An AHP/TOPSIS-Based Approach for an Optimal Site Selection of a Commercial Opening Utilizing GeoSpatial Data

One of the most important factors in the success of a business is its location, therefore the problem of identifying an optimal site for a new commercial opening has remained the focus of the research community. The ideal business site depends on many criteria including competitors, ease of access, traffic condition, etc. Precisely, optimal business site selection is a Multi Criteria Decision Making (MCDM) problem, which deals with the selection of the best alternative from several potential candidates based on several criteria. In this work we present an AHP/TOPSIS hybrid approach to identify an optimal site for a commercial opening, given a set a candidate sites. Both the AHP and TOPSIS are MCDM methods, however the hybrid approach is chosen as it results in the reduction of the computational complexity, and the reduction in the manual effort required in the construction of the AHP pairwise comparison matrices. The proposed approach ranks all the candidate sites based on their performance scores and the candidate with the highest score is identified as the optimal site. A nexus of complex factors such as competition in the area, traffic conditions, and area popularity are considered for ranking the candidates, where the factor values are computed with the assistance of real GeoSpatial data. The proposed approach is flexible and can effectively incorporate any number of factors to rank the candidates. The effectiveness of the proposed approach is proved with the help of a case study to identify an optimal location for a new gas station in the New York City.

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