Do Commonly Recommended Preventive Actions Deter Identity Theft Victimization? Findings from NCVS Identity Theft Surveys

References

• Albrecht, C., C. Albrecht, and S. Tzafrir. 2011. “How to Protect and Minimize Consumer Risk to Identity Theft.” Journal of Financial Crime 18 (4): 405–414. doi:10.1108/13590791111173722.
   Google Scholar
• Allison, S. F., A. M. Schuck, and K. M. Lersch. 2005. “Exploring the Crime of Identity Theft: Prevalence, Clearance Rates, and victim/offender Characteristics.” Journal of Criminal Justice 33 (1): 19–29. doi:10.1016/j.jcrimjus.2004.10.007.
   Web of Science ®Google Scholar
• Anderson, K. B. 2006. “Who are the Victims of Identity Theft? the Effect of Demographics.” Journal of Public Policy & Marketing 25 (2): 160–171. doi:10.1509/jppm.25.2.160.
   Web of Science ®Google Scholar
• Baum, K. (2006). Identity theft, 2004. Bureau of Justice Statistics. Retrieved 22 January 2020, from https://bjs.gov/content/pub/pdf/it04.pdf (accessed 15 October 2021).
   Google Scholar
• Bureau of Justice Statistics. 2016. National Crime Victimization Survey: Identity Theft Supplement, 2016. Washington, DC: United States Department of Justice, Office of Justice Programs.
   Google Scholar
• Burnes, D., M. DeLiema, and L. Langton. 2020. “Risk and Protective Factors of Identity Theft Victimization in the United States.” Preventive Medicine Reports 17: 101058. doi:10.1016/j.pmedr.2020.101058.
   PubMedGoogle Scholar
• Chapple, M. (2019). “Taking Social Security Numbers Public Could Fix Our Data Breach Crisis”. CNN Business Perspectives. Available at https://www.cnn.com/2019/06/05/perspectives/labcorp-quest-diagnostics-data-breach-social-security-numbers/index.html (accessed 18 February 2021).
   Google Scholar
• Choi, K. S. 2008. “Computer Crime Victimization and Integrated Theory: An Empirical Assessment.” International Journal of Cyber Criminology 2 (1): 308–333.
   Google Scholar
• Copes, H., and L. M. Vieraitis. 2009a. “Bounded Rationality of Identity Thieves: Using Offender‐based Research to Inform Policy.” Criminology & Public Policy 8 (2): 237–262. doi:10.1111/j.1745-9133.2009.00553.x.
   Google Scholar
• Copes, H., and L. M. Vieraitis. 2009b. “Understanding Identity Theft: Offenders’ Accounts of Their Lives and Crimes.” Criminal Justice Review 34 (3): 329–349. doi:10.1177/0734016808330589.
   Google Scholar
• Copes, H., K. R. Kerley, R. Huff, and J. Kane. 2010. “Differentiating Identity Theft: An Exploratory Study of Victims Using a National Victimization Survey.” Journal of Criminal Justice 38 (5): 1045–1052. doi:10.1016/j.jcrimjus.2010.07.007.
   Web of Science ®Google Scholar
• Cowley, S. (2019). “Equifax to Pay at Least $650 Million in largest-ever Data Breach Settlement”. New York Times Business. New York Times. Retrieved 27 January 2020, from https://www.nytimes.com/2019/07/22/business/equifax-settlement.html (accessed 15 October 2021).
   Google Scholar
• Dean, P. C., J. Buck, and P. Dean. 2014. “Identity Theft: A Situation of Worry.” Journal of Academic and Business Ethics 1 (1): 1–14.
   Google Scholar
• European Commission. (2020). “Survey on Scams and Fraud Experienced by Consumers: Final Report. EU Consumer Programme”. Available at https://ec.europa.eu/info/sites/default/files/aid_development_cooperation_fundamental_rights/ensuring_aid_effectiveness/documents/survey_on_scams_and_fraud_experienced_by_consumers_-_final_report.pdf (accessed 6 June 2022).
