Research Paper on Theft and Shoplifting

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This sample research paper on theft and shoplifting features: 6200+ words (24 pages), an outline, APA format in-text citations, and a bibliography with 61 sources.

Outline

I. Introduction

II. Defining Common Types of Theft

A. Larceny-Theft

B. Motor Vehicle Theft

C. Burglary

III. Prevalence of Theft and Shoplifting in Society Today

A. Demographic Variations in Theft

IV. Understanding the Causes of Theft: Criminological Research and Theory

A. Economic Conditions and Theft

1. Income Inequality and Theft

2. Unemployment and Theft

3. Market Forces and Theft

B. Environment, Opportunity, and Theft

1. Routine Activities and Theft

2. Environmental Factors and Theft

C. Theft and Drug Use

V. Conclusion

I. Introduction

In the United States and elsewhere, theft commonly refers to the illegal taking and possessing of another’s property, anything of value, with the intent to permanently deprive that person of the item or the value of the item taken. Shoplifting is a certain kind of theft (i.e., larceny-theft) that occurs at retail stores and commercial businesses. Theft and shoplifting are two types of property crime. Other property crimes are burglary, motor vehicle theft, and arson. While there are many kinds of theft, those discussed here are larceny-theft, burglary, and motor vehicle theft. None of these crimes features the use of force against people. Common examples of larceny-theft include stealing a bike or someone’s wallet (pickpocketing), or taking things from a retail store, e.g., CDs or clothes.

Theft and shoplifting are important to address because they account for the largest portion of all criminal offending in the United States. Laws against them date back to ancient Roman law (e.g., Hammurabi Codes) and English common law. In those times, the crime of theft was rampant, and proscriptions about what to do with thieves dominated extant law. These codes and laws have played an important role in shaping modern criminal law in the United States. Today, the forces that motivate theft are powerful and ever present, and the consequences of theft are felt by individuals, businesses, communities, and government agencies.

The research paper begins with a discussion of the major types of theft and shoplifting, followed by the prevalence of each in U.S. society today. Here, some demographic and regional variations in theft rates are examined, as well as the offenders who are involved. From there, the discussion moves to the major schools of thought regarding why theft and shoplifting take place and what society can do to address the problem. The research paper concludes with some observations for future research, theory, and practice.

II. Defining Common Types of Theft

In most societies today, including the United States, there are many different legal classifications of theft across jurisdictions. In the United States, there are state and local laws against a variety of theft categories and another level of codes at the federal level. Most states divide theft into “major” or felony theft and “petty” or misdemeanor theft. Classifications usually depend on the value of the item taken. Below, three different kinds of theft are reviewed: larceny-theft (which includes shoplifting), motor vehicle theft, and burglary.

A. Larceny-Theft

The Federal Bureau of Investigation’s (FBI) Uniform Crime Reports (UCR) is the official and leading data source on crimes reported to the police and arrests made by them in the United States. As such, the definitions articulated in the UCR formally define what is known about crime in society today. According to the UCR, larceny-theft is the “unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another” (FBI, 2008). Common examples of larceny-theft include stealing bicycles, shoplifting goods from retail stores or businesses, pickpocketing, or swiping someone’s laptop at an Internet cafe or other location. Larceny-theft covers any stealing of property that is not taken by force, violence, or fraud. Included in the FBI’s definition are attempted larcenies.

B. Motor Vehicle Theft

The FBI has a separate category of theft for stolen automobiles and other motor vehicles. Motor vehicles are those that are self-propelled on land surfaces, not on water or railways. Examples include cars, motorcycles, trucks, buses, sport utility vehicles, snowmobiles, and so forth. This category of theft does not, however, include farm equipment, airplanes, or any type of boat or Jet Ski. Joyriding, or the temporary taking of a vehicle, is not included in the category of motor vehicle theft.

C. Burglary

Burglary is a type of theft very different from larceny-theft and motor vehicle theft because it requires unlawful entry—trespassing into a facility so as to steal a given item. This unlawful entry into a private or secured dwelling for purposes of theft makes burglary a more serious offense than simple larceny or shoplifting. The UCR defines burglary as “the unlawful entry of a structure to commit a felony or theft” (FBI, 2008). One does not have to exert force to enter a facility in order to be guilty of burglary. In fact, there are three subclassifications of burglary specified in the UCR. They include forcible entry, unlawful entry where no force was used, and attempted forcible entry. Common examples of structures that are burglarized include homes, apartments, offices, and retail stores.

