Deterrent Impact of Penal Policies on Telecom-Fraud in China: A Spatial and Empirical Analysis

Abstract

Telecom-fraud has grown rapidly in China, prompting concerns about the effectiveness of punitive policies. Drawing on deterrence theory, this study examines how legally prescribed aggravating factors shape subsequent fraud trends. Using 108,478 cases from 2014 to 2021 and coding aggravators specified in the 2011, 2016, and 2021 judicial interpretations, we analyze spatial patterns and estimate longitudinal Poisson models for completed and attempted offenses. Findings show that aggravators involving serious harm, prior punishment, and victim vulnerability predict declines in later case counts, whereas technologically sophisticated or organizationally coordinated schemes correspond to increases. The results indicate selective rather than uniform deterrence and highlight the need to complement punitive measures with regulatory and technological interventions.

Keywords

telecom-fraud deterrence theory penal policies China

Get full access to this article

View all access options for this article.

References

Agnew

White

H. R.

(1992). An empirical test of general strain theory. Criminology, 30(4), 475–500.

Ahmad

Thurasamy

(2022). A systematic literature review of routine activity theory’s applicability in cybercrimes. Journal of Cyber Security and Mobility, 11(3), 405–432.

Akers

R. L.

(1973). Deviant behavior: A social learning approach.

Bai

(2025). How online activities shape anti-fraud payment behavior: Evidence from Chinese youth. SAGE Open, 15(3), 21582440251378971.

Beccaria

(1986). On crimes and punishments ( Young

, Trans.). Hackett (Original work published 1764).

Becker

G. S.

(1968). Crime and punishment: An economic approach. Journal of Political Economy, 76(2), 169–217.

Bentham

(1789). An introduction to the principles of morals and legislation. Clarendon Press. (Original work published 1948).

Blumstein

Cohen

Nagin

(1978). Deterrence and incapacitation: Estimating the effects of criminal sanctions on crime rates (No. 2649). National Academy of Sciences.

Chen

Liu

Chen

Huang

(2025). Exploring illicit personal information trading behind telecom-fraud in China. Humanities and Social Sciences Communications, 12(1), 1–11.

10.

Chen

Peng

(2025). Understanding online shopping fraud among Chinese elderly: Extending routine activity theory in the online context. Telematics and Informatics, 96, Article 102208.

11.

Chen

Atkin

(2023). Migration stress, risky Internet uses, and scam victimization: An empirical study among Chinese migrant workers. Telematics and Informatics, 83, Article 102022.

12.

Chen

(2024). Dianxin Wangluo Zhapian She’an Zijin Jinji Zhifu de Shuangchong Luoji [The dual logic of emergency freezing of funds in telecom and online fraud cases]. Legal Science (Journal of Northwest University of Political Science and Law), 42(1), 124–134. https://doi.org/10.16290/j.cnki.1674-5205.2024.01.015

13.

Chen

Gao

Jiang

Hao

Ding

Zhang

(2021). The spatiotemporal pattern and driving factors of cyber fraud crime in China. ISPRS International Journal of Geo-Information, 10(12), 802.

14.

Chen

(2024). Xingshi Yitihua Shiye Zhong de Kuajing Dianxin Wangluo Zhapian Fanzui Yinan Wenti Yanjiu [Research on difficult issues of cross-border telecom and online fraud under the perspective of criminal integration]. Application of Law, 10, 117–132.

15.

Cohen

L. E.

Felson

. (1979). Social change and crime rate trends: A routine activity approach. American sociological review, 588–608.

16.

Deng

Liang

Yao

Wang

Zhang

(2023). An early warning model of telecommunication network fraud based on user portrait. Computers, Materials & Continua, 75(1), 1561–1576.

17.

Ehrlich

(1973). Participation in illegitimate activities: A theoretical and empirical investigation. Journal of political Economy, 81(3), 521–565.

18.

Geng

(2017). Research on how to deal with the dilemma of global cooperative governance of cross-border telecom network fraud in China. Chinese Studies, 6, 249–263.

19.

Holt

Bossler

(2015). Cybercrime in progress: Theory and prevention of technology-enabled offenses. Routledge.

20.

Zhu

(2023). A framework for analyzing fraud risk warning and interference effects by fusing multivariate heterogeneous data: A Bayesian belief network. Entropy, 25(6), 892.

21.

Huang

Wang

(2020). Mobile payment in China: Practice and its effects. Asian Economic Papers, 19(3), 1–18.

22.

Jiang

(2023). Dianxin Wangluo Zhapian Fanzui Shue “Zonghe Rending” de Lilun Shenshi he Wanshan Jinlu [A theoretical review and improvement path of the “comprehensive determination” of amount in telecom-network fraud]. China Criminal Law Journal, 6, 54–69. https://doi.org/10.19430/j.cnki.3891.2023.06.003

23.

Lee

C. S.

(2021). Online fraud victimization in China: A case study of Baidu Tieba. Victims & Offenders, 16(3), 343–362.

24.

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.

25.

Leukfeldt

E. R.

Yar

(2016). Applying routine activity theory to cybercrime: A theoretical and empirical analysis. Deviant Behavior, 37(3), 263–280.

26.

