建成环境对星级酒店内被盗的影响——以ZG市中心城区为例

盗窃是中西方酒店内财产犯罪中最为高发的一种,但鲜有研究关注建成环境对酒店被盗的影响。论文以2012—2014年ZG市中心城区发生过被盗的星级酒店作为研究样本,在综合分析酒店被盗时空特征的基础上,选取酒店周围500 m范围内的建成环境指标,利用负二项回归模型,对分时段各类型的星级酒店被盗的影响因素进行系统建模分析。结果表明：被盗星级酒店的时空分布呈现典型的集聚分布特征。不同时段空间“主热点”分布相对稳定,“次热点”有所不同。整体来看,提高服务水平对降低星级酒店被盗的作用最为稳定,周围的兴趣点(Point of Interest, POI)数量会显著增加星级酒店被盗的机会,道路交叉口则对星级酒店被盗起显著监管作用。分模型结果显示,服务水平对三星级和五星级酒店被盗的抑制作用显著,道路交叉口则对以商务客人为主的四星级酒店被盗的抑制作用更强,而POI数量对等级较低的三星、四星酒店被盗作用更为明显;大型零售商业中心能显著增加旅游旺季及周末时段的酒店被盗的数量,道路交叉口数量则对旅游淡季、工作日2个时段的星级酒店被盗风险的监控作用显著。研究表明建成环境在影响ZG市星级酒店被盗的机会和成本方面作用显著。结果验证了日常活动理论在中国大城市星级酒店被盗方面研究的适用性,拓展了犯罪地理学在星级酒店被盗方面的研究成果,对酒店盗窃预防有指导意义。

Relationship between the built environment and theft cases in star hotels in ZG central city

As a ticklish social problem, crime committed in hotels has been concerned by both Chinese and Western scholars. Theft is one of the most frequent crime types occurred in hotels, especially in star hotels. Previous studies on influencing factors of hotel theft cases mainly focused on star hotel and personal attributes of victims at the micro level from the perspective of sociology, rather than considering the built environmental factors at the macro level from the perspective of geography. Using the data on the star hotels with theft cases in 2012-2014 in ZG central city obtained from Municipal Public Security Bureau, this study examined the spatial-temporal characteristics of these hotels. Then the environmental indicators within 500 m around the hotels were examined and the negative binomial regression method was used to make a systematic analysis on the factors affecting the theft of different types of star hotels in various time periods. The main results are as follows: 1) The spatial-temporal distribution of star hotels showed obvious agglomeration features. Generally, most of the main hotspots in the high incidence areas of hotel theft were time invariant, all of them are highlighted near the old city central business district, the eastern extension of the main road and the railway station. However, the spatial distribution of secondary hotspots was time-varying. 2) The overall model analysis indicates that the improvement of the service level was the most effective way to reduce the theft cases of all star hotels. The surrounding property and community points of interest (POIs) will significantly increase the opportunity for all star hotels to be stolen, while road intersections play a significant regulatory role in the theft of all star hotels. 3) The results of the sub models demonstrate that the effect of service level on the theft of three-star and five-star hotels is significant, and the effect of road intersection on the theft of four-star hotels often used by guests of business travel is stronger; the number of POIs has more obvious effect on three-star and four-star hotels. Large-scale retail business center can significantly increase the number of theft cases in hotels in the peak season and the weekend, and the number of road intersections is significant for the monitoring of stolen risk of the star hotels in the off-season period and the working days. These results have shown that the built environment played a significant role in affecting the opportunity and cost of hotel theft. The results verify the applicability of the daily activity theory in the study of hotel crimes in large cities in China, and expand the research results of crime geography in the direction of star hotel theft, which has a guiding effect for the prevention of hotel theft.