Factors Predisposing Individuals to Scam Victimization: A Case Study in Seremban, Negeri Sembilan

Authors

  • Aqeelah Balqis Abdul Samad Faculty of Computer and Mathematical Sciences, Universiti Teknologi Mara Cawangan (UiTM) Negeri Sembilan Branch, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia. Author
  • Nornadiah Mohd Razali Faculty of Computer and Mathematical Sciences, Universiti Teknologi Mara Cawangan (UiTM) Negeri Sembilan Branch, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia. Author
  • Siti Aishah Mohd Shafie Faculty of Computer and Mathematical Sciences, Universiti Teknologi Mara Cawangan (UiTM) Negeri Sembilan Branch, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia. Author
  • Az’lina Abdul Hadi Faculty of Computer and Mathematical Sciences, Universiti Teknologi Mara Cawangan (UiTM) Negeri Sembilan Branch, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia. Author

DOI:

https://doi.org/10.24191/jcrinn.v11i2.563

Keywords:

Scam victimization, Awareness, Logistic regression, Trust, Technological literacy

Abstract

Scam, which include investment schemes, job offer fraud, Macau scams, love scams, and internet shopping scams has become an alarming problem in Malaysia. Scammers frequently utilize internet platforms or pose as officials to trick victims into sending money or disclosing private information. In response to these issues, this study investigated the factors that predispose individuals to scam victimization. Questionnaire was distributed to a total of 385 samples encompassed individuals from various demographic backgrounds residing in Seremban, Negeri Sembilan. Factors such as age, income level, level of awareness, trust, and technological literacy were regressed towards scam victimization (had or had never been a scam victim) in a logistic regression analysis. Upon completion of the study, the results revealed that age, level of awareness and technological literacy contributed significantly to scam victimization. Hence, this study concluded that promoting critical thinking, enhancing technological literacy, and encouraging responsible online behaviour are essential steps in reducing scam victimization.

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References

Alotaibi, S., & Furnell, S. (2018). A study of cyber-security awareness in Saudi Arabia. Journal of Information Security and Applications 40, 15-20. https://10.1109/ICITST.2016.7856687.

Anderson, J., & Rainie, L. (2018). The future of well-being in a tech-saturated world. Pew Research Center. https://www.pewresearch.org/internet/2018/04/17/the-future-of-well-being-in-a-tech-saturated-world/.

Bhandari, P (2021). Statistical power and why it matters: A simple introduction. https://www.scribbr.com/statistics/statistical-power/

Beach, S. R., Czaja, S. J., & Schulz, R. (2023). Novel methods for assessment of vulnerability to financial exploitation (FE). Journal of Elder Abuse & Neglect, 35(4-5), 151–173. https://doi.org/10.1080/08946566.2023.2281672.

Bernama (2025). Increase in online fraud cases, nearly RM600 million losses recorded. https://www.bernama.com/en/news.php?id=2414124.

Button, M., Lewis, C., & Tapley, J. (2014). Not a victimless crime: The impact of fraud on individual victims and their families. Security Journal, 33(4), 498-519. https://10.1057/sj.2012.11.

Cole, K., Kelly & Datar, T., & Rogers, M. (2015). Awareness of scam e-mails: An exploratory research study – Part 2. 115-125. International Conference on Digital Forensics and Cyber Crime. https://10.1007/978-3-319-25512-5_9.

Federal Trade Commission (2022). Who experiences scams? A story of all ages. https://www.ftc.gov/news-events/data-visualizations/data-spotlight/2022/12/who-experiences-scams-story-all-ages.

Gao, N., Ma, Y., & Xu, L. C. (2020). Credit constraints and fraud victimization: evidence from a representative Chinese household survey. Policy Research Working Paper. https://doi.org/10.1596/1813-9450-9460.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th Edition). Pearson Prentice Hall.

Holtfreter, K., Reisig, M. D., & Pratt, T. C. (2008). low self-control, routine activities, and fraud victimization. Criminology, 46(1),189 - 220. https://10.1111/j.1745-9125.2008.00101.x.

Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd Edition). Wiley.

Juremi, J (2024). Target: The young and vulnerable (2024). The Star. https://www.thestar.com.my/news/focus/2024/11/24/target-the-young-and-vulnerable.

Liu, X. F., Ai, Y., Jiang, L. C., Wang, X. & Wu, Y. (2025). Understanding the human element in scams: a multidisciplinary approach. Journal of Information Technology Case and Application Research, 27(1), 9-24. https://doi.org/10.1080/15228053.2024.2439192.

Kipngetich, A. (2025). A review of online scams and financial fraud in the Digital Age. GSC Advanced Research and Reviews, 22(01), 302-329. https://doi.org/10.30574/gscarr.2025.22.1.0025.

Koning, L., Junger, M., & Veldkamp, B. (2024). Risk factors for fraud victimization: The role of socio-demographics, personality, mental, general, and cognitive health, activities, and fraud knowledge. International Review of Victimology, 30(3), 443-479. https://doi.org/10.1177/02697580231215839.

Kubilay, E., Raiber, E., Spantig, L., Cahlikova, J. & Karia, L. (2023). Can you spot a scam? Measuring and improving scam identification ability. Journal of Development Economics, 165, 103147. https://doi.org/10.1016/j.jdeveco.2023.103147.

Mauricio, B. A., Barbosa, R. R. (2009). Ontologies in knowledge management support: A case study. Journal of the American Society for Information Science and Technology, 60(10), 2032-2047. https://doi.org/10.1002/asi.21120.

Muniam, R., Jaafar, N. S., Belaman, J. A. X., Suppiah, P. C. & Hussin, A. A. (2025). Education on scam awareness through digital literacy. International Journal of Advanced Research in Education and Society, 7(4), 39-47. https://doi.org/10.55057/ijares.2025.7.4.4.

Shang, Y., Wu, Z., Du, X., Jiang, Y., Ma, B., & Chi, M. (2022). The psychology of the internet fraud victimization of older adults: A systematic review. Frontiers In Psychology, 13, 912242. https://doi: 10.3389/fpsyg.2022.912242.

Ueno, D., Daiku, Y., Eguchi, Y., Iwata, M., Amano, S., Ayani, N., Nakamura, K., Kato, Y., Matsuoka, T., & Narumoto, J. (2021). Mild cognitive decline is a risk factor for scam vulnerability in older adults. Frontiers in Psychiatry, 12, 685451. https://10.3389/fpsyt.2021.685451.

Yu, L., Mottola, G., Barnes, L. L., Valdes, O., Wilson, R. S., Bennett, D. A., & Boyle, P. A. (2022). Financial fragility and scam susceptibility in community dwelling older adults. Journal of Elder Abuse & Neglect, 34(2), 93-108. https://10.1080/08946566.2022.2070568.

Zhang, Z. & Ye, Z. (2022). The role of socio-psychological factors of victimity on victimization of online fraud in China. Front. Psychol, 13. https://doi.org/10.3389/fpsyg.2022.1030670.

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Published

2026-09-01

Issue

Section

General Computing

How to Cite

Factors Predisposing Individuals to Scam Victimization: A Case Study in Seremban, Negeri Sembilan. (2026). Journal of Computing Research and Innovation, 11(2), 78-87. https://doi.org/10.24191/jcrinn.v11i2.563