(2024). Fanzui Rending Zhong Shikong Biaozhun de Fazhi Luoji ji qi Kongzhi: Yi Dianxin Wangluo Zhapian Fanzui de Xinxing Ruzui Biaozhun wei Shijiao [The rule-of-law logic and control of temporal-spatial criteria in crime determination: From the perspective of new criteria for telecom-network fraud]. Law Science, 7, 78–93.

27.

(2024). Does digital literacy help residents avoid becoming victims of frauds? Empirical evidence based on a survey of residents in six provinces of east China. International Review of Economics & Finance, 91, 364–377.

28.

Lin

Sun

I. Y.

(2025). Telecommunication and cyber fraud victimization among Chinese college students: An application of routine activity theory. Criminology & Criminal Justice, 25(3), 717–735.

29.

Luo

Zhao

(2025). Butcher or be butchered: Understanding the unwitting recruitment by cybercrime groups in China. Trends in Organized Crime. Advance online publication. https://doi.org/10.1007/s12117-025-09568-2

30.

Luo

Zhang

(2021). Jiyu Beiyesi Wangluo de Dianxin Wangluo Zhapian Shouhairen Tezheng Fenxi [Analysis of victim characteristics of telecom-network fraud based on Bayesian networks]. Information Network Security, 21(12), 25–30.

31.

Nagin

D. S.

(2013). Deterrence: A review of the evidence by a criminologist for economists. Annual Review of Economics, 5(1), 83–105.

32.

Nagin

D. S.

Pogarsky

(2003). An experimental investigation of deterrence: Cheating, self-serving bias, and impulsivity. Criminology, 41(1), 167–194.

33.

Shan

(2025). “Fandianxin Wangluo Zhapian Fa” de Junheng Shixian: Yufangxing Zhixu he Zhengdangxing Quanyi Zhijian [The balanced realization of the anti-telecom and online fraud law: Between preventive order and legitimate rights]. Law and Social Development, 31(1), 40–64.

34.

Sun

. (2025). Jiyu Dayuyan Moxing he Shijian Ronghe de Dianxinzhapian Shijian Fengxian Fenxi [Risk Analysis of Telecom Fraud Events Based on Large Language Models and Event Fusion]. Data Analysis and Knowledge Discovery, 9(7), 38–51.

35.

Siu

J. C. L.

Zhong

Nivette

(2024). Exploring the impact of routine activity and financial strain on fraud victimization during the COVID-19 pandemic in Hong Kong. Asian Journal of Criminology, 19(3), 441–458.

36.

Sun

Zhao

(2024). Dianxin Wangluo Zhapian Zhong 90 Hou Beihai Guocheng Yanjiu [A study on the victimization process of post-90s in telecom-network fraud]. Journal of the People’s Public Security University of China (Social Sciences Edition), 40(2), 52–66.

37.

Supreme People’s Court (SPC). (2022, September 6). Supreme People’s Court Releases Update on the Adjudication of Telecom and Online Fraud Cases: Strict Punishment as the “Primary Principle,” and Combating Cross-Border Fraud as the “Top Priority.” https://www.court.gov.cn/zixun/xiangqing/371151.html

38.

Wang

Zhou

(2023). Persuasive schemes for financial exploitation in online romance scam: An Anatomy on Sha Zhu pan (杀猪盘) in China. Victims & Offenders, 18(5), 915–942.

39.

Whitty

M. T.

(2015). Anatomy of the online dating romance scam. Security Journal, 28(4), 443–455.

40.

Williamson

S. M.

Prybutok

(2024). The era of artificial intelligence deception: Unraveling the complexities of false realities and emerging threats of misinformation. Information, 15(6), 299.

41.

Wortley

Prichard

(2023). Online messaging as a cybercrime prevention tool in the post-pandemic age. In Smith

R. G.

Sarre

Chang

L. Y. C.

Lau

L. Y. C.

(Eds.), Cybercrime in the pandemic digital age and beyond (pp. 209–232). Springer International Publishing.

42.

H. Q.

Wang

Zheng

Z. W.

(2023). Spatial characteristics and influencing factors of the origin of telecommunication network fraud criminals. Geographical Research, 42(12), 3219–3234.

43.

Zhang

(2024). Bangzhu Xinxi Wangluo Fanzui Huodong Zui de Zaitan tao [A re-examination of the crime of assisting information network criminal activities]. Studies in Law and Business, 41(1), 21–41.

44.

Zhao

Huang

Chen

(2020). Dianxin Zhapian Zhong Qingnian Shoupianzhe de Xinren Xingcheng ji qi Xinli: Jiyu 9 Ming 90 Hou Dianxin Zhapian Shoupianzhe de Zhixing Fenxi [Trust formation and psychological mechanisms among young victims of telecom-fraud: A qualitative analysis of nine post-90s victims]. China Youth Studies, 3, 49–54.

45.

Zhao

Gan

Luo

(2024). Beidong Juanru yu Zhudong Xuanze: Qingnian Canyu Dianxin Wangluo Zhapian Fanzui de Guochengxing Jizhi [Passive involvement and active choice: The processual mechanism of youth participation in telecom-network fraud]. Youth Exploration, 4, 55–67.