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New Technology of Library and Information Service  2016, Vol. 32 Issue (11): 11-19    DOI: 10.11925/infotech.1003-3513.2016.11.02
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Detecting Investment Risks of Photovoltaic Projects with Big Data: Case Study of
Yang Yang1,Lin Hui1,Hu Guangwei2()
1School of Business, Nanjing University, Nanjing 210093, China
2School of Information Management, Nanjing University, Nanjing 210093, China
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[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.

Key wordsBig data monitoring index      Photovoltaic project      Investment risk      CHAID decision tree      R-Q mode factor analysis     
Received: 25 July 2016      Published: 20 December 2016

Cite this article:

Yang Yang,Lin Hui,Hu Guangwei. Detecting Investment Risks of Photovoltaic Projects with Big Data: Case Study of New Technology of Library and Information Service, 2016, 32(11): 11-19.

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