Low Self-Control, Information Disclosure, and the Risk of Online Fraud
Abstract
This study investigates the risk of being a target of an attempt at fraud through email by assessing the role of low self-control, online activities, and the disclosure of personal information. A secondary analysis of the 2014 U.S. “Caught in the Scammers’ Net”, a national survey of online victimization ( N = 1,539), indicates that those with low self-control and individuals who engage in online activities are more likely to disclose personal information online. The risk of being targeted with a fraudulent offer is also associated with low self-control and online routine activities. Responding to a fraudulent offer is associated with disclosing personal information online and low self-control. Taken together, our empirical evidence strengthens the central role of low self-control theory.
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Other surveys on fraud have found little to no association between race and risk of victimization, but sample sizes were significantly smaller and these studies focused on online forms of fraud.
“Other surveys on fraud have found little to no association between race and risk of victimization (e.g., Holtfreter et al. 2008;Mesch and Dodel 2018), but sample sizes were significantly smaller and these studies focused on online forms of fraud.”
From Profiling consumers who reported mass marketing scams: demographic characteristics and emotional sentiments associated with victimization (2024) · cites this paper as Mesch and Dodel 2018
Cites
Gottfredson, M. R., & Hirschi, T. (1990) · doi:10.1515/9781503621794 · Cited by 10,127 · see citing works
(1977) · Medical Entomology and Zoology · Cited by 1,496 · see citing works
Examining the Applicability of Lifestyle-Routine Activities Theory for Cybercrime Victimization
Holt, T., & Bossler, A. M. (2008) · Deviant Behavior · doi:10.1080/01639620701876577 · Cited by 432 · see citing works
SELF‐CONTROL AND VICTIMIZATION: A META‐ANALYSIS
Pratt, T. C., Turanovic, J. J., Fox, K. A., & Wright, K. A. (2013) · Criminology · doi:10.1111/1745-9125.12030 · Cited by 430 · see citing works
Pratt, T. C., Holtfreter, K., & Reisig, M. D. (2010) · Journal of Research in Crime and Delinquency · doi:10.1177/0022427810365903 · Cited by 411 · see citing works
LOW SELF‐CONTROL, ROUTINE ACTIVITIES, AND FRAUD VICTIMIZATION*
HOLTFRETER, K., REISIG, M. D., & PRATT, T. C. (2008) · Criminology · doi:10.1111/j.1745-9125.2008.00101.x · Cited by 375 · cited 3× · see citing works
“The scant research regarding online fraud victimization suggests that there are several consistent demographic indicators associated with these victims (Holtfreter et al., 2008; Pratt et al., 2010).”
BackgroundReyns, B. W. (2013) · Journal of Research in Crime and Delinquency · doi:10.1177/0022427811425539 · Cited by 287 · see citing works
“Can’t Stop, Won’t Stop”: Self-Control, Risky Lifestyles, and Repeat Victimization
Turanovic, J., & Pratt, T. C. (2012) · Journal of quantitative criminology · doi:10.1007/s10940-012-9188-4 · Cited by 259 · see citing works
Cybercrime Victimization: An Examination of Individual and Situational Level Factors
Ngo, F. T., & Paternoster, R. (2011) · Digital Commons - University of South Florida (University of South Florida) · Cited by 247 · see citing works
Computer Crime Victimization and Integrated Theory: An Empirical Assessment
Choi, K.-S. (2008) · International journal of cyber criminology · Cited by 205 · see citing works
Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2010) · Deviant Behavior · doi:10.1080/01639620903004903 · Cited by 199 · see citing works
Holtfreter, K., Reisig, M. D., Piquero, N. L., & Piquero, A. R. (2010) · Criminal Justice and Behavior · doi:10.1177/0093854809354977 · Cited by 180 · see citing works
'Bought it, but Never Got it' Assessing Risk Factors for Online Consumer Fraud Victimization
