Data-driven retail decision-making using spatial partitioning and delineation of communities

Urbanisation is resulting in rapid growth in road networks within cities. The evolution of road networks can be indicative of a city's economic growth and it is a field of research gaining prominence in recent years. This paper proposes a framework for spatial partition of large scale road netw...

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Bibliographic Details
Main Authors: TAN, Ming Hui, TAN, Kar Way
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
H3
Online Access:https://ink.library.smu.edu.sg/sis_research/7199
https://ink.library.smu.edu.sg/context/sis_research/article/8202/viewcontent/Community_Detection_PACIS2022.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Urbanisation is resulting in rapid growth in road networks within cities. The evolution of road networks can be indicative of a city's economic growth and it is a field of research gaining prominence in recent years. This paper proposes a framework for spatial partition of large scale road networks that produces appropriately sized geospatial units in order to identify the type of community they serve. To this end, we have developed a three-stage procedure which first partitions the road network using Louvain method, followed by outlining the boundary of each partition using Uber H3 grids before classifying each partition using K-means clustering. Experimental results in Da Nang, Vietnam, show that the proposed method can partition and classify a large scale road network into various community types.