基于模糊综合评价方法的房地产决策研究

Research on Real Estate Decision Making Based on Fuzzy Comprehensive Evaluation Method

摘要: 房地产公司正在面临着极端天气带来的危机。近年来，全球经历了“来自1000多次极端天气事件的1000多亿美元的损失”，因此对城市进行房地产建设可行性评价有着至关重要的作用。本文首先使用麦肯锡逻辑树分析法确定出影响房地产公司决策的各项指标，然后根据已经收集的中国北京，德国柏林，摩洛哥卡萨布兰卡的历史气温数据使用SPSS专家建模器进行时间序列预测，得出三个城市在2024~2029年中月平均气温在30˚C以上的次数，并将其作为未来气候风险这一指标的评价依据，最后采用模糊综合评价方法建立房地产建设决策模型，使用熵权法确定各指标权重，计算出综合评判向量。最终结果表明本文建立的房地产决策模型是有效的，具有一定的创新性，可以为房地产开发商提供决策依据。

Abstract: Real estate companies are facing a crisis brought on by extreme weather. In recent years, the world has experienced “more than $100 billion in losses from more than 1000 extreme weather events”, so it is crucial to evaluate the feasibility of real estate construction in cities. In this paper, the McKinsey Logic Tree Analysis is used to determine the indicators affecting the decision-making of real estate companies. Then, based on the collected historical temperature data of Beijing (China), Berlin (Germany), and Casablanca (Morocco), the time-series prediction is made using the SPSS Expert Modeller to find out the number of times that the average monthly temperature of the three cities will be above 30˚C in the period of 2024~2029, which will be used as the basis for the evaluation of the indicator of future climate risk. The evaluation of this indicator of future climate risk is based on the fuzzy comprehensive evaluation method to establish a decision-making model for real estate construction, and the entropy weighting method is used to determine the weights of each indicator and calculate the comprehensive judgement vector. The final results show that the real estate decision-making model established in this paper is effective and innovative, and can provide a decision-making basis for real estate developers.