Modeling the investment strategy of commercial real estate in China

Abstract

Lack of reliable valuation data, risk of making a poor investment, macroeconomic uncertainty, and difficulty determining the best opportunities are the common conditions and problems for all investors in commercial real estate (CRE) in the current Chinese real estate industry. The current investment decision-making process for commercial real estate in China is usually based on predictions which are evaluated according to a variety of financial criteria. Investment results sometimes fall short of expectations even when the operating process and capital requirements of the financial prediction are satisfied. The main reason for the uncontrollable results is the lack of consideration given the external and internal influences on commercial real estate in China. At present, there is no systematic method of analysis for predicting investment results on commercial real estate in China that accounts for and includes these influences. A systematic analysis of the external and internal influence factors and modeling a method for predicting the investment result is the main subject of this thesis. In this research, I develop a systematic analytical model which is a kind of decision making model and includes the internal and external influences on the Chinese commercial real estate market for predicting future investment results. This model uses the "Weighted Sum Model" (WSM) and Strategic Assessment Model (SAM) methods, which are "Multi-Criteria Decision Making" (MCDM) methods, and 10 case studies to identify and validate the prediction model. In this research, cross comparison and analysis of each evaluation method as applied to these 10 cases is adopted to verify the consistency of the predictive model. Based on the predictive results available from this model, investors can make decisions to invest the CRE in China or not. Furthermore, investors can understand the weaknesses and strengths of internal and external factors through use of the model. This research will help investors understand these various influence factors and how they affect investment results when making CRE investment decisions. Application of the decision making model will increase the success probability for investment in the CRE in China. The primary purpose of this research is to develop a model which can help the investor to predict investment results and navigate the currently chaotic commercial real estate market in China. The model predicts the success rate by comparing different criteria comparison among the major and subordinate external and internal factors. Based on the final conclusion of this research, integrating subordinate external and subordinate internal factors together as decision making factors will be most reliable accuracy of predictive success rate for investment in Chinese CRE. The dissertation and its forecasting model will be useful for government agencies, commercial property developers, and both institutional and individual investors in this huge and growing market.

Date of Award	16 Jul 2012
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Muammer OZER (Supervisor)