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Shop Theft: The “innocent” crime of shoplifting

· Andreas Papavasiliou

SECU1007 "Understanding the Crime Event"

Word Count: 1954

Shoplifting is the crime problem of stealing from a store discreetly. It is distinct from burglary and

robbery, which are considered theft by breaking into a closed store and stealing by threatening

or engaging in violent behavior, respectively. Shoplifting has been a major issue in England and

the rest of the world for more than seventy years now. Although it has been around for a long

period of time, over the last few years there was a notable increase in the amount of offences

comitted of shoplifting in England. The amount of increase is 23% in the last five years, while the

number of offenders that have been arrested by the police dropped by 17% and the charges

decreased by 25% in the same period. (BBC News, 2019). With the introduction of environmental

criminology, a new point of view to this problem is provided. According to NASP(National

Association for Shoplifting Prevention), 73% of adult and 72% of teenager shoplifters don’t plan

to steal in advance, hence, this shows that the crime is encouraged during the presence of the

customer in the shop. (NASP, 2019). The lack of a security guard or CCTVs(closed-circuit

televisions) in the shop, during times when the shops are crowded,(seasonal occasions) are

patterns, within the shop, found to hugely affect the rate of this particular crime. Therefore, by

shifting our focus to the environmental conditions inside a shop, the event patterns identified

will be explained providing sufficient evidence as well as preventing techniques used for

shoplifting.

Moreover, this essay will focus on the crime of shoplifting without taking into consideration the

motivation or situation of the offender committing this crime but in fact look at how shops create

the opportunities for crime to occur. After researching the crime and analyzing the patterns

found around shoplifting, I concluded to my hypotheses. Continuing on this I lay down my main

hypothesis that shops act as crime generators; a location that even though people visiting it have

no intentions to commit a crime but the opportunity is too good to pass up. My second

hypothesis is that a shop that has been victimised already is most likely to be offended again.

Using the following fundamental theories within environmental criminology, routine activity

theory, rational choice along with situational precipitators theory and crime pattern, evidence

will be provided to back up this hypothesis and explain the existence of crime in shops. (Wortley

and Townsley, 2017).

To begin with, the routine activity theory proves that crime is dependent on more than simply

criminals. More specifically, crime requires the combination of the presence of an offender and

suitable victim with the absence of a capable guardian. When this scenario is in place, a crime

opportunity arises. Eck’s crime triangle is the basis of this theory and by forming the triangle for

shoplifting we can have a more specific approach on this crime. In this case our offenders, as you

can see on Figure 1, are the customers that visit a shop, our suitable place. As we are using the

extended version of the crime triangle, we can move to its outer triangle. The handler of the

offender will be his/her family, siblings or friends which are not present at the time of the offence,

therefore cannot affect his decision. The guardian can be both the employee and security guard,

depending on the shop, as well as the police in general. As for the place managers, this will be

the owner/manager of the shop or shopping mall based on the chosen place.

In case an offender comes across a shop in which the desired target is noticed, with the absence

of a shop employee or security guard, a crime opportunity exists. Therefore, the offender is more

Figure 1: Eck’s extended crime triangle. (Wortley and Townsley, 2017).

likely to commit the crime even if his initial intentions when visiting the shop were different; this

relates back to the first hypothesis that crime is generated from the shop.

Moving on to the second principle, rational choice theory explains the motive behind offenders’

actions and how they decide to commit a crime. Offenders analyse the situation they are in by

taking into consideration the effort, risk and reward each time. This simple cost-benefit analysis

will show them the expected benefits and expected costs. In case the benefits outweigh the costs,

then crime occurs. Applying this theory to our example shows that again the opportunity for

crime is offered by the shop, due to the lack of setting significant costs to the offenders. For

example, as mentioned before the most of the shop thefts occur on the busiest times of the year.

This can be again explained by this theory as crowded shops are considered easier to steal from

with lowered costs, as its more difficult to be spotted or arrested. (Cardone and Hayes, 2012).

Similarly, to the rational choice theory, the situational precipitators theory focuses on how

environmental factors can encourage offenders to commit crimes, which they would not have

otherwise. Prompts and pressures are two examples of precipitators of crime that are present in

shoplifting. Prompts are aspects from the surrounding environment that may tempt us, stimulate

us and set examples for us to follow. These include a crowded store, lack of authority figure and

no camera surveillance in the shop. Pressures are situations that exert social pressure on human

based on the expectations and demands of other human beings. Some examples of these are

teenagers that do it because of the pressure that all of their friends are doing and homeless

people that need to feed themselves. Figure 2 puts precipitators and opportunity together to

explain the relation between the two theories.

Figure 2: Relationship between precipitators and opportunities. (Wortley and

Townsley, 2017, pp.66).

Moving on to the last theory, Crime Pattern Theory will help us understand the reasons behind

the location of the crime rather than the reasons the crime happens. Offenders move around

between their home, work and entertainment areas as they follow their everyday activities. The

places they visit the most as well as their best-known routes form their awareness space. Most

criminals will stay in their awareness space to commit offences because they are familiar with

the area and feel more confident in it. This theory is linked to our hypothesis regarding the repeat

victimization. A shop that falls in the awareness space of an offender, can be offended several

times by the same person. (Read Hayes, 2019).

According to these theories, my hypotheses states that there should be evidence of shops being

victimized more than once and shops acting as crime generators. Correspondingly, we should

expect to see differences between shops based on their location as well as their shop’s condition.

It will be interesting to see how the time period of the year affects as well the crime rates.

Most of the research of this project is based around shops in London, United Kingdom. To collect

data for the research, I used the police data (Data.police.uk, 2019). Even though the data

collected from the police might not be accurate enough as not all of the crime is recorded, but

its sufficient for evidence to be provided. After collecting all the data for the last year, I started

plotting online on the map the shops targeted over each month as well as the frequency of the

offences.

Figure 3: February 2018 Shoplifting incidents on City of London Street, labeled by frequency.

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The result for the month February 2018 can be seen in Figure 4, this month was selected

specifically so that there is no seasonal period to alter our results. The frequency that each shop

was victimized during this month is labeled next to each shops location. As it can be seen on the

map, a supermarket located opposite to Liverpool Street Station was victimized the most

reaching a number of 13 incidents recorded by the police. This can be explained due to the

crowded area almost throughout the whole day and due to the fact, the shop is next to an

underground station where a lot of people are already been attracted to. Crowded shops are

more difficult to keep secure as you cannot monitor and control every customer in it. In addition,

the shop has a facing on the open street which make it a suitable for “grab and go” as the offender

has multiple escape routes from the shop. By paying close attention to the common points

between all of the offended shops we can see that the all of them have a fronting on high streets.

Continuing on, to have a broader view of our problem, a full year analysis needed to be done.

This will help identify any crime patterns that exist through the year and not specifically on a

given period. In the Figure 5, found below, we can see the shoplifting offences of last year that

occur at the City of London Street. Looking closely to the diagram, we can see that the most

incidents happened in October, November, August and March. The Easter was on the 1st of April

last year, therefore, March can be considered the pre-Easter period; hence the shops were more

busy than usual. Same goes with October and November which can be considered as preChristmas period. Hence the time period can be correctly said to affect the crime of shoplifting.

Figure 4: Police data used to form Figure 3 (Data.police.uk, 2019)

Figure 5: Chart created using police data for each month of the year 2018

In order to completely test my hypothesis of the shops creating the opportunity for the item theft

to occur, I needed specific data for the environmental conditions inside the shop. Obtaining data

showing whether there are CCTVs or a security guard in the targeted shop. Having this data would

help me identify patterns proving that with the absence of a security guard crime rate increases.