III. Prevalence of Theft and Shoplifting in Society Today

According to official data (FBI, 2008), there were about 10 million property crimes reported to the police in 2006. This translates to an estimated property crime rate of 3,334.5 for every 100,000 U.S. residents. Nearly two thirds of all property crimes are larceny-thefts (Bureau of Justice Statistics [BJS], 2006). According to the BJS, theft from motor vehicles (a type of larceny-theft and not theft of the actual vehicle, i.e., motor vehicle theft) comprises the largest portion of larceny-thefts annually. This pattern has remained consistent over time. Theft from buildings and shoplifting follow in second and third place, respectively. As indicated above, property crimes like theft yield significant costs to society. According to the BJS, losses from property crimes in 2006 totaled about $17.6 billion. Like other crimes, rates of property crime have declined significantly from the early 1990s, when the United States began to see a national crime drop (Blumstein & Wallman, 2005). Rates of property crime offending and victimization are highest in cities and much lower in the suburbs and rural areas (BJS, 2005b, 2006).

Contrary to logic, perhaps, the highest rates of property crime victimization are reported in the poorest of American households (BJS, 2005b). For example, burglary, motor vehicle theft, and major and minor larceny victimizations are higher in households with incomes below $7,500 per year than in households earning more than that. The exception to this pattern is that larceny-theft victimizations are about as high in households earning $75,000 or more per year as they are in households earning less than $7,500.

Below is a comparison of the crime literature on the market value of goods and their risk of theft with claims by routine activities theorists. The market value approach suggests that theft should be highest where goods are most plentiful and most valuable. This would seem to suggest higher rates of theft victimization in higher-income households, a contradiction to the data reported above by the BJS (2005b). However, the routine activities claim that motivated offenders (e.g., lower-income people residing in poorer households) confronted with easy targets (e.g., unattended households not guarded by locks or alarms) leads to high rates of property crime victimization, may help explain greater theft victimization in poorer households.

A. Demographic Variations in Theft

Offenses and arrests for theft are not evenly distributed across demographic groups. In general, adult males who live in urban areas are responsible for the highest levels of theft and other property crimes. The exception to this pattern is for motor vehicle theft, which has been historically dominated by adolescent males. While research shows most females offenders are arrested for drug offenses, property crimes, and prostitution (Anderson, 2008), males still outpace females with respect to arrests for theft and shoplifting. However, women have gained ground on men in recent times.

With respect to theft victimizations, data show that African Americans are more likely to have their homes burglarized and their vehicles stolen than are whites (BJS, 2005a). Whites, on the other hand, are more often victims of larceny-theft than are blacks.

Data (BJS, 2005a) show that a large portion of property arrestees at the local and state level committed their offense to get money for drugs. In fact, property arrestees were more likely than violent crime or drug arrestees to commit their crimes for money for drugs. The relationships among theft, shoplifting, and drugs are elaborated below.

IV. Understanding the Causes of Theft: Criminological Research and Theory

The field of criminology has approached the study of theft with respect to two theoretical issues that have occupied scholarly attention for several decades. The first is the relationship between macro-level economic forces and theft, typically conceptualized in terms of classic strain theory (Merton, 1938) or social disorganization theory (Shaw & McKay, 1942). The second centers on the extent to which rates of theft reflect the opportunities for crime provided by certain locations and the processes by which potential victims and offenders converge in space and time. This conceptual focus was strongly influenced both by the development of routine activities theory (Cohen & Felson, 1979) and a growing emphasis on the role of the physical and social environment in shaping opportunities for theft (Reppetto, 1974). In the following sections, a summary of research in these two main conceptual areas is provided. Following that, research is reviewed that has examined the relationship between drug use and addiction and theft.

A. Economic Conditions and Theft

1. Income Inequality and Theft

The relationship between income inequality and theft is one of the most enduring in all of criminology and is generally conceptualized in terms of classic strain theory (Merton, 1938). Strain theory posits that theft is the result of the gap between the culturally induced aspirations for economic success and the structurally distributed possibilities for achieving it. Merton predicted that some individuals would respond to the strain between aspiration and the lack of opportunity by engaging in criminal behavior such as theft. The theory assumes similar success aspirations across social classes and posits that crime is disproportionately concentrated in the lower class because they have the fewest legitimate opportunities for achievement and so are the most vulnerable to this pressure or strain. Simply put, overemphasis on material success and lack of opportunity for this kind of success lead to crime.

Recent research indicates that income inequality is the most consistent structural correlate of rates for theft and other forms of property crime (Bursik & Grasmick, 1993; Walsh &Taylor, 2007). All forms of theft tend to occur disproportionately in poor, isolated, socially disadvantaged neighborhoods (Bernasco & Nieuwbeerta, 2005; Reisig & Cancino, 2004). In the United States in particular, social isolation and poverty are highly racialized. Research also finds that residential segregation, which is often a proxy measure for black–white income inequality, is strongly associated with burglary, larceny, and motor vehicle theft (Akins, 2003). Racialized income inequality leading to residential segregation can be traced to fundamental changes in the labor market, which resulted in the elimination of industrial jobs in major cities (Wilson, 1987). This fundamental economic shift is consistent with both sociological and criminological anomie theories, which predict an inability or failure of certain segments of the population to effectively adapt to major structural or economic changes (Merton, 1938), or that they will react to such changes by engaging in crime.

Similarly, research has also found links between welfare and theft suggested by classic strain, familial support, and variations of social disorganization theory. Both monetary assistance levels and welfare participation rates are negatively associated with all forms of theft (R. C. Allen & Stone, 1999). Basically, if state and local governments take measures to alleviate economic inequality by providing job training, welfare benefits, as well as ground-level efforts to improve communities by providing access to after-school programs and such, rates of theft decline substantially. In general, it is evident that state and local governments with strong welfare and monetary assistance programs will experience lower rates of theft. This research is also consistent with more recent formulations of social disorganization theory (Hunter, 1985; Sampson, Raudenbush, & Earls, 1997). That is, the inability or unwillingness of families and neighbors to come together for the betterment of their community tends to result in higher rates of all forms of crime. These factors are particularly well established as correlates of major forms of theft such as residential burglary, motor vehicle theft, and robbery (Reisig & Cancino, 2004; Rice & Smith, 2002). Accordingly, establishing higher levels of social control and cooperation among families, friends, neighbors, and public organizations such as the police will lead to lower rates of theft.

2. Unemployment and Theft

The unemployment rate is one of the most commonly used measures in research on the relationship of economic conditions and theft. Research and theory addressing the connection between unemployment and theft consistently predict that higher rates of unemployment lead to higher rates of theft (Bursik & Grasmick, 1993; Merton, 1938; Wilson, 1987). Given the theoretical consensus, one would assume that the empirical relationship would be fairly strong regardless of its interpretation. Findings, however, are quite inconsistent. Some research has found a positive relationship between unemployment and theft (Carmichael & Ward, 2001; Reilly & Witt, 1996), some research has found a negative relationship (Cantor & Land, 1985; Land, Cantor, & Russell, 1995), and other work has failed to find any appreciable effect (Weatherburn, Lind, & Ku, 2001). The continuation of mixed findings has led some criminologists to question whether the unemployment rate is a useful indicator in conceptualizing the relationship between economic conditions and theft, or at least, to conclude that it must be understood as one of a number of measures of economic hardship (Cantor & Land, 1985).

