第五章 、 結論與建議
第二節 、 建議
國外已廣泛的利用多層次概念從事相關實證研究，而國內在教育、管理相關 領域亦有不少的相關研究文獻。但就不動產領域而言，本研究係初次嘗試以多層 次概念來分析住宅特徵價格模型，因此，不論從文獻回顧或資料蒐集乃至於模型 設定與實證過程中，深感本研究議題仍有相當未竟之處，本節就其未竟之處提出 說明以為後續研究建議。
台灣建物種類、用途複雜性，很難界定區域邊界。而本研究曾就縣(市)地區 組內住宅價格作變異數同質性的檢定，但檢定結果顯示各縣(市)地區組內變異均 達 5%顯著水準，意味著，以各縣(市)地區劃分作為住宅價格的估計，仍隱含著 次市場的問題。也就是說，在劃定一個地區時，不動產相關特性的變化，可能顯 示必須建立更小之邊界。例如，以一個城市為例，城市中許多高層公寓建築在天 然湖岸邊，並被主要交通幹道分隔開；在此類型地區中，公寓的價格、大小、外 觀、停車容量、公共交通幹線之接近性、及屋齡等，存在著很大的差異。這些差 異可能顯示，必須再確認更小範圍的地區邊界，以反映市場及次市場之特徵。因 此，若想更進一步達到較佳的估計結果，實有必要進一步更精確的劃分次市場邊 界。例如，Goodman and Thibodeau(1998)以超過 4 萬筆的住宅交易紀錄，使用特 徵價格方程式檢驗住宅價格預測的精確度。結果發現住宅價格的評估精確度取決 於都會區內(within metropolitan area)住宅次市場之範圍。
本研究時間範圍為1998 年至 2005 年，其中住宅價格資料是以 2006 年 1 月 為基期，配合物價指數調整。因此係為橫斷面研究(cross-sectional studies)，而未 能完成縱貫研究(longitudinal studies)或趨勢研究(trend studies)。現實狀況中，隨 著時間的變動，住宅建物特徵及區域特徵對住宅價格的影響，可能有大小不一之 影響效果，甚至區域特徵與時間亦有可能產生顯著之交互影響效果，如同 Kohlhase(1991)所指出，建物的特徵的重要性會隨時間發生變化。因此爾後研究 可考量將各年份以虛擬變項置入模型第一層，並以多層次縱貫研究分析來估計住
宅價格之變動趨勢，及建物特徵之估計參數變化情形。
本研究於以平均數為結果的迴歸模型分析結果顯示，在控制總體層次變項後，
各縣(市)地區之平均住宅價格仍有顯著差異，隱含著總體層次變項除了「人口密 度」、「教育水平」與「可支配所得」之外，當另有其它影響各縣(市)平均住宅價 格之總體層次變項未被考量。本研究並未就該重要影響因素作進一步深究，亦或 許可探究造成縣(市)地區平均住宅價格差異的主要影響因素有哪些？
本研究係以個體層次與總體層次來作多層次特徵價格模型的分析，也就是僅 考量兩層的空間層級。若可進一步細分縣市或鄉鎮市地區或住宅次市場空間內，
住宅鄰里地區環境品質或公共設施對價格的影響效果，也就是可考量在縣(市)地 區特徵的影響下，住宅鄰里地區之公共設施或環境品質與住宅價格間的變化情形，
以建立三個層級或多層級的線性模式分析。
本文縣市特徵係以縣市統計資料來代表，而未將傳統代表建物特徵之可及性 納入考量。因此爾後可考量進一步結合 GIS 技術，可有效的將該等影響距離(可 及性)有效量化。多層次模型分析若能結合 GIS 技術，或可更有效的評估區位因 素的影響及量測次市場邊界，使得住宅價格估計更有效率。
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