Which view states the definition of crime reflects the preferences of those who hold social power and influence in a particular legal jurisdiction?

• Ackerman, J. M., & Rossmo, D. K. (2015). How far to travel? A multilevel analysis of the residence-to-crime distance. Journal of Quantitative Criminology, 31(2), 237–262. https://doi.org/10.1007/s10940-014-9232-7.

  Article  Google Scholar 

• Alessandretti, L., Sapiezynski, P., Sekara, V., Lehmann, S., & Baronchelli, A. (2018). Evidence for a conserved quantity in human mobility. Nature Human Behaviour, 2(7), 485–491. https://doi.org/10.1038/s41562-018-0364-x.

  Article  Google Scholar 

• Arentze, T. A., Dellaert, B. G. C., & Timmermans, H. J. P. (2008). Modeling and measuring individuals’ mental representations of complex spatio-temporal decision problems. Environment and Behavior, 40(6), 843–869. https://doi.org/10.1177/0013916507309994.

  Article  Google Scholar 

• Arentze, T. A., & Timmermans, H. J. P. (2005). Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics. Transportation, 32(4), 321–340. https://doi.org/10.1007/s11116-004-7964-1.

  Article  Google Scholar 

• Banerjee, A., Duflo, E., Keniston, D., & Singh, N. (2019). The efficient deployment of police resources: Theory and new evidence from a randomized drunk driving crackdown in India (No. w26224). Cambridge, MA : National Bureau of Economic Research. https://doi.org/10.3386/w26224.

  Book  Google Scholar 

• Barbosa, H., de Lima-Neto, F., Evsukoff, A., & Menezes, R. (2015). The effect of recency to human mobility. EPJ Data Science, 4(1), 1–14. https://doi.org/10.1140/epjds/s13688-015-0059-8.

  Article  Google Scholar 

• Ben-Akiva, M. E., & Bowman, J. L. (2016). Integration of an activity-based model system and a residential location model. Urban Studies. https://doi.org/10.1080/0042098984529.

  Article  Google Scholar 

• Ben-Akiva, M. E., & Lerman, S. R. (1985). Discrete choice analysis: Theory and application to travel demand. Cambridge, MA: MIT Press.

  Google Scholar 

• Bernasco, W. (2006). Co-offending and the choice of target areas in burglary. Journal of Investigative Psychology and Offender Profiling, 3(3), 139–155. https://doi.org/10.1002/jip.49.

  Article  Google Scholar 

• Bernasco, W. (2008). Them again?: Same-offender involvement in repeat and near repeat burglaries. European Journal of Criminology, 5(4), 411–431. https://doi.org/10.1177/1477370808095124.

  Article  Google Scholar 

• Bernasco, W. (2010). A sentimental journey to crime: Effects of residential history on crime location choice. Criminology, 48(2), 389–416. https://doi.org/10.1111/j.1745-9125.2010.00190.x.

  Article  Google Scholar 

• Bernasco, W. (2018). Mobility and location choice of offenders. In G. J. N. Bruinsma & S. D. Johnson (Eds.), The Oxford handbook of environmental criminology. Oxford : Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190279707.001.0001/oxfordhb-9780190279707-e-17

  Chapter  Google Scholar 

• Bernasco, W. (2019). Adolescent offenders’ current whereabouts predict locations of their future crimes. PLoS ONE, 14(1), e0210733. https://doi.org/10.1371/journal.pone.0210733.

  Article  Google Scholar 

• Bernasco, W., & van Dijke, R. (2020). Do offenders avoid offending near home? A systematic review of the buffer zone hypothesis. Crime Science, 9(1), 1–10. https://doi.org/10.1186/s40163-020-00118-5.

  Article  Google Scholar 

• Bernasco, W., Johnson, S. D., & Ruiter, S. (2015). Learning where to offend: Effects of past on future burglary locations. Applied Geography, 60(Supplement C), 120–129. https://doi.org/10.1016/j.apgeog.2015.03.014.

  Article  Google Scholar 

• Bernasco, W., & Kooistra, T. (2010). Effects of residential history on commercial robbers’ crime location choices. European Journal of Criminology, 7(4), 251–265. https://doi.org/10.1177/1477370810363372.

  Article  Google Scholar 

• Bernasco, W., Ruiter, S., Bruinsma, G. J. N., Pauwels, L. J. R., & Weerman, F. M. (2013). Situational causes of offending: A fixed-effects analysis of space–time budget data. Criminology, 51(4), 895–926. https://doi.org/10.1111/1745-9125.12023.

  Article  Google Scholar 

• Bichler, G., Christie-Merrall, J., & Sechrest, D. (2011). Examining juvenile delinquency within activity space: Building a context for offender travel patterns. Journal of Research in Crime and Delinquency, 48(3), 472–506. https://doi.org/10.1177/0022427810393014.

  Article  Google Scholar 

• Bichler, G., Malm, A., & Christie-Merrall, J. (2012). Urban backcloth and regional mobility patterns as indicators of juvenile crime. In M. A. Andresen & J. B. Kinney (Eds.), Patterns, prevention, and geometry of crime (pp. 118–136). London, UK: Routledge.

  Google Scholar 

• Bichler, G., Malm, A., & Enriquez, J. (2014). Magnetic facilities: Identifying the convergence settings of juvenile delinquents. Crime and Delinquency, 60(7), 971–998. https://doi.org/10.1177/0011128710382349.

  Article  Google Scholar 

• Bichler, G., Schwartz, J. A., & Orosco, C. A. (2010). Delinquents on the move: Examining subgroup travel variability. Crime Patterns and Analysis, 3(1), 14–37.

  Google Scholar 

• Brantingham, P. J., & Tita, G. (2008). Offender mobility and crime pattern formation from first principles. In L. Liu & J. Eck (Eds.), Artificial crime analysis systems: Using computer simulations and geographic information systems (pp. 193–208). Pennsylvania: IGI Global.

  Chapter  Google Scholar 

• Brantingham, P. L., & Brantingham, P. J. (1991). Notes on the geometry of crime. In P. J. Brantingham & P. L. Brantingham (Eds.), Environmental criminology (2nd ed., pp. 27–54). Long Grove: Waveland Press.

  Google Scholar 

• Brantingham, P. L., & Brantingham, P. J. (1993). Environment, routine, and situation: Toward a pattern theory of crime. In R. V. Clarke & M. Felson (Eds.), Routine activity and rational choice (pp. 259–294). Piscataway, NJ: Transaction Publishers.

  Google Scholar 

• Brantingham, P. L., & Brantingham, P. J. (1995). Criminality of place: Crime generators and crime attractors. European Journal on Criminal Policy and Research, 3(3), 5–26. https://doi.org/10.1007/BF02242925.

  Article  Google Scholar 

• Brantingham, P. J., & Brantingham, P. L. (2012). The theory of target search. In F. T. Cullen & P. Wilcox (Eds.), The Oxford Handbook of Criminological Theory. Oxford : Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199747238.013.0028.

  Chapter  Google Scholar 

• Brantingham, P. J., Brantingham, P. L., & Andresen, M. A. (2008). The geometry of crime and crime pattern theory. In R. Wortley & M. Townsley (Eds.), Environmental Criminology and Crime Analysis (pp. 98–117). Milton Park: Taylor and Francis.

  Google Scholar 

• Brown, L. A., & Moore, E. G. (1970). The intra-urban migration process: A perspective. Geografiska Annaler Series B, Human Geography, 52(1), 1–13. https://doi.org/10.2307/490436.

  Article  Google Scholar 

• Canter, D., & Larkin, P. (2008). The environmental range of serial rapists. In D. Canter & D. Youngs (Eds.), Applications of geographical offender profiling (pp. 57–68). Farnham, UK: Ashgate.

  Google Scholar 

• Chorus, C. G., & Timmermans, H. J. P. (2010). Determinants of stated and revealed mental map quality: An empirical study. Journal of Urban Design, 15(2), 211–226. https://doi.org/10.1080/13574801003638095.

  Article  Google Scholar 

• Clare, J. (2011). Examination of systematic variations in burglars’ domain-specific perceptual and procedural skills. Psychology, Crime and Law, 17(3), 199–214. https://doi.org/10.1080/10683160903025810.

  Article  Google Scholar 

• Clarke, R. V., & Cornish, D. B. (1985). Modeling offenders’ decisions: A framework for research and policy. Crime and Justice, 6, 147–185.

  Article  Google Scholar 

• Cornish, D. B., & Clarke, R. V. (1986). The reasoning criminal: Rational choice perspectives on offending. Berlin: Springer-Verlag.

  Book  Google Scholar 

• Costello, A., & Wiles, P. (2001). GIS and the journey to crime: An analysis of patterns in South Yorkshire. In K. J. Bowers & A. Hirschfield (Eds.), Mapping and analysing crime data: Lessons from research and practice (pp. 27–60). Milton Park: Taylor and Francis.

  Google Scholar 

• Cromwell, P. F., Olson, J. N., & Avary, D. W. (1990). Breaking and entering: An ethnographic analysis of burglary (1st ed.). Newbury Park, CA: Sage.

  Google Scholar 

• Downs, R. M., & Stea, D. (1973). Cognitive maps and spatial behavior: Process and products. In R. M. Downs & D. Stea (Eds.), Image and environment: Cognitive mapping and spatial behavior (pp. 8–26). Aldine, CA: Aldine.

  Google Scholar 

• Elffers, H. (2004). Decision models underlying the journey to crime. In G. J. N. Bruinsma, H. Elffers, & J. W. De Keijser (Eds.), Punishment, places and perpetrators: Developments in criminology and criminal justice research (pp. 182–197). London: Willan.

  Google Scholar 

• Felson, M. (2008). The routine activity approach. In R. Wortley & L. Mazerolle (Eds.), Environmental criminology and crime analysis (pp. 87–97). London: Willan.

  Google Scholar 

• Frith, M. J. (2019). Modelling taste heterogeneity regarding offence location choices. Journal of Choice Modelling, 33, 100187. https://doi.org/10.1016/j.jocm.2019.100187.

  Article  Google Scholar 

• Frith, M. J., Johnson, S. D., & Fry, H. M. (2017). Role of the street network in burglars’ spatial decision-making. Criminology, 55(2), 344–376. https://doi.org/10.1111/1745-9125.12133.

  Article  Google Scholar 

• Gärling, T., & Axhausen, K. W. (2003). Introduction: Habitual travel choice. Transportation, 30(1), 1–11. https://doi.org/10.1023/A:1021230223001.

  Article  Google Scholar 

• Gentner, D., & Medina, J. (1998). Similarity and the development of rules. Cognition, 65(2), 263–297. https://doi.org/10.1016/S0010-0277(98)00002-X.

  Article  Google Scholar 

• Golledge, R. (1978). Representing, interpreting and using cognized environments. Papers in Regional Science, 41(1), 169–204. https://doi.org/10.1111/j.1435-5597.1978.tb01046.x.

  Article  Google Scholar 

• Golledge, R. (1999). Human wayfinding and cognitive maps. In R. Golledge (Ed.), Wayfinding behavior: Cognitive mapping and other spatial processes (pp. 5–45). Baltimore: Johns Hopkins University Press.

  Google Scholar 

• Golledge, R., & Stimson, R. (1997). Spatial behavior: A geographic perspective. New York, NY: Guilford Press.

  Google Scholar 

• González, M. C., Hidalgo, C. A., & Barabási, A.-L. (2008). Understanding individual human mobility patterns. Nature, 453(7196), 779–782. https://doi.org/10.1038/nature06958.

  Article  Google Scholar 

• Gould, P. (1966). On mental maps. Ann Arbor, MI: University of Michigan.

  Google Scholar 

• Gould, P. (1973). On mental maps. In R. M. Downs & D. Stea (Eds.), Image and environment: Cognitive maps and spatial behavior (pp. 182–220). Aldine, CA: Aldine.

