Risky Business: Examining the 80-20 Rule in Relation to a RTM Framework

• DOI: 10.1177/0734016820938859
• Date: 01 March 2021
• Published date: 01 March 2021
• Author: Casey T. Harris,Hannah Steinman,Grant Drawve,Shaun A. Thomas,Jyotishka Datta
• Subject Matter: Articles

Article

Risky Business: Examining the

80-20 Rule in Relation to a

RTM Framework

Hannah Steinman

1

, Grant Drawve

1

,

Jyotishka Datta

2

, Casey T. Harris

1

,

and Shaun A. Thomas

1

Abstract

The spatial elements of crime occurrence and the identification of crime generators/attractors have

remained a prominent area of research. We focus on the utility of the 80-20 rule and the labeling of

risky facilities in crime forecasting models with risk terrain modeling (RTM). We first examine

whether the rule holds across types of crime generating places including liquor stores, department

stores, hotels/motels, restaurants/bars, and apartment complexes. Next, we use our findings to test

whether conducting preliminary analyses to identify risky facilities increases the predictive power of

RTM versus using all possible facilities. When restricting the RTM approach to only risky facilities,

results were more accurate than a traditional RTM approach. Findings and implications are nested in

the utilization of the wider body of environmental criminology research to increase our understanding

of where crime is likely to occur.

Keywords

ecology and crime/spatial analysis, crime/delinquency theory, property crime, other, violent

behavior

Traditionally, research has overwhelmingly focused on understanding who commits a crime, leading

to the identification of chronic offending by Wolfgang and colleagues. Their landmark finding was

that 6.3%of delinquent youth accounted for 52%of the recorded police contact. In other words, most

youths are not delinquent, but a subset of youth is best described as chronic offenders. More contem-

porary research continues to support this general finding that a small percentage of individuals account

for a disproportionate amount of any particular crime outcome (e.g., Vaughn & DeLisi, 2008).

Although there are relatively few chronic offenders, considerable attention is afforded to those

offenders due to the disproportionate amount of crime that is attributed to them (McGloin & Stickle,

1

Department of Sociology & Criminology, University of Arkansas, Fayetteville, AR, USA

2

Department of Mathematical Sciences, University of Arkansas, Fayetteville, AR, USA

Corresponding Author:

Grant Drawve, Department of Sociology & Criminology, University of Arkansas, Fayetteville, AR 72701, USA.

Email: drawve@uark.edu

Criminal Justice Review

2021, Vol. 46(1) 20-39

ª2020 Georgia State University

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DOI: 10.1177/0734016820938859

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2011). With a focus on who commits the crime, where crime occurs warrants the same focus.

Certainly, research continues to indicate crime is not random in space and time, leading to a small

percentage of places accounting for a disproportionate share of crime occurrence.

As a growing analytical tool, risk terrain modeling (RTM) has been utilized to identify attributes

from the environment spatially associated with crime occurrence (RTM; see Caplan et al., 2011;

Caplan & Kennedy, 2016; Kennedy etal., 2018). RTM has a foundation in environmental criminology,

focusing primarily on the spatial attributes of crime with temporal scales of secondary priority,

including the influence of crime generators and attractors (CGAs; see Brantingham & Brantingham,

1995). These features of the environment such as bars, restaurants, rental housing units, public transit

stops, and so on, attract or generate crime based on their presence. Yet while advancements in RTM

applications have furthered crime and place research, the risk terrain approach overlooks variability in

crime occurrence at any one facility type. That is, RTM can identify bars as crime risk generators or

attractors, but ignores important issues raised by environmental criminology broadly, and the “80-20

rule” specifically (Clarke & Eck, 2003; Eck et al., 2007). In short, and expanded on later, the 80-20 rule

stipulates that a small subset of establishments of one type of facility (20%) usually accounts for a

majority of crime (80%), identifying certain risky facilities.

The current study builds on these observations to test the predictive accuracy of RTM using a model

limited to only risky facilities. To do so, we compare risk terrain models for all facilities against a risky

facility model using two crime types—aggravated assaults and theft from a motor vehicle—for the

calendar year 2018 to forecast January through September 2019 crime occurrence in Little Rock, AR.

These models are compared using the updated predictive accuracy index (PAI) outlined by Drawve and

Wooditch (2019), building from Chainey et al.’s (2008) original metric. In addition, we compare the

predictive accuracy of the two RTM analyses to a more simplistic approach, risky facility buffers.

Review of Literature

Extant literature dating back to Guerry (1833) and Quetelet (1831) demonstrate spatial patterning in

crime occurrence. Subsequently, Sherman et al. (1989) brought this argument to prominence in more

contemporary research at the microlevel with emphasis on the hotspots of crime. In comparison to

studies of individual criminal offending, spatial research has found that the concentration of crime

within relatively few places is more extreme than the disproportionate offending of high-crime indi-

viduals (Spelman & Eck, 1989). Naturally, research has sought to leverage theory to understand why

crime occurs in specific places, including through the lenses of routine activities theory (Cohen &

Felson, 1979) and crime pattern theory (P . J. Brantingham & Brantingham, 1984) lead ing to the

development of the law of crime concentration (Weisburd, 2015). In turn, this has led to an increased

effort to forecast where crime is going to occur, often down to the street level, in hopes of being able to

implement place-based efforts to reduce offending or prevent crime from occurring at all.

Environmental Criminology Foundation

Environmental criminology often relies on three theoretical perspectives as the foundation to explain

why crime occursin specific spaces at particulartimes: routine activitiestheory, rational choicetheory,

and crimepattern theory. Routineactivities theoryargues criminalopportunities are presentduring daily

routine activities such as going to school, work, and running errands when a likely target, motivated

offender,and lack or absenceof capable guardianshipconverge intime and space. When multiplepeople

havesimilar or overlappingroutine activities,this leads to the concentrationsof criminal opportunitiesat

certain places. Although there areopportunities for crime, offenders still have to makethe decision to

act. Presentedwith criminal opportunities, the decisionto act follows a rationalchoice model where the

offender seeks to maximize their rewards whileminimizing the risks involved (see Cornish& Clarke,

Steinman et al. 21