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A Mathematics Model for Quantitative Analysis of Demand Disruption Caused by Rumor Spreading

Author

Listed:
  • Haifeng Zhao

    (School of Economic and Management, Tongji University, 1239, Siping Road, Shanghai, P. R. China)

  • Bin Lin

    (School of Economic and Management, Tongji University, 1239, Siping Road, Shanghai, P. R. China)

  • Chongqing Guo

    (School of Economic and Management, Tongji University, 1239, Siping Road, Shanghai, P. R. China)

Abstract

Rumors greatly impact consumers' attitudes and purchasing intention. Rumor spreading can disrupt supply chain demand, particularly in today's Internet age. We propose a mathematical model for the quantitative analysis of demand disruption caused by rumor spreading based on the susceptible-infective-isolated-immune (SI2I) rumor spreading model, which extends the susceptible-infective-recovered (SIR) rumor spreading model by dividing stiflers into isolators and immunes. Both groups represent individuals who do not propagate a rumor, but the former believes the rumor while the latter does not. From the firms' perspective, only ignorants and immunes will still purchase their products and services after a rumor has spread. Hence, the influence of rumors on demand can be quantitatively reflected by the proportion of ignorants and immunes in the population. This study offers a new method for company managers to predict the variation trend of demand and estimate demand loss when a firm is attacked by rumors.

Suggested Citation

  • Haifeng Zhao & Bin Lin & Chongqing Guo, 2014. "A Mathematics Model for Quantitative Analysis of Demand Disruption Caused by Rumor Spreading," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 13(03), pages 585-602.
    • Handle: RePEc:wsi:ijitdm:v:13:y:2014:i:03:n:s0219622014500515
    DOI: 10.1142/S0219622014500515
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    Cited by:

    1. Chuan Zhao & Luyao Li & Hongxia Sun & Hongji Yang, 2021. "Multi-Scenario Evolutionary Game of Rumor-Affected Enterprises under Demand Disruption," Sustainability, MDPI, vol. 13(1), pages 1-26, January.
    2. Kumar, Ajay & Swarnakar, Pradip & Jaiswal, Kamya & Kurele, Ritika, 2020. "SMIR model for controlling the spread of information in social networking sites," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

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