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Applying Multi-Dimensional Pattern Analysis of S ubway Passenger Usage Datamarts to Enhance Customer Service

광운대학교 디지털경영연구소
Publication Date
  • 데이터마트
  • Olap
  • 다차원모델링
  • 비즈니스 인텔리전스
  • 업무성과측정
  • Data Mar
  • Olap
  • Performance Measurement
  • Multi-Dimensional Analysis Model
  • Business Intelligence


The Seoul Metropolitan Rapid Transit Corporation (SMRT), which manages the city's four second-generation subway lines, has implemented data marts to analyze the usage patterns of its passengers. this report describes the multidimensional modeling undertaken, the resulting models constituting the passenger usage pattern analysis system, and the managerial impacts of this system. After implementing data marts, SMRT has been able to analyze traditional KPIs including basic on-off passenger ratios (involving the number of passengers boarding and disembarking at a given station), to explore these on-off ratios from a greater variety of perspectives than ever before, and to consider totally new KPIs (such as the contribution ratio of each ticket type and the contribution ratio of each station) in various dimensions (time, day, year, station, and ticket type). Through this system SMRT has been able to understand its passengers more throughly. On the basis of this deeper understanding, SMRT will be able to provide more passenger-centric services and policies.

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