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Juanjuan Suo

Bio: Juanjuan Suo is an academic researcher from Hebei University of Engineering. The author has contributed to research in topics: Investment (macroeconomics) & Risk management. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.

Papers
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Proceedings ArticleDOI
14 Aug 2009
TL;DR: A new model based on the AHM (Analytic hierarchical model) and the fuzzy comprehensive evaluation and it has significance in theory and practice for the risk management of investment.
Abstract: To find an effective method to deal with the uncertainty of the risk management of real estate investment, a new model based on the AHM (Analytic hierarchical model) and the fuzzy comprehensive evaluation was proposed. After the establishment of the index system, the AHM was employed to determine the weight of every index, and the value of the risk was obtained by using the fuzzy set. Engineering practice showed the rationality of the method. This study provides a promising approach for the risk evaluation of real estate investment and it has significance in theory and practice for the risk management of investment.

5 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping is developed, which allows cause and effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions.
Abstract: Risk analysis of residential real estate investments requires careful analysis of certain variables (or determinants). Because real estate is a key sector for economic and social development, this risk analysis is seen as critical in supporting decision processes relating to buying or selling residential properties, partly due to the pressures caused by the current economic environment. This study aims to develop a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping. This fuzzy model allows cause-and-effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions. The results show that the use of cognitive maps reduces the number of omitted criteria and favors learning with regard to how the criteria relate to each other, holding great potential and versatility in structuring complex decision problems. Practical implications, strengths and weaknesses of our proposal a...

57 citations

Journal ArticleDOI
01 Dec 1929

10 citations

Book ChapterDOI
01 Dec 2012
TL;DR: In this article, the authors proposed a risk-based decision-making framework for risk analysis of investment in the real estate industry, based on a review of the research, which comprises the basic concepts, process, sources and factors, techniques/approaches, and issues and challenges of RBDM.
Abstract: Investment in the real estate industry is subject to high risk, especially when there are a large number of uncertainty factors in a project. Risk analysis has been widely used to make decisions for real estate investment. Accordingly, risk-based decision making is a vital process that should be considered when a list of projects and constraints are being assessed. This chapter proposes a risk-based decision making (RBDM) framework for risk analysis of investment in the real estate industry, based on a review of the research. The framework comprises the basic concepts, process, sources and factors, techniques/approaches, and issues and challenges of RBDM. The framework can be applied to problem solving different issues involved in the decision making process when risk is a factor. Decision makers need to understand the terms and concepts of their problems and be familiar with the processes involved in decision making. They also need to know the source of their problems and the relevant factors involved before selecting the best and most suitable technique to apply to solve their problems. Furthermore, decision makers need to recognize the issues and challenges related to their problems to mitigate future risk by monitoring and controlling risk sources and factors. This framework provides a comprehensive analysis of risk-based decision making and supports decision makers to enable them to achieve optimal decisions.

5 citations

Journal Article
TL;DR: A new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach is proposed.
Abstract: Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert’s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts’ experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper. Keywords—Uncertainty factors, data mining, multidimensional data model, risk analysis.

3 citations

01 Jan 2011
TL;DR: A new personalized multidimensional process (PMP) framework based on knowledge discovery is proposed which will be based on deterministic approach using historical data driven to decision support using knowledge discovery in database and the heuristic approach which is refers to investors’ personalization of the risk factors which fulfil their requirements.
Abstract: The risk analysis for real estate property investment is subject to high risk. It is qualitatively and quantitatively assessed by various techniques such as the analytical hierarchy process (AHP) and the analytic network process (ANP) which determine the risk factors based on expert survey, weight and rank the factors using algorithm and mathematical formula and decide the best investment based on performance index of the alternatives given. However, experts from the field have different opinions and judgments about the environment of the real estate industry and this scenario will affect the result of the risk factor weight and ranking. Moreover, different investors have different goals and objectives to be achieve. Thus, this paper will propose a new personalized multidimensional process (PMP) framework based on knowledge discovery. This framework comprises of two new methods namely the personalized association mapping (PAM) method and the personalized multidimensional – sensitivity analysis (PMSA) method. The innovations of this research are the justification of risk factor weight and ranking. It will be based on deterministic approach using historical data driven to decision support using knowledge discovery in database and the heuristic approach which is refers to investors’ personalization of the risk factors which fulfil their requirements.

3 citations