Skip to main content
SpringerLink
Log in

Examining context-specific perceptions of risk: exploring the utility of “human-in-the-loop” simulation models for criminology

  • Published:
Journal of Experimental Criminology Aims and scope Submit manuscript

Abstract

Objectives

To utilize a “human-in-the-loop” simulation methodology to examine the impact of high-risk environmental contexts on perceptions of victimization risk.

Methods

Fifty-nine participants navigated a virtual environment and encountered five two-alternative forced-choice decision points, with one alternative representing a high-risk environmental context in each case.

Results

Participants risk-aware decision-making was examined as a function of sex and age, both for their decisions overall and also at each specific decision point. Overall differences in total risk-aware decisions were observed for sex (with females more risk-aware) but not age. In addition to this, variation in perceived risk was also observed across the range of high-risk environmental contexts and there was also some indication of varying influence of age and sex on specific types of risk-aware decisions.

Conclusions

These results have interesting implications for research into context-specific perceptions of risk. These findings also support a stance that “human-in-the-loop” simulation modeling has good potential to contribute to criminology more broadly.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. For a review of human-in-the-loop simulations, see Dudfield and Butt (2003).

  2. These categories were originally termed ‘fear generators’; however, to maintain the clear focus on risk of victimization within this paper, this term has been dropped.

  3. This simulation used the most powerful workstation computer available at that time. The computer model was a Dell Precision M90 with a NVidia Quadro FX 1500 graphics card. Technically, the benchmark score for the Dell Precision M90 was 3,926 points for 3DMark 06 with the capacity to calculate Super Pi to 2 million in 1 minute and 12 seconds.

  4. It is unclear based on current literature that has examined alternative types of data which of these alternatives would produce the greatest sense of risk. Subsequent experiments will examine these issues in a systematic manner.

  5. No violation of the assumption of homogeneity of variance occurred here: Levene’s test, F (3,55) = 1.09, p < .37.

  6. For this analysis, the risk-aware decision each participant made was not an experimentally-defined independent variable. This resulted from the choice that they made when they encountered each decision-point. However, there is a precedent for undertaking this type of analysis based on cognitive psychology literature (e.g., the eyewitness identification literature from cognitive psychology dealing with lineup decision making such as Clare and Lewandowsky 2004, Meissner et al. 2001, Meissner and Memon 2002), which has been followed here.

References

  • Andrews, M., & Gatersleben, B. (2010). Variations in perceptions of danger, fear and preference in a simulated natural environment. Journal of Environmental Psychology. doi:10.1016/j.jenvp.2010.1004.1001.

  • Blascovich, J., Loomis, J., Beall, A. C., Swinth, K. R., Hoyt, C. L., & Bailenson, J. N. (2002). Immersive virtual environment technology as a methodological tool for social psychology. Psychological Inquiry, 13(2), 103–124.

    Article  Google Scholar 

  • Brantingham, P. J., & Brantingham, P. L. (1997). Understanding and controlling crime and fear of crime: conflicts and trade-offs in crime prevention planning. In S. P. Lab (Ed.), Crime Prevention at a Crossroads (pp. 43–60). Cincinatti: Andreson.

    Google Scholar 

  • Bronaugh, W. F. J. (2007). ‘Human-in-the-loop’ simulation: the right tool for port design. Port Technology International, 32, 1–2.

    Google Scholar 

  • Chen, B.-C., & Peng, H. (2000). Rollover prevention for sports utility vehicles with human-in-the-loop evaluations. Paper presented at the 5th International Symposium on Advanced Vehicle Control, Abb Arbor, Michigan.

  • Clare, J. (2011). Examination of systematic variations in burglars’ domain-specific perceptual and procedural skills. Psychology, Crime & Law, 17(3), 199–214.

    Article  Google Scholar 

  • Clare, J., & Lewandowsky, S. (2004). Verbalizing facial memory: Criterion effects in verbal overshadowing. Journal of Experimental Psychology. Learning, Memory, and Cognition, 30(4), 739–755.

    Article  Google Scholar 

  • Cozens, P., Neale, R., & Whitaker, J. (2003). Managing crime and the fear of crime at railway stations: a case study in South Wales. International Journal of Transport Management, 1(3), 121–132.

    Article  Google Scholar 

  • Cubukcu, E., & Nasar, J. L. (2005). Relation of physical form to spatial knowledge in large-scale virtual environments. Environment and Behavior, 37(3), 397–417.

    Article  Google Scholar 

  • Cummings, M. L. (2004). The need for command and control instant message adaptive interfaces: lessons learned from Tactical Tomahawk human-in-the-loop simulations. Cyberpsychology & Behavior, 7(6), 653–661.

    Article  Google Scholar 

  • Design Council. (2003). Think Thief: A Designer’s Guide to Designing Out Crime: Design Council.

  • Dudfield, H., & Butt, J. (2003). Review of non-ATM human-in-the-loop simulations: European Organisation for the Safety of Air Navigation: European Air Traffic Management Programme.

  • Eck, J. E., & Liu, L. (2008). Contrasting simulated and empirical experiments in crime prevention. Journal of Experimental Criminology, 4(3), 195–213.

