2022
DOI: 10.1155/2022/1108105
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RFM Model and K-Means Clustering Analysis of Transit Traveller Profiles: A Case Study

Abstract: Public transportation users increase as the population grows. In Taipei, Taiwan, this tendency is observed by analyzing historical data from the Mass Rapid Transit (MRT) and economy-shared bicycle (known as YouBike) riders. While this trend exists, the Taipei City government promotes green transportation by providing discounts to users who transfer from MRT or bus to YouBike within a particular period. Therefore, this study focuses on analyzing the patterns of users in order to identify possible clusters. Clus… Show more

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Cited by 5 publications
(3 citation statements)
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“…In the literature, RFM Model and the K-means algorithm are widely used for customer segmentation [1][2][3][4][5][6][8][9][10][11][12][13][14]. Zhao et al [1] combined both methods and the additional Apriori algorithm to segment customers and provided a recommendation system using historical sales data.…”
Section: Related Workmentioning
confidence: 99%
See 2 more Smart Citations
“…In the literature, RFM Model and the K-means algorithm are widely used for customer segmentation [1][2][3][4][5][6][8][9][10][11][12][13][14]. Zhao et al [1] combined both methods and the additional Apriori algorithm to segment customers and provided a recommendation system using historical sales data.…”
Section: Related Workmentioning
confidence: 99%
“…Huang et al [11] improved the RFM model by extending the community (C) dimension to represent community relations to introduce the value of social interaction to the educational ecommerce system and achieved accuracy by the modification. Chen et al [9] investigated the travel patterns of using public transport via subway and bike-sharing using the RFM model and K-means clustering.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation