i
THE EFFECTS OF CRIME PREVENTION ON SMALL AND
MEDIUM BUSINESS ENTERPRISES:
A CASE OF ILALA MUNICIPALITY, DAR-ES-SALAAM
By
Mohamed Ally Salum
A Dissertation Submitted to Dar Es Salaam Campus College in Partial
Fulfillment for the Requirements of the Award of the Degree of Master of
Business Administration in Corporate Management of Mzumbe University,
Tanzania
2019
i
CERTIFICATION
We, the undersigned, certify that we have read and hereby recommend for acceptance
by the Mzumbe University, a research report entitled “The Effects of Crime
Prevention on Small and Medium Business Enterprises: A Case of Ilala
Municipality, Dar-Es-Salaam”, in partial fulfillment of the requirement for the
award of a degree of Master of Business Administration in Corporate Management of
Mzumbe University, Tanzania.
____________________________
Major Supervisor
_____________________________
Internal Examiner
______________________________
External Examiner
Accepted by the Board of MUDCC
_________________________________________________
PRINCIPAL, DAR ES SALAAM CAMPUS COLLEGE
ii
DECLARATION AND COPYRIGHT
I, Mohamed Ally Salum, declare that this research report is my original work and it
has not been presented and will not be presented to any other university for a similar
or any other degree award.
Signature ___________________
Date: _______________________
© 2019
This research report is a copyright material protected under the Berne Convention, the
Copyright Act 1999 and other international and national enactments on their behalf,
on intellectual property. It cannot be duplicated by any means in full or in part except
for short extracts in fair dealings, for research or private study, critical scholarly review
or discourse with an acknowledgment, without the written permission of Mzumbe
University, on behalf of the author.
iii
ACKNOWLEDGMENTS
I iiam iithankful iito iiall iiindividuals iiwho iicontributed iiin iithe iiachievement iiof
this iistudy. I iiwould iilike iito iipraise iiGod iifor iiwhom iihe iimade iieverything
possible. I iiam iithankful iito iimy iisupervisor Dr. Kanty iiP.Feksi Mtey, for iithe
tirelessly iiencouragement iiand iiadvice iithat iiI iiobtained iifrom iihim, which iihas
contributed iifor iithe iiaccomplishment iiof imyiithesis iiwriting.
Correspondingly, iiI iiexpress iiappreciation iito iithe Small Medium Entrepreneurs of
Ilala Municipality and Police officer of Ilala Police Centreiifortheir iitime iiand
iicooperation iithroughout iiall iiperiod iiof iistudy iiand iiduringdataicollection.
Last iibut iinot ileast; I iilike iito acknowledge iimy wife Edna Kadogoifor supporting
iime iimorally, financially and spiritually iithroughout iiaccomplishment of iithis
iidissertation iiand iimy life in general.
iv
DEDICATION
Thisiidissertationiisidevoted to imy beloved wife Edna Kadogoiforiher kindness,
devotion, love, patience andiendlessimoral and material isupport.
v
LIST iiOF iiABBREVIATIONS
CPTED - Crime Prevention through Environmental Design
SIDP - Sustainable Industrial Development Policy
SMBs - Small Medium Sized Businesses
SMEs - Small Medium Sized Enterprises
URT - United Republic of Tanzania
vi
ABSTRACT
The study was set to investigate the effect of crime prevention on the growth of SMEs
at Ilala Municipality.In approaching these research questions, the researcher used two
set of well-prepared structured questionnaires and interview guide questions to obtain
the study results. Data were collected and analyzed by descriptive analysis and
correlation analysis technique while considering a sample size of 92 SMEs owners and
48 police officers of Ilala Police Centre.
The study revealed that the direction relationships among the identified variables are
positively correlated. Therefore findings of the study entail that there is a strong
relationship between crime preventation and the growth of SMEs. With respect to the
types of crimes affecting SMEs at Ilala Municipality, the study also revealed that
among the crime types include but not limited to all burglary, vandalism, cyber crime,
all fraud, all theft, and assaults and threats. The study further revealed that theft as the
type of crime was found to be mostly regularly reported by SMEs owners at Ilala Police
Centre, while the least type of crimes reported at Ilala Police centre were assaults and
threats.
The study also concludes that among the strategies for crime prevention towards SMEs
that were used by the SMEs owners of Ilala Municipality include surveillance cameras,
burglar alarms, use of locks, key control, keeping minimal cash on hand and security
guards or guard dogs. It was discovered that the among these strategies, security guards
or guard dogs strategy was found to be the most effective strategies to prevent my
business from criminals. The study uncovered that crime prevention contributes on
the growth of SMEs in terms of enhancing safety of customers, enhancing confidence
in business, minimizing robbery and burglary risk, minimizing fraud risk and
minimizing the theft risk.
The study suggests that another study need to be conducted while focusing on
exploring the extent to which crime prevention has an impact towards the entire
community.
vii
TABLE OF CONTENTS
CERTIFICATION .................................................................................................. i
DECLARATION AND COPYRIGHT ................................................................. ii
ACKNOWLEDGMENT ....................................................................................... iii
DEDICATION ...................................................................................................... iv
LIST OF ABBREVIATIONS .................................................................................v
ABSTRACT .......................................................................................................... vi
LIST OF TABLES ............................................................................................... xii
LIST OF FIGURES ............................................................................................ xiii
CHAPTER ONE .....................................................................................................1
INTRODUCTION ..................................................................................................1
1.1 Background iiInformation ...................................................................................1
1.2 Statement of the problem ....................................................................................5
1.3 Objective of the study .........................................................................................7
1.3.1General Objectives ............................................................................................8
1.3.2Specific Objectives............................................................................................8
1.4Research Question ...............................................................................................8
1.5Significance of the study ......................................................................................9
1.6Scope of the Study ...............................................................................................9
1.7 Limitation of the study ........................................................................................9
CHAPTER TWO .................................................................................................. 11
LITERATURE REVIEW ..................................................................................... 11
2.1 Introduction ...................................................................................................... 11
2.2 Definition of Key Concepts ............................................................................... 11
2.2.1 Crime ............................................................................................................. 11
2.2.2 Prevention ...................................................................................................... 12
2.2.3 Crime Prevention ........................................................................................... 12
2.2.4Crime Prevention and Safety for Businesses .................................................... 12
2.2.5 Business ......................................................................................................... 13
viii
2.2.6 Small Business ............................................................................................... 13
2.2.7 Medium Business ........................................................................................... 14
2.2.8 Small and Medium Sized Businesses (SMBs)/ Small and Medium-Sized
Enterprises (SMEs) ..................................................................................... 14
2.3 Conceptual understanding of the crimes in Small and Medium Businesses ........ 15
2.3.1 Conceptual meaning of crimes ....................................................................... 15
2.3.2 Causes of Crimes ........................................................................................... 15
2.3.3 Crimes offences in Tanzania .......................................................................... 15
2.4 Theoretical Review ........................................................................................... 17
2.4.1 Routine Activity Theory ................................................................................. 17
2.4.2 Crime Pattern Theory ..................................................................................... 18
2.4.3 Rational Choice Theory .................................................................................. 18
2.5 Empirical Review of Previous Studies ............................................................... 19
2.5.1 Empirical review of studies on the forms of crime prevalent to small and medium
enterprises. .................................................................................................. 19
2.5.2 Empirical review of studies on the strategies for crime prevention in small and
medium business enterprises........................................................................ 21
2.5.3 Empirical review of studies on the contributions of crime prevention in the
growth of small and medium business enterprises. ....................................... 22
2.5.4 Empirical review of studies on the role of stakeholders in the prevention of crime
in business enterprises. .................................. Error! Bookmark not defined.
