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Book ChapterDOI

Risk-Based Decision Making Framework for Investment in the Real Estate Industry

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.
Citations
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01 Jan 2003
TL;DR: In this article, a study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments, and it was found that the most influential factors affecting risk and uncertainties resulted from forecasting errors.
Abstract: A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.

36 citations

Journal ArticleDOI
01 Dec 2017
TL;DR: In this paper, the authors examined the critical risk factors that influence the private sector's investment decisions on PPP transportation projects in Vietnam and found that the most important risk factors of PPP infrastructure projects are acquisition/compensation problems, approvals and permits, inadequate feasibility studies, finance market issues, subjective evaluation methods, and change in laws and regulations.
Abstract: The rapidly increasing demand and the inefficacy of financing transportation infrastructure project investments have contributed to various challenges for Vietnam in recent decades. Since the country’s budget is inadequate for investing in all necessary infrastructure projects, the Vietnam government has been inviting other economic sectors, especially the private sector, to participate in infrastructure development. The cooperation between the government agencies and the private entities, called Public-Private Partnership (PPP), must encounter various challenges leading to difficulties in attracting private investors. A main reason is that private investors must deal with critical risks concerning PPP investment environment. It is a challenging task for the government to optimally manage such risks to enhance the attractiveness of PPP projects for private investors. This paper examines the critical risk factors that influence the private sector’s investment decisions on PPP transportation projects in Vietnam. Risk factors inherent in typical PPP projects were compiled by comprehensive literature review. To reflect unique characteristics of PPP projects in Vietnam, the compiled risk factors were reviewed by a group of PPP experts from both the public and private sectors in Vietnam through in-depth interviews and questionnaire surveys. In addition, ten PPP project case studies in Vietnam were analyzed to derive the risk profile of PPP transportation projects of the nation. These risk factors were quantitatively assessed based on their probabilities and impact levels. We found that the critical risk factors of PPP infrastructure projects in Vietnam are acquisition/compensation problems, approvals and permits, inadequate feasibility studies, finance market issues, subjective evaluation methods, and change in laws and regulations. By performing factor analysis, these critical risk factors were grouped into four categories: (1) bidding process, (2) finance issues, (3) laws and regulations, and (4) project evaluation issues. These critical risk factors represent the obstacles that repel private investors from PPP transportation projects in Vietnam. Thus, the Vietnam government agencies should meticulously address these issues to attract both domestic and foreign private investors in PPP projects.

21 citations


Cites background from "Risk-Based Decision Making Framewor..."

  • ...Risk assessment has been widely used to make investment decisions by the private sector [28]....

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Journal ArticleDOI
TL;DR: A gap analysis methodology is used to identify the gap between theory and practice in presenting information on location choice by using a seven-factor classification tool and an assessment of international property websites to suggest that real-estate websites are poor at providing sufficient location information to support efficient spatial decision making.
Abstract: Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location ...

14 citations

01 Jan 2018
TL;DR: Mixed-use developments have shown to have positive effects on areas attractiveness and have thus turned into a planning principle in Swedish urban areas as discussed by the authors, to ensure that a mix of property uses is o...
Abstract: Mixed-use developments have shown to have positive effects on areas’ attractiveness and have thus turned into a planning principle in Swedish urban areas. To ensure that a mix of property uses is o ...

2 citations


Cites background from "Risk-Based Decision Making Framewor..."

  • ...Real estate projects are therefore also subject to high risk (Demong & Lu 2012)....

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  • ...However, projects have a duration of several years where a lot can happen with the economy (Demong & Lu 2012)....

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  • ...A lot of research has been made on how the decision process is structured when investing in a new property or developing an undeveloped real estate (Demong & Lu 2012)....

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Book ChapterDOI
01 Jan 2019
TL;DR: In this article, relevanten Determinanten fur die unternehmensindividuelle Ausgestaltung des RMs konnen nach ihrer Bedeutung hierarchisch geordnet und in sechs Ebenen unterteilt werden.
Abstract: Die relevanten Determinanten fur die unternehmensindividuelle Ausgestaltung des RMs konnen nach ihrer Bedeutung hierarchisch geordnet und in sechs Ebenen unterteilt werden. Die Position der einzelnen Anforderung richtet sich dabei nach ihrer Bedeutung fur das RM in der Immobilienwirtschaft. Nach einer kurzen Erlauterung der damit einhergehenden Grunduberlegung, werden die jeweiligen Teilbereiche in den folgenden Abschnitten naher beleuchtet.

1 citations

References
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01 Jan 2011
TL;DR: In this paper, a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions is presented.
Abstract: This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol’s method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent. Mathematical modeling of complex systems often requires sensitivity analysis to determine how an output variable of interest is influenced by individual or subsets of input variables. A traditional local sensitivity analysis entails gradients or derivatives, often invoked in design optimization, describing changes in the model response due to the local variation of input. Depending on the model output, obtaining gradients or derivatives, if they exist, can be simple or difficult. In contrast, a global sensitivity analysis (GSA), increasingly becoming mainstream, characterizes how the global variation of input, due to its uncertainty, impacts the overall uncertain behavior of the model. In other words, GSA constitutes the study of how the output uncertainty from a mathematical model is divvied up, qualitatively or quantitatively, to distinct sources of input variation in the model [1].

1,296 citations

Journal ArticleDOI
TL;DR: In this article, a modified analytical hierarchy process is used to structure and prioritize diverse risk factors, and an illustrative example on risk analysis of steel erection of the superstructure in a shopping centre was used to demonstrate the proposed methodology.

484 citations

Journal ArticleDOI
TL;DR: In this paper, the authors use the Panel Study on Income Dynamics (PSI) to compare the quantitative properties of the competitive asset pricing framework with those of observed asset returns, and show that a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP can be found in a stationary overlapping generations framework.
Abstract: A number of existing studies have concluded that risk sharing allocations supported by competitive, incomplete markets equilibria are quantitatively close to first-best. Equilibrium asset prices in these models have been difficult to distinguish from those associated with a complete markets model, the counterfactual features of which have been widely documented. This paper asks if life cycle considerations, in conjunction with persistent idiosyncratic shocks which become more volatile during aggregate downturns, can reconcile the quantitative properties of the competitive asset pricing framework with those of observed asset returns. We begin by arguing that data from the Panel Study on Income Dynamics support the plausibility of such a shock process. Our estimates suggest a high degree of persistence as well as a substantial increase in idiosyncratic conditional volatility coincident with periods of low growth in U.S. GNP. When these factors are incorporated in a stationary overlapping generations framework, the implications for the returns on risky assets are substantial. Plausible parameterizations of our economy are able to generate Sharpe ratios which match those observed in U.S. data. Our economy cannot, however, account for the level of variability of stock returns, owing in large part to the specification of its production technology.

384 citations

Book
01 Jan 2007
Abstract: This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including algorithms) to solve these problems. One distinguishing feature of this book is that it provides two decision support systems software for readers to apply these proposed methods. A set of real-world applications and some new directions in this area are then described to further instruct readers how to use these methods and software in their practice.

312 citations

Journal ArticleDOI
TL;DR: This paper used a stationary overlapping-generations model to show that life-cycle effects can either mitigate or accentuate the equity premium, the critical ingredient being whether agents accumulate or deccumulate riskt assets as they age.

260 citations

Trending Questions (1)
What challenges do real estate professionals commonly encounter in decision-making?

The paper does not specifically mention the challenges that real estate professionals commonly encounter in decision-making.