The Impact of Organised Crime on Business

Nick Tilley

Jill Dando Institute of Crime Science

UCL

Background to the research/ key aims

• Research commissioned by the Home Office• Rationale

– concern about OC harms in local neighbourhoods

• Main aims– To develop a method of measuring the impact of OC on local

businesses in high crime communities– To pilot survey methods with a study of up to 400 businesses,

building on the Commercial Victimisation Survey questionnaire

• Key challenges– To formulate and operationalise a definition of OC– To identify ‘potential’ impacts of OC on business– To devise valid and reliable measurement instruments– To find a way of approaching businesses to talk about OC

Method

• Fieldwork in three contrasting sample neighbourhoods, where police believed organised crime to be significant

• All businesses identified through visual audit• Survey of businesses within the sample areas

– ‘Teach’ respondents working definition of OC:• ‘Any deliberate, co-operative criminal activity engaged in over a

sustained period by the same set of three or more collaborating individuals.’

– Ask respondents about wide range of types of crime, establishing if they thought any were ‘organised’

– Ask respondents about repeat patterns of incident and event similarities

• Elicit ‘community knowledge’ of organised crime patterns, through semi structured interviews with key local business leaders

• Canvass police intelligence on organised crime, gangs and business victimisation

Data source 1: The survey

• Representative sample of businesses (though not areas)• Indicators suggest high levels of reliability• Key queries over validity

– Do the business respondents remember the number and attributes of incidents accurately?

– In practice, do respondents use the researcher-specified definition of organised crime?

– Do respondents know whether the incidents they have experienced result from ‘organised’ crime?

– Are respondents willing to talk candidly about their own organised crime victimisation?

– Will respondents talk candidly about offers of illicit goods and their own participation in organised crime?

Data source 2: Police intelligence

• Informed by access to range of police sources of information: reported crime, community consultation, informants, offenders, detected offences.

• No indicators of reliability• No direct access to intelligence files• Key queries over validity

– How typical are the cases the police remember or focus on?– Do the police know about organised crime as understood for the

research purposes?– Do the police over-generalise from the extreme and dramatic?– Are the police sometimes deliberately misinformed?– Are police intelligence inferences from information warranted?– Do the police tell researchers what they really know?

Data source 3: Community intelligence

• Informed by informal liaisons with community members, not compromised by mistrust of police or reluctance to be candid with researchers

• No time or resource for detailed ethnography, capturing what is ‘known’

• Sources picked up opportunistically• No indicators of reliability• Key queries over validity

– Do the sources used by community informants have an accurate picture of organised crime, as understood in the research?

– Would well-informed community members tell researchers the truth as they see it?

– How likely is it that well-informed community members generalise from rather particular and dramatic events?

Main findings

• Businesses in high crime neighbourhoods experience extraordinarily high rates of crime

• Much of this crime involves repeat victimisation• There is little evidence that these businesses are

suffering substantial, serious organised crime• Businesses in high crime neighbourhoods are

frequently invited to participate in organised crime• Different high crime neighbourhoods furnish

different ‘chemistries’ for organised crime

Survey findings on victimisation patterns

Business perceptions of specific problems in their area: percentage of businesses stating the issue is a problem in their area

West

Midlands London East

Midlands All Crime general 69 64 72 69 Graffiti 32 29 65 44 Vandalism 41 39 38 39 Stolen goods 54 60 55 56 Young people hanging around 59 53 41 50 Drugs 60 46 37 47 Gun crime 44 23 28 31 Money laundering 9 20 19 16 Racial crime 24 24 25 24 Counterfeit goods 53 55 30 45 Protection 4 27 24 18 Prostitution 20 24 19 21 Base: All 420 businesses

OC survey and CVS crime prevalence per 100 retail premises with nine or fewer staff

OC survey%

CVS%

Customer theft 62 36

Intimidation 27 14

Vandalism 23 18

Outsider fraud 18 13

Burglary 15 13

Employee theft 9 4

Theft of vehicles 5 2

Robbery (including attempts) 4 4

Outsider theft 3 7

Employee fraud 0 4

Offered stolen goods 35 12

Base: OC=175; CVS=2,738

Risk increases with numbers of incidents

Burglary External fraud

Premises robbery

Vehicle theft

Customer violence

Outsider violence

% % % % % %

At least once (N=420)

20 19 5 5 9 2

Of those at least once, percent victimised at last twice

40 70 23 26 61 60

Of those at least twice, per cent victimised at least three times

48 76 20 67 68 50

Of those at least three times, per cent victimised at least four times

63 64 0 50 53 0

Of those at least four Times, per cent victimised at least five times

60 93 0 0 75 0

Base: All 420 businesses

Victim beliefs about whether or not incidents experienced resulted from organised crime

