Environmental Criminology and Cybercrime: Shifting Focus from the Wine to the Bottles

  • Fernando Miró-Llinares
  • Asier MonevaEmail author
Living reference work entry


This chapter addresses the ability of the criminological approaches that comprise Environmental Criminology to constitute an adequate theoretical framework to analyze and understand the situational aspects of crimes committed through cyberspace and to define the most appropriate prevention strategies. The chapter begins by examining how these approaches have been applied. Subsequently, the reasons why the environmental approach can offer much more in this area if some apparent obstacles are overcome are presented. Finally, a method of applying these midrange theoretical frameworks to different cybercrimes is proposed. Relying on multiple empirical studies, it is stated that the essential premise of the environmental approach is also observed in cybercrime: the existence of situational patterns. These patterns are derived from the different ways in which offenders and targets, in the absence of guardians, converge in cyber places: digital interaction environments that shape the situational opportunities in which people interact. The chapter ends by summarizing the application possibilities of approaches such as the Crime Pattern Theory and Situational Crime Prevention in connection with the Routine Activity Theory and the Rational Choice Theory. It is proposed that many of the geographical applications derived from these approaches and some of their basic theoretical premises need to be adapted while seeking to enhance their strengths and mitigate the effects of their weaknesses.


Environmental Criminology Crime Science Criminological theory Prevention Opportunity Geographical gap Cyber place Crime event Crime patterns 



We thank the editors of this fantastic handbook and especially Prof. Tom Holt from Michigan State University, for their confidence in us to write this chapter on Environmental Theories. We would also like to thank Prof. Marcus Felson of Texas State University for his insights in several discussions that have served to consolidate the research presented here. Finally, we would like to thank Prof. Steven Kemp of the University of Girona for his comments that have greatly improved the translation of this work.


This research has been funded by the Spanish Ministry of Economy, Industry, and Competitiveness under the Criminology, empirical evidence, and criminal policy project: on incorporating scientific evidence to decision-making regarding criminalization of conducts (Reference DER2017-86204-R).

This research has been funded by the Spanish Ministry of Education, Culture and Sports under the University Faculty Training (FPU) Grant (Reference FPU16/01671).


