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篇名 共享住宿空間分布影響因素之探討-以臺北市Airbnb為例
卷期 51:1
並列篇名 The Influence of Factors the Spatial Pattern of Accommodation Sharing: A Case Study of Airbnb in Taipei City
作者 呂政孝鄭皓騰
頁次 001-028
關鍵字 共享住宿空間土地使用分區管制多重尺度地理加權迴歸Sharing AccommodationZoningMultiscale Geographically Weighted RegressionTSSCI
出刊日期 202403
DOI 10.6128/CP.202403_51(1).0001

中文摘要

共享住宿空間興起促使都市空間活動分布發生移轉,與既有都市規劃是否存在潛在衝突成為近代重要議題。在考量既有商業發展、觀光產業、交通便捷度與地區社經條件等多元條件下,其空間分布特性可視為決策者願意投入市場的行為表徵,而與既有都市空間規劃產生不同的影響。因此,國內外研究仍處於初探階段而影響因素尚待釐清,在缺乏對計畫因素的考量下,多著重於以決策者角度預測共享住宿的空間分布。本研究目的為探討共享住宿空間分布之影響因素,包含使用社經環境條件、商業發展程度、交通便利程度、都市觀光景點與土地使用分區管制五大項目共13個變數,解析其因果關係。考量議題具空間聚集現象下運用多元迴歸分析與多重尺度地理加權迴歸進行因果關係之探討與比較,並以共享住宿空間數量最多的臺北市為實證地區。研究發現公告地價與整體住商混合比例對整體共享住宿空間分布具正面影響;空間自相關高的單元中,零售業者家數、景點涵蓋範圍數高者有正面影響;空間自相關低的單元中,公告地價高有正面影響。根據本研究成果,都市規劃者得以據此掌握共享住宿空間分布影響因素之特性,尤其對土地使用分區管制與允許使用標準檢討上能有所有助益,作為未來都市空間規劃策略布局參考。

英文摘要

The booming of sharing accommodation has caused a spatial shift in the urban activities, which may potentially conflict with existing urban planning and thus become an urgent issue. Considering commercial development, tourism industry, transportation, and socioeconomic factors, the spatial distribution of sharing accommodation reflects the investor's willingness of sharing accommodation. However, since current study is still at the exploratory phase, the correlation of the influence factors needs to be clarified. Considering the spatial clustering, we use multiple regression analysis and multiscale geographically weighted regression to measure and compare the relationship of the sharing accommodation and its influence factors in Taipei City, which embraces the largest number of sharing accommodation. Thirteen representative variables concerning socioeconomic environment, commercial development, public transport convenience, city tourist attractions, and zoning are selected to explore the causal relationship. Results reveals that the assessed land value and the mixed ratio of residential and commercial zoning causes a positive impact on the overall distribution of sharing accommodation; among the units with high-high spatial autocorrelation, the number of retail businesses and the number of sightseeing spots area are positive impact factors; among the units with low-low spatial autocorrelation, the assessed land value has a positive impact. Planners can get more information about the characteristics of the influence factors for the sharing accommodation distribution, especially in the influence of zoning, which can serve as a reference for planning strategies.

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