不同主体特征的犯罪人空间出行行为分析

doi:10.18306/dlkxjz.2020.04.007

Abstract

Abstract:

The spatial travel behavior of criminals plays an important role in describing and understanding the journey to crime process of criminals. Current studies focus on the statistics of travel distance of criminals, lacking studies on refined individualization of spatial travel behavior under different individual characteristics of criminals. Using theft cases of electric bicycles in Beijing region, an empirical analysis was conducted in this study to explore the spatial distribution of the criminals' travel distance under different individual characteristics. The results show that individual differences that affect travel distance distribution primarily concern gender, age, origin, and frequency of crimes attributes. Among them, the crime travel distance of male criminals is higher than that of female criminals, but their spatial buffer radius is closer than that of female criminals. Middle-aged criminals have larger crime travel distance and spatial buffer radius than juvenile and elderly criminals. The crime travel distance and spatial buffer zone of alien criminals are farther than that of local criminals. The crime offenders who commit multiple crimes have higher travel distance and spatial buffer distance than those who commit fewer crimes. Finally, this study constructed a decision model of spatial travel of criminals from travel cost, risk perception of neighborhood guardianship, and profit on the basis of the least effort principle and rational choice theory, and explained the difference of spatial travel behavior of criminals under the influence of different individual characteristics. The conclusions can provide effective support for crime prediction and policing practice.

Key words: journey to crime, criminal, individual characteristics, rational choice theory

HOU Chao, CHEN Peng, ZENG Zhaolong, SHI Shaochong, YUAN Penghui, SHEN Bing. Spatial travel behavior of criminals with different individual characteristics[J].PROGRESS IN GEOGRAPHY, 2020, 39(4): 602-613.

Figures/Tables 9

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References 30

[1]	龙冬平, 柳林, 周素红等. 地理学视角下犯罪者行为研究进展[J]. 地理科学进展, 2017,36(7):886-902. doi: 10.18306/dlkxjz.2017.07.010
	[ Long Dongping, Liu Lin, Zhou Suhong , et al. Research progress of criminal behavior from the perspective of geography. Progress in Geography, 2017,36(7):886-902. ] doi: 10.18306/dlkxjz.2017.07.010
[2]	Koppen P J V, Jansen R W J . The road to the robbery: Travel patterns in commercial robberies[J]. British Journal of Criminology, 1998,38(2):230-246. doi: 10.1093/oxfordjournals.bjc.a014233
[3]	Ackerman J M, Rossmo D K . How far to travel? A multilevel analysis of the residence-to-crime distance[J]. Journal of Quantitative Criminology, 2015,31(2):237-262. doi: 10.1177/135581969900400304 pmid: 10538878
[4]	Lammers M, Menting B, Ruiter S , et al. Biting once, twice: The influence of prior on subsequent crime location choice[J]. Criminology, 2015,53(3):309-329. doi: 10.1111/crim.2015.53.issue-3
[5]	Van Daele S, Beken T V . Outbound offending: The journey to crime and crime sprees[J]. Journal of Environmental Psychology, 2011,31(1):70-78. doi: 10.1016/j.jenvp.2010.09.002
[6]	Rengert G F, Piquero A R, Jones P R . Distance decay reexamined[J]. Criminology, 1999,37(2):427-446. doi: 10.1111/crim.1999.37.issue-2
[7]	Smith W, Bond J W, Townsley M . 2009. Determining how journeys-to-crime vary: Measuring inter- and intra-offender crime trip distributions[M]// Weisburd D, Bernasco W, Bruinsma G J N. Putting crime in its place: units of analysis in geographic criminology. New York, USA: Springer: 217-236.
[8]	Gabor T, Gottheil E . Offender characteristics and spatial mobility: An empirical study and some policy implications[J]. Canadian Journal of Criminology, 1984,26(3):267-281. doi: 10.3138/cjcrim.26.3.267
[9]	Phillips P D. Characteristics and typology of the journey to crime [M]// Georges-Abeyie D E, Harries K D. Crime: A spatial perspective. New York, USA: Columbia University Press, 1980: 167-180.
[10]	Levine N, Lee P . Journey-to-crime by gender and age group in Manchester, England[M]// Leitner M. Crime modeling and mapping using geospatial technologies. Berlin, Germany: Springer, 2013: 145-173.
[11]	Bernasco W, Block R . Where offenders choose to attack: A discrete choice model of robberies in Chicago[J]. Criminology, 2010,47(1):93-130. doi: 10.1111/crim.2009.47.issue-1
[12]	Bernasco W, Block R, Ruiter S . Go where the money is: Modeling street robbers' location choices[J]. Journal of Economic Geography, 2012,13(1):119-143. doi: 10.1093/jeg/lbs005
[13]	Johnson S, Summers L . Testing ecological theories of offender spatial decision making using a discrete choice model[J]. Crime & Delinquency, 2015,61(3):454-480. doi: 10.1177/0011128714540276 pmid: 25866412
[14]	Deakin J, Smithson H, Spencer J , et al. Taxing on the streets: Understanding the methods and process of street Robbery[J]. Crime Prevention & Community Safety, 2007,9(1):52-67.
[15]	Menting B, Lammers M, Ruiter S , et al. Family matters: Effects of family members's residential areas on crime location choice[J]. Criminology, 2016,54(3):413-433. doi: 10.1111/1745-9125.12109
[16]	赵勇, 刘民, 柏书华 , 等. 系列入室盗窃案件的犯罪距离研究[J]. 中国人民公安大学学报(社会科学版), 2010(2):143-149.
	[ Zhao Yong, Liu Min, Bai Shuhua , et al. A study on the distance of series of burglary cases. Journal of People's Public Security University of China (Social Sciences Edition), 2010(2):143-149. ]
[17]	徐永胜 . 系列入室盗窃犯罪距离个体差异影响因素分析[J]. 中国刑警学院学报, 2014(2):3-8.
	[ Xu Yongsheng . Analysis of the influencing factors of individual differences in crime distance on the serial burglary. Journal of Criminal Investigation Police University of China, 2014(2):3-8. ]
[18]	侯超, 陈鹏 . 基于不同个体要素的犯罪人出行距离统计特征分析[J]. 犯罪研究, 2018(1):37-43.
	[ Hou Chao, Chen Peng . Analysis of the distance statistics of criminal travel based on offender characteristics. Chinese Criminology Review, 2018(1):37-43. ]
[19]	Chainey S, Austin B, Holland F . London borough of harrow: Insights into the analysis and patterns of offender journeys to crime[M]. London, UK: InfoTech Enterprises Europe, 2001.
[20]	Andresen M A, Frank R, Felson M . Age and the distance to crime[J]. Criminology and Criminal Justice, 2014,14(3):314-333. doi: 10.1177/1748895813494870
[21]	George K, George K. Human behavior and the principle of least effort: An introduction to human ecology [M]. Boston, USA: Addison-Wesley Press, 1949.
[22]	Cornish D B, Clarke R V . The reasoning criminal: Rational choice perspectives on offending[M]. New York, USA: Springer, 1986.
[23]	Wiles P, Costello A . The 'road to nowhere': The evidence for travelling criminals[M]. London, UK: Home Office, 2000.
[24]	常超凡 . 城市居民短距离出行行为研究[D]. 北京: 北京交通大学, 2007.
	[ Chang Chaofan . Study on short-distance travel behavior of urban resident. Beijing, China: Beijing Jiaotong University, 2007. ]
[25]	潘婷 . 西宁市居民通勤特征研究[D]. 西宁: 青海师范大学, 2015.
	[ Pan Ting . Study on characteristics of Xining residents commute. Xining, China: Qinghai Normal University, 2015. ]
[26]	申悦, 柴彦威 . 基于性别比较的北京城市居民活动的时空弹性研究[J]. 地理学报, 2017,72(12):2214-2225. doi: 10.11821/dlxb201712007
	[ Shen Yue, Chai Yanwei . Space-time flexibility of daily activities and gender differences: A case study of Beijing. Acta Geographica Sinica, 2017,72(12):2214-2225. ] doi: 10.11821/dlxb201712007
[27]	Cohen L E, Felson M . Social change and crime rate trends: A routine activity approach[J]. American Sociological Review, 1979,44(4):588-608. doi: 10.2307/2094589
[28]	West P A, Norris T E, Gore E J , et al. The geographic and temporal patterns of residency-trained family physicians: University of Washington Family Practice Residency Network[J]. Journal of the American Board of Family Practice, 1996,9(2):100-108. pmid: 8659258
[29]	张真理 . 流动人口犯罪及其预防研究[J]. 现代商业, 2013(2):259-261.
	[ Zhang Zhenli . Analysis of the prevention on crimes committed by floating population. Modern Business, 2013(2):259-261. ]
[30]	楼伯坤, 满涛 . 我国流动人口犯罪的防控策略: 基于“破窗理论”的本土化思考[J]. 犯罪研究, 2013(6):42-48.
	[ Lou Bokun, Man Tao . Prevention and control strategies on crimes committed by floating population in our country. Chinese Criminology Review, 2013(6):42-48. ]