Prevalence% (n)

Yes%

Don't know

%

No%

Shop theft 42 (178) 31 15 54

Vandalism 30 (128) 13 18 70

Intimidation 30 (125) 13 12 75

Graffiti 25 (103) 11 19 70

Burglary 20 (82) 39 22 39

Outsider fraud 19 (78) 37 33 29

Violence 10 (44) 14 11 75

Employee theft 8 (32) 6 6 88

Robberies 7 (29) 41 21 38

Vehicle theft 5 (23) 13 43 43

Outsider theft 3 (13) 15 8 77

Extortion 1 (4) 100 0 0Base: All 420 businesses

Main grounds survey respondents gave for believing crime to be organised

• Just a hunch

• The MO used

• Series of events

• Known/observed offenders

Estimates for evidence-based prevalence of organised crime

Percentage of total sample where offence experienced AND it is believed to be organised AND there were grounds stronger than a hunch

Percentage of total sample where there were repeat incidents AND it was believed that there were linkages between incidents AND there were grounds stronger than a hunch

Shop theft 11 14

Burglary 5 3

Outsider fraud 2 5

Vandalism 2 6

Graffiti 2 5

Variations in business vulnerability to organised crime

• By size

• By sector

• By area

0

5

10

15

20

25

30

35

40

45

50

0-2 (n=99) 3-9 (n= 252) 10+ (n=68) Total (n=419)

Number of workers and per cent prevalence of organised crime

0

5

10

15

20

25

30

35

40

45

50

Retail food/alcohol/newsagents (n=56)

Pubs/hotels/restaurants(n=71)

Retail non-food (n=149)

Not retail (n=141) Total (N=417)

Sector and per cent prevalence of organised crime

West Midlands

%London

%

East Midlands

%

Shop-theft 15 16 9

Burglary 10 8 6

Outsider Fraud 4 9 8

Intimidation 2 2 6

Vandalism 3 2 6

Graffiti 2 3 3

Robbery 3 4 2

Violence 2 0 3

Any Organised 31 (n=40) 34 (n=45) 36 (n=48)

Base: All 420 businesses

Area percentages of businesses experiencing any organised incident

Invitations to participate

• Receive smuggled alcohol– Each business received on average 0.6 offers– Each business receiving at least one offer received on average 12

of them• Receive stolen goods

– Each business received on average 12 offers– Each business receiving at least one offer received on average 36

of them• Receive smuggled tobacco

– Each business received on average 12 offers– Each business receiving at least one offer received on average 74

of them• Receive counterfeit goods

– Each business received on average 37 offers– Each business receiving at least one offer received on average 85

of them

Qualitative findings on neighbourhoods and organised

crime

Neighbourhood organised crime and data sources

• The survey turned up less organised crime against businesses than expected

• The police, and some members of e community, believed the areas to be ones where organised crime was thriving– The businesses might not have recognised the

organised crime affecting them– The businesses may not have been candid about the

organised crime they knew they were suffering– The impressions of organised crime may have been

derived from prominent but quite rare events– The organised crime in the areas may not have local

businesses as its main target

Variations in organised ‘crime chemistries’ in the three areas

• What locally brought suitable organised crime victims and likely offenders together in the absence of protection of the former from the latter through ‘capable guardianship’.

• What local ‘props’ were available to help commit or prevent organised crime: for example camouflage enabling the offender to escape notice

• What local ‘audiences’ were present to persuade or dissuade organised criminal behaviour by the likely offender?

The organised crime ‘chemistries’ appeared to vary by area

• East Midlands– White working class– Established crime families– Intimidation and collaboration with businesses

• West Midlands– Transitional area with changing ethnic composition– Loosely-knit ‘gangs’ committing crimes for status– High turnover of businesses, some used for crime some driven

out by it• London

– Middle-Eastern population, businesses and community organisations, with links back to countries of origin

– Community organisations fronts for organised crime– Some pressure on businesses to collude and contribute

Conclusions

• The methods we used were the best in practice that we were able to come up with

• The findings from the three data sources do not in all cases sit easily with one another

• The survey findings appear to be reliable, though their validity is uncertain

• The survey findings are, we think, plausible and provide an alternative to professional and community impressions

• The professional/community views provide, however, a plausible but hard-to-test theory explaining different ways in which organised crime is produced and sustained in some high crime neighbourhoods.

• Some perceived benefits as well as harms to the local community were associated with organised crime