Analyzing survey data from 1037 college students in China, a country with the world’s largest number of Internet users and the world’s largest e-commerce market, the current study demonstrates that consistent with previous research, some routine telecom/cyber activities of Chinese college students predict higher odds of being targeted for telecom/cyber fraud, but online routines do not seem to predict the odds of completed victimization resulting in a financial loss. In contrast, the perceived presence of effective formal guardianship and target suitability exert a greater influence. These findings suggest that those previously and commonly used measures of routine activity theory are better suited for explaining attempted telecom/cyber fraud victimization, whereas completed victimization is chiefly predicted by target suitability such as risky/deviant online behaviors and low self-control.
BosslerAMHoltTJ (2009) On-line activities, guardianship, and malware infection: An examination of routine activities theory. International Journal of Cyber Criminology3(1): 400–420.
3.
ChenJ (2021) “You are in trouble!”: A discursive psychological analysis of threatening language in Chinese cellphone fraud interactions. International Journal for the Semiotics of Law / Revue internationale de Sémiotique juridique34(4): 1065–1092.
ChoiJKruisNEChooKS (2021) Explaining fear of identity theft victimization using a routine activity approach. Journal of Contemporary Criminal Justice37(3): 406–426.
7.
ChoiKS (2008) Computer crime victimization and integrated theory: An empirical assessment. International Journal of Cyber Criminology2(1): 308–333.
8.
ClarkeRV (2004) Technology, criminology and crime science. European Journal on Criminal Policy and Research10(1): 55–63.
9.
CohenLEFelsonM (1979) Social change and crime rate trends: A routine activity approach. American Sociological Review44: 588–608.
Europol (2021) Telecommunication Fraud. Europol. Available at: europol.europa.eu/operations-services-and-innovation/public-awareness-and-prevention-guides/telecommunications-fraud (accessed 25 March 2022).
16.
FanJXYuZ (2021) Understanding aging and consumer fraud victimization in the Chinese context: A two-stage conceptual approach. Journal of Elder Abuse & Neglect33(3): 230–247.
GrasmickHGTittleCRBursikRJJr, et al. (1993) Testing the core empirical implications of Gottfredson and Hirschi’s general theory of crime. Journal of Research in Crime and Delinquency30(1): 5–29.
20.
GroffER (2007) Simulation for theory testing and experimentation: An example using routine activity theory and street robbery. Journal of Quantitative Criminology23(2): 75–103.
21.
HagleTMMitchellGE (1992) Goodness-of-fit measures for probit and logit. American Journal of Political Science36: 762–784.
KempSMiró-LlinaresFMonevaA (2020) The dark figure and the cyber fraud rise in Europe: Evidence from Spain. European Journal on Criminal Policy and Research26(3): 293–312.
24.
LeeCS (2021) Online fraud victimization in China: A case study of Baidu Tieba. Victims & Offenders16(3): 343–362.
25.
LeukfeldtERYarM (2016) Applying routine activity theory to cybercrime: A theoretical and empirical analysis. Deviant Behavior37(3): 263–280.
NguyenTR (2020) Cybercrime in Vietnam: An analysis based on routine activity theory. International Journal of Cyber Criminology14(1): 156–173.
30.
PartinRDMeldrumRCLehmannPS, et al. (2022) Low self-control and cybercrime victimization: An examination of indirect effects through risky online behavior. Crime & Delinquency68: 2476–2502.
31.
PiqueroARMacIntoshRHickmanM (2000) Does self-control affect survey response? Applying exploratory, confirmatory, and item response theory analysis to Grasmick et al.’s self-control scale. Criminology38(3): 897–930.
32.
PrattTCHoltfreterKReisigMD (2010) Routine online activity and internet fraud targeting: Extending the generality of routine activity theory. Journal of Research in Crime and Delinquency47(3): 267–296.
33.
PrattTCTuranovicJJFoxKA, et al. (2014) Self-control and victimization: A meta-analysis. Criminology52(1): 87–116.
34.
ReynsBW (2013) Online routines and identity theft victimization: Further expanding routine activity theory beyond direct-contact offenses. Journal of Research in Crime and Delinquency50(2): 216–238.
35.
ReynsBW (2015) A routine activity perspective on online victimisation: Results from the Canadian General Social Survey. Journal of Financial Crime22: 396–411.
36.
ReynsBWHensonB (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 Criminology60(10): 1119–1139.
37.
ShiW (2008) The paradox of Confucian determinism: Tracking the root causes of intellectual property rights problem in China. The John Marshall Review of Intellectual Property Law7(3): 454–468.
38.
StahuraJMSloanJJIII(1988) Urban stratification of places, routine activities and suburban crime rates. Social Forces66(4): 1102–1118.
39.
TaylorRWCaetiTJLoperDK, et al. (2006) Digital Crime and Digital Terrorism. Upper Saddle River, NJ: Pearson Prentice Hall.
Van WilsemJ (2011) Worlds tied together? Online and non-domestic routine activities and their impact on digital and traditional threat victimization. European Journal of Criminology8(2): 115–127.
43.
Van WilsemJ (2013) “Bought it, but never got it” assessing risk factors for online consumer fraud victimization. European Sociological Review29(2): 168–178.
44.
VazsonyiATMikuškaJKelleyEL (2017) It’s time: A meta-analysis on the self-control-deviance link. Journal of Criminal Justice48: 48–63.
45.
VeallMRZimmermannKF (1992) Pseudo-R2’s in the ordinal probit model. Journal of Mathematical Sociology16(4): 333–342.
46.
VeallMRZimmermannKF (1994) Evaluating Pseudo-R2’s for binary probit models. Quality and Quantity28(2): 151–164.
XuY (2022) Research on Offenders’ Decision-Making of New Cyberfraud Crime. Unpublished dissertation, East China University of Political Science and Law, Shanghai, China.
51.
XuYXuT (2021) Research on the characteristics and countermeasures of cross-border telecom-network fraud: Based on 18 typical cases. Issues on Juvenile Crime and Delinquency4: 88–103.
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
