Study of system dynamics for urban housing development in Hong Kong

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Study of system dynamics for urban housing development in Hong Kong

 

Author: Hu, Yucun
Title: Study of system dynamics for urban housing development in Hong Kong
Degree: Ph.D.
Year: 2003
Subject: Hong Kong Polytechnic University -- Dissertations
Housing development -- China -- Hong Kong
Public housing -- China -- Hong Kong
Department: Dept. of Building and Real Estate
Pages: 1, 214 leaves : ill. ; 30 cm.
InnoPac Record: http://library.polyu.edu.hk/record=b1701142
URI: http://theses.lib.polyu.edu.hk/handle/200/5562
Abstract: As a metropolitan city, Hong Kong is a nice and over-crowded place. One of the main characteristics of the city is the huge population and very limited land. Because of this, the real estate industry pLays an important role in the whole economy of the city. As an important component of the property market, any change in the housing market can have significant impact on the society, the economy, and many families. Can Hong Kong maintain a stable and healthy development of the housing industry? A key to this is whether or not an appropriate development plan can be prepared. The plan should be based on a comprehensive and accurate assessment of housing demand in the future. The purpose of this study is to establish a descriptive simulation model for Hong Kong urban housing development based on "Systems Thinking". It uses System Dynamics (SD) method as a tool to illustrate the relations and interactions among corresponding factors in urban housing development. The model establishes the quantitative relationship between several sub-systems, and the major factors that affect urban housing development. The computer simulation results can be used as a basis for investment decisions in urban housing development. The model established in this research project simulates the demand and development trend of the housing industry in Hong Kong. The prediction of the demand for housing involves judgement as well as monitoring a moving target, because demand varies according to economic conditions, population migration, as well as policies that may create housing demands. In order to investigate the development in the future, it is necessary to devise a model that can produce an accurate estimate of future demand at any time. Essentially this model contains a series of equations, which are supported by a number of reasonable assumptions, policy parameters, and dates in order to produce a simulation result of the demand trend in the years ahead. If parameters change, the model can be used again to simulate the new results easily by taking into account the latest situation. The simulated results show that the system dynamics method can be used to forecast housing demand in Hong Kong successfully. The model in this thesis is created using the System Dynamics methodology and is built with the interactive ITHINK software package. The model significantly improves the quality of decisions in urban housing development through simulations and analysis. The model also incorporates several new features, including the ability to simulate the effect of different policies and resource allocations, which makes it useful for practitioners in the housing industry. This project has explored the feasibility of using system dynamics to solve real problems and show how problems of big complexity could be dealt with. The proposed model can be a useful tool for policymakers in their housing-related decision-making. The "policymakers" are persons who make decisions on land use, market development, and investment scale etc. For example, government officials, main officers in related departments, and the senior managers of property companies are all considered as policymakers. The result of this project has also shown that other industries can benefit from developing a similar tool that simulates the dynamic forces that affect organisational performance. The model can be used to help develop strategies, policies and resource allocations for a firm operating under various competitive environments.

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