van Wilsem, J. (2011) · European Sociological Review · doi:10.1093/esr/jcr053 · Cited by 168 · see citing works
Technology, Criminology and Crime Science
Clarke, R. V. (2004) · European Journal on Criminal Policy and Research · doi:10.1023/b:crim.0000037557.42894.f7 · Cited by 135 · see citing works
Donner, C. M., Marcum, C. D., Jennings, W. G., Higgins, G. E., & Banfield, J. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.01.040 · Cited by 128 · see citing works
Examining the Relationship Between Routine Activities and Malware Infection Indicators
Holt, T. J., & Bossler, A. M. (2013) · Journal of Contemporary Criminal Justice · doi:10.1177/1043986213507401 · Cited by 117 · see citing works
Crimes of privilege : readings in white-collar crime
Shover, N., & WRIGHT, J. P. (2001) · Oxford University Press eBooks · Cited by 100 · see citing works
Mesch, G. S., & Beker, G. (2010) · Human Communication Research · doi:10.1111/j.1468-2958.2010.01389.x · Cited by 87 · see citing works
Self-citationMesch, G. S. (2012) · Computers in Human Behavior · doi:10.1016/j.chb.2012.03.010 · Cited by 83 · see citing works
Self-citationExamining Risks and Protective Factors of On-Line Identity Theft
Holt, T. J., & Turner, M. G. (2012) · Deviant Behavior · doi:10.1080/01639625.2011.584050 · Cited by 76 · see citing works
Risk factors for advance fee fraud victimisation
Ross, S., & Smith, R. G. (2011) · Australian Institute of Criminology eBooks · doi:10.52922/ti268334 · Cited by 67 · see citing works
Risky remote purchasing and identity theft victimization among older Internet users
Holtfreter, K., Reisig, M. D., Pratt, T. C., & Holtfreter, R. E. (2015) · Psychology Crime and Law · doi:10.1080/1068316x.2015.1028545 · Cited by 55 · see citing works
Graham, R. S., & Triplett, R. A. (2016) · Deviant Behavior · doi:10.1080/01639625.2016.1254980 · Cited by 42 · see citing works
Does low self-control explain voluntary disclosure of personal information on the Internet?
Yu, S. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.055 · Cited by 22 · see citing works
Cross, C. (2012) · QUT ePrints (Queensland University of Technology) · Cited by 6 · see citing works
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DeLiema, M., & Witt, P. (2024) · Security Journal · doi:10.1057/s41284-023-00401-5 · Cited by 20 · see citing works
“Other surveys on fraud have found little to no association between race and risk of victimization (e.g., Holtfreter et al. 2008; Mesch and Dodel 2018), but sample sizes were significantly smaller and these studies focused on online forms of fraud.”
Wang, X., Ma, J., Liang, Y., Ma, L., & Liu, P. (2023) · Public Health · doi:10.1016/j.puhe.2023.01.002 · Cited by 11 · see citing works
- Authors
- Mesch, G. S., & Dodel, M.
- Affiliations
- University of Haifa (IL)
- Department of Sociology, University of Haifa, Haifa, Israel
- Corresponding author
- Mesch, Gustavo S.
- Venue
- American Behavioral Scientist
- Publisher
- SAGE Publications
- Published
- 2018-07-10
- Volume
- 62
- Issue
- 10
- Pages
- 1356-1371
- ISSN
- 0002-7642 (ISSN-L)
- 1552-3381
- OpenAlex
- W2864548321
- Cited by
- 57
- References
- 25
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 10 · 2023: 9 · 2022: 8 · 2021: 7 · 2020: 4 · 2019: 2 · 2018: 1
- FWCI
- 5.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Behavioral Scientist (publishedVersion)
- Funders
- Ministry of Science, Technology of Israel
- Faculty of Social Sciences at the University of Haifa
- Topics
- Physical Sciences › Computer Science › Information Systems › Cybercrime and Law Enforcement Studies
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- low self-control, online fraud, email fraud, personal information disclosure, cyber victimization, routine activity theory, online activities
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