  Google Scholar 

• Gould, P., & White, R. (1986). Mental maps (2nd ed.). London: Routledge.

  Google Scholar 

• Hammond, L., & Youngs, D. (2011). Decay functions and criminal spatial processes: Geographical offender profiling of volume crime. Journal of Investigative Psychology and Offender Profiling, 8(1), 90–102. https://doi.org/10.1002/jip.132.

  Article  Google Scholar 

• Hannes, E., Janssens, D., and Wets, G. (2006, August). Proximity is a state of mind: Exploring mental maps in daily activity travel behaviour. 11th International Conference on Travel Behaviour Research, Kyoto.

• Hannes, E., Janssens, D., & Wets, G. (2008). Destination choice in daily activity travel: Mental map’s repertoire. Transportation Research Record, 2054(1), 20–27. https://doi.org/10.3141/2054-03.

  Article  Google Scholar 

• Hannes, E., Janssens, D., & Wets, G. (2009). Does space matter? Travel mode scripts in daily activity travel. Environment and Behavior, 41(1), 75–100. https://doi.org/10.1177/0013916507311033.

  Article  Google Scholar 

• Hannes, E., Kusumastuti, D., Espinosa, M., Janssens, D., Vanhoof, K., & Wets, G. (2012). Mental maps and travel behaviour: Meanings and models. Journal of Geographical Systems, 14(2), 143–165. https://doi.org/10.1007/s10109-010-0144-2.

  Article  Google Scholar 

• Hanson, S., & Huff, O. J. (1988). Systematic variability in repetitious travel. Transportation, 15(1), 111–135. https://doi.org/10.1007/BF00167983.

  Article  Google Scholar 

• Hasan, S., Schneider, C. M., Ukkusuri, S. V., & González, M. C. (2013). Spatiotemporal patterns of urban human mobility. Journal of Statistical Physics, 151(1), 304–318. https://doi.org/10.1007/s10955-012-0645-0.

  Article  Google Scholar 

• Hillier, A., Smith, T. E., Whiteman, E. D., & Chrisinger, B. W. (2017). Discrete choice model of food store trips using National Household Food Acquisition and Purchase Survey (FoodAPS). International Journal of Environmental Research and Public Health. https://doi.org/10.3390/ijerph14101133.

  Article  Google Scholar 

• Horton, F. E., & Reynolds, D. R. (1971). Effects of urban spatial structure on individual behavior. Economic Geography, 47(1), 36–48. https://doi.org/10.2307/143224.

  Article  Google Scholar 

• Howard, R. W. (2000). Generalization and transfer: An interrelation of paradigms and a taxonomy of knowledge extension processes. Review of General Psychology, 4(3), 211–237. https://doi.org/10.1037/1089-2680.4.3.211.

  Article  Google Scholar 

• Ida, T., & Kuroda, T. (2006). Discrete choice analysis of demand for broadband in japan. Journal of Regulatory Economics, 29(1), 5–22. https://doi.org/10.1007/s11149-005-5124-y.

  Article  Google Scholar 

• Johnson, S. D., & Bowers, K. J. (2004). The stability of space-time clusters of burglary. The British Journal of Criminology, 44(1), 55–65. https://doi.org/10.1093/bjc/44.1.55.

  Article  Google Scholar 

• Johnson, S. D., Summers, L., & Pease, K. (2009). Offender as forager? A direct test of the boost account of victimization. Journal of Quantitative Criminology, 25(2), 181–200. https://doi.org/10.1007/s10940-008-9060-8.

  Article  Google Scholar 

• Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. American Economic Review, 93(5), 1449–1475. https://doi.org/10.1257/000282803322655392.

  Article  Google Scholar 

• Kang, C., Ma, X., Tong, D., & Liu, Y. (2012). Intra-urban human mobility patterns: An urban morphology perspective. Physica A: Statistical Mechanics and Its Applications, 391(4), 1702–1717. https://doi.org/10.1016/j.physa.2011.11.005.

