臺北市咖啡廳選址區位因子的空間分析研究

Abstract

咖啡廳為城市中兼具情感與經濟價值的重要場域，其空間分布不僅反映都市生活型態，更具備衡量都市活力的潛在意涵。本研究以臺北市為範圍，整合地理資訊系統（Geographic Information System, GIS）與空間計量模型，探討不同類型咖啡廳之空間分布特性與選址因子。本研究首先依據品牌規模與售價，將咖啡廳劃分為連鎖咖啡廳、獨立咖啡廳、平價連鎖與高價連鎖共四類，並建構500公尺矩形空間網格作為分析單元。解釋變數方面，整合交通、人流、商業活動、房價與設施吸引力等因子進行模型建構。研究流程以探索式空間資料分析（Exploratory Spatial Data Analysis, ESDA）辨識咖啡廳聚集特徵與空間離群區，並透過普通最小平方法（Ordinary Least Squares, OLS）與空間滯後模型（Spatial Lag Model, SLM）進行推論建模。研究結果指出，臺北市咖啡廳普遍青睞商業活動強度高的區域，傾向鄰近金融機構、辦公商業大樓及商圈等因子；且多聚集在捷運步行5分鐘範圍，注重交通可及性，同時仰賴捷運及公車所帶來的人流。此外也偏好在大學附近設址，除上班族外也重視年輕消費客群。在細部區位策略上，獨立咖啡廳則聚集多元生活圈，其倚重居住人口的特性與連鎖咖啡廳呈現差異；而高價品牌鎖定百貨公司周圍及高端消費場域，與平價品牌形成對比。Coffee shops serve as vital urban spaces that integrate emotional and economic value. Their spatial distribution not only reflects patterns of urban lifestyles but also holds potential as an indicator of urban vitality. Focusing on Taipei City, this study integrates Geographic Information Systems（GIS）and spatial econometric models to investigate the spatial distribution characteristics and location factors of different coffee shop types.Employing a classification based on brand scale and pricing, coffee shops were categorized into four types: chain stores, independent cafés, budget chains, and premium chains. A 500-meter rectangular grid system was constructed as the spatial analysis unit. Explanatory variables included factors such as transportation accessibility, pedestrian flow, commercial activity, housing prices, and s attraction facilities. The analytical workflow began with Exploratory Spatial Data Analysis (ESDA) to identify spatial clusters and outliers, followed by inferential modeling using Ordinary Least Squares (OLS) and Spatial Lag Models (SLM).Key findings reveal that coffee shops in Taipei exhibit a strong preference for areas with high commercial intensity, particularly near financial institutions, office buildings, and commercial districts. Most are concentrated within a five-minute walking distance from metro stations, indicating a strong emphasis on transportation accessibility and reliance on both metro and bus-generated foot traffic. University proximity also plays a role, highlighting the targeting of both professionals and younger demographics. Notably, independent cafés cluster in mixed-use residential zones, contrasting with chain stores that prioritize commercial hubs. Premium chains favor locations near department stores and high-end commercial districts, diverging from budget chains.