The Enhancement of Routine Activity Theory with the Introduction of Contextual
Variables
Various criminological researchers have focused their endeavors on a theoretical
perspective known as routine activity theory. The vast accumulation of research that has
been devoted to the study of this theory, has allowed for the adequate scrutiny of its
theoretical foundations. Thus, not surprisingly, an in-depth survey of the relevant
literature emphasizes various shortcomings inherent in this theoretical perspective
(Bennett; 1991, Groff; 2007, Sampson & Woolredge; 1987). Most of the aforementioned
authors highlight similar or overlapping flaws within the theory. Meier and Miethe
recapitulate these authors’ critiques succinctly, when they suggest that these problems
include, “inadequate attention to variation by type of crime, compartmentalized thinking,
poor links between theory and data, inadequate measures of key concepts, and failure to
specify clearly functional relationships between sets of variables” (Meier & Miethe,
1993, 459). Although this wide array of problems is well documented throughout the
literature, there is one inherent flaw in routine activities theory that warrants in-depth
investigation. This problem stems from the basic sociological concepts of micro and
macro level analyses. Numerous researchers point out, that routine activity theory
admittedly focuses upon micro level interactions in its explanation of crime (Sampson
and Woolredge; 1987, Kennedy and Forde; 1990, Miethe and McDowall; 1993 and Meier
and Miethe; 1993). One recommendation provides considerable impetus toward solving
the micro-macro problem. In short, this suggestion entails that contextual analysis be
used to bridge the macro-micro gap in sociological studies (Miethe & McDowall, 1993,
741). There is no shortage of literature that addresses the contextual issue. Specifically,
Sampson and Woolredge and Kennedy and Forde tackle this problem by introducing
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community context variables into analyses of routine activity theory. That is not the only
way however, to address this problem. An integration of micro and macro level theories,
for the purposes of comparison has also been suggested. More specifically, Miethe and
McDowall have combined the theoretical propositions of routine activity and social
disorganization theory, to examine the differential effects of micro and macro level
assumptions respectively. Although Sampson and Woolredge and Kennedy and Forde are
in a sense tapping into the dimensions investigated in opportunity theory, Miethe and
McDowall more explicitly state the importance of the combination of these two particular
theories. Lastly, it will be suggested that domain specific analyses will be essential for
continuing to investigate this issue in future research. Thus, the theoretical assumptions
essential to routine activity theory are weakened because of the theory’s narrow focus on
micro-level analysis. Therefore, the incorporation of macro-level indicators and the
integration of micro and macro theories serve to alleviate these problems.
In order to adequately discuss the depth and breadth of the contextual affect on
routine activity theory, a framework for discussion must be outlined. First to be
discussed, are the studies which incorporate general community context variables in the
analysis of routine activity theory, namely the studies of Sampson and Woolredge and
Kennedy and Forde. In order to facilitate proper in-depth data analysis, these two studies
will be examined separately. Secondly, the significance of the integrative theory models
of Miethe and McDowall will be investigated, in regards to this issue. Additionally, a
discussion of the general problems of routine activity theory, as suggested previously by
Miethe and Meier, will be interwoven into these separate discussions. Finally to conclude
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this paper, domain-specific models will be proposed as an adequate basis for future
research.
The first researchers to be discussed are Sampson and Woolredge, and it bears
repeating, that these researchers propose that the introduction of contextual variables will
enhance the explanatory power of routine activity theory. An examination of the data will
provide a better understanding of the importance of these contextual variables in
explaining victimization rates. It is important to note that within this study, the authors
examine several types of criminal activity including, personal theft, personal larceny,
burglary, and household theft. The former are identified by the researchers as crimes
against the person, whereas the latter are considered crimes against the household
(Sampson& Woolredge, 1987, 380). Due to the confines of this paper, burglary and
personal theft data will be examined in depth, while the other forms of criminal activity
will be touched upon more generally.
The researchers provide logistic regression tables for each of the specific crimes
investigated within the study. Each of these tables combines the findings of the individual
model-the model which only includes routine activity variables-and those of the
contextual model-which include the micro (individual) and macro (community) variable
findings. An important measurement to note in all of these tables is the x² value. This
value basically indicates the improvement in fit between the two models (Sampson &
Woolredge, 1987, 282). As indicated in Table 1 for the individual model of burglary, the
x² value is a mere 21.94. However, the introduction of contextual variables increases the
value of this measurement, and in this case x² equals 128.19 (Sampson & Woolredge,
1987, 282).
