The Risk Evaluation Model of Mining Project Investment Based on Fuzzy Comprehensive Method

2013 ◽  
Vol 295-298 ◽  
pp. 2928-2934 ◽  
Author(s):  
Zuo Gong Wang ◽  
Jie Zheng ◽  
Hui Yang Li
Keyword(s):  
Risk Factors ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Assessment Model ◽  
Investment Risk ◽  
Project Investment ◽  
Comprehensive Method ◽  
Mining Project ◽  
Risk Evaluation Model

Mining project investment has a lot of features, such as long period, slow effect, big capital size, irreversible investment, the numerous and complicated risk factors. Therefore, it is necessary to analyze and evaluate the investment risk before accepting project. On the basis of analyzing the mining project risk factors, establishing the risk evaluation index system, establishing the risk assessment model based on fuzzy comprehensive method, then evaluating the investment risk of mining project quantitatively, which provides the decision-making basis, makes the investment more scientific and safer and reduces the risk of investment.

Study on IT Project Investment Risk Evaluation Based on ANP

2011 ◽  
Vol 63-64 ◽  
pp. 557-560 ◽  
Author(s):  
Bing Sheng Liu ◽  
Hui Yan Ma ◽  
Li Lin
Keyword(s):  
Risk Management ◽  
Empirical Analysis ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Investment Risk ◽  
It Projects ◽  
Project Investment ◽  
It Project ◽  
Risk Evaluation Model

This paper has studied the classification of investment risks in IT projects, and got 5 categories of investment risks, which can be subdivided into 14 kinds. Then established the IT project investment risk evaluation model based on ANP and made empirical analysis on it with Super Decision Software. The results we got offered a reference for IT project investment risk management.

What are the investment risk differences of solar PV power generation projects between constructional and operational periods? An empirical study in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liping Ding ◽  
Jiangshan Li ◽  
Yuqing Wang ◽  
Jing Shuai ◽  
Xinxin Xu
Keyword(s):  
Risk Factors ◽  
Power Generation ◽  
Risk Management ◽  
Mutual Influence ◽  
Evaluation Index System ◽  
Risk Prevention ◽  
Evaluation Index ◽  
Investment Risk ◽  
Project Investment ◽  
Content Type

Purpose Under the pressure of environment degradation and energy consumption rises, solar photovoltaic power generation (SPPG) has been seen as a strategic emerging industry in China. However, the SPPG projects have many uncertain factors in the process of the life cycle. The purpose of this paper is to evaluate the investment risk comprehensively. Design/methodology/approach Specifically, this paper firstly identified the risk factors and consequences of SPPG project investment and constructed the investment risk factor evaluation index system. Secondly, the factor analysis method was used to reveal the key investment risk factors and risk consequences. Then, the research hypotheses and conceptual model were proposed, and the empirical analysis was conducted based on the structural equation model (SEM). Findings The results showed that the six key risk factors (political, economic, technological, management, market and natural) have a significant impact on the risks during the whole period. The influence degree of risk factors in the operational period is such that market factor > political factor > economic factor > management factor > natural factor > technical factor. In addition, the risk of constructional period has a significant impact during the risk of operational period. Except for natural factors, all risk factors are correlated among the mutual influence relationship of risk factors. Finally, this paper puts forward management implications based on the above conclusions: effectively identify investment risk factors and comprehensively improve risk management ability; (refine the risk factors of SPPG project investment and develop targeted risk prevention and control strategies; define risk management objectives and make relevant strategic plans. Research limitations/implications Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. Practical implications It can also help stakeholders propose risk prevention strategies throughout the entire process, to promote the sustainable development of SPPG projects. Originality/value This study focuses on the investment risk of SPPG projects, by building an evaluation index system to identify key risk factors, and then establishes a SEM covering constructional period risks and operational period risks to better explore SPPG project risks, in an effort to reveal the mutual influence relationship and influence path of investment risk factors of the projects.

scholarly journals A COMPUTERIZED RISK EVALUATION MODEL FOR PUBLIC-PRIVATE PARTNERSHIP (PPP) PROJECTS AND ITS APPLICATION

2012 ◽  
Vol 16 (3) ◽  
pp. 277-297 ◽  
Author(s):  
Yelin Xu ◽  
Yujie Lu ◽  
Albert P. C. Chan ◽  
Miroslaw J. Skibniewski ◽  
John F. Y. Yeung
Keyword(s):  
Risk Factors ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Risk Level ◽  
Illustrative Case ◽  
Fuzzy Synthetic Evaluation ◽  
Support Tool ◽  
The Third ◽  
Third Stage ◽  
Risk Evaluation Model

PPP projects usually involve more risks than other traditional procurement models because of their complexity. This paper presents the third stage of a funded study, which aims to develop a practical and computerized risk evaluation model for PPP projects. In the first and second stages, a risk hierarchal structure composed of 17 weighted risk factors is developed to describe risk profiles of PPP projects. The weightings and membership functions for risk factors are established using the Delphi survey technique and Fuzzy Set Theory. The risk evaluation model is then developed using a fuzzy synthetic evaluation approach. In the third stage, an automated decision support tool based on the risk evaluation model is designed for PPP practitioners by using Visual Basic for Application (VBA). The computerized tool can not only assist PPP participants to assess a PPP project's overall risk level for auxiliary investment decision, but can also help practitioners to identify the most risky areas of a PPP project for effective risk response. To demonstrate the applicability of the computerized model, an illustrative case is finally provided.

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