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題 名 | 結合模糊語意方法與多項Logit模式應用於透天住宅家戶購屋區位選擇行為之研究=A Study of Fuzzy Linguistic Approach and Multinomial Logit Model for Applying Single Unit Housing Location Choice Behavior in Household Purchase |
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作 者 | 連經宇; 陳彥仲; | 書刊名 | 玄奘管理學報 |
卷 期 | 2:2 2005.03[民94.03] |
頁 次 | 頁1-39 |
分類號 | 542.6 |
關鍵詞 | 區位選擇; 多項Logit模式; 模糊語意尺度法; Location choice; Multinomial logit model; Fuzzy linguistic scale; FLS; |
語 文 | 中文(Chinese) |
中文摘要 | 由於家戶在進行住宅區位選擇時通常包含甚為複雜的過程,其中隱含的不確定性甚高。加以消費者對自身需求並非明確具體,而其主觀感認的模糊性,欲取得明確的資訊實際土是非常困難的。本研究主要目的在建立一個更趨近於人類主觀知覺(subjective perception)的真實行為可處理語意變數之家戶購屋區位選擇行為模式,以作為試圖改造Logit模式在家戶住宅個體區位選擇行為研究中對於模糊性與不確定性問題的處理。本研究首度嘗試譜曲傳統不連續選擇理論中的Logit模式結合改良後的模糊語意尺度法(FuzzyLinguistic Scale, FLLM)來推估家戶住宅區位選擇之機率,以建構「在模糊語意下的Logit模式(FuzzyLinguistic Logit Model, FLLM)」。 在實證分析方面,本研究以透天住宅家戶購屋區位選擇行為之影響效果為例,實證資料選自於1998年初至1999年底台南都市地區的透天住宅購屋家戶住宅調查。經由實證結果發現,本研究所建立的在模糊語意下之透天住宅區位選擇個體行為分析模式,無論模式的配過能力、預測成功率、期望需求彈性與概似比統計量檢定等相關統計與經濟指標的意義上,在模糊語意下的多項Logit模式皆較傳統多項Logit模式為佳。其次,本研究所建立的在模糊語意下多項Logit模式在遑論與實務應用上,將可以解決傳統住宅選擇個體計量經濟模式中具模糊性與不確定性的解釋變數處理的問題,並可作為協助具質化資料與量化分析方法整合的重要參考。 |
英文摘要 | During households’ housing choice behavior, it includes a very complex and uncertain process. It is very difficult to get certain information on households’ housing choice behavior. The main purpose of this study is to purpose a new micro-choice behavior model in household purchase and to depict the reality of human subjective perception behavior. We hope to improve the multinomial Logit model in dealing with many uncertain and fuzzy situations about housìng choice behavior in household purchase. A new Fuzzy LinguisticLogit Model (FLLM) is proposed in this study to estate the probability of housing choice according to the Logit models of discrete choice theory combined with the well-developed Fuzzy LinguisticScale (FLS) approach. In empirical analysis, this study will give instances for the effects of single unit housing location choice behavior in household purchase. We selected data from a housing survey in Tainan city of the southeen Taiwan for the empirical case study from the beginning of 1998 to the end of 1999. The research results show the following two parts. First, in the comparison of different methodologies: the first finding of this study is that after comparing the different models, the goodness-of-fit, success rate of forecasting, expected demand elasticity and likelihood statistic test in FLLM are all better than those in Logit model. The second finding of this study is that the new model is proposed to be more capable of dealing with the problem of qualitative variables, which is one of the critical issues in quantitative approaches. |
本系統中英文摘要資訊取自各篇刊載內容。