2016
DOI: 10.5194/isprs-archives-xlii-4-w1-1-2016
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3d Geomarketing Segmentation: A Higher Spatial Dimension Planning Perspective

Abstract: ABSTRACT:Geomarketing is a discipline which uses geographic information in the process of planning and implementation of marketing activities. It can be used in any aspect of the marketing such as price, promotion or geo targeting. The analysis of geomarketing data use a huge data pool such as location residential areas, topography, it also analyzes demographic information such as age, genre, annual income and lifestyle. This information can help users to develop successful promotional campaigns in order to ac… Show more

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Cited by 18 publications
(9 citation statements)
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“…k -Means can be considered the most popular clustering algorithm due to its simplicity. Previous studies have adopted the k -means algorithm for different applications, such as geo-marketing (Azri et al, 2016b), database organization (Azri et al, 2016a), wireless sensor framework (Azri et al, 2019) and location-allocation problem (Kim et al, 2018). However, the drawback of k -means is that it is a NP hard problem (García et al, 2018; Tîrnăucă et al, 2018; Wang et al, 2019).…”
Section: Methodsmentioning
confidence: 99%
“…k -Means can be considered the most popular clustering algorithm due to its simplicity. Previous studies have adopted the k -means algorithm for different applications, such as geo-marketing (Azri et al, 2016b), database organization (Azri et al, 2016a), wireless sensor framework (Azri et al, 2019) and location-allocation problem (Kim et al, 2018). However, the drawback of k -means is that it is a NP hard problem (García et al, 2018; Tîrnăucă et al, 2018; Wang et al, 2019).…”
Section: Methodsmentioning
confidence: 99%
“…The mapping of data can allow spatial trends to become more apparent to a retail practitioner, and the QSR sector has leveraged this information to gain insight into spatial market trends (Anselin, 2003;Church, 2002;Murray, 2010). GIS can help answer spatial questions concerning where customers live, their purchasing power, where competitors are located, and the potential impact on store market share (Aboulola, 2018;Suhaibah et al, 2016). Trade area creation models can be orchestrated using GIS programs such as ArcMap which produce quantitative results as well as visual maps which help practitioners more easily understand spatial trends (Aboulola, 2018;Bas and Gulersoy, 2018;Suhaibah et al, 2016).…”
Section: Using Gis As a Tool For Trade Area Analysismentioning
confidence: 99%
“…GIS can help answer spatial questions concerning where customers live, their purchasing power, where competitors are located, and the potential impact on store market share (Aboulola, 2018;Suhaibah et al, 2016). Trade area creation models can be orchestrated using GIS programs such as ArcMap which produce quantitative results as well as visual maps which help practitioners more easily understand spatial trends (Aboulola, 2018;Bas and Gulersoy, 2018;Suhaibah et al, 2016).…”
Section: Using Gis As a Tool For Trade Area Analysismentioning
confidence: 99%
“…However, the process runs the risk of overlapping clusters, making geospatial analysis inefficient. Suhaibah et al (2016) use a variant of the k-means algorithm, called k-means ++; this variation prevents overlapping of the clusters, allowing the existence of boundary clusters. k-means ++ achieves an adequate initialization in a primary set of centers for k-means through a random seeding.…”
Section: Clustersmentioning
confidence: 99%