  Article  Google Scholar 

• Knabe-Nichol, S., & Alison, L. (2011). The cognitive expertise of Geographic Profilers. In L. Alison & L. Rainbow (Eds.), Professionalizing offender profiling: Forensic and investigative psychology in practice (pp. 126–159). Milton Park: Taylor and Francis.

  Google Scholar 

• Kuang, D., Brantingham, P. J., & Bertozzi, A. (2017). Crime topic modeling. Crime. Science, 6(1), 1–20. https://doi.org/10.1186/s40163-017-0074-0.

  Article  Google Scholar 

• Lammers, M. (2018). Co-offenders’ crime location choice: Do co-offending groups commit crimes in their shared awareness space? The British Journal of Criminology, 58, 1193–1211. https://doi.org/10.1093/bjc/azx069.

  Article  Google Scholar 

• Lammers, M., Menting, B., Ruiter, S., & Bernasco, W. (2015). Biting once, twice: The influence of prior on subsequent crime location choice. Criminology, 53(3), 309–329. https://doi.org/10.1111/1745-9125.12071.

  Article  Google Scholar 

• Lantz, B., & Ruback, R. B. (2017). A networked boost: Burglary co-offending and repeat victimization using a network approach. Crime and Delinquency, 63(9), 1066–1090. https://doi.org/10.1177/0011128715597695.

  Article  Google Scholar 

• Lattimore, P., & Witte, A. (1986). Models of decision making under uncertainty: The criminal choice. In D. B. Cornish & R. V. Clarke (Eds.), The reasoning criminal (pp. 129–155). Berlin: Springer-Verlag. https://doi.org/10.4324/9781315134482-2.

  Chapter  Google Scholar 

• Lloyd, R., & Cammack, R. (1996). Constructing cognitive maps with orientation biases. In J. Portugali (Ed.), The construction of cognitive maps (pp. 187–213). Netherlands: Springer. https://doi.org/10.1007/978-0-585-33485-1_9.

  Chapter  Google Scholar 

• Long, D., Liu, L., Feng, J., & Zhou, S. (2018). Assessing the influence of prior on subsequent street robbery location choices: A case study in ZG city China. Sustainability, 10(6), 1818. https://doi.org/10.3390/su10061818.

  Article  Google Scholar 

• Mark, D. M., Freksa, C., Hirtle, S. C., Lloyd, R., & Tversky, B. (1999). Cognitive models of geographical space. International Journal of Geographical Information Science, 13, 747–774. https://doi.org/10.1080/136588199241003.

  Article  Google Scholar 

• McDaniel, M. A., Cahill, M. J., Robbins, M., & Wiener, C. (2014). Individual differences in learning and transfer: Stable tendencies for learning exemplars versus abstracting rules. Journal of Experimental Psychology: General, 143(2), 668–693. https://doi.org/10.1037/a0032963.

  Article  Google Scholar 

• McFadden, D. L. (1984). Econometric analysis of qualitative response models. In P. Griliches & M. D. Intriligator (Eds.), Handbook of econometrics (Vol. 2, pp. 105–142). Amsterdam: Elsevier. https://doi.org/10.1016/S1573-4412(84)02016-X.

  Chapter  Google Scholar 

• Menting, B. (2018). Awareness × opportunity: Testing interactions between activity nodes and criminal opportunity in predicting crime location choice. The British Journal of Criminology, 58, 1171–1192. https://doi.org/10.1093/bjc/azx049.

  Article  Google Scholar 

• Menting, B., Lammers, M., Ruiter, S., & Bernasco, W. (2016). Family matters: Effects of family members’ residential areas on crime location choice. Criminology, 54(3), 413–433. https://doi.org/10.1111/1745-9125.12109.

  Article  Google Scholar 

• Menting, B., Lammers, M., Ruiter, S., & Bernasco, W. (2020). The influence of activity space and visiting frequency on crime location choice: Findings from an online self-report survey. The British Journal of Criminology, 60(2), 303–322. https://doi.org/10.1093/bjc/azz044.

