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Locating an ambulance base by using social media: a case study in Bangkok

Author

Listed:
  • Suriyaphong Nilsang

    (King Mongkut’s Institute of Technology Ladkrabang)

  • Chumpol Yuangyai

    (King Mongkut’s Institute of Technology Ladkrabang)

  • Chen-Yang Cheng

    (National Taipei University of Technology)

  • Udom Janjarassuk

    (King Mongkut’s Institute of Technology Ladkrabang)

Abstract

Response time reduction is a fundamental aspect of ambulance location management. To minimize patient mortality and disability, the response time of emergency medical services is critical. Therefore, real-time management is required to determine the location of an ambulance with a low response time or called or a dynamic allocation system. Dynamic allocation is moving the ambulance bases from low demand areas to high-demand areas that is useful in the operational level. However, the dynamic allocation model for real-time management requires re-allocation of ambulances, resulting in high costs and heavy workloads for the ambulance crews. This paper focuses on a covering model based on social media analysis. The model was used for developing an ambulance reallocation system. In addition to dynamic allocation, the proposed model considers real-time data from a social media application (Twitter) to minimize the response time and cost during emergencies and disasters. Twitter has been used in various ways to communicate during and manage emergencies. In this paper, we formulate the Maximal Covering Location Problem (MCLP), develop a solution procedure based on social media (Twitter application) and show the effect of the approach on the optimal solution by comparing it with the classical approach and also demonstrate our approach on Bangkok EMS.

Suggested Citation

  • Suriyaphong Nilsang & Chumpol Yuangyai & Chen-Yang Cheng & Udom Janjarassuk, 2019. "Locating an ambulance base by using social media: a case study in Bangkok," Annals of Operations Research, Springer, vol. 283(1), pages 497-516, December.
  • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-018-2918-8
    DOI: 10.1007/s10479-018-2918-8
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    References listed on IDEAS

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    1. Taiga Saito & Shivam Gupta, 2022. "Big Data Applications with Theoretical Models and Social Media in Financial Management," CIRJE F-Series CIRJE-F-1205, CIRJE, Faculty of Economics, University of Tokyo.
    2. Taiga Saito & Shivam Gupta, 2022. "Big data applications with theoretical models and social media in financial management," CARF F-Series CARF-F-550, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

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