    Article  Google Scholar 

  • Fattah, E. A. (1993). Research on fear of crime: some common conceptual and measurement problems. In W. Bilsky, C. Pfeiffer, & P. Wetzels (Eds.), Fear of Crime and Criminal Victimization (pp. 45–70). Stuttgart: Ferdinand Enke Verlag.

    Google Scholar 

  • Fisher, B. S., & Nasar, J. L. (1992). Fear of crime in relation to three exterior site features: prospect, refuge, and escape. Environment and Behavior, 24(1), 35–65.

    Article  Google Scholar 

  • Fisher, B. S., & Nasar, J. L. (1995). Fear spots in relation to microlevel physical cues: exploring the overlooked. Journal of Research in Crime and Delinquency, 32(2), 214–239.

    Article  Google Scholar 

  • Gabriel, U., & Greve, W. (2003). The psychology of fear of crime: conceptual and methodological perspectives. British Journal of Criminology, 43(3), 600–614.

    Google Scholar 

  • Goffman, E. (1971). Relations in Public: Microstudies of the Public Order. New York: Basic Books Inc.

    Google Scholar 

  • Groff, E., & Mazerolle, L. (2008). Simulated experiments and their potential role in criminology and criminal justice. Journal of Experimental Criminology, 4(3), 187–193.

    Article  Google Scholar 

  • Hanyu, K. (1997). Visual properties and affective appraisals in residential areas after dark. Journal of Environmental Psychology, 17(4), 301–315.

    Article  Google Scholar 

  • Hanyu, K. (2000). Visual properties and affective appraisals in residential areas in daylight. Journal of Environmental Psychology, 20(3), 273–284.

    Article  Google Scholar 

  • Herzog, T. R., & Flynn-Smith, J. A. (2001). Preference and perceived danger as a function of the perceived curvature, length, and width or urban alleys. Environment and Behavior, 33(5), 653–666.

    Article  Google Scholar 

  • Herzog, T. R., & Kirk, K. M. (2005). Pathway curvature and border visibility as predictors of preference and danger in forest settings. Environment and Behavior, 37(5), 620–639.

    Article  Google Scholar 

  • Hoyt, C. L., Blascovich, J., & Swinth, K. R. (2003). Social inhibition in immersive virtual environments. Prescence, 12(2), 183–195.

    Article  Google Scholar 

  • LaGrange, R. L., Ferraro, K. F., & Supancic, M. (1992). Perceived risk and fear of crime: role of social and physical incivilities. Journal of Research in Crime and Delinquency, 29(3), 311–334.

    Article  Google Scholar 

  • Meissner, C. A., & Memon, A. (2002). Verbal overshadowing: A special issue exploring theoretical and applied issues. Applied Cognitive Psychology, 16(8), 869–872.

    Article  Google Scholar 

  • Meissner, C. A., Brigham, J. C., & Kelley, C. M. (2001). The influence of retrieval processes in verbal overshadowing. Memory and Cognition, 29(1), 176–186.

    Article  Google Scholar 

  • Nee, C. (2011). Research on residential burglary: ways of improving validity and participants’ recall when gathering data. In W. Bernasco (Ed.), Offenders on offening: learning about crime from criminals. Devon: Willan Press (in press)

  • Nee, C., & Meenaghan, A. (2006). Expert decision making in burglars. British Journal of Criminology, 46(5), 935–949.

    Article  Google Scholar 

  • Park, A. J. (2008). Modeling the role of fear of crime in pedestrian navigation. PhD thesis, Simon Fraser University, Burnaby.

  • Smith, N. M., Lee, P. U., Prevôt, T., Mercer, J., Palmer, E. A., III, Battiste, V., et al. (2004). A human-in-the-loop evaluation of air-ground trajectory negotiation. Reston: American Institute of Aeronautics and Astronautics.

    Google Scholar 

  • Sollenberger, R. L., Willems, B., Della Rocco, P. S., Koros, A., & Truitt, T. (2005). Human-in-the-loop simulation evaluating the collection of the user request evaluation tool, traffic management advisor, and controller-pilot data link communications: experiment I - tool combinations. US Department of Transportation, Federal Aviation Administration.

  • Wang, K., & Taylor, R. B. (2006). Simulated walks through dangerous alleys: impacts of features and progress on fear. Journal of Environmental Psychology, 26, 269–283.

    Article  Google Scholar 

  • Warr, M. (1990). Dangerous situations: social context and fear of victimization. Social Forces, 68(3), 891–907.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Thompson Rivers University, Columbia, BC, Canada

    Andrew Park

  2. Crime Research Centre, University of Western Australia, 35 Stirling Hwy, Crawley, Western Australia, 6009, Australia

    Joseph Clare

  3. Simon Fraser University, Columbia, BC, Canada

    Andrew Park, Valerie Spicer, Patricia L. Brantingham & Tom Calvert

  4. Kwantlen Polytechnic University, Langley, BC, Canada

    Greg Jenion

Authors
  1. Andrew Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph Clare
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Valerie Spicer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Patricia L. Brantingham
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tom Calvert
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Greg Jenion
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joseph Clare.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Park, A., Clare, J., Spicer, V. et al. Examining context-specific perceptions of risk: exploring the utility of “human-in-the-loop” simulation models for criminology. J Exp Criminol 8, 29–47 (2012). https://doi.org/10.1007/s11292-011-9132-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11292-011-9132-x

Keywords

Search

Navigation