4

Fast Food Restaurants and Convenience Stores: Using Sales Volume to Explain Crim...

 3 years ago
source link: https://journals.sagepub.com/doi/abs/10.1177/0011128717714792
Go to the source link to view the article. You can view the picture content, updated content and better typesetting reading experience. If the link is broken, please click the button below to view the snapshot at that time.
neoserver,ios ssh client

Fast Food Restaurants and Convenience Stores: Using Sales Volume to Explain Crime Patterns in Seattle

First Published June 23, 2017

Research Article

Abstract

This study investigates how convenience stores and fast food restaurants influence crime patterns over time. Using sales volume data from fast food restaurants and convenience stores, we examine streetblock crime levels over a seven year period in Seattle using multilevel models. Results demonstrate that high sales volume links to high crime, even after controlling for local socio-economic status, the effects of retail businesses, and local crime trends. In addition, street segment crime trajectories were spatially clustered in a significant way. The dynamics that explain why specific types of commercial facilities link to street crime need further theoretical clarification. This is the first study demonstrating significant spatio-temporal patterning of streetblock crime trends.

Access Options
lean-library-1617803736157.svg

Research off-campus without worrying about access issues. Find out about Lean Library here

References

Ashe, M., Jernigan, D., Kline, R., Galaz, R. (2003). Land use planning and the control of alcohol, tobacco, firearms, and fast food restaurants. American Journal of Public Health, 93, 1404-1408.
Google Scholar | Crossref | Medline | ISI
Bernasco, W., Block, R. (2011). Robberies in Chicago: A block-level analysis of the influence of crime generators, crime attractors, and offender anchor points. Journal of Research in Crime & Delinquency, 48, 33-57.
Google Scholar | SAGE Journals | ISI
Brantingham, P. J., Brantingham, P. L. (1981). Mobility, notoriety, and crime: A study in the crime patterns of urban nodal points. Journal of Environmental Systems, 11, 89-99.
Google Scholar | Crossref
D’Alessio, S., StolzenBerg, L. (1990). A crime of convenience: The environment and convenience store robbery. Environment and Behavior, 22, 255-271.
Google Scholar | SAGE Journals | ISI
Duffala, D. C. (1976). Convenience stores, armed robbery, and physical environmental features. American Behavioral Scientist, 20, 227-245.
Google Scholar | SAGE Journals | ISI
Eck, J., Clarke, R., Guerette, R. (2007). Risky facilities: Crime concentration in homogeneous sets of establishments and facilities. Crime Prevention Studies, 21, 225-264.
Google Scholar
Exum, M. L., Kuhns, J. B., Koch, B., Johnson, C. (2010). An examination of situational crime prevention strategies across convenience stores and fast-food restaurants. Criminal Justice Policy Review, 21, 269-295.
Google Scholar | SAGE Journals
French, M. T., McCollister, K. E., Alexandre, P. K., Chitwood, D. D., McCoy, C. B. (2004). Revolving roles in drug-related crime: The cost of chronic drug users as victims and perpetrators. Journal of Quantitative Criminology, 20, 217-241.
Google Scholar | Crossref
Groff, E. R. (2011). Exploring “near”: Characterizing the spatial extent of drinking place influence on crime. Australian & New Zealand Journal of Criminology, 44, 156-179.
Google Scholar | SAGE Journals | ISI
Groff, E. R., McCord, E. S. (2012). The role of neighborhood parks as crime generators. Security Journal, 25, 1-24.
Google Scholar | Crossref | ISI
Groff, E. R., Weisburd, D., Yang, S.-M. (2010). Is it important to examine crime trends at a local “micro” level? A longitudinal analysis of street to street variability in crime trajectories. Journal of Quantitative Criminology, 26, 7-32.
Google Scholar | Crossref | ISI
Hipp, J. R. (2007). Block, tract, and levels of aggregation: Neighborhood structure and crime and disorder as a case in point. American Sociological Review, 72, 659-680.
Google Scholar | SAGE Journals | ISI
IBISWorld . (2015a). Convenience stores in the US: Market research report (NAICS 44512). Retrieved from http://www.ibisworld.com/industry/default.aspx?indid=1041
Google Scholar
IBISWorld . (2015b). Fast food restaurants in the U.S.: Market research report (NAICS 72221a). Retrieved from www.ibisworld.com/industry/default.aspx?indid=1980
Google Scholar
Jacobs, J. (1961). The death and life of great American cities. New York, NY: Random House.
Google Scholar
Kinney, J. B., Brantingham, P. L., Wuschke, K., Kirk, M. G., Brantingham, P. G. (2008). Crime attractors, generators and detractors: Land use and urban crime opportunities. Built Environment, 34, 62-74.
Google Scholar | Crossref
Kurtz, E. M., Koons, B. A., Taylor, R. B. (1998). Land use, physical deterioration, resident-based control, and calls for service on urban street blocks. Justice Quarterly, 15, 121-149.
Google Scholar | Crossref
Loftin, C. (1986). Assaultive violence as a contagious social process. Bulletin of the New York Academy of Medicine, 62, 550-555.
