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Operationalizing the telemedicine platforms through the social network knowledge: An MCDM model based on the CIPFOHW operator

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  • Zhang, Mengdan
  • Zhang, Chonghui
  • Shi, Qiule
  • Zeng, Shouzhen
  • Balezentis, Tomas

Abstract

Telemedicine is an effective way to address the excessive concentration of quality medical resources. Telemedicine platforms provide users with diversified high-quality medical and health services. These issues are topical in the context of the recent pandemic and the resulting socioeconomic transformations. In order to meet the multilevel and personalised health needs of users, optimise the management process of a telemedicine platform and rationally allocate medical resources, it is necessary to conduct scientific evaluations of telemedicine platforms. Therefore, this paper proposes a multi-criteria evaluation framework based on the interval value confidence induced Pythagorean fuzzy ordered hybrid weighted integration (CIPFOHW) operator and social network. To improve the fusion efficiency of user evaluation information and confidence level, the CIPFOHW operator is proposed. At the same time, since the trust relationship between users of the telemedicine platform influence the evaluation, the trust transfer network between users is given. In addition, based on SERVQUAL method, a five-dimension evaluation framework for telemedicine platforms is put forward. Finally, an applied case with five typical patients is used to verify the effectiveness of the method.

Suggested Citation

  • Zhang, Mengdan & Zhang, Chonghui & Shi, Qiule & Zeng, Shouzhen & Balezentis, Tomas, 2022. "Operationalizing the telemedicine platforms through the social network knowledge: An MCDM model based on the CIPFOHW operator," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    • Handle: RePEc:eee:tefoso:v:174:y:2022:i:c:s004016252100737x
    DOI: 10.1016/j.techfore.2021.121303
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    References listed on IDEAS

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    2. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Zeng, Shouzhen & Zhou, Jiamin & Zhang, Chonghui & Merigó, José M., 2022. "Intuitionistic fuzzy social network hybrid MCDM model for an assessment of digital reforms of manufacturing industry in China," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    4. Pal, Shounak & Biswas, Baidyanath & Gupta, Rohit & Kumar, Ajay & Gupta, Shivam, 2023. "Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach," Journal of Business Research, Elsevier, vol. 156(C).
    5. Wu, Qun & Liu, Xinwang & Qin, Jindong & Zhou, Ligang & Mardani, Abbas & Deveci, Muhammet, 2022. "An integrated multi-criteria decision-making and multi-objective optimization model for socially responsible portfolio selection," Technological Forecasting and Social Change, Elsevier, vol. 184(C).

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