  1. Agarwal, N., Gupta, R., Singh, S. K., & Saxena, V. (2017). Metadata based multi-labelling of YouTube videos. In 7th international conference on cloud computing, data science & engineering-confluence (pp. 586–590). Noida: IEEE. Scholar
  2. Aldridge, J., & Décary-Hétu, D. (2014). Not an ‘Ebay for Drugs’: The Cryptomarket ‘Silk Road’ as a paradigm shifting criminal innovation. SSRN Electronic Journal.
  3. Barr, R., & Pease, K. (1990). Crime placement, displacement, and deflection. Crime and Justice, 12, 277–318. Scholar
  4. Birks, D., Townsley, M., & Stewart, A. (2012). Generative explanations of crime: Using simulation to test criminological theory. Criminology, 50(1), 221–254. Scholar
  5. Bossler, A. M., & Holt, T. J. (2009). On-line activities, guardianship, and malware infection: An examination of routine activities theory. International Journal of Cyber Criminology, 3(1), 400–420.Google Scholar
  6. Bossler, A., & Holt, T. J. (2016). Cybercrime in progress: Theory and prevention of technology-enabled offenses. New York: Routledge.Google Scholar
  7. Bottoms, A. (2012). Developing socio-spatial criminology. In M. Maguire, R. Morgan, & R. Reiner (Eds.), The Oxford handbook of criminology (pp. 450–488). Oxford: Oxford University Press. Scholar
  8. Bowers, K., & Johnson, S. D. (2016). Situational prevention. In D. Weisburd, D. P. Farrington, & C. Gill (Eds.), What works in crime prevention and rehabilitation: Lessons from systematic reviews (pp. 111–136). New York: Springer.CrossRefGoogle Scholar
  9. Braga, A. A. (2005). Hot spots policing and crime prevention: A systematic review of randomized controlled trials. Journal of Experimental Criminology, 1(3), 317–342. Scholar
  10. Brantingham, P. L. (2011). Computational criminology. In 2011 European intelligence and security informatics conference (EISIC) (pp. 3–3). Athens, Greece IEEE.Google Scholar
  11. Brantingham, P. L., & Brantingham, P. J. (1981). Notes on the geometry of crime. In P. J. Brantingham & P. L. Brantingham (Eds.), Environmental criminology (pp. 27–53). Beverly Hills: SAGE.Google Scholar
  12. Brantingham, P., & Brantingham, P. (1995). Criminality of place. European Journal on Criminal Policy and Research, 3(3), 5–26. Scholar
  13. Broadhurst, R., Grabosky, P., Alazab, M., Bouhours, B., & Chon, S. (2014). An analysis of the nature of groups engaged in cyber crime. International Journal of Cyber Criminology, 8(1), 1–20.Google Scholar
  14. Burnap, P., & Williams, M. L. (2015). Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making. Policy and Internet, 7(2), 223–242. Scholar
  15. Caneppele, S., & Aebi, M. F. (2017). Crime drop or police recording flop? On the relationship between the decrease of offline crime and the increase of online and hybrid crimes. Policing: A Journal of Policy and Practice.
  16. Capone, D., & Nichols, W. J. (1976). Urban structure and criminal mobility. American Behavioral Scientist, 20(2), 199–213. Scholar
  17. Choi, K. S., & Lee, J. R. (2017). Theoretical analysis of cyber-interpersonal violence victimization and offending using cyber-routine activities theory. Computers in Human Behavior, 73, 394–402. Scholar
  18. Clarke, R. V. (1992). Situational crime prevention: Successful case studies. New York: Harrow and Heston Publishers.Google Scholar
  19. Clarke, R. V. (1997). Situational crime prevention: Successful case studies (2nd ed.). Guilderland: Harrow and Heston Publishers.Google Scholar
  20. Clarke, R. V. (2010). Crime science. In E. McLaughlin & T. Newburn (Eds.), The SAGE handbook of criminological theory (pp. 271–283). London: SAGE. Scholar
  21. Clarke, R. V. (2018). Book review [Review of the book Place matters: Criminology for the twenty-first century, by Weisburd, D., Eck, J. E., Braga, A. A., & Cave, B.]. Journal of Criminal Justice Education, 29(1), 157–159.CrossRefGoogle Scholar
  22. Clarke, R. V., & Weisburd, D. (1994). Diffusion of crime control benefits: Observations on the reverse of displacement. Crime Prevention Studies, 2, 165–184.Google Scholar
  23. Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44(4), 588–608.CrossRefGoogle Scholar
  24. Cornish, D. B., & Clarke, R. V. (1986). The reasoning criminal. New York: Springer.CrossRefGoogle Scholar
  25. Cornish, D. B., & Clarke, R. V. (2003). Opportunities, precipitators and criminal decisions: A reply to Wortley’s critique of situational crime prevention. Crime Prevention Studies, 16, 41–96.Google Scholar
  26. Cozens, P. M., Saville, G., & Hillier, D. (2005). Crime prevention through environmental design (CPTED): A review and modern bibliography. Property Management, 23(5), 328–356. Scholar
