A geospatial analytics approach to delineate trade areas for Quick Service Restaurants (QSR) in Singapore

• المؤلف الرئيسي: LIM, Hui Ting
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2020
• الموضوعات: Geospatial Analytics; Spatial Lagged Sum; Spatially Constrained Clustering; Trade Area Delineation; MITB student; Numerical Analysis and Scientific Computing; Sales and Merchandising
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/5918; https://ink.library.smu.edu.sg/context/sis_research/article/6921/viewcontent/3397536.3428352.pdf

According to Huff, trade area is defined as “a geographically delineated region containing potential customers for whom there exists a probability greater than zero of their purchasing a given class of products or services offered for sale by a particular firm or by a particular agglomeration of firms”. Several methods to delineate a store trade area have been proposed over the years. For drive-time or travel distance analysis method, the trade area is delineated according to how far or how long the customers are willing to travel to patronise the store. Another commonly used method is the Huff Model which assumes that consumer decisions are probabilistic and not deterministic. This model derived the probability (p_ij) that a consumer at location j will patronize the store in location i. In ArcGIS Network Analyst, the location-allocation function helped to find the optimal locations for facilities to serve a set of demand points base on the user-defined objective such as maximising market share.