2.6 Chapter Summary ............................................................................................. 28
2.7 Research Gap .................................................................................................... 28
CHAPTER THREE .............................................................................................. 30
RESEARCH METHODOLOGY ......................................................................... 30
3.1 Introduction ...................................................................................................... 30
3.2 Research Design................................................................................................ 30
3.3 Area of Study .................................................................................................... 30
3.3.1Map of the study area ...................................................................................... 31
3.4. Study Population .............................................................................................. 32
ix
3.5Sampling unit ..................................................................................................... 32
3.6Sampling frame .................................................................................................. 32
3.7Sample size of the study ..................................................................................... 32
3.8Sampling techniques and procedures .................................................................. 34
3.8.1Probability sampling technique ....................................................................... 34
3.8.1.1 Simple random sampling technique ............................................................. 35
3.8.2Non-probability iisampling iitechnique............................................................ 35
3.8.2.1 Purposive sampling technique ..................................................................... 35
3.9Description of variable and their measurement approach and scales ................... 36
3.9.1Measurement of variables ................................................................................ 36
3.10Sources of data ................................................................................................. 38
3.10.1 Primary data sources ................................................................................... 38
3.10.2 Secondary data source ................................................................................. 38
3.11Data collection methods ................................................................................... 38
3.11.1 Questionnaire .............................................................................................. 39
3.11.2 Interview ..................................................................................................... 39
3.12Reliability and validity of data.......................................................................... 39
3.12.1Reliability ..................................................................................................... 39
3.12.2Validity 40
3.13Analysis and management of data .................................................................... 40
3.13.1 Assumption for Correlation analysis ............................................................. 41
3.13.2Qualitative iidata iianalysis ........................................................................... 42
3.14 Ethical Consideration ...................................................................................... 42
CHAPTER FOUR................................................................................................. 43
DATA PRESENTATION, ANALYSIS AND DISCUSSION .............................. 43
4.1.Introduction ...................................................................................................... 43
4.2Demographic characteristics of the respondents ................................................. 43
4.2.1Demographic characteristics of the respondents (SMEs owners from Ilala
Municipality)............................................................................................... 45
4.2.1.1 Age of respondents ...................................................................................... 45
x
4.2.1.2 Gender status of respondents ....................................................................... 45
4.2.1.3 Business experience .................................................................................... 45
4.2.1.4 Education levels of the respondents ............................................................. 45
4.2.2Demographic characteristics of the respondents (Police officers at Ilala Police
Centre) ........................................................................................................ 46
4.2.2.1 Age of respondents ...................................................................................... 46
4.2.2.2 Gender status of respondents ....................................................................... 46
4.2.2.3 Departments where the respondents belong ................................................. 46
4.3Findings iiby iispecific iiresearch iiquestions ..................................................... 46
4.3.1Response iion iithe iirelationship iibetween crime prevention iiand the growth
of SMEs ...................................................................................................... 46
4.3.2Response on the types of crimes affecting small and medium businesses at Ilala
Municipality ................................................................................................ 51
4.3.2.1 Response on type of crimes that are regularly reported at Ilala Police centre by
SMEs owners .............................................................................................. 52
4.3.3Response on the strategies for crime prevention towards SMEs ....................... 56
4.3.4Response on the contribution of crime preventation on the growth of SMEs .... 59
CHAPTER FIVE .................................................................................................. 62
SUMMARY, CONCLUSION AND RECOMMENDATIONS ........................... 62
6.1 Introduction ...................................................................................................... 62
6.2Summary of the findings based on the research questions ................................... 62
6.2.1 Summary of the findings based on the the relationship between crime
prevention and the growth of SMEs ............................................................. 62
6.2.2 Summary of the findings based on the the types of crimes affecting small and
medium businesses ...................................................................................... 62
6.2.3 Summary of the findings based on the on the strategies for crime prevention
towards SMEs ............................................................................................. 63
6.2.3 Summary of the findings based on the the contribution of crime preventation
on the growth of SMEs ................................................................................ 63
6.3Conclusion of the study ...................................................................................... 63
xi
6.4Recommendations of the study ........................................................................... 64
6.4.1Recommendations to the management of Ilala Police centre ............................ 64
6.4.2Recommendations for further research ............................................................ 65
REFERENCES ..................................................................................................... 67
APPENDICES ....................................................................................................... 72
xii
LIST OF TABLES
Table 1.1 Categories of SMEs in Tanzania ................................................................4
Table 3.1: Determination of sample size for SMEs owners from IIlala Municipality,
Officials from the Business Department of the Ilala District Council and Police
officers from Ilala Police Centre .................................................................. 33
Table 3.2: Sample size for for SMEs owners from IIlala Municipality, Officials from
the Business Department of the Ilala District Council and Police officers from
Ilala Police Centre ....................................................................................... 34
Table 3.3 Explaination for the variables, dimensions and data source ...................... 37
Table 4.1: Characteristics of the respondents .......................................................... 44
Table 4.2 Descriptive statistics ................................................................................ 47
Table 4.3 Correlations ........................................................................................... 49
Table 4.4 Descriptive statistics ................................................................................ 56
Table 4.5 Descriptive statistics ................................................................................ 59
xiii
LIST OF FIGURES
Figure 2.1 Conceptual framework ........................................................................... 27
Figure 2.1 Conceptual framework ........................................................................... 27
Figure 3.1 Map of the study area ............................................................................ 31
Figure 4.1 Response on the extent of types of crimes affecting the growth of SMEs at
Ilala Municipality ........................................................................................ 51
Figure 4.2 Response on type of crimes that are regularly reported at Ilala Police centre
by SMEs owners ......................................................................................... 53
1
CHAPTER ONE
INTRODUCTION
1.1 iiBackground iiInformation
Crime prevention is regarded as an attempt to reduce and deter crime and criminals in
general. It is applied specifically to efforts made by governments to reduce crime,
enforce the law and maintain criminal justice. Crime occur among communities caused
by reasons such as; an individual or group having the desire or motivation to participate
in a banned or prohibited behaviour; at least some of the participants must have the
skills and tools needed to commit the crimes and an opportunity must be acted upon
(Felson & Boba, 2010).
Bressler (2009) identified list of types of crime that might commited towards SMEs
which include but not limited to; theft, or “skimming” of cash, theft of inventory,
merchandise or equipment, writing company checks, falsifying revenue reports,
processing fraudulent invoices, customer identity theft, money laundering, intellectual
property theft, credit card fraud, overstated expense reports, and payroll fraud. It was
also highlighted some of the more common crimes committed against businesses
including vandalism, shoplifting, and theft. Today, however, more businesses fall
victim to attack through computer systems. These “hack-attacks” may take the form
of sabotage, customer identity theft, or theft of funds.
Hendrickson i(2019)idetermined ithe ilist iof icrimes ithat ican ibe icommitted iin ibusinesses
ias ion iany istate’s icode, iso iit imay ibe ihelpful ito ibreak ithose icrimes idown iinto ithree
icategories iof iwho icommits ithe icrime: iemployees; inon-employees iwhich iincludes
icustomers iand iothers iwho icome iinto ibusiness; iand iCybercriminals ipeople iwho isteal
ifrom ior idamage ia ibusiness. i iiThe iGuidelines ifor ithe iPrevention iof iCrime iECOSOC
iResolution i2002/13, iAnnex iidentifies ithat iCrime iPrevention icomprises istrategies iand
imeasures ithat iseek ito ireduce ithe irisk iof icrimes ioccurring, iand itheir ipotential iharmful
ieffects ion iindividuals iand isociety, iincluding ifear iof icrime, iby iintervening ito iinfluence
2
itheir imultiple icauses.
The iUnited iNations iOffice ion iDrugs iand iCrime i(UNODC)(2003)determined ithat
iCrime iprevention iis ia imulti-sectoral, imulti-disciplinary, iand iintegrated iendeavour.
iThis ineeds iefforts ito iaddress ithe iproblem. iMoreover, iUNODC iclearly istates ithat ithere
iis ia iclear ievidence ithat iwell-planned icrime iprevention istrategies inot ionly iprevent
icrime iand ivictimization, ibut ialso ipromote icommunity isafety iand icontribute ito
isustainable idevelopment iof icountries. iThis itechnically imeans ithat ieffective iand
iresponsible icrime iprevention ienhances ithe iquality iof ilife iof iall icitizens iby iproviding
ilong-term ibenefits ithrough ireduction iof icosts iassociated iby iformal icriminal ijustice
isystem, ias iwell ias iother isocial icosts ithat iresult ifrom icrime i(Economic iand iSocial
iCouncil iresolution, i2002/13). i
Moreover, iemployees iare iin iposition ito isteal iboth imoney iand imerchandise ibecause iin
ismall iand imedium ibusiness isome iemployees ihandle imoney idirectly ican iunder-charge
ia icustomer ior inot iring iup ia isale iand ipocket ithe icash, icrimes icommitted iin ithis icategory
iare iembezzlement i– ian iemployee idiverting imoney ifrom ia ibusiness iaccount, iLapping i–
iform iof iembezzlement iin iwhich iemployee iskims imoney iwhen itaking imoney ifrom ithe
ipay ioff ianother. iThis icrime ican ibe iprevented iby ihiring iresponsible iand itrustworthy
ipeople, ichecking ievery iapplicant’s ireferences, iestablishing irules iand iprocedures ithat
ireduce ithe iopportunities ifor ithe itheft, iperforming iregular iaudits ifor iemployees iwho
iwork iwith iinvoices, ireceipts iand ipayroll. iCrimes icommitted iby inon-employees,
ishoplifting iare ithe ibiggest iconcern iand ibiggest iproblem ifor imost ismall-business
iowners i(Hendrickson, i2017). i
Shoplifters icome iin iall iraces iand iall iages, ithey imay istuff iitems iinto ipockets, ipurses,
ibaby icarriages ior ibags, iburglary. iThis icrimes ican ibe iprevented iby ieyes ideter itheft,
iinstalling isurveillance icameras ior imirrors, ito iprevent iburglary iphysically iprotect iyour
ibusiness, iinstalling imore ithan ione ilock iand iuse ideadbolt ilocks iwhen ipossible. i
iiCybercrime iwhen ismall iand imedium ibusiness iis ilinked ito icomputer ito ikeep irecords,
ilike itheft, ifraud, ihackers imay isteal icustomer ilist ior icredit iinformation iand iviruses ican
iinfect ifiles icausing irandom ibut iexpensive ihavoc. iTo iprevent ithese icries iis ito iinstall
3
istrong, ipassword- iprotected ifirewalls iand ianti-virus isoftware, iupdating iand ikeeping
iback-up icopies ifor ibusiness irecords ion ia iseparate istorage idevice ilastly imonitor
iemployees iwho ihave iaccess ito icompany iinformation i(U.S. iBureau iof iJustice
iStatistics, i2005).
The critical link between crimes and SMEs was observed by different number of
scholars for example Motta (2017) contended that despite of the fact that Small and
medium-sized enterprises (SMEs) are in the forefront of economic policy in
developing economies, playing critical role in local economic growth and
development, yet SMEs tend to serve local rather than global markets. However,
several obstacles prevent greater participation of SMEs in the economy. Among them,
crime is a major issue that negatively affects local development in developing
countries, as robbery, theft, vandalism and arson increase the cost of doing business.
It was further uncovered by Islam (2014) that criminials are targeting SMEs in a
growing number of ways, however crimes may also retard the growth and performance
of the SMEs. From the results, it was revealed that business has adopted many
strategies of countering crimes. This including closing the business early and dashing
for safety, confirmed intelligence information and passing it over to the security
organs.
The irise iof ithe iurban iinformal isector iin iAfrica iis iparticularly iassociated iwith ithe
ipostcolonial iperiod, iwhen irapid iurbanisation itended inot ito ibe iaccompanied iby
iconcomitant igrowth iin iurban iformal ieconomies. i
The iurban ipeople iadopted idiverse iself-help iinitiatives ito icreate iemployment iand
iincomes. iHowever, iboth irapid iurbanisation iand ithis ientrepreneurial iresponse ihave
itheir iroots iin ithe ilate-colonial iperiod. iFor iexample, ithe iplanned isolution ito iwhat iwas
iseen ias ithe iproblem iof iurban igrowth iwas ito iattempt ito ilimit iit. iRestricted inumbers iof
imore iskilled iemployees i– ibeing ipaid isalaries iwhich iwere ifor ithe ifirst itime ihigh ienough
ito imake ipermanent iurban iresidence ian ioption i– iwere ito ireplace iscores ifind iigneous
iand itemporary imigrant ilabourers. iSuch ithinking iplainly ifailed ito iaddress iwhat iwas
4
ievident iin itowns iand icities ithroughout ithe icontinent, ithat iever-growing inumbers iof
ipeople iwere iopting ito imove ito ithe iurban iareas. iBy iso idoing, ithese imigrants iflagrantly
icontradicted icolonial ischemes iaimed iat irestricting iurban igrowth i(Mfaume i& iLeonard,
i2004). i
Faced iwith iwhat iwas ioften icontracting iemployment iin ithe iformal isector, ithese
imigrants iturned ito ithe iinformal ieconomy ito iget iby, iin icontravention iof iboth imunicipal
iby- ilaws iand ithe icolonial iideals iof ia irestricted iurban iAfrican iclass iengaged iin
iprivileged iformal iemployment. iFaced iwith ithe iunruly iingenuity iof itheir isubject
ipopulations, icolonial iauthorities ivainly iattempted ito ienforce itheir iurban ivision
ithrough ithe icriminalisation iof ithe iinformal isector, iand ithe ilater icolonial iperiod iwas
icharacterised iby iperiodic icampaigns iin iwhich iMunicipal iAdministrations ivainly
iattempted ito iclean ithe istreets iof iunsightly ivendors iand ihawkers. iDespite ithe imanifest
iinadequacy iof isuch ia ipolicy, ithose iAfrican iofficials iwho iassumed iresponsibility ifor
ithe iadministration iof iurban icentres iafter iindependence imaintained ithis iapproach. i iiIt iis
icomparatively irecently ithat ithose ipolicies, ithat iare imore itolerant iof iinformal ieconomic
iactivities, ihave ibeen iadopted iin isub-Saharan iAfrica i(Hendrickson, i2017). i
In iTanzania, iDar ies iSalaam iin iparticular, ithe iquestion iof ismall ibusiness iespecially
iitinerant itrading iwere ievident ieven iduring icolonial iperiod. iHawking iand ipeddling
iwere, iaccording ito iLeslie i(1967) i‘the istandard iexpedients iof ithose iunable ito ifind ipaid
iemployment.’ iFew iof ithese ipetty itraders iwere ilicensed: i‘the icasual ipeddlers’,
iobserved iLeslie, i‘seldom ibother ito icomply iwith ithe ilaw.’ iDespite ithe iobvious
iinefficacy iof imunicipal ipolicy, ithe iattempt ito icontrol iitinerant itrading ithrough
irestricting ithe inumber iof ilicences ipersisted. iUnlicensed ihawkers icontinued ito ibe
iapprehended iand itaken ito icourt. iAccording ito iSmall iand iMedium iEnterprise
iDevelopment iPolicy, i2002 ithe iSmall iand iMedium iBusinesses iare icategories ias ifollow;
Table i1.1 iCategories iof iSMEs iin iTanzania
Category Employees Capital iInvestment iin iMachinery
i(Tshs.)
5
Micro ienterprise 1 i–4 i ii iUp to i5 imil
Small ienterprise i ii i 5 i–49 i iiAbove 5 imil. ito i200 imil. i
Medium ienterprise i ii 50 i–99 i iiAbove 200mil.to i800 imil. i
Source: iResearch iConstruction, i2019
In iIlala iDistrict, ismall iand imedium ibusiness ihas ibeen ioperating iin ithis idistrict ifor
idecades. iThe imunicipality, iwhich iaccounts ifor iabout i50% iof iall itaxes ipaid iin ithe
icountry, iis iTanzania’s ieconomic ipowerhouse. iIt ihosts ithe imajority iof ilarge iindustries
ias iever-growing inumbers iof imigrants iwere ientering ithe itownship iimany iof iwhom iwere
iresorting ito ipetty itrade ito iget iby iithe iMunicipal iCouncil ideliberately idecided ito ireduce
ithe iamount iof itrading ilicenses iavailable. iDrunkenness iand ihooliganism iwere, ias ia
iresult, ion ithe iincrease iespecially iamong ithe iyouths iof ithe isuburban iareas iwho
ipatronised iillegal i‘Tembo’ iclubs iand i‘Marijuana’ ito ia ivery ilarge iextent iMunicipal iand
idistrict iofficials iviewed iunlicensed istreet itrading ias ieither ia ipublic ihealth ithreat iand/or
ian iactivity iwhich iundermined ithe ilicensed iand icontrolled itrade iconducted iin ithe
iofficial imarkets i(Kilimyi, i2013).
It iis ihustle iand ibustle iof iIlala ithat ihas iattracted ithousands iof istreets ivendors iand
ihawkers ito iits iroads, ipavements iand iopen ispaces. iMany iyoung ipeople icome ifrom
ivillages ihoping ito ifind ijobs iin iurban iareas, ibut iend iup iin ithe istreets, iselling ivarious
igoods. iThus ivending ibusiness ihas ibecome ithe ilargest iemployer iof iyouth inot ionly iin
iIlala ibut ialso iin iother imunicipalities iin iDar ies iSalaam. iAlso ithere ihave ibeen iattempts
ito idesignate ispecial iareas ifor ismall iand imedium ibusinesses iwhich ihave ioften ibeen
ifutile ibecause imost iof ithem ihave ibeen irefusing ito imove icomplaining ithat ithe iareas iare
ifar ifrom icity icentre iand itherefore iinaccessible iby icustomers iand ithat ithey ilack iproper
iinfrastructures i(The iCitizen, i2017).
1.2 iiStatement of the problem
Crimes present challenges for the social and economic development of cities and towns
in which case crimes are viewed as real developmental problem. As per the
6
Constitution of the United Republic of Tanzania (1977) safety and security is
everyone’s right. In this concern, the constitution of the URT attaches a pronounced
significance to the safety and security of all persons. Moreover, Article 13 of the URT
constitution affirms that the equality of all persons before the law and guarantees their
entitlement, without discrimination to protection before the law.
In ithe icurrent iera, isecurity ichallenges ifrom ithe icrimes icommitted ibecome imore
icomplex ito idevelopment iissues iespecially ibusinesses. iNevertheless, ipolicies iin ithe
iURT iprovide iguidance ion icrime iprevention ito iensure ithat ipeople iand ibusiness iare
iprevented ifrom icritical iand ithreatening isituations ifor isustainable ienvironment iof
idevelopment iin ithe icountry. iThese iare isuch ias iTanzania iDevelopment iVision i2025,
iNational iStrategy ifor iGrowth iand iReduction iof iPoverty, iNational iGender iPolicy iof
i1999, ithe iNational iEnvironmental iPolicy iof i1997, iand ithe iNational iHuman
iSettlements iDevelopment iPolicy i(NHSDP) iof i2000. iIn iits icontext, ithe iLocal
igovernment iauthorities iand iother istakeholders ihave ia iresponsibility ito iimplement iall
iof ithe ipolicies.
The statistics in the Crime and Inquest registrer at Ilala Police Station by August 2019
showed that between February 2016 and June 2018 there were over 400 criminal cases
reported compare to the year between 2013 to 2015 whereby there were about 298
cases were reported at Ilala Police Station. These criminal cases were indicated to have
been reported by to SMEs owners of Ilala Municipal Council. Following the given
statistical report data, this indicates that the crime had been increasing from is year to
year, thus posed a need effective crime prevention.
Mfaume and Leonard (2004) discovered thatin Tanzania, entry into small business
entrepreneurship is usually not seen as a problem. One can start small business at any
time and in any place. However, the development of this informal sector has been
profoundly characterized by the parallel increase in events suggesting prevalence of
crime and bureaucratic hurdles, which affect SME and counter reaction from the small
traders.
7
Upon ithe iimplementation iof isuch ipolicies and the existing crimes facing SMEs in
Tanzania, this has posed the need for crime prevention and to determined the extent in
which such crime prevention is adhered and whether there is effective implemention
of crime prevention towards the business environment of SMEs in Tanzania.
Therefore, ithis istudy iwill iexamine ithe ieffect iof icrime iprevention ion ismall iand imedium
ibusiness ienterprises iat iIlala iMunicipality. iIt iwill ispecifically; ianalyse ithe iforms iof
icrime iprevalent iin iSmall iand iMedium iBusinesses i(SMBs), iexamine ithe istrategies
iemployed ifor icrime iprevention iin iSMBs, ianalyse ithe icontributions iof icrime
iprevention, iand iexamine ithe irole iof istakeholders iinvolved iin ithe icrime iprevention ifor
iSMBs iin ithe istudy iarea.
1.3 Objective of the study
This iistudy iiconstitutes iiboth iimain iiand iispecific iiobjectives, iiwhich iiare iias
iifollows:
8
1.3.1 General Objectives
To investigate the effects of crime prevention against small and medium business
enterprises at Ilala Municipality, Dar-es-salaam.
1.3.2 Specific Objectives
(i) To determine the types of crimes affecting Small and Medium businesses in Ilala
Municipality.
(ii) To examine the relationship between crime prevention and the growth of Small
and Medium Enterprises.
(iii)To examine strategies for crime prevention in small and medium businesses in
Ilala Municipality.
(iv) To assess the contribution of crime prevention strategies in the growth of small
and medium businesses.
1.4 Research Question
The study will address the following research questions
(i) What are the types of crimes prevalent to small and medium businesses in Ilala
Municipality?
(ii) What is the relationship between crime prevention and the growth of Small and
Medium Enterprises?
(iii)What are strategies for crime prevention in small and medium businesses?
(iv) What are the contributions of crime prevention strategies in the growth of small
and medium businesses enterprises?
9
1.5 Significance of the study
The study serves as a reference to future research, which relate to a problem in
examining the effects of crime prevention in small and medium businesses at Ilala
Municipal, Dar-es-salaam. This study would help small and medium businesses in
understanding common forms of crime that are affecting their businesses as well as
understanding strategies for crime prevention, and measure and understand well roles
of stakeholders including the government and SMEs owners in move of crime
prevention.The Ilala Police station may use the findings of the study to come up with
the strategies that may help the SMEs of Ilala Municipality to safe guard their property.
The SMEs owners may use the findings of the study to come up with the strategies
that can help them counter crime at Ilala Municipality. The study may serve as
reference point for researchers who would be interested to conduct a study in the
similar subject matter.The study would also provide knowledge to the society, and
indicate their obligation on how they are supposed to participate in the presentation of
crimes.
1.6 Scope of the Study
The istudy iwas iconducted iat iIlala iDistrict, iDar ies isalaam iwhich icover i365 ikm2, idensity
i3,344/km2 iand ihas i3 idivisions iand i23 iwards, ithe iwards iare; iBuguruni, iChanika,
iGerezani, iIlala, iJangwani, iKariakoo, iKinyerezi, iKipawa, iKitunda, iKisutu, iKivukoni,
iKiwalani, iMchafukoge, iMchikichini, iMsongola, iPugu, iSegerea, iTabata, iUkonga,
iUpanga iEast, iUpanga iWest, iVingunguti iand iBuyuni.
1.7 Limitation of the study
This istudy imight ibe ilimited iby iaccess ito isensitive idata iwhere ithere iis iother
iinformation, iwhich icannot imerely ibe idisclosed ito ithe ipublic ifor ithe ireason ithat ithey
iare iprepared ifor iforensic iand inational iinterests. iHowever, ia icareful ichoice iof
imethodology iwas iemployed ito icollect iall ithe irequired iinformation iwithout icausing
iany idisturbances ito ithe iestablished isystem. i
10
On ithe iother ihand, ithe istudy imight ibe ilimited iby iaccess ito irespondents idue ito ithe ifact
ithat ithey imight ibe ibusy iin itheir ibusinesses. iThe istudy iensured ithat ithe imethodology
ifor idata icollection iis iappropriate iin isuch iground ifor iacquiring ireliable idata.
i
11
CHAPTER TWO
LITERATURE REVIEW
2.1Introduction
This ipart ipresents ithe definitions of key concepts, iviews iof ischolarly irelated istudies ion
ithe ieffects iof icrime iprevention iin ismall iand imedium ibusinesses iby ifocusing ion ithe
itheories, iempirical ifindings, iconceptual imodels, imethodologies, iareas iconducted itheir
istudies iand ithe iinterpretation iof itheir iresults. iThe itheoretical iframework ientails ithe
isignificance iof itheories ito ithe iobjectives iof ithe istudy iwhile iconceptual iframework
ientails ithe igeneral iassociation iof ithe idependent iand iindependent ivariables iof ithis
istudy. iThe ichapter isums iup iby ipresenting ithe iconceptual iframework ifor ithe istudy.
2.2 Operation definitions of key concepts
2.2.1 Crime
According ito iCambridge iDictionary (2008) icrime imeans iany iviolation iof ilaw, ieither
idivine ior ihuman; ian iomission iof iduty icommanded ior ithe icommission iof ian iact
iforbidden iby ilaw. iOn ithe iother ihand, iCrime ican ibe idefined ias ian iact ior ithe icommission
iof ian iact ithat iis iforbidden ior ithat iis iagainst ithe ilaw iand ithat imakes ithe ioffender iliable
ito ipunishment iby ithat ilaw i(Merrian- iWebster. iCom, i2019). iThus, ia icrime iis iharmful
ibehaviour iof ian iindividual, icommunity, isociety ior ithe istate.According to Michael
(2014) crime can be defined as the desecration of criminal law that forms the basis of
application of formal penalties by various government authorities. In Tanzania, crime
is classied into two groups that include; serious offences that comprise of burglary,
robbery, rape, murder and arson. The second class is non-serious offences that
comprise of minor crimes.
12
2.2.2 Prevention
Cambridge iDictionary (2008)defines iprevention ias ithe iact iof istopping isomething ifrom
ihappening ior iof istopping isomeone ifrom idoing isomething. iFor ithis istudy ithe ifocus iis
icentred ion icrime iprevention. iPrevention iis ithe ifirst iimperative iof ijustice.
2.2.3 Crime Prevention
Means iattempt ito ireduce iand ideter icrime iand icriminals. iIt iis iapplied ito iefforts imade iby
igovernments ito ireduce icrime, ienforce ithe ilaw iand imaintain icriminal ijustice. iCrime
iprevention iis ia imulti-sectoral, imulti-disciplinary, iand iintegrated iendeavour i(Zaben,
i2004)
Crime iPrevention icomprises istrategies iand imeasures ithat iseek ito ireduce ithe irisk iof
icrimes ioccurring, iand itheir ipotential iharmful ieffects ion iindividuals iand isociety,
iincluding ifear iof icrime, iby iintervening ito iinfluence itheir imultiple icauses
2.2.4 Crime Prevention and Safety for Businesses
According to Crowe and Fennelly (2013) the appearance of a business can attract or
deter crimes of many natures. Some of the precautions are as follows;
2.2.4.1 Robbery iPrevention
While ipotential irobbers iare ideciding iwhether ito irob ithe istore, istore imanagers ior iclerks
ican ido ithings ithat irobbers ido inot ilike ior ithat ifrustrate itheir iintentions. iThe iidea iis ito
iunnerve ipotential irobbers.
2.2.4.2 Internal iTheft iPrecautions i
Internal itheft iis ia ipotential iproblem iin iany ibusiness. iMost iemployees, ilike ithe irest iof
isociety iare ihonest ihowever; istudies ifrequently icite iinternal itheft ias ia imajor icause ifor
ismall ibusiness ifailures. iSMEs iowners ican itake iprecautions ito iprevent istaff ifrom
istealing ifrom itheir iemployer
13
2.2.4.3 Commercial iSecurity iSurveys i
Burglary iPrevention iBusinesses ican ireduce itheir ivulnerability ito icrime iin imany iways.
iSecurity imeasures ilike iupdated ilocks, ilighting, iand ialarms ican imake iany
iestablishment ia iless iattractive itarget ifor icriminals
2.2.4.4 Business iAlarms
Business ipremise isecurity iis ione iof ithe imost iimportant iaspects iof ipracticing isound
icrime iprevention itactics. iBurglary iis ia ibig ibusiness iand ito ihelp iprevent iit, igood
ilocking, ilighting iand ialarm isystems iplay ia icrucial irole iin iprotecting ithe ibusiness’
iassets.
2.2.4.5 Vandalism iPrevention i
Again icustomers ishoulder imost iof ithe iburden iof ithis icrime ias ibusinesses ipass ia iportion
iof ithe icosts iof ivandalism ion ito icustomers ithrough ihigher iprices. iMost ivandals iare
iyoung ipeople i- ifrom igrade ischool istudents ito iyoung iadults.
2.2.5 Business
Macmillan iDictionary (2008) idefines ibusiness ias ian iactivity iof imaking ione’s iliving ior
imaking imoney iby iproducing ior ibuying iand iselling iproducts i(such ias igoods iand
iservices). iSimply iit iis iany iactivity ior ienterprise ientered iinto ifor iprofit. iIt idoes inot imean
iit iis ia icompany ior icorporation, ipartnership ior ihave iany isuch iformal iorganization, ibut iit
ican irange ifrom ia istreet ipeddler ito igeneral imotors.
2.2.6 Small Business
There is no universally accepted definition of SME. Different countries define SME
differently depending on their level of development. However, the commonly used
criteria in the definition include the total number of employees, the total investment
and sales turnover.
14
These iare ibusiness iprivately iowned icorporations, ipartnerships ior isole iproprietorships
ithat ihave ifewer iemployees iand ior iless iannual irevenue ithat ia iregular-sized ibusiness ior
icorporation. iBusinesses iare idefined ias ismall iin iterms iof ibeing iable ito iapply ifor
igovernment isupport iand iquality ifor ipreferential itax ipolicy ivaries idepending ion ithe
icountry iand iindustry. iSmall ibusiness iincludes iretail ioperations isuch ias iconvenience
istores, ismall igrocery istores, ibakeries ior idelicatessens, ihairdressers ior itradespeople
i(example icarpenters, ielectricians), irestaurants, iguest ihouses, iphotographers, ivery
ismall-scale imanufacturing iand iinternet-related ibusinesses isuch ias iweb idesign iand
icomputer iprogramming. iSmall ibusiness ivary iin iterms iof isize, irevenues iand iregulatory
iauthorization iboth iwithin ia icountry iand ifrom icountry ito icountry i(Kushnir, i2010)
2.2.7 Medium Business
This iis ioften ithe iawkward imiddle ichild iof iits iindustry i– itoo ilarge ito iget ithe idiscounts
iand iservices iafforded ito ismall ibusinesses iand itoo ismall ito ihave ithe iweight iand iprestige
igranted ito ilarge ienterprises. iThere iare iparameters ineeded ito ibe iconsidering ibefore
iclassifying ithe isize iof ithe ibusiness ior icompany iwhich iare inumber iof iemployees iad
irevenues ithey ihave. i(Petrakis&Kostis, i2012)
2.2.8 Small and Medium Sized Businesses (SMBs)/ Small and Medium-Sized
Enterprises (SMEs)
The Tanzanian Government defines SMEs according to sector, employment size, and
capital invested in machinery. Accordingly, in the context of Tanzania SMEs are
defined as micro, small and medium size enterprises in non-farm activities, which
include manufacturing, mining, commerce and services. A micro enterprise is defined
as a firm with fewer than five employees whereas a small firm is a firm with 5 to 49
employees, a medium enterprises is a firm with 50 to 99 employees.
The iSMEs inomenclature iis iused ito imean imicro, ismall iand imedium ienterprises. iIt iis
isometimes ireferred ito ias imicro, ismall iand imedium ienterprises i(SMEs). iThe iSMEs
icover inon i-farm ieconomic iactivities imainly imanufacturing, imining, icommerce iand
15
iservices. iThere iis ino iuniversally iaccepted idefinition iof iSME. iSMBs ioutnumber ilarge
icompanies iby iwide imargin iand ialso iemploy imany ipeople ifor iexample iin iAustralian
iSMBs imake iup i98% iof iall iAustralian ibusinesses, iproduce ione ithird iof itotal iGDP iand
iemploy i4.7 imillion ipeople. iSMBs iare iimportant ifor ieconomic iand isocial ireasons,
igiven isectors irole iin iemployment. i(Small iand iMedium iEnterprise iDevelopment
iPolicy, i2002).
2.3 Conceptual understanding of the crimes in Small and Medium Businesses
2.3.1 Conceptual meaning of crimes
Crimes iare iregarded ias iillegal iacts ifor iwhich isomeone ican ibe ipunished iby ithe
igovernment. iLegal iservices icommission iof iAustralia idefines icrime ias ian ioffence ithat
imerits icommunity icondemnation iand ipunishment, iusually iby iway iof ifine ior
iimprisonment. iThis iis idifferent ifrom ia icivil iwrong i(a itort), iwhich iis ian iaction iagainst
ian iindividual ithat irequires icompensation ior irestitution i(Law iHandbook, i2017).
2.3.2 Causes of Crimesi
The causes of crime are complex to determine depending on the nature of the
environment they occur. Among other causes these may be: - poverty, parental neglect,
low self-esteem, and alcohol and drug abuse. These among others can be connected as
to why people break the law. Sometimes it may happen that some are at greater risk of
becoming offenders because of the circumstances into which they are born. Therefore,
the environmental set up may contribute to the extent to which people commit crimes.