A growing body of research suggests that the effect of unemployment on theft is not straightforward, but rather, is contingent on various demographic or contextual factors. One consistent predictor is length of unemployment. Research suggests that individuals are more likely to commit crime the longer they are unemployed (Witt, Clarke, & Fielding, 1996). This indicates that individuals are generally able to endure short-lived instances of economic hardship, but will resort to theft if no legitimate opportunities surface in a reasonable period of time. Other demographic predictors are less reliable. The relationship appears to vary by age, but research is mixed as to the precise nature of the relationship. For example, some research has identified a link between adult male unemployment and theft (Carmichael &Ward, 2001), while other studies have found that unemployment is only related to rates of theft among juveniles (Britt, 1997). The kind of theft that occurs as a result of unemployment also appears to be impacted by considerations related to national or regional culture. For example, one recent study (Herzog, 2005) examined the relationship between unemployment and crime by focusing on the unique framework provided by the large, integrated labor force of Palestinian workers employed in Israel over the past few decades. Overall, a relationship between unemployment among Palestinians and theft in Israel was not found, except in one case: motor vehicle theft. As such, it appears that the relationship between economic hardship and crime may not be a general one, but rather, is specific to certain forms of activity (Herzog, 2005).

The main point to emphasize is that the relationship between unemployment and theft is far more nuanced than previously believed. The complexity of this relationship is further illustrated by Cantor and Land’s (1985) seminal work on the differential effects of motivation and opportunity. They argue that although rises in the unemployment rate may increase criminal motivation to commit theft, they may also decrease the opportunity to successfully complete theft. Simply put, if people aren’t working, they’re likely at home, which increases guardianship (Cantor & Land, 1985; Land et al., 1995). Despite this reasoning, recent research has found that overall, opportunity levels are unrelated to theft rates and do not appear to mediate the unemployment– crime relationship for most forms of theft (Kleck & Chiricos, 2002). Presently, then, it appears that the motivation to commit theft due to unemployment is stronger than the decreased opportunities that are theorized to decrease theft during periods of unemployment.

3. Market Forces and Theft

Theft is also directly impacted by the nature of the capitalist economy and the market for certain items, as well as other, more subjective economic indicators such as consumer confidence. A recent study (Rosenfeld & Fernango, 2007) found that consumer confidence and optimism had significant effects on theft rates that were largely independent of objective indicators such as unemployment and economic growth. Consumer sentiment also accounted for a significant portion of the overall crime decline that began during the early 1990s. This suggests that broad economic conditions, beyond the unemployment rate, are useful in modeling rates of theft in recent decades.

Research also suggests that theft rates are directly impacted by the cycle of the free market. Patterns of theft seem to be initially related to goods production. The relationship is straightforward: with more new items to consume, there is more to steal (Von Hofer & Tham, 2000). Then, when products reach the “saturation” stage, where people who want an item (such as a VCR or CD player) already have it, prices decline and such items are less likely to be stolen (Felson, 1996). This line of research supports a theft market life cycle of innovation, growth, mass market, and saturation. The optimum time to steal goods is during the “growth” phase, where demand for newer items is highest. The most inopportune time to steal goods is during the “saturation” period, where most everyone who wants an item already has it. These factors are also related to both prices and ownership levels of an item (Felson, 1996; Von Hofer & Tham, 2000). This research suggests that instances of theft can likely be reduced by an awareness and manipulation of certain licit markets as well as the pricing of merchandise (Wellsmith & Burrell, 2005).

B. Environment, Opportunity, and Theft

1. Routine Activities and Theft

There is a large amount of literature devoted to conceptualizing the relationship between criminal opportunity and theft. The dominant theoretical framework shaping this line of inquiry is routine activities theory (Cohen & Felson, 1979), which assumes that crime represents a convergence in time and space of motivated offenders, suitable targets, and a lack of effective guardianship (surveillance and protection) of persons and property. These key variables were later refined to incorporate dimensions of exposure (physical visibility), proximity (physical distance), and target attractiveness, and the guardianship variable was extended to account for security guards, bouncers, police presence, and so forth.

