面對詭譎多變的都市住宅市場，反波動策略施以經驗為本、試誤法為之，怠忽市場的反轉力道與後續波動效應，策略效能與適宜性常成為爭議焦點！究其因，由於缺乏周延系統思維，無法明晰市場運作階段性影響要因，且未建構都市住宅市場動態模擬模式，無以進行演變趨勢探討、敏感性變數分析、策略情境模擬及政策評價。本研究視都市住宅市場為一系統，以系統思維方法為核心，結合模糊德爾菲法、系統動態學因果圖示法，剖析都市住宅市場運作機制，彙整都市住宅市場指標體系，探討市場系統變數間因果關係，應用衝擊矩陣進行系統敏感性變數分析，辨識及確認系統影響關鍵變數。結果顯示系統思維協同研究可以完善都市住宅市場運作指標體系建構、因果關係界定及關鍵變數識別；建議儘速建構都市型住宅市場運作監測系統，設置「都市住宅市場系統動態運作模擬實驗室」，開展都市住宅市場動態運作模型及其應用研究，進行多重策略情境模擬，落實住宅市場政策尋優，提昇都市住宅市場風險防制，強化資源有效利用，促進都市住宅市場健全發展。

Facing the ever changing urban housing market, we are unable to understand the interim key factors which affect the operation of the market due to lack of systems thinking. Without simulation mode of dynamic housing market, we are unable to probe its development trends, analyze the sensibility, simulate the strategic scenario, or make a policy evaluation. Anti-fluctuation strategy is based on experience, and is carried out by means of Try and Error method. However, it always becomes a controversial issue to ignore the market reversal force, its subsequent fluctuation effect and the suitability of the strategy! In this research, the urban housing market was regarded as one system. The systems thinking approach was employed as the axis. Fuzzy Delphi method and system dynamics were integrated to analyze the operational mechanism of urban housing market. Indicator systems of urban housing market were collected to probe into the relation between cause and effect for the variables of the market systems. Impact matrix was adopted to conduct the variable analysis for the system sensibility in order to verify and identify the key variables which affected the systems. The findings showed that the systems thinking and the collaborative research could perfect the operation of urban housing market, construct the indicator systems, define the relation between cause and effect, and identify the key variables. Therefore, it is suggested that a monitoring system for the operation of urban type housing market should be established as soon as possible. Besides, a simulation laboratory of system dynamic operation for urban housing market should be set up so as to make a dynamic operation mode for urban housing market, and apply the mode to conduct a variety of strategic scenario simulations. Thus, policy optimization of housing market is practicable.