2.3.3 Crimes offences in Tanzania
Crime and Traffic Incidents Statistics Reports look at a whole range of criminal cases
that have been reported in Tanzania. Offences are of two types that is, major and minor
criminal and traffic offences. Criminal offences are further divided into three
categories, which are; offences against person, offences related to property and
offences against public tranquillity (TPF, 2019) For the sake of this study the
16
concentration is mainly focused on criminal offences. According the TPF report, the
commonly reported crimes, which affect the business operations, are regarded as
falling into the category of offences committed against persons and property.
Furthermore, According to the Crime and Traffic Incidents Statistics Report, (2015),
it was reported that the number of criminal offences reported in 2015 was 519,203,
compared with 528,575 that were reported in 2014. This was a decrease of 9,372
offences, which was equivalent to 1.8 percent. In regard to major criminal offences,
the police regions with large numbers of crimes are Kinondoni (8,804), Temeke
(5,848), Morogoro (4,210), Ilala (4,011) and Pwani (3,735). Police regions with a
small numbers of crimes are TAZARA (35), Wanamaji (70), Kusini Pemba (77) and
Reli (85).
The icauses iof icrime iin iDar ies iSalaam iand iits isub iregions iare imultiple iand itentative
ibecause iof ithe ion-going iglobal iphenomenon iin isocio-economic, ipolitical iand icultural
iactivities. iWith ithe iadvancement iof ithe iglobal itechnology iand icommunication isystem
ioriented iand ideveloped ithrough imarket ieconomy isystem, iTanzania, iand iDar ies
iSalaam iin iparticular, ihas icontinually ibeen ipart iof iinternational iurban icriminality
irooted ion iurban ipoverty, irural imigration, ienvironmental idegradation iscarcity iand
imismanagement iof iits ibasic isocial iservices iand iinfrastructures, iespecially ithe ipoor iand
ithe imarginalized imajority igroups. iAs inoted iearlier, iIlala iMunicipality iis ithe ibusiness
iheart iof ithe iDar ies iSalaam iregion iwhere ifor iits ipotentiality iit ibecomes iprone ito
icriminal ioffences.
The igovernment iof iTanzania ihas imade iin ipalace ia inumber iof iinitiatives ito ideal iwith
icrimes ioccurring iin ithe icountry iwhere iIlala iregion ias iamong ithe ilocalities iinvolved ican
ibe icovered. iAmong ithe iinitiatives iare ithe iintroduction iof ithe iCybercrimes iact iof i2015
iamid ithe iimprovement iof iother ilaws igoverning ithe icrimes ienvironment, iproviding
ieducation ito idifferent istakeholders ion ithe icrimes iprevention iissues. i
17
2.4 Theoretical Review
Theoretically there exists different approaches to crime prevention behind which the
desired results can be obtained after a variety of mechanisms are applied. The study is
escorted by three major theories; Routine activity Theory, Crime Pattern Theory, and
Rational Choice Theory. The theories are explained as follows;-
2.4.1 Routine Activity Theory
Routine activity theory, first formulated by Lawrence E. Cohen and Marcus Felson
(1979) and later developed by Felson, is one of the most widely cited and influential
theoretical constructs in the field of criminology and in crime science more broadly.
In contrast to theories of criminality, which are centered on the figure of the criminal
and the psychological, biological, or social factors that motivated the criminal act, the
focus of routine activity is the study of crime as an event, highlighting its relation to
space and time and emphasizing its ecological nature and the implications thereof.
Routine iactivities itheory iis ian ienvironmental, iplace‐based iexplanation iof icrime, iwhere
ithe ibehavioural ipatterns iand iintersections iof ipeople iin itime iand ispace iinfluence iwhen
iand iwhere icrimes ioccur. iRoutine iactivity itheory, ifrom iCohen iand iFelson i(1979),
iemphasizes ithat icrime ioccurs iwhen ithree ielements iconverge: ia imotivated ioffender, ia
isuitable itarget, iand ithe iabsence iof ia icapable iguardian. iThis itheory iincludes ithe iroutine
iactivities iof iboth ioffender iand ivictim. i
An ioffender imay iroutinely iwalk ithrough ispecific ineighbourhoods ilooking ifor ihomes
ithat iappear ias ieasy itargets ifor iburglary ior iinto ibuildings iin ia icommercial iarea ito iseek
iopportunities ifor itheft. iThe itheory iseeks ito iexplain ihow isocietal ichanges ican iimpact
iupon iopportunities ifor icrime i(Sutton, iCherney i& iWhite i2008). i ii
The Implication of the Routine Activity Theory
The implication of the theory in this study is based on criminal events, on the
distribution and grouping in space and time of the minimal elements that make them
18
up, rather than on the search for offenders’ motives, and it thus offers a frame of
reference for concrete and individualized crime analysis and facilitates the
applicationon criminal events, on the distribution and grouping in space and time of
the minimal elements that make them up, rather than on the search for offenders’
motives, and it thus offers a frame of reference for concrete and individualized crime
analysis and facilitates the application.Through the years routine activity theory has
had a significant impact on criminology and has received important empirical support.
Along with rational choice and crime pattern approaches, it maintains a close
relationship with crime analysis and prevention, and has been applied to strategies such
as situational prevention or problem-oriented policing and problem analysis with a
significant degree of effectiveness. Although there have been important criticisms of
its ethical and methodological underpinnings, the majority of critics articulate its
limitations and risks but are unable to deny its capacity to express and explain the need
to look at crime, in order to prevent it, by paying attention to the way in which daily
life unfolds in different places.
2.4.2 Crime Pattern Theory
iAccording ito ithe itheory icrime ihappens iwhen ithe iactivity ispace iof ia ivictim ior itarget
iintersects iwith ithe iactivity ispace iof ian ioffender. iCrime ipattern itheory iseeks ito iexplain
ithe iinfluence iof icommunities iand ineighbourhoods, iand ifocuses ion ihow ioffenders imay
icome iacross iopportunities ifor icrime iin ithe icourse iof itheir ieveryday ilives i(Clarke,
i2005).I
The implication of the Crime Pattern Theory
The implication of the crime pattern theory in this study is based a iway iof iexplaining
iwhy icrimes iare icommitted iin icertain iareas. It further implied that icrime iis inot irandom,
iit iis ieither iplanned ior iopportunistic.Also crime pattern theory provides analysts an
organized way to explore patterns of behaviour. Criminals come across new
opportunities for crime every day. These opportunities arise as they go to and from
personal nodes using personal paths.
19
2.4.3 Rational Choice Theory
Rational iChoice itheory istates ithat i“individuals irely ion irational icalculations ito iachieve
ioutcomes ithat iare iin iline iwith itheir ipersonal iobjectives”. iThe itheory iattempts ito
iexplain iall isocial iphenomenon iin iterms iof ihow iself-interested iindividuals imake
ichoices iunder ithe iinfluence iof itheir ipreferences. iRational ichoice itheory ihas ia imore
iindividualistic ifocus iand iexplores ithe idecision-making iprocesses ithat ilead ito ian
ioffender ichoosing ito ibecome iinvolved iin icrime ior ispecific icriminal ievents, iincluding
iweighing iup ithe irelative irisks iand irewards iassociated iwith ioffending i(Clarke, i2005).
The implication of the Rational Choice Theory
The implication of the rational choice theory in this study is based on the determinants
of the individual choices. Rational choice theory then assumes that an individual has
preferences among the available choice alternatives that allow them to state which
option they prefer.This theory does not claim that it describes the choice process, but
rather that it predicts the outcome and pattern of choices. The rational choice
approach allows preferences to be represented as real-valued utility functions. It
provides a compact theory that makes empirical predictions with a relatively sparse
model just a description of the agent's objectives and constraints.
2.5 Empirical Review of Previous Studies
The empirical review of previous studies is conducted on the basis of specific
objectives. Each specific objective is presented and offered specific review of
literature. This will help to identify relevant studies conducted on the specific issue so
as to give room for this study to obtain a gap that can be worked on. The review is as
follows: -
2.5.1 Empirical review from Africa
Sitharam iand iHoque i(2016) iconducted ia istudy ion ithe ifactors iaffecting ithe iperformance
iof ismall iand imedium ienterprises iin iKwaZulu-Natal, iSouth iAfrica. iThe istudy
20
icontended ithat iSmall iand imedium ienterprises i(SMEs) ihave ian iimportant irole ito iplay
iin ithe idevelopment iof ithe icountry. iA istrong iSME isector icontributes ihighly ito ithe
ieconomy, icontributing ito ithe igross idomestic iproduct, iby ireducing ithe ilevel iof
iunemployment, ireduction iin ipoverty ilevels iand ipromotion iof ientrepreneurship
iactivity. iIn iSouth iAfrica i(SA), ithe igrowth iof iSMEs iand iprevalence iof iSMEs iis
isignificantly ilow. iTherefore, ithe iaim iof ithe istudy iis ito iidentify ithe iinternal iand iexternal
ifactors iaffecting ithe iperformance iof iSMEs iin iKwaZulu-Natal, iSA. iThis iwas ia icross-
sectional istudy iconducted iamong i74 iSMEs iowners/managers iwho iwere imembers iof
ithe iDurban iChamber iof iCommerce ivia ionline iusing ianonymous iquestionnaire. iThe
iresults irevealed itechnological iadvancement iwould iimprove ithe iperformance iof ithe
ibusiness. iWith iregards ito ichallenge, ithe imajority iof ithe irespondents iviewed
icompetition ias ia imajor ichallenge.