  27. Cross, C. (2015). No laughing matter: Blaming the victim of online fraud. International Review of Victimology, 21(2), 187–204. Scholar
  28. Cullen, F. T., & Kulig, T. C. (2018). Evaluating theories of environmental criminology: Strengths and weaknesses. In G. J. N. Bruinsma & S. D. Johnson (Eds.), The Oxford handbook of environmental criminology (pp. 160–176). Oxford: Oxford University Press. Scholar
  29. Décary-Hétu, D., & Morselli, C. (2011). Gang presence in social network sites. International Journal of Cyber Criminology, 5(2), 876–890.Google Scholar
  30. Eck, J. (1994). Drug markets and drug places: A case-control study of the spatial structure of illicit drug dealing. Doctoral dissertation, University of Maryland.Google Scholar
  31. Ekblom, P. (1997). Gearing up against crime: A dynamic framework to help designers keep up with the adaptive criminal in a changing world. International Journal of Risk Security and Crime Prevention, 2, 249–266.Google Scholar
  32. Felson, M. (1986). Linking criminal choices, routine activities, informal control, and criminal outcomes. In D. Cornish & R. Clarke (Eds.), The reasoning criminal (pp. 119–128). Secaucus: Springer.CrossRefGoogle Scholar
  33. Felson, M. (2012). Prólogo. In F. Miró-Llinares (Ed.), El Cibercrimen. Fenomenología y criminología de la delincuencia en el ciberespacio [Foreword] (pp. 13–16). Madrid: Martial Pons.Google Scholar
  34. Felson, M., & Eckert, M. (2016). Crime and everyday life (5th ed.). Los Angeles: SAGE.Google Scholar
  35. Ferrara, E., Varol, O., Davis, C., Menczer, F., & Flammini, A. (2016). The rise of social bots. Communications of the ACM, 59(7), 96–104. Scholar
  36. Gabor, T. (1981). The crime displacement hypothesis: An empirical examination. Crime & Delinquency, 27(3), 390–404. Scholar
  37. Grabosky, P. N. (2001). Virtual criminality: Old wine in new bottles? Social & Legal Studies, 10(2), 243–249. Scholar
  38. Guerette, R. T., & Bowers, K. J. (2009). Assessing the extent of crime displacement and diffusion of benefits: A review of situational crime prevention evaluations. Criminology, 47(4), 1331–1368. Scholar
  39. Guerry, A. M. (1833). Essai sur la statistique morale de la France. Paris: Crochard.Google Scholar
  40. Guo, R. M. (2008). Stranger danger and the online social network. Berkeley Technology Law Journal, 23(1), 617–644. Scholar
  41. Harries, K. D. (1976). Cities and crime: A geographic model. Criminology, 14, 369–386. Scholar
  42. Harries, K. (1999). Mapping crime: Principles and practice. Washington, DC: National Institute of Justice.Google Scholar
  43. Hartel, P. H., Junger, M., & Wieringa, R. J. (2010). Cyber-crime science = crime science + information security. University of Twente. Retrieved from
  44. Hinduja, S., & Kooi, B. (2013). Curtailing cyber and information security vulnerabilities through situational crime prevention. Security Journal, 26(4), 383–402. Scholar
  45. Holt, T. J., & Bossler, A. M. (2008). Examining the applicability of lifestyle-routine activities theory for cybercrime victimization. Deviant Behavior, 30(1), 1–25. Scholar
  46. Holt, T. J., & Bossler, A. M. (2013). Examining the relationship between routine activities and malware infection indicators. Journal of Contemporary Criminal Justice, 29(4), 420–436. Scholar
  47. Holt, T. J., Smirnova, O., & Hutchings, A. (2016). Examining signals of trust in criminal markets online. Journal of Cybersecurity, 2(2), 137–145. Scholar
  48. Holt, T. J., van Wilsem, J., van de Weijer, S., & Leukfeldt, R. (2018). Testing an integrated self-control and routine activities framework to examine malware infection victimization. Social Science Computer Review.
  49. Hosseinmardi, H., Mattson, S. A., Rafiq, R. I., Han, R., Lv, Q., & Mishra, S. (2015). Detection of cyberbullying incidents on the Instagram social network. arXiv preprint arXiv:1503.03909.Google Scholar
  50. Hutchings, A., & Clayton, R. (2016). Exploring the provision of online booter services. Deviant Behavior, 37(10), 1163–1178. Scholar
  51. Hutchings, A., & Holt, T. J. (2014). A crime script analysis of the online stolen data market. British Journal of Criminology, 55(3), 596–614. Scholar
  52. Hutchings, A., & Holt, T. J. (2017). The online stolen data market: Disruption and intervention approaches. Global Crime, 18(1), 11–30. Scholar
  53. Jeffery, C. R. (1977). Crime prevention through environmental design. Beverly Hills: SAGE.Google Scholar