Research in this area implies that individual-level efforts to increase the security, surveillance, or guardianship provided should decrease theft victimization risk. Several measures of individual-level guardianship have been linked to burglary victimization, specifically. For example, type of residence (Coupe & Blake, 2006), household composition (Tseloni, Wittebrood, Farrell, & Pease, 2004), and certain leisure activities (Miethe & Meier, 1994; Mustaine & Tewksbury, 1998) are all highly correlated with theft outcomes. Research consistently demonstrates that younger, single persons who are renting, living in transitional neighborhoods, or engaging in nighttime leisure activities experience a substantially higher risk of theft victimization. Specifically, lifestyles that include dining out often and regularly frequenting bars, clubs, and taverns are all highly correlated with minor theft victimization (Anderson, Kavanaugh, Bachman, & Harrison, 2007; Mustaine & Tewksbury, 1998; Smith, Bowers, & Johnson, 2006). These lifestyle factors are also strong predictors of repeat theft victimization and repeated violent victimizations (Anderson et al., 2007; Wittebrood & Nieuwbeerta, 2000). Other research finds that older people are an increasingly attractive target population for various forms of theft, including residential burglary (Mawby & Jones, 2006) and petty theft (Harris & Benson, 1999).

Conversely, engaging in routine activities that provide protection of homes and vehicles (target hardening), including locking doors, installing alarms, and light timer devices, are negatively correlated with theft victimization (Miethe & Meier, 1994). Accordingly, successful theft reduction initiatives include hardening techniques that overlap with individual-level guardianship. These include improved street lighting (Painter & Farrington, 1998), the establishment of Neighborhood Watch groups (Forrester, Chatterton, & Pease, 1988), alarm systems (Hakim, Gaffney, Rengert, & Shachmurove, 1995), improved locks and doors (Tilley & Webb, 1994), ensuring possessions are out of view (Bromley & Cochran, 2002), and the gating of residential property (Bowers, Johnson, & Hirschfield, 2004).

2. Environmental Factors and Theft

Brantingham and Brantingham (1999) suggested that the selection of theft targets is largely dependent on an assessment of the immediate environment of the target. Essentially, this work makes a strong case for incorporating elements of social context in understanding theft. As such, more recent research has incorporated elements of neighborhood control, derived from social disorganization theory (Miethe & Meier, 1994; Wilcox, Madensen, & Tillyer, 2007), in an attempt to offer a more holistic model of theft that accounts for social context and the role of the physical environment. This work has found that environmental cues in neighborhoods extending beyond the specific target are, in fact, important considerations. Findings consistently indicate that all forms of theft tend to occur at higher rates in poor, socially isolated neighborhoods (Akins, 2003; Rice & Smith, 2002;Walsh &Taylor, 2007).

It is important to note that the role of “environment” in theft extends beyond a consideration of the neighborhood. More recent research has begun to conceptualize the role of the environment in broader terms. Other environmental factors such as the time of day, time of week, and season of the year (Bromley & Cochran, 2002; Coupe & Blake, 2006) all function to shape theft outcomes. Local or regional culture can play a role as well (Herzog, 2005; Painter & Farrington, 1998). For example, Burns (2000) found that the southern and western regions of the United States experience higher percentages of stolen trucks than the Midwestern and Northeastern regions. Burns (2000) suggests that this is because in these regions, trucks are recognized as ingrained artifacts of their respective cultures. Their attractiveness as targets has increased due to the fact that these vehicles are an integral part of their local culture. Proximity to major roads is another important environmental consideration shaping perceived opportunity for residential burglary (Rengert &Wasilchick, 2000) and especially for auto theft (Lu, 2006). With respect to commercial theft, research has found that it is typically clustered in areas with a large number of liquor licenses— namely, convenience stores, restaurants, and bars— indicating that land use is another important variable in structuring theft outcomes (Smith et al., 2006).

Predicting when and where theft crimes are most likely to occur is crucial for prioritizing police resources (Kane, 2006), and research indicates that theft is highly likely to be deterred by aggressive policing practices that target “hot spots” and certain neighborhoods. The potential deterrent effect, however, is further shaped by environmental factors. With respect to residential burglary, for example, research has found that (1) repeat victimization in general tends to occur in poorer areas; (2) houses located next to a previously victimized house are at a substantially higher risk relative to those located farther away, particularly within one week of an initial burglary; and (3) properties located on the same side of the street as a previously victimized house are at significantly greater risk compared with those opposite (Bowers at al., 2004).