Almost iall ithe irespondent iindicated ithat icrime iand icorruption iaffecting ibusiness
iperformance. iCompetition iwas ithe ionly ifactor iamongst ithe istudied iinternal iand
iexternal ifactors ithat irevealed ia isignificant iassociation iwith ithe iperformance iof iSMEs
iin iKwaZulu-Natal i(p i= i0.011). iSMEs ineed ito irecognize ithey imust iprepare ifor iboth
idomestic iand iinternational icompetition. iCollaboration ibetween iSMEs icould ibe ia iway
ifor iSMEs ito iconfront icompetition. i
Gbetnkom i(2012) iconducted ia istudy ion ithe ientitled i“Corruption iand ismall iand
imedium-sized ienterprise igrowth iin iCameroon.” iThis ipaper iused idata ifrom ia ifirm-level
isurvey icarried iout iin iCameroon ito iinvestigate ithe itypes iof ipublic iservices ifor iwhich
ismall iand imedium-sized ienterprises ipay ibribes, ithe icharacteristics iof ithese
itransactions iand ito iestimate ithe iimpact iof ibribe ipayments ion ithe iSMEs igrowth. iThe
iresults ishowed ithat itax iinspectors, ipolice iofficers, ihygiene iand iepidemiological
iofficers, iOfficials ifrom iministries iand iother ipublic ibodies, icustoms iofficers iand
iElectricity iofficers iexercise ipressure ion ibusiness ipeople imost ioften ifor iinformal
ipayment. iBank istaff iand itelecommunication iofficers iare iassessed ias ibeing ithe ileast
icorrupt. iThe ieconometric iassessment iof ithe icorrelation ibetween icorruption iand ifirm
iperformance ireveals ithat ibribe ipayments isignificantly islow iSMEs igrowth. iThe ifirms’
21
iage, imarket ishare, iinvolvement iin iinternational itrade iimpact ipositively ion ifirm
igrowth, iwhile ifrequent icontact iwith ipublic iservices inegatively iaffects ithe igrowth iof
ifirms. iThe ikey imessage iis ithat iunofficial ipayments iare icostly ito iSMEs iin imonetary
iterms iand iin iterms iof iunfulfilled itransactions.
Crimes icommitted iagainst ibusiness iare inothing inew. iThe iliterature irecords inumerous
iexamples ithroughout ihistory. iBy i1995, ithe iSBCI isurvey ifound i35% iof iretailers
ireporting icustomer itheft iwith isimilar ipercentages ifor imanufacturing iand iwholesaling
iindustries. iIn iall, i75% iof isurveyed ibusinesses ireported ione ior imore iincidents iof icrime,
iwith i3.5 iincidents ion iaverage i(Burrows i& iHopkins, i2005).
ICAEW i(2010) ion istudying ibusiness iand ieconomic icrime iin ian iinternational icontext
iprovided ia ireview iof ithe imain itypes iof ibusiness icrimes. iThe iprevalent icrimes iin
ibusiness iwere iidentified ias ibribery iand icorruption, imoney ilaundering, icorporate ifraud,
icartels iand iother icompetition ioffences, icorporate itax ievasion, iusury iand iriba,
ienvironmental iand iemployment icrimes, ismuggling iand iexchange icontrol iviolations,
iintellectual iproperty itheft iand iother iinformation iinfringements. iThese icrimes iwere
icategorized iinto ipolitical iand ireligious icrime, iregulatory iand iadministrative icrimes,
iand icorporate ioffences iand ioffences ifor iindividual idirectors ior imanagers.
2.5.2 iEmpirical ireview from abroadfo
Shanmugam, iHaat iand iAli i(2012) iconducted ian iexploratory istudy iof iinternal icontrol
iand ifraud iprevention imeasures iin iSMEs. iThe istudy icontended ithat, ismall ibusiness iand
ientrepreneurship ihas iemerged ias ian iimportant iarea iof iresearch iover ithe ipast i40 iyears.
iThis ipaper irevolves iaround ithe iissues iof ithe iinternal icontrols iand ifraud iprevention
imeasures ion iSMEs iperformance. iThe ilevel iof ifraud iincidence ias ireported iby iowners iis
istill iat ia ivery ilow ilevel iand ithe ioverall icost iincurred iis istill iwithin iexpectation.
iHowever, ithere iis ia iquestion iof iwhether ithe ilow ireported irate iof ifraud iis idue ito
iadequate ipreventive iactions icurrently iemployed iby iowners, ior iwhether ithe iowners iare
ireluctant ito ireveal ithe itruth iin iorder ito iportray itheir iefficiency iand ieffectiveness iin
irunning itheir ibusinesses. iThis iconceptual ipaper iattempts ito ianalyze irelevant iliterature
22
ion iinternal icontrol, ifraud, icurrent itrends ion ifraud iand ibusiness icrime iprevention
imeasure iadopted iby iSMEs. iBased ion ithe iliterature, ia ifuture iresearch icould ibe
isuggested iin ithe icontext iof iMalaysia. iIt iis ihoped ithat ifuture iresearch iin ithis iaspect iwill
iuncover ithe irelationship ibetween ithe ieffectiveness iof iinternal icontrol iwithin iSMEs
iand ito igauge ithe iadequacy iof ifraud iprevention imeasure itaken iby iowners iof iSMEs iin
iMalaysia. iIt iis iexpected ithat ieffective iinternal icontrol iand ithe ipresence iof iappropriate
ifraud ipreventive imeasures iwill ihelp ito iimprove iSMEs iperformance.
N’Guilla iSow, iBasiruddin, iMohammad iand iRasid i(2018) iconducted ia istudy ientitled
i“Fraud iprevention iin iMalaysian ismall iand imedium ienterprises i(SMEs).” iIn iMalaysia,
ias iin imost iof ithe ideveloping icountries, ismall ibusinesses iplay ipivotal iroles iin ithe
ieconomy. iYet, idespite ithe icontribution iof ismall ibusinesses, iprevious iresearchers ihave
ioverlooked ithe ifraud iissues ithat iare ithreating ithe isustainability iof ithose ibusinesses iand
iinstead ifocus imainly ion ilarge iand ipublic ilisted icompanies. iTherefore, ithe ipurpose iof
ithis istudy iis ito iidentify ihow ismall ibusinesses ican iprevent ifraudulent iactivities. iThis
istudy iused iself-administer iquestioners iand idistributed i126 iquestionnaires ito igeneral
imanagers, ifinancial imanagers iand isupervisors iin iMalaysian ismall iand imedium
ienterprises i(SMEs). iMultiple iregression iwas iused ito itest ithe itheoretical imodel. iThe
ioutput iof imultiple iregressions ishowed ithat iculture iof ihonesty iand ihigh iintegrity, ianti-
fraud iprocesses iand icontrols iand iappropriate ioversight ifunctions ihas ia ipositive iand
isignificant ieffective ion ifraud iprevention imechanisms. iOverall, ithis istudy isuggests
ieffective ifraud iprevention imeasures ito imitigate ithe ifraud irisk isurrounding iMalaysian
iSMEs iand iother iSMEs iin iemerging icountries.
New York State Police on a guide to business security claim that security to a business
against crimes should be established by focusing on frequent checks on doors and
windows, alarm systems, using lights, install convex mirrors, and closed circuit TV
cameras, keep little cash as possible, keeping calm at robbery, being an observant,
being cautious and finally report to the police. These strategies are important to be
considered at crimes.
Williams i(2017) istudied icrime iagainst ibusinesses ibasing ion ithe ifindings ifrom ithe i2016
23
iCommercial iVictimization iSurvey iin iWales iand iEngland. iThe istudy iidentified ithat ithe
imost icommon icrimes iare icategorized iinto icrime iagainst iadministration iand isupport
ipremises, icrime iagainst itransportation iand istorage ipremises, iand iCrime iagainst
iwholesale iand iretail ipremises. iTherefore, iaccording ito ithe istudy ifindings iit iis ishown
ithat ithe imost iprevalent icrimes iin ithe istudy iareas itook ithe iprescribed iform.
Mohamed (2015) studied on prevention, detection, and remedy of crimes in business.
The study identified different strategies for dealing with crimes. These are such as:-
Situational strategy, developmental strategy, community strategy, criminal justice
strategy, security lighting, cameras, locks, security checks for employees, Substance
misuse check and substance misuse policies, web security, password security,
firewalls, minimization of use of cash, and use of secured credit card payments. These
strategies are regarded as very important in preventing crimes in the business
environments. Upon effective use of the strategies, there is assurance of security to the
particular business against crimes.
Bressler i(2009) istudied ithe iimpact iof icrime ion ibusiness ithrough iprevention, idetection
iand iremedy imodel iin ithe iUSA. iThe istudy iidentified ithat iaccording ito ithe iU.S.
iChamber iof iCommerce, icrime imay ibe iregarded ias ia ifactor iin ias imany ias i30 ipercent iof
iall ibusiness ifailures. iDespite iother ivariables ithat imay icontribute ito iincreases iin
icriminal iactivity, ithe icurrent ieconomic irecession iwill ilikely iaccelerate icriminal
iactivity iranging ifrom ishoplifting iand irobbery ito ifraud iand iembezzlement. iIn ithe istudy
iit iwas iexamined ithat ithe irole iof iprevention iand idetection iof icriminal iactivity iand
ioffers iprevention ias ithe imost icost-effective imeans ito ireduce ithe iimpact ion ibusiness
igrowth. i
Motta i(2017) iconducted ia istudy ion ithe iimpact iof icrime ion ithe iperformance iof ismall
iand imedium-sized ienterprises iin iLatin iAmerica. iSmall iand imedium-sized ienterprises
i(SMEs) iare iin ithe iforefront iof ieconomic ipolicy iin ideveloping ieconomies, iplaying
icritical irole iin ilocal ieconomic igrowth iand idevelopment. iSMEs itend ito iserve ilocal
irather ithan iglobal imarkets. iHowever, iseveral iobstacles iprevent igreater iparticipation iof
iSMEs iin ithe ieconomy. iAmong ithem, icrime iis ia imajor iissue ithat inegatively iaffects
24
ilocal idevelopment iin ideveloping icountries, ias irobbery, itheft, ivandalism iand iarson
iincrease ithe icost iof idoing ibusiness. iThe ipurpose iof ithis istudy iis ito iinvestigate ithe
irelationship ibetween icrime iand ifirm iperformance ifor iLatin iAmerican iSMEs iin iboth
iservice iand ihospitality isectors, iusing ilabor iproductivity ias ia imeasure iof ifirm
iperformance. iLabor iproductivity iis ia ikey iconcern iin iLatin iAmerica ias iinstitution-
related iissues iof icorruption, iinfrastructure, iregulations, itrade ipolicies, iaccess ito
ifinance, iand ihuman icapital imay ireduce ithe iefficiency iof ifirms iin ideveloping
ieconomies. iThe ioverall ifindings isuggest ithat ithere iis ia inegative irelationship ibetween
icriminal iactivity iand ifirm iperformance ifor iSMEs iin iLatin iAmerica.
