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Real-Time Monitoring of Intercity Passenger Flows Based on Big Data: A Decision Support Tool for Urban Sustainability

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  • Zheng Li

    (School of Business, Xi'an Eurasia University, Xi'an, China)

  • Yan Wang

    (School of Business, Xi'an Eurasia University, Xi'an, China)

  • Qin Chen

    (BBD Index, Business Big Data (BBD), Chengdu, China)

Abstract

Managing population mobility is a key to urban growth and sustainable development. This study uses administrative and business data from a number of trustworthy and publicly-available websites for public transport to access passenger flows in a real-time manner. A case study is used to illustrate the application, with intercity passenger flows by public transport mode (rail or air), by rail service type and by time. Moreover, a model is developed for monitoring the implications of population movements, which can be a decision support tool for governments and policy makers to manage population mobility. The big-data approach to accessing public transport passenger movement has the following characteristics: (1) low cost, (2) a population scale, (3) instantaneous data collection/update, and (4) high quality.

Suggested Citation

  • Zheng Li & Yan Wang & Qin Chen, 2017. "Real-Time Monitoring of Intercity Passenger Flows Based on Big Data: A Decision Support Tool for Urban Sustainability," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 8(4), pages 120-128, October.
  • Handle: RePEc:igg:jsds00:v:8:y:2017:i:4:p:120-128
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