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The Dissemination Strategy of an Urban Smart Medical Tourism Image by Big Data Analysis Technology

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  • Zijian Zhao

    (Department of Performing Arts and Culture, The Catholic University of Korea, Bucheon-si 14662, Republic of Korea
    School of Journalism and Communication, University of Chinese Academy of Social Sciences, Beijing 102488, China
    School of Communication and Film, Hong Kong Baptist University, Hong Kong 999077, China
    College of Educations, Arts and Sciences, Lyceum of the Philippines University-Batangas, Batangas 4200, Philippines)

  • Zhongwei Wang

    (Management School, The University of Sheffield, Sheffield S10 2TN, UK)

  • Javier Garcia-Campayo

    (School of Medicine, University of Zaragoza, 50009 Zaragoza, Spain
    Hospital Universitario Miguel Servet, 50009 Zaragoza, Spain)

  • Hector Monzales Perez

    (Republic of the Philippines Professional Regulation Commission, Manila 1008, Philippines)

Abstract

The advanced level of medical care is closely related to the development and popularity of a city, and it will also drive the development of tourism. The smart urban medical system based on big data analysis technology can greatly facilitate people’s lives and increase the flow of people in the city, which is of great significance to the city’s tourism image dissemination and branding. The medical system, with eight layers of architecture including access, medical cloud service governance, the medical cloud service resource, the platform’s public service, the platform’s runtime service, infrastructure, and the overall security and monitoring system of the platform, is designed based on big data analysis technology. Chengdu city is taken as an example based on big data analysis technology to position the dissemination of an urban tourism image. Quantitative analysis and questionnaire methods are used to study the effect of urban smart medical system measurement and tourism image communication positioning based on big data analysis technology. The results show that the smart medical cloud service platform of the urban smart medical system, as a public information service system, supports users in obtaining medical services through various terminal devices without geographical restrictions. The smart medical cloud realizes service aggregation and data sharing compared to the traditional isolated medical service system. Cloud computing has been used as the technical basis, making the scalability and reliability of the system have unprecedented improvements. This paper discusses how to effectively absorb, understand, and use tools in the big data environment, extract information from data, find effective information, make image communication activities accurate, reduce the cost, and improve the efficiency of city image communication. The research shows that big data analysis technology improves patients’ medical experience, improves medical efficiency, and alleviates urban medical resource allocation to a certain extent. This technology improves people’s satisfaction with the dissemination of urban tourism images, makes urban tourism image dissemination activities accurate, reduces the cost of urban tourism image dissemination, and improves the efficiency of urban tourism image dissemination. The combination of the two can provide a reference for developing urban smart medical care and disseminating a tourism image.

Suggested Citation

  • Zijian Zhao & Zhongwei Wang & Javier Garcia-Campayo & Hector Monzales Perez, 2022. "The Dissemination Strategy of an Urban Smart Medical Tourism Image by Big Data Analysis Technology," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:15330-:d:978357
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    References listed on IDEAS

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    1. Soojung Kim & Charles Arcodia & Insin Kim, 2019. "Critical Success Factors of Medical Tourism: The Case of South Korea," IJERPH, MDPI, vol. 16(24), pages 1-15, December.
    2. de la Hoz-Correa, Andrea & Muñoz-Leiva, Francisco & Bakucz, Márta, 2018. "Past themes and future trends in medical tourism research: A co-word analysis," Tourism Management, Elsevier, vol. 65(C), pages 200-211.
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