Shanmugam, iHaat iand iAli i(2012) iconducted ia istudy ientitled i“An iexploratory istudy iof
iinternal icontrol iand ifraud iprevention imeasures iin iSMEs.” iThe istudy iemphasized ithat
iSmall ibusiness iand ientrepreneurship ihas iemerged ias ian iimportant iarea iof iresearch
iover ithe ipast i40 iyears. iThis istudy irevolves iaround ithe iissues iof ithe iinternal icontrols
iand ifraud iprevention imeasures ion iSMEs iperformance. iThe ilevel iof ifraud iincidence ias
ireported iby iowners iis istill iat ia ivery ilow ilevel iand ithe ioverall icost iincurred iis istill
iwithin iexpectation. iHowever, ithere iis ia iquestion iof iwhether ithe ilow ireported irate iof
ifraud iis idue ito iadequate ipreventive iactions icurrently iemployed iby iowners, ior iwhether
ithe iowners iare ireluctant ito ireveal ithe itruth iin iorder ito iportray itheir iefficiency iand
ieffectiveness iin irunning itheir ibusinesses. i
This iconceptual ipaper iattempts ito ianalyze irelevant iliterature ion iinternal icontrol, ifraud,
icurrent itrends ion ifraud iand ibusiness icrime iprevention imeasure iadopted iby iSMEs.
iBased ion ithe iliterature, ia ifuture iresearch icould ibe isuggested iin ithe icontext iof
iMalaysia. iIt iis ihoped ithat ifuture iresearch iin ithis iaspect iwill iuncover ithe irelationship
ibetween ithe ieffectiveness iof iinternal icontrol iwithin iSMEs iand ito igauge ithe iadequacy
iof ifraud iprevention imeasure itaken iby iowners iof iSMEs iin iMalaysia. iIt iis iexpected ithat
ieffective iinternal icontrol iand ithe ipresence iof iappropriate ifraud ipreventive imeasures
iwill ihelp ito iimprove iSMEs iperformance.
Taylor i(2002) iconducted ia istudy ientitled i“Under-reporting iof icrime iagainst ismall
ibusinesses: iattitudes itoward ipolice iand ireporting ipractices.” iIn ithis istudy, ithe
25
iresearcher ireported ithat icrime isurveys iof ibusinesses ihave irevealed ithat iwhile icrimes
isuch ias iburglary iand irobbery itend ito ibe ireported ito ipolice, iother icrimes isuch ias
iemployee itheft, icredit icard ifraud iand icustomer itheft iare ilikely ito igo iunreported ito
ipolice. iUnderstanding iwhy isome icrimes iare ireported iand iothers iare inot iis iessential ito
iencouraging ibusiness iproprietors ito ireport icrime, iwhich iin iturn iis iessential ifor
iimproving ithe iaccuracy iof ipolice icrime idata. iData ifrom ia isurvey iconducted iwith
iAustralian ismall ibusinesses ifound ithat iwhile ialmost iall iburglaries iand irobberies iwere
ireported ito ipolice, iincidents iof iemployee itheft, icustomer itheft iand icheque/credit icard
ifraud iwere ilikely ito igo iunreported. iOne iof ithe imost icommon ireasons ireflected ia
ipessimistic ibelief ithat ireporting icrime iwas ipointless iand iachieved inothing. iIt iis iargued
ithat iwhile ireasons ifor inon-reporting ivary, ithere iis imuch ithe ipolice ican ido ito iincrease
ithe iwillingness iof ibusiness iowners ito ireport icrime iand ithese iavenues ishould ibe
ipursued.
Capobianco (2005) on studying Private Sector Involvement in Crime Prevention
identified that the role of the private sector in crime prevention received increasing
attention. A number of national and international events, seminars, and training
courses have highlighted their involvement in and support of crime prevention.
Many of the events identified have focused on private security technologies, on private
policing, or on business and NGO engagement in the larger area of corporate social
responsibility. The study noted and concluded that the studies which have largely been
conducted focus on crime reduction or control measures rather than prevention.
Conclusively, the study depicted the role of private sector being; the growing use of
public-private partnerships in service provision, the development of specific
mechanisms at the national, regional, local and international level to encourage private
sector involvement in crime prevention and reduction, increased demand for business
crime to be a national priority for government, expansion of private security,
proliferation of security technologies and the privatization of public space, and the rise
of corporate social responsibility.
26
2.6 Conceptual Framework
Aconceptualframeworkisthecollectionofresearchconceptscombinedtogetherwithdiffer
entvariableswiththeirlogicalrelationshipoftenrepresentedintheformofdiagrams,charts,f
lowcharts,organgramormathematicalequations. The following figure presents the link
clearly to portray the relationship between variables in the study.
27
Conceptual framework
Independent iivariable ii ii ii ii ii ii ii Dependent iivariable
Figure ii2.1 Conceptual iiframework
Source: iiResearcher iidesign(2019)
From the figure 2.1. It can be denoted that business prosperity or growth may be
contributed by the proper control or prevention of crimes that may face the business
whereas other factors, which may affect growth of business, are kept constant. On the
other hand, the reduced number of crimes on any particular business largely as per the
study are thought to be relying on dealing with the identified forms of crimes in
Types of crimes affecting
small and medium
businesses
All burglary
Vandalism
Cyber Crime
All fraud
All theft
Assaults and threats
Contribution of crime
prevention in the growth of
small and medium
businesses
Enhance safety of
customers
Enhance confidence in
business
Minimize robbery and
burglary risk
Minimize fraud risk
Minimize the theft risk
Growth of Small medium
businesses
Strategies for crime
prevention in small and
medium businesses
Security guards or
guard dogs
Surveillance cameras
Burglar alarms
Use of Locks
Key control
Keeping minimal cash
on hand
Alarm systems
Employee securing
training
Equipment tagging
Crime preventation
28
business, having in place the improved strategies on crimes prevention in business,
and increased role and concern of stakeholders on addressing crimes may significantly
lead to a reduced number of crimes committed on business environments.
2.6 Chapter Summary
This chapter presented the review of Literature for studying the effects of crimes on
small and Medium Business in Ilala Municipality, Dar es Salaam Region. Theories
such as Routine Activity, Crime Pattern, and Rational Choice have been reviewed for
appraising the validity of the study. On the other hand, different studies depending on
the forms of crime prevalent to small and medium businesses, strategies for crime
prevention in small and medium business businesses, contributions of crime
prevention in the growth of small and medium businesses, and role of stakeholders in
the prevention of crime in businesses have been reviewed.
However, the reviewed studies provide little information to support the study in the
context that majority of them provide sufficient details on the impacts of crimes on
business environment. With this understanding of the literature, it is important that the
study be conducted under the assumptions that the results will be interesting to
stakeholders to improve the business setting in the study area and elsewhere similar to
the study area’s environment.
2.7 Research Gap
According to the past research studies both theoretical and empirical reviewed, it is
evident that not much research has been carried out in Tanzania regarding effects of
crime prevention against small and medium business enterprises at Ilala Municipality,
Dar-es-salaam. However among the existing studies pertaining crime prevention tried
to analyse the effects of crime prevention against small and medium business
enterprises without considered specifically determining the types of crimes affecting
small and medium businesses, examining strategies for crime prevention in small and
medium businesses, assessing the contribution of crime prevention strategies in the
29
growth of small and medium businesses and examining the role of stakeholders in the
prevention of crime in businesses. This study therefore has managed to bridge the
given existing gap knowledge that has been left with other researchers such as
Capobianco (2005); Bressler (2009); Mohamed (2015) and Williams (2017).
i
30
CHAPTER THREE
RESEARCH METHODOLOGY
3.1 iiIntroduction
This iichapter iipresents iithe iiresearch iimethods iito iibe iiused iito iiachieve iithe
istudyobjectives.iThe iimethodological iiapproach iistructure iiemployed
iiinthisiithesis iiincludes iiresearch iidesign, iistudy iipopulation, iiunit iiof iia
iisample,and iisize iiof iithe iisample, iiprocedure iiemployed iifor iisampling,
iiinstrumentsused iifor iicollecting iidata iiand iitechnique iiemployed iifor iianalyzing
iidata.
3.2 iiResearch iiDesign
Adami(2008) defines iiresearchdesign iiasawork iiplanior
iidetailedstructureofitheresearchstudyitobedoneinordertoiattain iithe
iiresearchobjective.Thestudyuseddescriptiveicaseistudydesign.AccordingitoRobson(1
993)aicaseistudydesignallow itheresearcheritoemployvarious
iimethodofdatasources,whereby
iithroughthemaresearcherwasabletoiprovideanempirical iiinvestigationof iia iireal
iilife iicontext.
3.3 iiArea iiof iiStudy
Babbiei(2013) iidefines iithe iigiven iiterm iias iia iiplace iiwhere iithe iistudy
iiwasconducted.It iiis iithe iiplace iiwhere iithe iiresearcher iiwould iigo iifor
iidatacollection iiabout iithe iistudy iitopic.This iiresearch iiwas iiundertaken iiat iIlala
Municipality in iiDar iies iiSalaam iiregion. iiThe iireason iiwhy iithe iiresearcher
iiusedIlala Municipality iin iiconducting iithis iistudy iiis iidue iito iithe iifact
iithatIlala is commonly referred to as “Downtown Dar” where much of the commerce,
banking and national offices are located iiand iithis iihelped iithe iiresearcher iito
iiaccess iiinformation iieasily iifor iithis iistudy.
31
3.3.1Map of the study area
Figure3.1Map of the study area ii
Source: iiGoogle iimap ii(2019)
32
3.4. iiStudy iiPopulation
According to Cambridge Dictionary (2008) population is regarded as the entire pool
from which a statistical sample for research study is drawn. A population may refer to
an entire group of people, objects, events, hospital visits, or measurements. A
population can thus be said to be an aggregate observation of subjects grouped together
by a common feature (Cambridge Dictionary, 2008).
The target population for this study included all individuals who could provide
information about crimes in SMEs operations. These include SMEs Owners and Police
Officers of Ilala Police Centre. Ilala Municipality is regarded as the business heart of
the Dar es Salaam Region, this reason has given room to make SMEs as unit of
analysis.
3.5 Sampling iiunit
The iiresearcherconsidered SMEs ofiIlala Municipality and Police officers from Ilala
Police Centreiispecifically iias iia isampling iiunit.