Google Scholar | Medline
McCord, E. S., Ratcliffe, J. H. (2009). Intensity value analysis and the criminogenic effects of land use features on local crime patterns. Crime Patterns and Analysis, 2, 17-30.
Google Scholar
Miethe, T. D., McDowall, D. (1993). Contextual effects in models of criminal victimization. Social Forces, 71, 741-759.
Google Scholar | Crossref | ISI
Mitchell, O., Wilson, D. B., MacKenzie, D. L. (2007). Does incarceration-based drug treatment reduce recidivism? A meta-analytic synthesis of the research. Journal of Experimental Criminology, 3, 353-375.
Google Scholar | Crossref
Morenoff, J. D., Sampson, R. J., Raudenbush, S. W. (2001). Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology, 39, 517-560.
Google Scholar | Crossref | ISI
Nagin, D. S. (2010). Group-based trajectory modeling: An overview. In Piquero, A. R., Weisburd, D. (Eds.), Handbook of Quantitative Criminology (pp. 53-67). New York, NY: Springer.
Google Scholar | Crossref
Perkins, D. D., Florin, P., Rich, R., Wandersman, A., Chavis, D. (1990). Participation and the social and physical environment of residential blocks: Crime and community context. American Journal of Community Psychology, 18, 83-115.
Google Scholar | Crossref | ISI
Pratt, T. C., Cullen, F. T. (2005). Macro-level predictors and theories of crime: A meta-analysis. Crime and Justice, 32, 373-450.
Google Scholar | Crossref | ISI
Rabe-Hesketh, S., Skrondal, A. (2012). Multilevel and longitudinal modeling using stata (3rd ed.). College Station, TX: Stata Press.
Google Scholar
Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111-163.
Google Scholar | Crossref | ISI
Ratcliffe, J. H. (2004). Geocoding crime and a first estimate of a minimum acceptable hit rate. International Journal of Geographical Information Science, 18, 61-72.
Google Scholar | Crossref | ISI
Raudenbush, S. W. (2005). How do we study “what happens next”? The ANNALS of the American Academy of Political and Social Science, 602, 131-144.
Google Scholar | SAGE Journals | ISI
Raudenbush, S. W., Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks, CA: Sage.
Google Scholar
Rengert, G. F. (1996). The geography of illegal drugs. Boulder, CO: Westview Press.
Google Scholar
Roberts, D., Taylor, R. B., Garcia, R. M., Perenzin, A. (2014). Intra-streetblock ordered segmentation in a high crime urban neighborhood. Journal of Architectural and Planning Research, 31, 143-162.
Google Scholar
Roncek, D. W., Maier, P. A. (1991). Bars, blocks, and crimes revisited: Linking the theory of routine activities to the empiricism of “hot spots.” Criminology, 29, 725-753.
Google Scholar | Crossref | ISI
Schweitzer, J. H., Kim, J. W., Mackin, J. R. (1999). The impact of the built environment on crime and fear of crime in urban neighborhoods. Journal of Urban Technology, 6, 59-73.
Google Scholar | Crossref | ISI
Skardhamar, T. (2010). Distinguishing facts and artifacts in group-based modeling. Criminology, 48, 295-320.
Google Scholar | Crossref | ISI
Smith, W. R., Frazee, S. G., Davidson, E. L. (2000). Furthering the integration of routine activity and social disorganization theories: Small units of analysis and the study of street robbery as a diffusion process. Criminology, 38, 489-524.
Google Scholar | Crossref | ISI
Stucky, T. D., Ottensmann, J. R. (2009). Land use and violent crime. Criminology, 47, 1223-1259.
Google Scholar | Crossref | ISI
Taylor, R. B. (1997). Social order and disorder of street blocks and neighborhoods: Ecology, microecology, and the systemic model of social disorganization. Journal of Research in Crime & Delinquency, 33, 113-155.
Google Scholar | SAGE Journals
Taylor, R. B. (2015). Community criminology: Fundamentals of spatial and temporal scaling, ecological indicators, and selectivity bias. New York: New York University Press.
Google Scholar | Crossref
Taylor, R. B., Ratcliffe, J. H., Perenzin, A. R. (2015). Can we predict long-term community crime problems? The estimation of ecological continuity to model risk heterogeneity. Journal of Research in Crime & Delinquency, 52, 635-657.
Google Scholar | SAGE Journals | ISI
Tukey, J. W., McLaughlin, D. H. (1963). Less vulnerable confidence and significance procedures for location based on a single sample: Trimming/winsorization. Sankhyā: The Indian Journal of Statistics, Series A (1961-2002), 25, 331-352.
Google Scholar
Weisburd, D., Groff, E. R., Yang, S.-M. (2012). The criminology of place: Street segments and our understanding of the crime problem. Oxford, UK: Oxford University Press.
Google Scholar | Crossref
Wilcox, P., Quisenberry, N., Cabrera, D. T., Jones, S. (2004). Busy places and broken windows? Toward defining the role of physical structure and process in community crime models. Sociological Quarterly, 45, 185-207.
Google Scholar | Crossref | ISI
Wyant, B. R., Taylor, R. B. (2007). Size of household firearm collections: Implications for gender and subcultures. Criminology, 45, 519-546.
Google Scholar | Crossref | ISI

Recommend

About Joyk


Aggregate valuable and interesting links.
Joyk means Joy of geeK