个体要素		N	均值	中位数	标准差	极小值	极大值	空间缓冲半径
性别	男性	1475	15.43	9.81	16.25	0	131.23	5
	女性	185	14.29	11.23	11.33	0	66.91	10
年龄	25岁以下	311	12.08	5.06	16.74	0	77.70	<5
	25~44岁	1049	16.32	12.05	15.17	0	131.63	7
	45岁以上	300	15.08	7.34	16.45	0	101.63	<5
籍贯	北京	362	11.78	7.08	15.89	0	131.63	5
	河北	178	10.63	7.12	13.55	0	69.81	不明显
	河南	476	22.34	21.15	15.06	0.20	86.93	15~20
	湖北	121	17.58	14.24	8.94	0.80	42.48	15~20
作案频次	作案1次	202	12.18	7.33	14.83	0	101.63	<5
	作案2~8次	583	14.00	8.29	16.51	0	131.63	<5
	作案9~22次	434	13.06	8.44	14.31	0.06	71.3	<5
	作案22次以上	441	20.67	17.81	15.36	1.22	80.33	10
全部		1660	15.30	10.37	15.78	0	131.63	7

非参数检验要素	检验统计	自由度	显著性
年龄要素	69.174	2	<0.001
25岁以下与25~44岁	-251.901		<0.001
25岁以下与45岁以上	-143.159		<0.001
25~44岁与45岁以上	108.743		0.001
籍贯(省份)要素	232.305	3	<0.001
北京与河北	32.976		0.273
北京与河南	-293.204		<0.001
北京与湖北	-250.408		<0.001
河北与河南	-326.180		<0.001
河北与湖北	-283.384		<0.001
河南与湖北	42.796		0.201
作案频次要素	8.505	3	0.037
作案1次与2~8次	-19.082		0.111
作案1次与9~22次	-26.610		0.198
作案1次与22次以上	-78.315		0.009
作案2~8次与9~22次	-7.527		0.716
作案2~8次与22次以上	-59.233		0.050
作案9~22次与22次以上	-51.706		0.135

Spatial travel behavior of criminals with different individual characteristics

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