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Integrating Individual Factors to Construct Recognition Models of Consumer Fraud Victimization

Author

Listed:
  • Liuchang Xu

    (College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China)

  • Jie Wang

    (Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China)

  • Dayu Xu

    (College of Mathematics and Computer Science, Zhejiang A&F University, Hangzhou 311300, China)

  • Liang Xu

    (Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China)

Abstract

Consumer financial fraud has become a serious problem because it often causes victims to suffer economic, physical, mental, social, and legal harm. Identifying which individuals are more likely to be scammed may mitigate the threat posed by consumer financial fraud. Based on a two-stage conceptual framework, this study integrated various individual factors in a nationwide survey (36,202 participants) to construct fraud exposure recognition (FER) and fraud victimhood recognition (FVR) models by utilizing a machine learning method. The FER model performed well (f1 = 0.727), and model interpretation indicated that migration status, financial status, urbanicity, and age have good predictive effects on fraud exposure in the Chinese context, whereas the FVR model shows a low predictive effect (f1 = 0.565), reminding us to consider more psychological factors in future work. This research provides an important reference for the analysis of individual differences among people vulnerable to consumer fraud.

Suggested Citation

  • Liuchang Xu & Jie Wang & Dayu Xu & Liang Xu, 2022. "Integrating Individual Factors to Construct Recognition Models of Consumer Fraud Victimization," IJERPH, MDPI, vol. 19(1), pages 1-12, January.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:1:p:461-:d:716034
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    References listed on IDEAS

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    Cited by:

    1. Zhou Yu & Jessie X. Fan, 2024. "Migrant Status and Consumer Financial Fraud in China: A Two-Stage Approach Using a Representative Household Survey," SAGE Open, , vol. 14(2), pages 21582440241, May.
    2. Xin Wen & Liang Xu & Jie Wang & Yuan Gao & Jiaming Shi & Ke Zhao & Fuyang Tao & Xiuying Qian, 2022. "Mental States: A Key Point in Scam Compliance and Warning Compliance in Real Life," IJERPH, MDPI, vol. 19(14), pages 1-16, July.

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