Retail Site Recommendation: AI Approach for Location Analytics


Bhattacharijee, Arpita and Ting, Choo Yee and Ghauth, Khairil Imran (2022) Retail Site Recommendation: AI Approach for Location Analytics. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

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Location analytics for retail business is very challenging, especially for new retailers in the market. Retail site selection costs long-term capital investment; hence a strategic site selection method is inevitable while setting up the retail business A tactical site analysis helps to know the suitable area for a particular business which helps to attract potential customers. Demographics and Geospatial information that includes nearby competitor businesses of prospective location, age groups, education, lifestyle, profession, income, and property are considered key features for analyzing the site of a retail business.[1] The existing research shows the application of different approaches to find the optimal algorithm for recommending a business of given location data.

Item Type: Conference or Workshop Item (Poster)
Uncontrolled Keywords: Algorithm, analytics
Subjects: Q Science > QA Mathematics > QA801-939 Analytic mechanics
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 19 Dec 2022 04:24
Last Modified: 19 Dec 2022 04:24


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