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Table 1: Logistic Regression Predicting Risk of Burglary Victimization by
Individual Characteristics and Community Context, British Crime Survey (1982)
Needless to say, this measurement indicates that there is a better data fit when contextual
variables are introduced in addition to routine activity variables. The increases in the x²
values when comparing the micro and macro data are less profound with the other types
of crime. The documented increases in the x² values are: 37.46, 40.88 and 37.92 for
household theft, personal theft and larceny respectively (Sampson and Woolredge, 1987,
384-7). Since a basic explanation of the data has now been provided, a more intricate
examination of the data will commence. The following analysis will explain why specific
relationships were found within the data and in the process, illuminate some of the
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general flaws in routine activity theory. The examination of the data pertaining to
burglary will be examined first.
In one of their most influential works entitled “Social Change and Crime Rates: A
Routine Activity Approach,” Cohen and Felson outline the major concepts pertinent to
routine activity theory. In this paper the authors propose that the combined aspects of
target suitability including value, accessibility and inertia, “imply that expensive and
moveable durables, such as vehicles and electronic appliances, have the highest risk of
illegal removal” (Cohen & Felson, 1979, 595). Arguably, it is from this basic assumption
that many researchers, including Sampson and Woolredge, derive the idea to use
ownership of a videocassette recorder as an indicator of target attractiveness. However,
the findings recorded in the authors’ research does not run parallel to Cohen and Felsons’
predictions. In short, “…owning a VCR has no influence on burglary, [however] living in
an area where a high percentage of households has VCRs, does increase the victimization
risk” (Sampson & Woolredge, 1987, 383). This finding can further be illustrated when a
quantitative analysis is performed on the data in Table 1. In the “contextual model”
section of Table 1, the individual variable “VCR” has a regression coefficient of -0.004.
(Sampson & Woolredge 1987, 382). However, the regression coefficient community
variable “percentage of VCRs” is more significant as it is 0.012 (Sampson & Woolredge,
1987, 382). This highlights one of the more general problems of routine activity theory as
specified by Meier and Miethe. In particular this finding reflects a poor link between
theory and data (Meier & Miethe, 1993, 459). Thus, using portable electronic devices as
an indicator of target attractiveness, is an example of misspecification and an inherent
flaw in routine activities theory. This simultaneously highlights the attenuation of routine
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activity theory and the importance of adding contextual variables into this model. This is
not the only set of variables however, to be strengthened when examined in relation to
contextual variables. The data additionally indicates that, “living alone and living in a
high- “singles” area simultaneously increases the risk of burglary” (Sampson &
Woolredge, 1987, 383). This finding once again reinforces the significant impact that
community variables have on routine activity theory. An examination of the findings
pertaining to personal theft similarly reiterates this idea.
Looking exclusively at the individual model for personal theft in Table 2, it is
evident that these variables exhibited significance, and that their relation to victimization
followed the expected direction as proposed by routine activity theory. Specifically, the
regression coefficients were -0.008, 0.510, -.737, -0.713 and 0.053 for age, education,
married persons, males and the amount of nights out (Sampson & Woolredge 1987, 385).
Thus, “theft increases with education and decreases for married persons, males and older
persons” (Sampson & Woolredge, 1987, 385). However, the inclusion of variables that
are typically excluded from routine activity theory, once again enhanced the explanation
of victimization risks. In particular, the authors included a measure of social cohesion as
a community variable. What the researchers found was that, “living in areas characterized
by extensive social ties and low mobility serves to substantially reduce theft risk”
(Sampson and Woolredge, 1987, 386). Thus, while age, education and marital status may
help to explain victimization, these variables are only a subset of factors that lead to
higher victimization risks. This suggests that examining either micro or macro level data
exclusively, is ill-advised.
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Table 2: Logistic Regression Predicting Risk of Personal Theft Victimization by
Individual Characteristics and Community Context, British Crime Survey (1982)
There are a few findings that warrant further investigation with regards to all of
the crimes examined in this study. Particularly, “once lifestyle and activity patterns are
controlled (in addition to community context), variations in labor force participation are
unrelated to victimization risk” (Sampson & Woolredge, 1987, 388). Arguably, this
finding could have resulted because this particular measure is an insufficient indicator of
key concepts. This is a flaw of routine activity theory that was previously mentioned
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(Meier & Miethe, 1993, 459). This inadequacy may have resulted from the need to
specify between daytime and nighttime activities. Following this assumption would
suggest that it is nighttime activities, as opposed to daytime activities, that lead to the
increase of victimization risks. Thus, daytime activities such as work may have minimal
effects on victimization in comparison to nighttime activities. It has also been suggested
in other research that, “a void in formal guardianship due to labor force participation will
[or has] be[en] filled by other forms of guardianship whether informal (neighborhood
watches), formal (e.g. career criminal programs developed by [officials]), or target
hardening (e.g., defensible space through environmental design” (Bennet, 1991, 157).
