Advertisement

Improving Offence Solvability and Detection Rates at Non-residential Burglary: Predicting Single and Multiple Repeat Incidence

  • Richard Timothy CoupeEmail author
  • Katrin Mueller-Johnson
Chapter
  • 128 Downloads

Abstract

Predicting repeat burglary incidence at non-residential premises promises to make what may be safer burglaries for offenders into very risky ones by facilitating the use of entrapment techniques. By isolating the subset of cases that are highly likely to be repeat victimised, burglary solvability and detection rates may be cost-effectively improved. A fifth of burgled premises face an 80% risk of being re-victimised and, through the use of covert CCTV, silent or ‘delayed-audible’ alarms and electronic tracking devices installed in stolen goods, present opportunities for cost-effectively improving detection rates by up to 15%, with multiple repeat burglaries offering additional opportunities. Realising the benefits of improved incident solvability and detection is likely to depend on how the approach is dealt with in practice and the responses that offenders make.

Keywords

Burglary Single repeat Multiple repeat Prediction Solvability Detection 

References

  1. Ahlberg, J., & Knutsson, J. (1990). The risk of detection. Journal of Quantitative Criminology, 6(1), 117–130.CrossRefGoogle Scholar
  2. Ashton, J., Brown, I., Senior, B., & Pease, K. (1998). Repeat victimisation: Offender accounts. International Journal of Risk, Security and Crime Prevention, 3(4), 269–279.Google Scholar
  3. Bernasco, W. (2008). Them again? Same-offender involvement in repeat and near repeat burglaries. European Journal of Criminology, 5(4), 411–431.CrossRefGoogle Scholar
  4. Blumstein, A., Cohen, J., Das, S., & Miotra, D. (1988). Specialization and seriousness during adult criminal careers. Journal of Quantitative Criminology, 4(4), 303–345.Google Scholar
  5. Bowers, K., Hirschfield, A., & Johnson, S. (1998). Victimisation revisited: A case study of non-residential repeat burglary on Merseyside. The British Journal of Criminology, 38(3), 429–452.CrossRefGoogle Scholar
  6. Bowers, K., & Johnson, S. (2005). Domestic burglary repeats and space-time clusters: The dimensions of risk. European Journal of Criminology, 2(1), 67–92.CrossRefGoogle Scholar
  7. Budd, T. (1999). Burglary of domestic dwellings: Findings from the British Crime Survey (Home Office Statistical Bulletin 4/99). London: Home Office.Google Scholar
  8. Cahalane, M. (2001). Reducing false alarms has a price—so does response: Is the real price worth paying? Security Journal, 14(1), 31–53.CrossRefGoogle Scholar
  9. Chenery, S., Holt, J., & Pease, K. (1997). Biting back II: Reducing repeat victimisation in Huddersfield (Crime Detection and Prevention Series, Paper 82). London: Home Office.Google Scholar
  10. Coupe, R. T., & Kaur, S. (2005). The role of alarms and CCTV in detecting non-residential burglary. Security Journal, 18(2), 53–72.CrossRefGoogle Scholar
  11. Coupe, R. T., & Onodu, N. M. (1997). Evaluating the impact of CASE: An empirical comparison of retrospective and cross-sectional survey approaches. European Journal of Information Systems, 6(1), 15–24.CrossRefGoogle Scholar
  12. Coupe, T. (2017). Burglary decisions. In W. Bernasco, H. Elffers, & J.-L. van Gelder (Eds.), The Oxford handbook on offender decision making. Oxford: Oxford University Press.Google Scholar
  13. Coupe, T., & Fox, B. H. (2015). A risky business: How do access, exposure and guardians affect the chances of non-residential burglars being seen? Security Journal, 28(1), 71–92.CrossRefGoogle Scholar
  14. Coupe, T., & Griffiths, M. (1996). Solving residential burglary (Police Research Group Crime Detection and Prevention Services, Paper 77). London: Home Office.Google Scholar
  15. Eck, J. E. (1979). Managing case assignments: The burglary investigation decision model replication. Washington, DC: Police Executive Research Forum.Google Scholar
  16. Ericsson, U. (1995). Straight from the horse’s mouth. Forensic Update, 43, 23–25.Google Scholar