  54. Junger, M., Montoya, L., Hartel, P., & Heydari, M. (2017). Towards the normalization of cybercrime victimization: A routine activities analysis of cybercrime in Europe. In 2017 international conference on cyber situational awareness, data analytics and assessment (cyber SA) (pp. 1–8). London, United Kingdom, IEEE.
  55. Khey, D. N., & Sainato, V. A. (2013). Examining the correlates and spatial distribution of organizational data breaches in the United States. Security Journal, 26(4), 367–382. Scholar
  56. Kigerl, A. (2012). Routine activity theory and the determinants of high cybercrime countries. Social Science Computer Review, 30(4), 470–486. Scholar
  57. Kigerl, A. C. (2013). Infringing nations: Predicting software piracy rates, bittorrent tracker hosting, and p2p file sharing client downloads between countries. International Journal of Cyber Criminology, 7(1), 62–80.Google Scholar
  58. Klausen, J., Barbieri, E. T., Reichlin-Melnick, A., & Zelin, A. Y. (2012). The YouTube Jihadists: A social network analysis of Al-Muhajiroun’s propaganda campaign. Perspectives on Terrorism, 6(1), 36–53.Google Scholar
  59. 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. Scholar
  60. Leukfeldt, E. R., & Yar, M. (2016). Applying routine activity theory to cybercrime: A theoretical and empirical analysis. Deviant Behavior, 37(3), 263–280. Scholar
  61. Leukfeldt, E. R., Kleemans, E. R., & Stol, W. P. (2016). Cybercriminal networks, social ties and online forums: Social ties versus digital ties within phishing and malware networks. British Journal of Criminology, 57(3), 704–722. Scholar
  62. Maimon, D., Kamerdze, A., Cukier, M., & Sobesto, B. (2013). Daily trends and origin of computer-focused crimes against a large university computer network: An application of the routine-activities and lifestyle perspective. British Journal of Criminology, 53(2), 319–343. Scholar
  63. Maimon, D., Alper, M., Sobesto, B., & Cukier, M. (2014). Restrictive deterrent effects of a warning banner in an attacked computer system. Criminology, 52(1), 33–59. Scholar
  64. Maimon, D., Wilson, T., Ren, W., & Berenblum, T. (2015). On the relevance of spatial and temporal dimensions in assessing computer susceptibility to system trespassing incidents. British Journal of Criminology, 55(3), 615–634. Scholar
  65. Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2010). Potential factors of online victimization of youth: An examination of adolescent online behaviors utilizing routine activity theory. Deviant Behavior, 31(5), 381–410. Scholar
  66. Medina-Ariza, J. J. (2011). Políticas y estrategias de prevención del delito y seguridad ciudadana. Madrid: Edisofer.Google Scholar
  67. Miró-Llinares, F. (2011). La oportunidad criminal en el ciberespacio: aplicación y desarrollo de la teoría de las actividades cotidianas para la prevención del cibercrimen. Revista Electrónica de Ciencia Penal y Criminología, 13(7), 1–55.Google Scholar
  68. Miró-Llinares, F. (2012). El cibercrimen. Fenomenología y criminología de la delincuencia en el ciberespacio. Madrid: Marcial Pons.Google Scholar
  69. Miró-Llinares, F. (2015). That cyber routine, that cyber victimization: Profiling victims of cybercrime. In R. G. Smith, R. C. C. Cheung, & L. Y. C. Lau (Eds.), Cybercrime risks and responses (pp. 47–63). London: Palgrave Macmillan. Scholar
  70. Miró-Llinares, F., & Johnson, S. D. (2018). Cybercrime and place: Applying environmental criminology to crimes in cyberspace. In G. J. N. Bruinsma & S. D. Johnson (Eds.), The Oxford handbook of environmental criminology (pp. 883–906). Oxford: Oxford University Press. Scholar
  71. Miró-Llinares, F., & Rodriguez-Sala, J. J. (2016). Cyber hate speech on twitter: Analyzing disruptive events from social media to build a violent communication and hate speech taxonomy. International Journal of Design and Nature and Ecodynamics, 11(3), 406–415. Scholar
  72. Miró-Llinares, F., Moneva, A., & Esteve, M. (2018). Hate is in the air! But where? Introducing an algorithm to detect hate speech in digital microenvironments. Crime Science, 7(15), 1–12. Scholar
  73. Näsi, M., Räsänen, P., Kaakinen, M., Keipi, T., & Oksanen, A. (2017). Do routine activities help predict young adults’ online harassment: A multi-nation study. Criminology & Criminal Justice, 17(4), 418–432. Scholar
  74. Navarro, J. N., & Jasinski, J. L. (2013). Why girls? Using routine activities theory to predict cyberbullying experiences between girls and boys. Women & Criminal Justice, 23(4), 286–303. Scholar
  75. Newman, G. R., & Clarke, R. V. (2003). Superhighway robbery: Preventing e-commerce crime. New York: Routledge.Google Scholar