   Google Scholar
• Fawcett, T. 2006. “An Introduction to ROC Analysis.” Pattern Recognition Letters 27 (8): 861–874. doi:10.1016/j.patrec.2005.10.010.
   Web of Science ®Google Scholar
• Gibert, J., and N. Archer. 2012. “Consumer Identity Theft Prevention and Identity Fraud Detection Behaviours.” Journal of Financial Crime 19 (1): 20–36.
   Google Scholar
• Golladay, K., and K. Holtfreter. 2017. “The Consequences of Identity Theft Victimization: An Examination of Emotional and Physical Health Outcomes.” Victims & Offenders 12 (5): 741–760. doi:10.1080/15564886.2016.1177766.
   Web of Science ®Google Scholar
• Golladay, K. A. 2017. “Reporting Behaviors of Identity Theft Victims: An Empirical Test of Black’s Theory of Law.” Journal of Financial Crime 24 (1): 101–117. doi:10.1108/JFC-01-2016-0010.
   Google Scholar
• Harrell, E., and L. Langton (2013). “Victims of Identity Theft, 2012”. US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics. Available at https://www.bjs.gov/content/pub/pdf/vit12.pdf (accessed 22 January 2020).
   Google Scholar
• Harrell, E. (2015). “Victims of Identity Theft, 2014”. US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics. Available at https://bjs.gov/content/pub/pdf/vit14.pdf (accessed 22 January 2020).
   Google Scholar
• Harrell, E. (2019). “Victims of Identity Theft, 2016”. US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics. Available at https://www.bjs.gov/content/pub/pdf/vit16.pdf (accessed 20 January 2020).
   Google Scholar
• Holt, T. J., and A. M. Bossler. 2008. “Examining the Applicability of lifestyle-routine Activities Theory for Cybercrime Victimization.” Deviant Behavior 30 (1): 1–25. doi:10.1080/01639620701876577.
   Web of Science ®Google Scholar
• Holt, T. J., and M. G. Turner. 2012. “Examining Risks and Protective Factors of on-line Identity Theft.” Deviant Behavior 33 (4): 308–323. doi:10.1080/01639625.2011.584050.
   Web of Science ®Google Scholar
• Holtfreter, K., M. D. Reisig, T. C. Pratt, and R. E. Holtfreter. 2015. “Risky Remote Purchasing and Identity Theft Victimization among Older Internet Users.” Psychology, Crime & Law 21 (7): 681–698. doi:10.1080/1068316X.2015.1028545.
   Web of Science ®Google Scholar
• Hu, X., J. Wu, M. J. DeValve, and B. S. Fisher. 2020. “Exploring Violent Crime Reporting among school-age Victims: Findings from NCVS SCS 2005-2015.” Victims & Offenders 15 (2): 141–158. doi:10.1080/15564886.2019.1705452.
   Web of Science ®Google Scholar
• Hu, X., X. Zhang, and N. Lovrich. 2021a. “Forecasting Identity Theft Victims: Analyzing Characteristics and Preventive Actions through Machine Learning Approaches.” Victims & Offenders 16 (4): 465–494. doi:10.1080/15564886.2020.1806161.
   Web of Science ®Google Scholar
• Hu, X., X. Zhang, and N. Lovrich. 2021b. “Public Perceptions of Police Behavior during Traffic Stops: Logistic Regression and Machine Learning Approaches Compared.” Journal of Computational Social Science 4 (1): 355–380. doi:10.1007/s42001-020-00079-4.
   Google Scholar
• Internet Crime Complaint Center. (2022). “Internet Crime Report 2021”. Federal Bureau of Investigation”. Available at https://www.ic3.gov/Media/PDF/AnnualReport/2021_IC3Report.pdf (Accessed 6 June 2022).
   Google Scholar
• Lai, F., D. Li, and C. T. Hsieh. 2012. “Fighting Identity Theft: The Coping Perspective.” Decision Support Systems 52 (2): 353–363. doi:10.1016/j.dss.2011.09.002.