  17. Farrell, G., & Pease, K. (1993). Once bitten, twice bitten: Repeat victimisation and its implications for crime prevention (Crime Prevention Unit Series, Paper 46). London: Home Office.Google Scholar
  18. Farrell, G., Phillips, C., & Ken Pease, K. (1995). Like taking candy. Why does repeat victimisation occur? The British Journal of Criminology, 35(3), 384–399.CrossRefGoogle Scholar
  19. Hakim, S., & Shachmurove, Y. (1996). Spatial and temporal patterns of commercial burglaries. American Journal of Economics and Sociology, 55(4), 443–456.CrossRefGoogle Scholar
  20. Johnson, D. (2008). The near-repeat burglary phenomenon. In S. Chainey & J. Ratcliffe (Eds.), Crime mapping case studies: Practice and research. Chichester: Wiley.Google Scholar
  21. Johnson, S. D., & Bowers, K. J. (2004). The burglary as clue to the future: The beginnings of prospective hot-spotting. European Journal of Criminology, 1(2), 237–255.CrossRefGoogle Scholar
  22. Johnson, S. D., Bowers, K. J., & Hirschfield, A. (1997). New insights into the spatial and temporal distribution of repeat victimisation. The British Journal of Criminology, 37(2), 224–241.CrossRefGoogle Scholar
  23. Johnson, S. D., Summers, L., & Pease, K. (2009). Offender as forager? A direct test of the boost account of victimisation. Journal of Quantitative Criminology, 25(2), 181–200.CrossRefGoogle Scholar
  24. Mirrlees-Black, C., & Ross, A. (1996). Crime against retail and manufacturing premises: Findings from the 1994 Commercial Victimisation Survey. London: Home Office.Google Scholar
  25. Palmer, E. J., Holmes, A., & Hollin, C. R. (2002). Investigating burglars’ decisions: Factors influencing target choice, method of entry, reasons for offending, repeat victimisation of a property and victim awareness. Security Journal, 15(1), 7–18.CrossRefGoogle Scholar
  26. Pease, K. (1998). Repeat victimisation: Taking stock (Crime Detection and Prevention Series, Paper 90). London: Home Office.Google Scholar
  27. Polvi, N., Looman, T., Humphries, C., & Pease, K. (1991). The time course of repeat burglary victimisation. The British Journal of Criminology, 31(4), 411–414.CrossRefGoogle Scholar
  28. Shover, N. (1991). Burglary. In M. Tonry & N. Morris (Eds.), Crime and justice: An annual review of research (pp. 73–113). Chicago: University of Chicago Press.Google Scholar
  29. Smit, P., Meijer, R. F., & Groen, P.-P. J. (2004). Detection rates, an international comparison. European Journal on Criminal Policy and Research, 10(2–3), 225–253.CrossRefGoogle Scholar
  30. Spelman, W. (1995). Once bitten, then what? Cross-sectional and time-course explanations of repeat victimisation. The British Journal of Criminology, 35(3), 366–383.CrossRefGoogle Scholar
  31. Taylor, P., & Bond, S. (2012). Crimes detected in England and Wales 2011/12 (Home Office Statistical Bulletin 08/12). London: Home Office.Google Scholar
  32. Thanassoulis, E. (1995). Assessing police forces in England and Wales using data envelopment analysis. European Journal of Operational Research, 87(3), 641–657.CrossRefGoogle Scholar
  33. Townsley, M., Homel, R., & Chaseling, J. (2003). Infectious burglaries: A test of the near repeat hypothesis. The British Journal of Criminology, 43(3), 615–633.CrossRefGoogle Scholar
  34. Tseloni, A., & Pease, K. (2003). Repeat personal victimisation. ‘Boosts’ or ‘flags’? The British Journal of Criminology, 43(1), 196–212.CrossRefGoogle Scholar
  35. Tseloni, A., & Pease, K. (2004). Repeat personal victimisation: Random effects, event dependence and unexplained heterogeneity. The British Journal of Criminology, 44(6), 931–945.CrossRefGoogle Scholar
  36. Wright, O. (2013). Urban to rural: An exploratory analysis of burglary and vehicle crime with a rural context (unpublished MSt thesis). University of Cambridge.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Richard Timothy Coupe
    • 1
    Email author
  • Katrin Mueller-Johnson
    • 1
  1. 1.University of Cambridge, Institute of CriminologyCambridgeUK

Personalised recommendations