Thus, it is possible that society has responded to fluctuating social factors and has found
an alternative means of guardianship for the home. The next set of researchers to be
discussed is Kennedy and Forde.
The research conducted by Kennedy and Forde in the paper entitled “Routine
Activities and Crime: An Analysis of Victimization in Canada,” supplements the work
put forth by Sampson and Woolredge, as it similarly investigates the importance of social
context variables in routine activity theory. Like their fellow researchers, Kennedy and
Forde explored various types of crime including breaking and entering, vehicle theft,
assault and robbery (Forde & Kennedy, 1990, 142-5). Once again, it is not within the
scope of this paper to discuss all of these forms of crime in depth. Thus, breaking and
entering and assault will be thoroughly analyzed. These two types of crime were chosen
for investigation because they represent property and personal crimes. In this study, the
analyses of routine activity variables were allocated a separate table from those of the
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contextual variables. Table 3, thus documents the logistic regression for breaking and
entering pertaining to routine activity variables.
Table 3: Logistic Regression Predicting Breaking and Entering by Respondent
Characteristics and Routine Activities
A glance at this chart indicates that the relationship of several of the routine
activity variables is in the expected direction. For example, youth are more likely to be
victimized, and victimization increases with non-household activities such as going to a
bar, a movie, bingo or work/class (Forde & Kennedy, 1990, 142). Admittedly, at first
glace, this data supports the theoretical assumptions set forth by routine activity theory.
However, a look at the chart including contextual variables (Table 4), will help to
determine if the introduction of these variables increases the explanatory power of routine
activity theory.
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Table 4: Reduced Form Logistic Regression Predicting Breaking and Entering by
Respondent Characteristics, Routine Activities and Structural Variables
A comparison of these two tables is required to understand the effect of
situational variables on routine activity theory. It is obvious that the structural variables
table (Table 4), includes indicators not analyzed in the routine activity model. For
example, routine activity theory does not include situational variables such as, the
percentage of divorce and the percent of low income families within a structural setting.
However as the authors point out, “where there are more low-income families and more
divorced persons there is a greater likelihood of being a victim of breaking and entering”
(Forde & Kennedy, 1990, 145). To put it concretely, the percent of divorced families
within the community increases a person’s chance of victimization by .294, while the
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percent of low-income families increases this probability by .106 (Kennedy and Forde,
1990, 146). The exclusion of such variables may exasperate one particular flaw with
routine activity theory, and that is a supposed poor link between theory and data (Meier
& Miethe, 1993, 459). This is understandable because the data is bias toward one level of
analysis and thus the theory may be incorrectly supported because of its lack of scope.
Finally, with regards to this research, the data pertaining to assault will be
analyzed. As before, the significance of the routine activity variables will be discussed
first, and then a comparison between the routine activity model and the structural model
will ensue.
With regards to assault, the relationship of the routine activity variables are once
again in the expected direction. As shown in Table 5, “the most vulnerable groups are the
young, unmarried males who frequent bars, go to movies, go out to work, or spend time
out of the house walking or driving around” (Forde and Kennedy, 1990, 143). Thus,
taken on its own, routine activity theory seems to be based on a solid theoretical
foundation, since its predictions have been borne out time and time again.
However, once again the introduction of contextual variables in this type of crime, helps
to further the predictive power of the theory. This is shown in Table 6.
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Table 5: Logistic Regression Predicting Assault by Respondent Characteristics and
Routine Activities
Specifically, Table 6 shows that the structural characteristics studied by the authors,
further explain those most likely to be victimized. As pointed out by the researchers,
“residents in areas where there are higher levels of unemployment, more one-person
households, fewer one-parent families and fewer low-income families are more likely to
be victims of assault” (Forde & Kennedy, 1990, 147). Further comparison of the data
shows that the significance of some of the variables increases with the presence of
structural variables. For example, routine activity variables consistently show that youth
are more likely to be victimized. This is shown in Table 5, as having a regression
coefficient of -.203 (Forde & Kennedy, 1990, 144). However the introduction of
structural variables slightly increases this relationship. This is shown as the regression
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coefficient for age, with the introduction of structural variables in Table 6, is -.223. A
similar finding is documented with the variable that measures the amount of time
respondents spend time outside their home walking or driving around
Table 6: Reduced Form Logistic Regression Predicting Assault by Respondent
Characteristics, Routine Activities, and Structural Variables
The authors do not fully discredit routine activity theory in their research. In
reference to assault and robbery the researchers point out that, “it appears that individual
level demographic variables are the most important for estimating victimization” (Forde
& Kennedy, 1990, 147-8). This suggests that routine activities theory is an indispensable
body of research for crime prevention initiatives. Thus, this theory may aid officials in
creating prevention programs geared toward those most likely to be targeted.