  Article  Google Scholar 

• Miller, J. (2013). Individual offending, routine activities, and activity settings: Revisiting the routine activity theory of general deviance. Journal of Research in Crime and Delinquency, 50(3), 390–416. https://doi.org/10.1177/0022427811432641.

  Article  Google Scholar 

• Nee, C. (2015). Understanding expertise in burglars: From pre-conscious scanning to action and beyond. Aggression and Violent Behavior, 20(Supplement C), 53–61. https://doi.org/10.1016/j.avb.2014.12.006.

  Article  Google Scholar 

• Nee, C., & Meenaghan, A. (2006). Expert decision making in burglars. The British Journal of Criminology, 46(5), 935–949. https://doi.org/10.1093/bjc/azl013.

  Article  Google Scholar 

• Nevo, A. (2001). Measuring market power in the ready-to-eat cereal industry. Econometrica, 69(2), 307–342.

  Article  Google Scholar 

• Nguyen, H. T. A., Chikaraishi, M., Fujiwara, A., & Zhang, J. (2017). Mediation effects of income on travel mode choice: Analysis of short-distance trips based on path analysis with multiple discrete outcomes. Transportation Research Record, 2664(1), 23–30. https://doi.org/10.3141/2664-03.

  Article  Google Scholar 

• Pappalardo, L., Simini, F., Rinzivillo, S., Pedreschi, D., Giannotti, F., & Barabási, A.-L. (2015). Returners and explorers dichotomy in human mobility. Nature Communications, 6, 8166–8173. https://doi.org/10.1038/ncomms9166.

  Article  Google Scholar 

• Pease, K. (1998). Repeat victimisation: Taking stock. London: Home Office.

  Google Scholar 

• Ratcliffe, J. H. (2006). A temporal constraint theory to explain opportunity-based spatial offending patterns. Journal of Research in Crime and Delinquency, 43(3), 261–291. https://doi.org/10.1177/0022427806286566.

  Article  Google Scholar 

• Reid, A. A., Frank, R., Iwanski, N., Dabbaghian, V., & Brantingham, P. L. (2014). Uncovering the spatial patterning of crimes: A criminal movement model (CRiMM). Journal of Research in Crime and Delinquency, 51(2), 230–255. https://doi.org/10.1177/0022427813483753.

  Article  Google Scholar 

• Rengert, G. (1996). The geography of illegal drugs. Boulder: Westview Press.

  Google Scholar 

• Rengert, G., & Wasilchick, J. (1985). Suburban burglary: A time and a place for everything. Springfield: C.C Thomas.

  Google Scholar 

• Rengert, G., & Wasilchick, J. (2000). Suburban burglary: A tale of two suburbs (2nd ed.). Springfield: C.C Thomas.

  Google Scholar 

• Rossmo, D. K. (2000). Geographic profiling. Boca Raton, FL: CRC Press.

  Google Scholar 

• Rossmo, D. K. (2014). Geographic profiling. In G. J. N. Bruinsma & D. Weisburd (Eds.), Encyclopedia of criminology and criminal justice (pp. 1934–1942). Berlin: Springer.

  Chapter  Google Scholar 

• Rossmo, D. K., Lu, Y., & Fang, T. B. (2012). Spatial-temporal crime paths. In M. A. Andresen & J. B. Kinney (Eds.), Patterns, prevention, and geometry of crime (pp. 3–15). London: Routledge.

  Google Scholar 

• Ruiter, S. (2017). Crime location choice. In W. Bernasco, J.-L. Van Gelder, & H. Elffers (Eds.), The Oxford handbook of offender decision making (pp. 398–420). Oxford: Oxford University Press.

  Google Scholar 

• Ruiter, S., and Davies, T. (2018, July). BTW, a test of crime pattern theory. Environmental Criminology and Crime Analysis Symposium, Spain.

• Sivakumar, A., & Bhat, C. R. (2007). A comprehensive, unified framework for analyzing spatial location choice. Transportation Research Record, 2003(1), 103–111. https://doi.org/10.3141/2003-13.