In addition, the condition of the shop is highly suggested that it will affect the crime occurrence,

therefore data relating how well taken care of the shop is by its employees. According to the

Broken Window Theory (Wilson & Kelling) a broken window is considered a physical sign that the

residents in a neighborhood do not especially care about their environment and that similar

crime will be tolerated. (tutor2u, 2019). In the case of shops, employees who do not respect and

keep the shop in order, will result in encouraging anti-social behavior to the customers.

The most important way of preventing a crime is removing the opportunity for this crime to

occur, in this way it is certain that no crime will exist. A lot of techniques can be employed in

order to minimize the crime rate of shoplifting. To begin with, the most effective method would

be the use of modern tags. New tagging methods include computer chips in them which can be

used to track where and when an item was stolen. Offenders will notice the new updated tags

and affect their decision. Additionally, the shop must be always kept to perfect condition,

maintaining a clean and organized shop will attract the right customers as well as remove the

Number

of

incidents

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precipitator of crime from the shop. The right security tools are the most common solution, but

still a lot of shops lack the presence of a security guard or closed-circuit televisions. This can be

explained due to the extra costs for the salary of the guard. A solution to this problem can be the

hiring of a security guard as part-time only for the months of the year where the shop is busiest.

(Supply, 2019).

To conclude, it has been shown that using environmental criminology the crime of shoplifting can

be approached in a new way using the patterns identified to minimize this crime. Continuing this

research using data from other countries would be interesting in order to check the validity of

the result, even though the results of the current study provided solid empirical data.

Consequently, shop managers can benefit from this study, using the preventive techniques

presented to minimize this crime.

References

• BBC News. (2019). Shoplifters and a law that doesn't deter them. [online] Available

at: https://www.bbc.co.uk/news/uk-45512468 [Accessed 3 Apr. 2019].

• Moore, R. (1984). Shoplifting in Middle America: Patterns and Motivational

Correlates. International Journal of Offender Therapy and Comparative Criminology,

28(1), pp.53-64.

• Moschis, G., Cox, D. and Kellaris, J. (2019). An Exploratory Study of Adolescent

Shoplifting Behavior. [online] Acrwebsite.org. Available at:

http://www.acrwebsite.org/search/view-conference-proceedings.aspx?Id=6757

[Accessed 3 Apr. 2019].

• Read Hayes, C. (2019). How Store Environments Affect Shoplifting Crime. [online]

LPM. Available at: https://losspreventionmedia.com/insider/shoplifting-organizedretail-crime/how-store-environments-affect-shoplifters-and-organized-retail-crime/

[Accessed 3 Apr. 2019].

• Cardone, C. and Hayes, R. (2012). Shoplifter Perceptions of Store Environments: An

Analysis of how Physical Cues in the Retail Interior Shape Shoplifter

Behavior. Journal of Applied Security Research, 7(1), pp.22-58.

• NASP. (2019). Shoplifting Statistics -. [online] Available at:

http://www.shopliftingprevention.org/what-we-do/learning-resourcecenter/statistics/ [Accessed 3 Apr. 2019].

• Wortley, R. and Townsley, M. (2017). Environmental criminology and crime analysis.

2nd ed.

• Mail Online. (2019). 'Tis the season to be light-fingered: Top ten shoplifted items

revealed as stores prepare for annual rush. [online] Available at:

https://www.dailymail.co.uk/news/article-2067976/Top-shoplifted-items-revealedstores-prepare-annual-rush.html [Accessed 3 Apr. 2019].

• tutor2u. (2019). Broken Windows Theory | Sociology | tutor2u. [online] Available at:

https://www.tutor2u.net/sociology/reference/broken-windows-theory-explained

[Accessed 3 Apr. 2019].

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• Supply, B. (2019). Shoplifting Prevention | Tips To Stop Shoplifting In Your Store.

[online] Pricegun.com. Available at: https://www.pricegun.com/shopliftingprevention/ [Accessed 3 Apr. 2019].

• Data.police.uk. (2019). Your download | data.police.uk. [online] Available at:

https://data.police.uk/data/fetch/79f4fe43-893a-495c-a0c5-e387d96cdb9d/

[Accessed 3 Apr. 2019].