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Environmental factors influencing target selection for residential burglary: experimental study using virtual reality

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Abstract

Data on the decision-making process of residential burglars at the micro-level are scarce. Furthermore, to the best of our knowledge, none of the related studies have investigated multiple relationships between the design features of a target, a burglar’s assessment of effort and risk involved in the crime, and the final decision on target selection. This study aimed to test the hypothesis that a burglar’s judgment of how difficult (ease of intrusion) and how risky (risk of detection) it would be to break into a certain target may mediate the relationship between the target’s design features and target selection. The experiment using virtual reality was conducted to obtain more credible data by maximizing the immersion of participants, and the collected data were analyzed using path analysis. The results showed that the assessment of ease of intrusion and risk of detection for a burglary target served as mediators between the design features of the target and the decision on target selection. This study also found that the ease of intrusion and risk of detection were not evaluated independently but instead had influential relationships. These results suggest that when developing design strategies for burglary prevention, it is important to check the overall level of ease and risk of the possible intrusion routes of a target and their correlation by considering various environmental factors around the intrusion routes.

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Notes

  1. The term “assessment criteria” employed in this study refers to the criteria that burglars would use to compare the costs and benefits of their decisions. More specifically, based on the rational choice theory, the “risk of detection (indicating risks)” and “ease of intrusion (indicating efforts)” were defined as elements of the assessment criteria. Other studies have adopted different terminology, such as “surveillability,” “accessibility,” “visibility,” “occupancy,” and “wealth,” which seems to be partly based on the concept of Crime Prevention Through Environmental Design (e.g., Langton and Steenbeek 2017; Roth and Roberts 2017; Roth and Trecki 2017).

  2. The values of all variables in this study were set in a direction favorable to burglary. Thus, in the case of the variable “Risk of detection,” the higher the variable value, the lower the risk of detection. Intuitively speaking, the variable “Risk of detection” indicates the degree of "safety" from detection for burglars. The term “risk of detection” was adopted in consideration of continuity with the terminology of previous studies.

  3. The list of 24 previous studies reviewed is as follows: Agarbati (2015); Amiri (2019); Bernasco (2011); Blevins et al. (2012); Buddhadasa (2021); Comeau and Klofas (2014); Garcia-Retamero and Dhami (2009); Homel et al. (2013); Hwang et al. (2017); Kim et al. (2017); Langton and Steenbeek (2017); Lee and Lee (2008); Macintyre (2001); Montoya et al. (2016); Nee (2015); Nee and Meenaghan (2006); Nee and Taylor (1988); Peeters (2013); Peeters et al. (2018); Roth and Roberts (2017); Sanders et al. (2017); Snook et al. (2011); Van Gelder et al. (2017); Wright and Logie (1988).

  4. In our previous study (Park and Lee 2021) that analyzed the same database, we conducted a logistic regression analysis to investigate how the design features of a detached house affect burglars’ intrusion route choice. In contrast, the present study aimed to test a hypothetical path model estimating the impact of design features on a burglar’s target selection and to investigate the mediating effects of the assessment criteria between design features and burglar’s target selection.

  5. Since this study aims to investigate the general relationships between the research variables, we did not include a discussion of why the path models of these two intrusion routes were not well-fitted to the collected data and, if so, how the variables would relate to each other, especially for these routes.

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Funding

This work was supported by the National Research Foundation of Korea grant funded by the Korea government [No. NRF-2019R1A2C1085262].

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Authors and Affiliations

  1. Department of Architecture, Korea University, 145, Anam-Ro, Seongbuk-Gu, Seoul, 02841, Republic of Korea

    So Yeon Park & Kyung Hoon Lee

  2. Department of Urbanism, Faculty of Architecture and the Built Environment, Delft University of Technology (TU Delft), Julianalaan 134, 2628 BL, Delft, The Netherlands

    So Yeon Park

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  1. So Yeon Park
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Contributions

Conceptualization: SY.P., KH.L.; Methodology: SY.P., KH.L.; Formal analysis and investigation: SY.P.; Writing—original draft preparation: SY.P.; Writing—review and editing: SY.P., KH.L.; Funding acquisition: KH.L.; Resources: SY.P.; Supervision: KH.L.

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Correspondence to Kyung Hoon Lee.

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Appendices

Appendix 1

See Table 5.

Table 5 Previous studies related to our variables
Full size table

Appendix 2

A short description explaining the virtual situation presented to the participants.

“You are currently unemployed. You have committed several crimes (breaking into houses and stealing goods) to cover living and entertainment expenses. Fortunately, you have never been arrested by the police. For the past few months, you have been suffering from a lack of money and thus have decided to commit burglary to make some money. Based on past criminal experiences, you have selected a certain residential area, in which detached houses are concentrated, in the suburbs. The chosen area is known to be predominantly populated by the middle class. At 3 pm on weekdays, you visited the selected area and picked one block. Now you are standing at the entry of the block, wanting to find the right target to commit a crime.”

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Park, S.Y., Lee, K.H. Environmental factors influencing target selection for residential burglary: experimental study using virtual reality. J Hous and the Built Environ 38, 1149–1175 (2023). https://doi.org/10.1007/s10901-022-09987-5

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