  Article  Google Scholar 

• Smith, W., Bond, J. W., & Townsley, M. (2009). Determining how journeys-to-crime vary: Measuring inter- and intra-offender crime trip distributions. In D. Weisburd, W. Bernasco, & G. J. N. Bruinsma (Eds.), Putting crime in its place (pp. 217–236). Berlin: Springer.

  Chapter  Google Scholar 

• Song, C., Qu, Z., Blumm, N., & Barabási, A.-L. (2010). Limits of predictability in human mobility. Science, 327(5968), 1018–1021. https://doi.org/10.1126/science.1177170.

  Article  Google Scholar 

• Sorg, E. T., Haberman, C. P., Ratcliffe, J. H., & Groff, E. R. (2013). Foot patrol in violent crime hot spots: The longitudinal impact of deterrence and posttreatment effects of displacement. Criminology, 51(1), 65–101. https://doi.org/10.1111/j.1745-9125.2012.00290.x.

  Article  Google Scholar 

• Summers, L., Johnson, S. D., & Rengert, G. (2010). The use of maps in offender interviewing. In W. Bernasco (Ed.), Offenders on offending: Learning about crime from criminals (pp. 246–272). London: Willan.

  Google Scholar 

• Tenenbaum, J. B., & Griffiths, T. L. (2001). Generalization, similarity, and Bayesian inference. Behavioral and Brain Sciences, 24(4), 629–640. https://doi.org/10.1017/S0140525X01000061.

  Article  Google Scholar 

• Tillyer, M. S., & Walter, R. J. (2019). Busy businesses and busy contexts: The distribution and sources of crime at commercial properties. Journal of Research in Crime and Delinquency, 56(6), 816–850. https://doi.org/10.1177/0022427819848083..

  Article  Google Scholar 

• Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240. https://doi.org/10.2307/143141.

  Article  Google Scholar 

• Tolman, E. C. (1948). Cognitive maps in rats and men. Psychological Review, 55(4), 189–208. https://doi.org/10.1037/h0061626.

  Article  Google Scholar 

• Tonkin, M., Santtila, P., & Bull, R. (2012). The linking of burglary crimes using offender behaviour: Testing research cross-nationally and exploring methodology. Legal and Criminological Psychology, 17(2), 276–293. https://doi.org/10.1111/j.2044-8333.2010.02007.x.

  Article  Google Scholar 

• Tonkin, M., Woodhams, J., Bull, R., Bond, J. W., & Palmer, E. J. (2011). Linking different types of crime using geographical and temporal proximity. Criminal Justice and Behavior, 38(11), 1069–1088. https://doi.org/10.1177/0093854811418599.

  Article  Google Scholar 

• Toole, J. L., Herrera-Yaqüe, C., Schneider, C. M., & González, M. C. (2015). Coupling human mobility and social ties. Journal of the Royal Society Interface, 12(105), 20141128–20141128. https://doi.org/10.1098/rsif.2014.1128.

  Article  Google Scholar 

• Townsley, M. (2016). Offender mobility. In R. Wortley & M. Townsley (Eds.), Environmental criminology and crime analysis (pp. 142–161). London: Routledge.

  Google Scholar 

• Townsley, M., Birks, D., Ruiter, S., Bernasco, W., & White, G. (2016). Target selection models with preference variation between offenders. Journal of Quantitative Criminology, 32(2), 283–304. https://doi.org/10.1007/s10940-015-9264-7.

  Article  Google Scholar 

• van Daele, S., & Vander Beken, T. (2011). Out of sight, out of mind? Awareness space and mobile offenders. European Journal of Crime, Criminal Law and Criminal Justice, 19(2), 125–137. https://doi.org/10.1163/157181711X566326.

  Article  Google Scholar 

• van Daele, S., Vander Beken, T., & Bruinsma, G. J. N. (2012). Does the mobility of foreign offenders fit the general pattern of mobility? European Journal of Criminology, 9(3), 290–308. https://doi.org/10.1177/1477370812440065.

  Article  Google Scholar 

• van Sleeuwen, S. E. M., Ruiter, S., & Menting, B. (2018). A time for a crime: Temporal aspects of repeat offenders’ crime location choices. Journal of Research in Crime and Delinquency, 55(4), 538–568. https://doi.org/10.1177/0022427818766395.