  76. Pease, K. (2001). Crime futures and foresight: Challenging criminal behaviour in the information age. In D. Wall (Ed.), Crime and the Internet (pp. 30–40). London: Routledge.Google Scholar
  77. Pratt, T. C., Holtfreter, K., & Reisig, M. D. (2010). Routine online activity and Internet fraud targeting: Extending the generality of routine activity theory. Journal of Research in Crime and Delinquency, 47(3), 267–296. Scholar
  78. Quetelet, L. A. J. (1842). A treatise on man and the development of his faculties. Edinburgh: W. and R. Chambers.Google Scholar
  79. Reyns, B. W. (2010). A situational crime prevention approach to cyberstalking victimization: Preventive tactics for Internet users and online place managers. Crime Prevention and Community Safety, 12(2), 99–118. Scholar
  80. 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. Scholar
  81. Reyns, B. W., & Henson, B. (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. Scholar
  82. Reyns, B. W., Henson, B., & Fisher, B. S. (2011). Being pursued online: Applying cyberlifestyle–routine activities theory to cyberstalking victimization. Criminal Justice and Behavior, 38(11), 1149–1169. Scholar
  83. Rossmo, D. K. (1999). Geographic profiling. Boca Raton: CRC Press.CrossRefGoogle Scholar
  84. Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and violent crime: A multilevel study of collective efficacy. Science, 277, 918–924. Scholar
  85. Shaw, C. R., & McKay, H. D. (1942). Juvenile delinquency and urban areas: A study of rates of delinquency in relation to differential characteristics of local communities in American cities. Chicago: University of Chicago Press.Google Scholar
  86. Sherman, L. W., Gartin, P. R., & Buerger, M. E. (1989). Hot spots of predatory crime: Routine activities and the criminology of place. Criminology, 27(1), 27–56. Scholar
  87. Shu, K., Sliva, A., Sampson, J., & Liu, H. (2018). Understanding cyber attack behaviors with sentiment information on social media. In R. Thomson, C. Dancy, A. Hyder, & H. Bisgin (Eds.), Social, cultural, and behavioral modeling (pp. 377–388). Cham: Springer. Scholar
  88. Vakhitova, Z. I., & Reynald, D. M. (2014). Australian Internet users and guardianship against cyber abuse: An empirical analysis. International Journal of Cyber Criminology, 8(2), 156–171.Google Scholar
  89. Van Wilsem, J. (2013). ‘Bought it, but never got it’: Assessing risk factors for online consumer fraud victimization. European Sociological Review, 29(2), 168–178. Scholar
  90. Vishwanath, A. (2014). Habitual Facebook use and its impact on getting deceived on social media. Journal of Computer-Mediated Communication, 20(1), 83–98. Scholar
  91. Wall, D. S. (2007). Policing cybercrimes: Situating the public police in networks of security within cyberspace. Police Practice and Research, 8(2), 183–205. Scholar
  92. Wei, C., Sprague, A., Warner, G., & Skjellum, A. (2008, March). Mining spam email to identify common origins for forensic application. In Proceedings of the 2008 ACM symposium on applied computing (pp. 1433–1437). Fortaleza, Brazil, ACM.Google Scholar
  93. Weisburd, D., & Green, L. (1995). Policing drug hot spots: The Jersey City drug market analysis experiment. Justice Quarterly, 12(4), 711–735. Scholar
  94. Weisburd, D., Bernasco, W., & Bruinsma, G. (Eds.). (2009). Putting crime in its place. New York: Springer.Google Scholar
  95. Weisburd, D., Telep, C. W., Hinkle, J. C., & Eck, J. E. (2010). Is problem-oriented policing effective in reducing crime and disorder? Findings from a Campbell systematic review. Criminology & Public Policy, 9(1), 139–172. Scholar
  96. Welsh, B. C., & Farrington, D. P. (2009). Public area CCTV and crime prevention: An updated systematic review and meta-analysis. Justice Quarterly, 26(4), 716–745. Scholar
  97. Wolfe, S. E., Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2016). Routine cell phone activity and exposure to sext messages: Extending the generality of routine activity theory and exploring the etiology of a risky teenage behavior. Crime & Delinquency, 62(5), 614–644. Scholar
  98. Wortley, R., & Townsley, M. (Eds.). (2016). Environmental criminology and crime analysis (2nd ed.). London: Routledge.Google Scholar
  99. Yar, M. (2005). The novelty of ‘cybercrime’ an assessment in light of routine activity theory. European Journal of Criminology, 2(4), 407–427. Scholar

Copyright information

© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CRIMINA Research Center for the Study and Prevention of CrimeMiguel Hernandez UniversityElcheSpain

Personalised recommendations