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Towards understanding socially influenced vaccination decision making: An integrated model of multiple criteria belief modelling and social network analysis

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  • Ni, Lei
  • Chen, Yu-wang
  • de Brujin, Oscar

Abstract

Understanding the socially influenced decision-making process that determines voluntary vaccination is essential for developing strategies and interventions of vaccine-preventable diseases. Both theoretical and experimental studies have suggested that a variety of factors, such as safety of vaccines, severity of diseases, information and advice from healthcare professionals, influence an individual's intention to vaccinate. However, limited research has been conducted on analysing systematically how individuals’ vaccine acceptance decisions are made from their beliefs and judgements on the influential factors. In particular, there is lack of quantitative analysis on how individuals’ beliefs and judgements may evolve from the spreading of vaccination-related information in a social network, which further affects their decision making. In this paper, an integrated model is first proposed to characterise the socially influenced vaccination decision-making process, in which each individual's beliefs and subjective judgements on the decision criteria are formulated as belief distributions in the framework of multiple criteria decision analysis (MCDA). The spreading of social influence in the network environment is further incorporated into the information aggregation process for supporting informed vaccination decision analysis. A series of simulation-based analyses on a real-world social network is conducted to demonstrate that the overall vaccination coverage is determined primarily by individuals’ beliefs and judgements on the decision criteria, and is also affected sensitively by the characteristics of influence spreading (including the content and amount of vaccination-related information) in the social network.

Suggested Citation

  • Ni, Lei & Chen, Yu-wang & de Brujin, Oscar, 2021. "Towards understanding socially influenced vaccination decision making: An integrated model of multiple criteria belief modelling and social network analysis," European Journal of Operational Research, Elsevier, vol. 293(1), pages 276-289.
    • Handle: RePEc:eee:ejores:v:293:y:2021:i:1:p:276-289
    DOI: 10.1016/j.ejor.2020.12.011
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    References listed on IDEAS

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    1. de Bekker-Grob, E.W. & Donkers, B. & Bliemer, M.C.J. & Veldwijk, J. & Swait, J.D., 2020. "Can healthcare choice be predicted using stated preference data?," Social Science & Medicine, Elsevier, vol. 246(C).
    2. Markus Schöbel & Jörg Rieskamp & Rafael Huber, 2016. "Social Influences in Sequential Decision Making," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-23, January.
    3. Edmundas Kazimieras Zavadskas & Valentinas Podvezko, 2016. "Integrated Determination of Objective Criteria Weights in MCDM," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 267-283, March.
    4. Wang, Ying-Ming & Yang, Jian-Bo & Xu, Dong-Ling & Chin, Kwai-Sang, 2006. "The evidential reasoning approach for multiple attribute decision analysis using interval belief degrees," European Journal of Operational Research, Elsevier, vol. 175(1), pages 35-66, November.
    5. Mats Danielson & Love Ekenberg & Ying He, 2014. "Augmenting Ordinal Methods of Attribute Weight Approximation," Decision Analysis, INFORMS, vol. 11(1), pages 21-26, March.
    6. Xu, Dong-Ling & Yang, Jian-Bo & Wang, Ying-Ming, 2006. "The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1914-1943, November.
    7. Ling, Mathew & Kothe, Emily J. & Mullan, Barbara A., 2019. "Predicting intention to receive a seasonal influenza vaccination using Protection Motivation Theory," Social Science & Medicine, Elsevier, vol. 233(C), pages 87-92.
    8. Markus M. Mobius & Neel Rao & Tanya Rosenblat, 2007. "Social networks and vaccination decisions," Working Papers 07-12, Federal Reserve Bank of Boston.
    9. Ivlev, Ilya & Vacek, Jakub & Kneppo, Peter, 2015. "Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty," European Journal of Operational Research, Elsevier, vol. 247(1), pages 216-228.
    10. Enayati, Shakiba & Özaltın, Osman Y., 2020. "Optimal influenza vaccine distribution with equity," European Journal of Operational Research, Elsevier, vol. 283(2), pages 714-725.
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    2. Li, Siran & Xiao, Fuyuan, 2023. "Normal distribution based on maximum Deng entropy," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).

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