地理学报 ›› 2017, Vol. 72 ›› Issue (2): 315-328.doi: 10.11821/dlxb201702011
柳林1,2(), 张春霞1, 冯嘉欣1, 肖露子1, 贺智1, 周淑丽1
收稿日期:
2016-06-25
修回日期:
2017-01-10
出版日期:
2017-02-15
发布日期:
2017-02-15
作者简介:
作者简介:柳林(1965-), 男, 湖南湘潭人, 博士, 教授, 中国地理学会会员(S110007983M), 主要研究方向为犯罪空间模拟、GIS应用等。E-mail:
基金资助:
Lin LIU1,2(), Chunxia ZHANG1, Jiaxin FENG1, Luzi XIAO1, Zhi HE1, Shuli ZHOU1
Received:
2016-06-25
Revised:
2017-01-10
Published:
2017-02-15
Online:
2017-02-15
Supported by:
摘要:
诈骗犯罪是现代城市中亟待解决的一大社会难题。现有研究多从社会学角度,基于微观层次探讨影响诈骗受害的个人属性特征,缺乏从地理学视角对诈骗受害者生存环境中的中宏观层次因素的考虑。本文基于犯罪地理学视角,综合运用平均最近邻、核密度以及负二项回归等研究方法,对ZG市5类诈骗警情的时空分布特征和基于建成环境与社会环境两大维度的影响因素进行了深入探讨。结果表明:① 各类诈骗的时间分布规律各异,但整体上呈现出工作日高于休息日、下午或晚上高于上午、凌晨时段为最低的特征;② 和其他类型的城市犯罪类似,诈骗犯罪整体呈现出与老城区距离衰减的“多中心”显著性集聚特征;各类型诈骗热点的空间分布大同小异,多分布在城市的老城区、CBD、火(汽)车站、城中村或高校布局的周边地带;③ 各类诈骗犯罪的空间分布影响因素各异,但整体表现出与银行网点、旅游景点、道路密度、土地利用混合度、高校等建成环境因素高度相关;与购买商品房家庭占比、受教育水平、人口老龄化和城镇化水平等社会环境显著相关的特性。本文拓展了犯罪地理学领域对诈骗犯罪的研究成果,证实了各类诈骗犯罪符合日常活动理论的理论假设,对诈骗受害情景预防具有重要意义。
柳林, 张春霞, 冯嘉欣, 肖露子, 贺智, 周淑丽. ZG市诈骗犯罪的时空分布与影响因素[J]. 地理学报, 2017, 72(2): 315-328.
Lin LIU, Chunxia ZHANG, Jiaxin FENG, Luzi XIAO, Zhi HE, Shuli ZHOU. The spatial-temporal distribution and influencing factorsof fraud crime in ZG city, China[J]. Acta Geographica Sinica, 2017, 72(2): 315-328.
表1
ZG市诈骗犯罪警情平均最近邻距离分析
诈骗类型 | 样本数(个) | 平均最近邻 距离(m) | 期望平均最近邻距(m) | 平均最近邻 指数(NNA) | Z检验值 | 显著性 水平 |
---|---|---|---|---|---|---|
总诈骗 | 6175 | 93.87 | 255.54 | 0.367 | -95.10 | 0.01 |
电话诈骗 | 2434 | 167.67 | 404.25 | 0.414 | -55.23 | 0.01 |
网络诈骗 | 2156 | 191.51 | 425.33 | 0.450 | -48.83 | 0.01 |
短信诈骗 | 728 | 348.43 | 676.10 | 0.515 | -25.01 | 0.01 |
信用卡诈骗 | 344 | 614.27 | 998.38 | 0.615 | -13.65 | 0.01 |
接触型诈骗 | 440 | 509.13 | 886.19 | 0.575 | -17.74 | 0.01 |
表3
负二项模型估计结果
变量 | 共线性检验VIF | 总诈骗 | 电话诈骗 | 网络诈骗 | 短信诈骗 | 接触型诈骗 | 信用卡诈骗 | |
---|---|---|---|---|---|---|---|---|
建 成 环 境 | (截距) | -6.13*** | -7.12*** | -7.05*** | -8.95*** | -9.86*** | -8.09*** | |
地产小区个数 | 1.26 | -0.006** | -0.01** | 0.00 | 0.00 | 0.00 | 0.00 | |
餐饮设施个数 | 2.10 | 0.00* | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | |
银行网点个数 | 2.11 | 0.02*** | 0.03*** | 0.01* | 0.01 | 0.02** | 0.03** | |
医疗机构个数 | 1.97 | 0.004 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | |
商务大厦个数 | 1.41 | 0.08** | 0.07* | 0.06 | 0.08* | 0.03 | 0.13** | |
公司企业个数 | 1.80 | 0.00** | 0.00** | 0.00** | 0.00 | 0.00 | 0.00 | |
旅游景点个数 | 1.10 | 0.32** | 0.33** | 0.44*** | 0.40** | 0.55** | 0.39* | |
住宿设施个数 | 1.81 | 0.05*** | 0.04*** | 0.05*** | 0.05*** | 0.07*** | 0.01 | |
道路密度 | 1.26 | 0.01*** | 0.01** | 0.01** | 0.01** | 0.01 | 0.01 | |
土地利用混合度 | 1.01 | 0.16*** | 0.15*** | 0.16*** | 0.19*** | 0.18*** | 0.14 | |
有无高校 | 1.19 | 0.18** | 0.22** | 0.15 | 0.06 | 0.29* | 0.20 | |
社 会 环 境 | 购买商品房家庭占比 | 2.43 | -0.75*** | -0.55** | -1.03*** | -0.58* | -0.55 | -0.43 |
月收1000元以下占比 | 1.91 | 0.05 | 0.02 | 0.13 | -0.39* | 0.12 | -0.64** | |
人均住房面积 | 1.72 | 0.00 | 0.00 | 0.01 | 0.00 | 0.01 | -0.02** | |
离婚丧偶者占比 | 2.98 | 2.67* | 2.45 | 1.06 | 4.16 | -1.09 | 6.41* | |
中等以下受教育占比 | 2.69 | -1.13*** | -0.69* | -1.44*** | -0.40 | 0.13 | -0.76 | |
老龄化人口占比 | 5.36 | -5.79*** | -5.23*** | -6.41*** | -3.00 | -4.72* | -7.12** | |
农业人口占比 | 4.43 | -0.60** | -0.73** | -0.40 | -0.91** | -0.64 | -0.60 | |
外来人口占比 | 2.86 | 0.35 | -0.15 | 0.53* | 0.76** | 0.25 | -0.02 |
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