The selection of theft targets is also conditioned by two additional factors related to accessibility: (1) proximity to the homes of the offenders and (2) proximity to the central business and entertainment districts (Bernasco & Nieuwbeerta, 2005; Bromley & Cochran, 2002). This is the case with both residential and auto burglaries (breaking into cars to steal stereos or possessions), as well as auto thefts. Installation of new security measures often fails to deter repeat victimization, suggesting target familiarity is an overriding priority for offenders and can sometimes negate the beneficial effects of target hardening and even police presence (Palmer, Holmes, & Hollon, 2002).

C. Theft and Drug Use

Illicit drug use, particularly heroin use, became associated with property crime in the 1970s based on the reasoning that users will turn to burglary, fraud, shoplifting, as well as other forms of crime such as robbery and prostitution, to obtain money to maintain their addictions. Such reports emerged during the Nixon administration, and remain popular in anti-drug campaigns today. In criminology, this reasoning was formalized in Goldstein’s (1985) economic-compulsive model of drug use and crime. Heroin and cocaine, because they are expensive drugs typified by compulsive patterns of use, are the most relevant substances in this category.

While some scholars have framed these claims as exaggerated attempts to drum up public support for “get tough on crime” policies, an empirical link between drug use and theft does exist. Two things, however, should be noted. First, the onset of participation in crimes such as theft and shoplifting tends to precede induction into drug use (C. Allen, 2005), so the relationship is not directly causal. Second, the relationship between theft and drug use is observable only with serious and prolonged narcotics use. There is a much weaker, almost negligible relationship between regular use of marijuana or other hallucinogens and theft. In studies that have observed a positive relationship, theft and drug use tend to be correlated simply because they are common measures of general delinquency. However, research consistently demonstrates that regular use of harder drugs such as heroin and crack cocaine will eventually lead to participation in theft and is therefore strongly related to, if not a direct cause of, theft (C. Allen, 2005; Best, Sidwell, Gossop, Harris, & Strang, 2001).

Patterns of theft involvement tend to vary with respect to the recent levels of drug activity, with users reporting the highest levels of drug expenditure and accordingly, the highest rates of crime (Best et al., 2001; Manzoni, Brochu, Fischer, & Rehm, 2006). Petty forms of crime by drug users such as shoplifting and bicycle theft tend to be the most common, whereas burglaries and motor vehicle thefts are exceedingly rare (Van der Zanden, Dijkgraaf, Blanken, Van Ree, & Van den Brink, 2006). Violent forms of theft such as street robbery and purse snatchings tend to be one-off occurrences rather than criminal lifestyles (C. Allen, 2005). Frequent crack cocaine and other hard drug users are equally likely to be heavily involved in drug selling or prostitution, as well as the performance of marginal, part-time work in the legal economy (Cross, Johnson, Davis, & Liberty, 2001). The point is that neither serious nor petty theft functions as a primary source of income to support individual drug habits. Drug offenders are far more likely to recidivate with a drug offense than either theft or violent crime.

V. Conclusion

Theft has very immediate and costly consequences. It is one of the most prevalent forms of criminal behavior in the United States, consistently accounting for around 80% of all crimes reported to the police in a given year. However, the social processes reflected in theft are extremely complex. More so than almost any other crime, theft is heavily dependent on opportunity. Even the most motivated offenders may ignore attractive targets if they are well guarded. This fundamental consideration has led many criminologists to approach the study of theft in terms of routine activities theory, the most enduring explanatory framework that accounts for variables such as time, place, space, and situations.

Routine activities theory is linked to both opportunity and lifestyle, and living arrangements. This, in turn, has led to an increasing focus on the role of environmental context in shaping theft outcomes, and more recent research has made an effort to conceptualize routine activities variables in broader terms, incorporating variables related to neighborhood social organization. This inevitably opens the door to readdressing issues of income inequality, unemployment, and community poverty and exploring how these interrelated variables coalesce to constitute risk environments, shaping both opportunity and motivation in new and unique ways.

Such conclusions have important crime-prevention implications. Prior research has focused on either situational theft and theft prevention or aggregate-level rates of theft in countries or states, highlighting socioeconomic inequality. Recent research suggests that incorporating these two broad explanatory frameworks is useful in effectively understanding the whens and whys of theft. Such possibilities suggest the use of more context-driven crime-prevention policies that incorporate new and inventive understandings of social environments as well as economic factors.

See also:

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