   Web of Science ®Google Scholar
• Leukfeldt, E. R. 2014. “Phishing for Suitable Targets in the Netherlands: Routine Activity Theory and Phishing Victimization.” Cyberpsychology, Behavior, and Social Networking 17 (8): 551–555. doi:10.1089/cyber.2014.0008.
   PubMed Web of Science ®Google Scholar
• Liu, F. 2019. “Does Identity Theft Insurance Undermine Risk Perceptions and Increase Risky Behavioral Intentions?” Asian Economic and Financial Review 9 (8): 926–935. doi:10.18488/journal.aefr.2019.98.926.935.
   Google Scholar
• Marcum, C. D. 2008. “Identifying Potential Factors of Adolescent Online Victimization for High School Seniors.” International Journal of Cyber Criminology 2 (2): 346–367.
   Google Scholar
• Piquero, N. L., M. A. Cohen, and A. R. Piquero. 2011. “How Much Is the Public Willing to Pay to Be Protected from Identity Theft?” Justice Quarterly 28 (3): 437–459. doi:10.1080/07418825.2010.511245.
   Web of Science ®Google Scholar
• Piquero, N. L., A. R. Piquero, S. Gies, B. Green, A. Bobnis, and E. Velasquez. 2021. “Preventing Identity Theft: Perspectives on Technological Solutions from Industry Insiders.” Victims & Offenders 16 (3): 444–463. doi:10.1080/15564886.2020.1826023.
   Web of Science ®Google Scholar
• Pontell, H. 2002. “Pleased to Meet You … Won’t You Guess My Name: Identity Fraud, cyber-crime, and white-collar Delinquency.” Adelaide Law Review 23 (2): 305–328.
   Google Scholar
• Randa, R., and B. W. Reyns. 2020. “The Physical and Emotional Toll of Identity Theft Victimization: A Situational and Demographic Analysis of the National Crime Victimization Survey.” Deviant Behavior 41 (10): 1290–1304. doi:10.1080/01639625.2019.1612980.
   Web of Science ®Google Scholar
• Rebovich, D. J. 2009. “Examining Identity Theft: Empirical Explorations of the Offense and the Offender.” Victims and Offenders 4 (4): 357–364. doi:10.1080/15564880903260603.
   Google Scholar
• Reisig, M. D., T. C. Pratt, and K. Holtfreter. 2009. “Perceived Risk of Internet Theft Victimization: Examining the Effects of Social Vulnerability and Financial Impulsivity.” Criminal Justice and Behavior 36 (4): 369–384. doi:10.1177/0093854808329405.
   Web of Science ®Google Scholar
• Reyns, B. W. 2013. “Online Routines and Identity Theft Victimization: Further Expanding Routine Activity Theory beyond direct-contact Offenses.” Journal of Research in Crime and Delinquency 50 (2): 216–238. doi:10.1177/0022427811425539.
   Web of Science ®Google Scholar
• Reyns, B. W., and B. Henson. 2016. “The Thief with a Thousand Faces and the Victim with None: Identifying Determinants for Online Identity Theft Victimization with Routine Activity Theory.” International Journal of Offender Therapy and Comparative Criminology 60 (10): 1119–1139. doi:10.1177/0306624X15572861.
   PubMed Web of Science ®Google Scholar
• van de Weijer, S. G., R. Leukfeldt, and W. Bernasco. 2019. “Determinants of Reporting Cybercrime: A Comparison between Identity Theft, Consumer Fraud, and Hacking.” European Journal of Criminology 16 (4): 486–508. doi:10.1177/1477370818773610.
   Web of Science ®Google Scholar
• Williams, M. L. 2016. “Guardians upon High: An Application of Routine Activities Theory to Online Identity Theft in Europe at the Country and Individual Level.” British Journal of Criminology 56 (1): 21–48. doi:10.1093/bjc/azv011.
   Web of Science ®Google Scholar