  Article  Google Scholar 

• Vandeviver, C. (2014). Applying Google Maps and Google Street View in criminological research. Crime Science, 3(1), 13. https://doi.org/10.1186/s40163-014-0013-2.

  Article  Google Scholar 

• Vandeviver, C., & Bernasco, W. (2019). “Location, location, location”: Effects of neighborhood and house attributes on burglars’ target selection. Journal of Quantitative Criminology. https://doi.org/10.1007/s10940-019-09431-y.

  Article  Google Scholar 

• Wang, J., Dong, L., Cheng, X., Yang, W., & Liu, Y. (2019). An extended exploration and preferential return model for human mobility simulation at individual and collective levels. Physica A: Statistical Mechanics and Its Applications, 534, 121921. https://doi.org/10.1016/j.physa.2019.121921.

  Article  Google Scholar 

• Ward, T., Polaschek, D. L. L., & Beech, A. R. (2005). Theory construction, development and evaluation. Theories of sexual offending (pp. 3–16). Hoboken: Wiley. https://doi.org/10.1002/9780470713648.ch1.

  Chapter  Google Scholar 

• Weisburd, D., Eck, J. E., Braga, A. A., Telep, C. W., Cave, B., Bowers, K., et al. (2016). Place matters: Criminology for the twenty-first century. Cambridge University Press. https://doi.org/10.1017/CBO9781139342087.

  Article  Google Scholar 

• Wikström, P.-O., Ceccato, V., Hardie, B., & Treiber, K. (2010). Activity fields and the dynamics of crime. Journal of Quantitative Criminology, 26(1), 55–87. https://doi.org/10.1007/s10940-009-9083-9.

  Article  Google Scholar 

• Wiles, P., & Costello, A. (2008). The ‘road to nowhere’: The evidence for travelling criminals. In D. Canter & D. Youngs (Eds.), Principles of geographical offender profiling (pp. 165–175). Farnham: Ashgate.

  Google Scholar 

• Wolpert, J. (1965). Behavioral aspects of the decision to migrate. Papers in Regional Science, 15(1), 159–169. https://doi.org/10.1111/j.1435-5597.1965.tb01320.x.

  Article  Google Scholar 

• Wright, R., & Decker, S. H. (1994). Burglars on the job: Streetlife and residential break-ins. Boston, MA: Northeastern University Press.

  Google Scholar 

• Xiao, L., Liu, L., Song, G., Ruiter, S., & Zhou, S. (2018). Journey-to-crime distances of residential burglars in China disentangled: Origin and destination effects. ISPRS International Journal of Geo-Information, 7(8), 325. https://doi.org/10.3390/ijgi7080325.

  Article  Google Scholar 

• Yan, X.-Y., Wang, W.-X., Gao, Z.-Y., & Lai, Y.-C. (2017). Universal model of individual and population mobility on diverse spatial scales. Nature Communications, 8(1), 1–9. https://doi.org/10.1038/s41467-017-01892-8.

  Article  Google Scholar 

• Zhang, W., Ahmad Termida, N., & Susilo, Y. O. (2019). What construct one’s familiar area? A quantitative and longitudinal study. Environment and Planning B: Urban Analytics and City Science, 46(2), 322–340. https://doi.org/10.1177/2399808317714798.

  Article  Google Scholar 

• Zhang, W., Susilo, Y. O., & Ahmad Termida, N. (2016). Investigating the interactions between travellers’ familiar areas and their multi-day activity locations. Journal of Transport Geography, 53, 61–73. https://doi.org/10.1016/j.jtrangeo.2016.04.012.

  Article  Google Scholar 

Page 2

Model of the influence of prior activities on location choice. Location choice is a product of both opportunity and knowledge of the opportunity generated during prior activities. The frequency, recency and duration of prior activities affect the reliability of that knowledge; the behaviour (e.g. crime, recreation, work), type of location, and timing involved in prior activities affect the relevance of that knowledge to the location decision