structure in Data and Information[J]. The Computer Journal, 2010, 53(3): 304-315.