Lastly, integrative theories have assisted in facilitating a more in-depth
investigation into the micro-macro problem. One specific study conducted by Miethe and
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McDowall, combined routine activity and social disorganization theory to examine the
effect of structural variables on the former theory.
The researchers highlight the importance of combining the two theories by stating
that, “empirical tests of either theory would be misspecified by failing to include what the
other perspective assumes to be critical information” (Miethe & McDowall, 1993, 743).
The practicality of combining these two theories may not seem obvious at first. However,
Miethe and McDowall state that, “social disorganization theory provides a basis for
identifying…criminogenic areas and criminal opportunity [routine activity] theories,
establish a set of necessary elements for predatory victimization” (Miethe & McDowall,
1993, 743). Thus, it is evident that a comparison of these two theories is an essential asset
in helping to solve the micro-macro problem. Table 7 provides a concise summary of the
findings gathered by these researchers.
Table 7: Logistic Regression Estimates for Models of Individuals’ Risks of Violent
and Burglary Victimization
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With regards to this table, the authors note that, “regardless of the type of crime,
including contextual variables significantly improved the baseline model (the model with
only the controls and individual level attributes)” (Miethe & McDowall, 1993, 750).
Thus, once again a recurrent theme has reappeared, that is that, routine activity theory
may have a fairly great explanatory power, but the introduction of contextual variables
serves to enhance this power. Miethe and McDowall’s data also reveals one significant
piece of information. That is “for each crime, the contextual factor most important in
explaining victimization is the socioeconomic condition of the area (Miethe &
McDowall, 1993, 750). A quantitative explanation can further emphasize this point. In
Table 7, the logistic regression value for poor socioeconomic condition was 1.00 for
violent crime and .44 for burglary (Miethe & McDowall, 751). These values obviously
indicate the exceptionally strong effect that this contextual factor has on explaining
victimization rates.
Lastly, the data uncovered one more significant finding. This is that “differences
in individuals’ risks of violent crime by both income and living alone were eliminated
once controls were introduced for the neighborhood context” (Miethe &McDowall, 1993,
751). This finding once again, illuminates a flaw in routine activity theory. This problem
as suggested by Meier and Miethe, is that routine activity theory employs insufficient
indicators of key variables. Therefore, target attractiveness as measured by income and
guardianship as measured by living alone, do not seem to have significant impacts on
victimization. This could be because routine activity theory ignored contextual factors
which nullify these measures.
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The last topic to be examined is how the investigation of the implications of the
micro-macro link should be replicated in future research. The plethora of research
provided within this paper has illustrated the importance of including situational variables
in routine activities theory. One strand of research that provides considerable promise for
future research is domain-specific models. This strand of research still has not gained
momentum and thus there are a limited amount of sources regarding this type of research.
Lynch who is credited with contriving the idea of studying separate domains, states that,
“classifying both life activity and victimization by domain strikes a balance between the
scope of behaviour to be explained and the precision of measurement in empirical tests”
(Lynch, 1987, 285). This type of research may have more explanatory power than regular
routine activity theory studies. This is because the convergence of suitable targets,
offenders and guardians and the routine activities that allow this convergence, can differ
from domain to domain. Mustaine attempted to supplement Lynch’s work and concluded
that this type of research can aid in explaining “how lifestyle influences the risks of
victimization for a specific subpopulation” (she studies the subpopulations of males and
females) (Mustaine, 1997, 42). Nevertheless, the branch of domain-specific research
warrants further investigation. It arguably can help enhance the scope and theoretical
foundations of routine activity theory.
In conclusion, the evidence astoundingly points in one direction. As it has been
reiterated throughout the entirety of this paper, the introduction of contextual variables is
essential to enhancing the explanatory power of routine activity theory. This assertion has
been empirically verified despite the type of contextual model used. Thus, the works of
Sampson and Woolredge, Kennedy and Forde and Miethe and McDowall, collectively
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serve to reinforce this research assumption. Throughout all of these research endeavours,
statistical comparisons have been completed between the baseline and contextual models.
In all three studies, the relationship between the routine activity theory variables,
followed the expected direction. However, in the aforementioned studies, the introduction
of contextual variables improved the fit of the data. This reoccurring finding
inadvertently highlighted the flaws inherent in routine activity theory. Specifically, these
findings exposed that some general flaws of routine activity theory, including poor links
between data and theory and the use of insufficient indicators for key variables (Meier &
Miethe, 1993, 459). Additionally, domain-specific models are another type of contextual
analysis which promises to further enhance the explanatory power and applicability of
routine activity theory.
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References
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Groff, E.R. (2007). Simulation for Theory Testing and Experimentation: An Example Using Routine
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