3.6 Sampling iiframe
A iiframe iiof iisampling iiconsidered iiin iithe iistudy iiconsisted iiof iia iiSMEs
owners from iIlala Municipalityand Police officers from Ilala Police
Centre.Theresearcher iidrew iiits iisampleof
respondentsibyconsideringtheirirespective business and working experience. w
3.7 Sample iisize iiof iithe iistudy
The iisize iiof iisampling iiis iithe iinumber iiof iiparticipants iiin iithe iiresearchstudy
ii(Hair iiet iial., ii2015). iDavies iiand iiHughes ii(2014) iicontend, iiin iiorderto iihave
iiconducted iian iiacceptable iiand iidependable iianalysis, iithe iisize iiofsample
iishould iinot iibe iiless iithan ii30% iiof iiits iipopulace.
33
Yamanei(1967) iideveloped iithe iiformula iifor iidetermining iisample
iisize.Thisformula iideveloped iiby iiYameni iiwas iiused todefine theisize iiof
iisampleemployedin iithis iistudy iiwhereby iithe iiresearcher iiemployed iisuch
iiformula iito iiarriveatSample size of 92 for Small Medium Enterprise’s owners and Sample size
of 42 for Police officers of Ilala Police Center.The iiestimate iiprocedureiis iias iifollows: ii
ii ii ii ii ii n ii= ii ii ii ii i N ii
ii ii ii ii ii ii ii ii ii ii ii ii ii ii ii ii ii1+N ii(e) ii2
Where: ii iin= iisample iisize iito iibe iidetermined, iiN ii= iithe iientire iipopulation
iiof iiinterest, ii
ie ii= iithe iiacceptable iisampling ii(0.05), ii1 ii= iiconstant. Ii
Table 3.1: Determination of sample size for SMEs owners from IIlala
Municipality and Police officers from Ilala Police Centre
Sample size for Small Medium Enterprise’s
owners
Sample size for Police officers of Ilala Police
Center
n=?, N = 120, e = 0.05, 1 = constant.
Substituting in the formula we have:
n = 120 .
1+120 (0.05)2
n = 92 SMEs owners
n=?, N = 55, e = 0.05, 1 = constant.
Substituting in the formula we have:
n = 55 .
1+55 (0.05)2
n = 48 Police officer
Source: Researcher design, (2019)
The sample drawn from the targeted SMEs owners’ population was 92SMEs while the
sample drawn from the targeted population of Police officer of Ilala Police Centre was
48 staff. The selection is shown in Table 3.2 below
34
Table 3.2: Sample size for for SMEs owners from IIlala Municipality and Police
officers from Ilala Police Centre
Source: Researcher design, (2019)
3.8 Sampling iitechniques iiand iiprocedures
Sampling technique is defined as a technique received for choice of subset of
components from a bigger gathering of items (Bryman, 2015). This can be
characterized as an area of a portion of a total or totality based on which a judgment
or induction about the total is made. This is a clear arrangement for acquiring an
example from the inspecting outline. It alludes to the system or technique the specialist
embraced in choosing some examining units from which surmising about the populace
is drawn (Zikmund, Babin, Carr and Griffin, 2013). In iithis iistudy, iithe iiresearcher
iiused both probability sampling technique and iinon-probability sampling
iitechniques iifor iisampling iitechnique iithat iiis iiexplained iias iifollows;
3.8.1 Probability sampling technique
Neuman and Robson (2014) describe the term probability sampling as an examining
strategy wherein each part of the populace has an opportunity to be chosen and end up
one among the individual from the chose test. During this investigation, the scientist
utilized basic arbitrary testing method and purposive examining system as depicted
beneath;
S/n Category Number of respondents
1 Small Medium Enterprise’s owners 92
2 Police officers of Ilala Police Center 48
TOTAL 140
35
3.8.1.1 Simple random sampling technique
Simple random sampling technique is the sort of testing whereby each individual from
the populace has an equivalent possibility of being chosen to frame an example (Levy
and Lemeshow, 2013). The analyst received straightforward irregular testing method
to give an equivalent possibility of each of the chosen components. This sampling
technique empowers to acquire the respondents who are the SMEs owners at Ilala
Municipality.
3.8.2 Non-probability iisampling iitechnique
Msabila iiand iiNalaila i(2013)idemonstrated iinon-probability
iisamplingtechniquesare iisampling iitechniques iiwhere iia iiselection iiof
iiindividuals iiforthe iisampledoes iinot iigive iiall iithe iiindividuals iiin iithe
iipopulation iiequalchances iiofbeing iiselected.There iiis iino iirandom iiselection iiof
iielements iior iiindividuals.Subjects, iiin iia iinon-probability iisample, iiare iiusually
iiselected iion iithe iibasisof iitheir iibasis iiof iiaccessibility iior iiby iia iipurposive
iipersonal iijudgment iiofthe iiresearcher. ii
3.8.2.1 iiPurposive iisampling iitechnique
Gu, iiHu iiand iiLiu ii(2001) iidefine iipurpose-sampling iitechnique iias iithesampling
iitechnique iiinvolving iiselecting iisample iirespondents iiby iiconsideringtheir
iiexperience, iiprofession iior iiposition. iiThis iitechnique iichoosesrespondents iifor
iithe iistudy iiby iinot iidelivering iiequivalent iichance iiofchoiceto iievery
iirespondent iiin iithe iitarget iipopulation ii(Singh ii& iiMasuku, ii2014).Researcher
iiemployed iipurposive iitechnique iifor iisampling iiwhile iichoosingsize iiof iisample
iifrom Police officers of Ilala Police Centre and Local Government officials from Ilala
Municipality. iiThe iirespondents iiwere iichosen iiconsideringdifferent iipositions
iithey iihold iiat iiIlala Police Centre and at Ilala Municipality.
36
3.9 Description of variable and their measurement approach and scales
3.9.1 Measurement of variables
The variables were measured using nominal and ordinal types of measurements. The
questionnaires specifically for respondents were measured on a five interval Likert
Scale, the level of agreement was ranked as strong disagree, disagree, neutral, strongly
agree and agree, while ordinal scale as measurement of variables did only categorize
the elements being measured but also ranked them into some order.
Therefore, the numbers in the ordinal scale represented relative position or order
among the variables (DeVellis, 2016). The nominal scale of measurement was applied
to cases, which had some common characteristics such as sex, age, and employment
title among others. In nominal measurement of variables, numbers were assigned only
for the purposes of identification but were not allowed for comparison of the variables
to be measured. On the other hand, an interval scale of measurement was used to
capture personal data of respondents.
37
Table ii3.3 iiExplaination iifor iithe iivariables, iidimensions iiand iidata iisource
Research iiobjectives Name iiof iivariable Values iiand
iiMeasurements
Data iisource
Relationship
iibetweenCrime prevention iiand Growth
of SMEs
Variable iiX= Crime
prevention
Variable iiY= Growth of SMEs
iiCorrelation
iianalysis
Primary iidata
iisource ii
Types of the crime
preventation All burglary Vandalism
Cyber Crime
All fraud
All theft
Assaults and threats
Values; iiNominal
Measurements;
Ranking iiusing iia
iiscale iiof ii1-6 iiin
iiwhich;
1. All burglary
Vandalism
2. Cyber Crime
3. All fraud
4. All theft, 5. Assaults and
threats
Primary iidata
iisource ii
Strategies for crime
prevention in small and
medium businesses
Security guards or guard
dogs
Surveillance cameras
Burglar alarms
Use of Locks
Key control
Keeping minimal cash on
hand
Descriptive analysis Primary data
source
Contribution of crime
prevention strategies in the growth of small and
medium businesses
Enhance safety of
customers
Enhance confidence in
business
Minimize robbery and
burglary risk
Minimize fraud risk
Minimize the theft risk
Values; iiNominal
Measurements; Ranking iiusing iia
iiscale iiof ii1-5 iiin
iiwhich;
1= iiNo iiextent, ii
2=Very ismallextent,
ii
3= iiSmall iiextent, ii
4=Large iiextent, ii
5= iiVery iilarge
iiextent
Primary iidata
iisource
Source: iiResearch iidesign(2019)
38
3.10 Sources iiof iidata
The iiresearcher iiused iiboth iiprimary iiand iisecondary iisources iias iifollows;
3.10.1 Primary iidata iisources
These iiare iiinitial iiinformation iigathered iidirectly iifrom iirespondents
ii(Palinkaset iial., ii2015). iiPrimary iidata iiare iiobtained iidirectly iifrom iithe
iirespondentsduring iiinterview iisession, iiincluding iithose iidata iiwhich iithe
iiresearchercollects iihimself iiusing iidifferent iidata iicollection iimethods
iiincludingquestionnaires iiand iiobservation.
3.10.2 Secondary iidata iisource
These iiare iidata iithat iihave iialready iihave iibeen iicollected iiand iicompiled
iibysomeone iielse iior iiother iiresearchers. iiSecondary iidata iiinvolves
iithecollectionand iianalysis iiof iidata iifrom iipublished iimaterials iiand
iiinformation iifrominternal iisources ii(Neuman, ii2016). iiSecondary iidata iiwere
iiobtained iifrompublished iimaterials iisuch iias reports and iirjournals iiand
iiprevious iiresearchesrelated iito iithis iistudy. iiAll iithese iihelped iithe iiresearcher
iito iiprepare iithefinal iireport. iiThis iisecondary iidata iiprovided iithe iiresearcher
iiwith iiinsightsonhow iithe iicollected iidata iiwere iianalyzed iiand iiinterpreted iito
iidraw iiameaningful iiconclusion iifrom iithe iistudy.
3.11 Data iicollection iimethods
Data iicollection iimethods iirefer iito iigathering iispecific iiinformation iiaimed
iiatproviding iior iirefuting iisome iifacts ii(Merriam, ii& iiTisdell, ii2015).
iiTheresearcher iiused iisuitable iimethods iifor iidata iicollection iiin iiaccordance
iitothenature iiand iitype iineeded. iiThe iifollowing iimethods iiof iidata
iicollectionwereused iito iigather iiboth iiprimary iiand iisecondary iidata.
39
3.11.1 Questionnaire
A iiquestionnaire iicontains iiof iia iilist iiprinted/typed iiquestions, iiwhich iiare iiinan
iiexplicit iiorder ii(Moser ii& iiKalton, ii2017). iiResearcher iiused iia iilist iiofclear
iiquestions, iiwhich iiwas iidesigned iiin iiadvance iito iiobtain iimore iidata.The
iiresearcher iiused iithis iimethod iito iicomplement iithe iiweakness iiof iiothertype
iidata iisources. iiBy iiusing iiquestionnaires iimore iidata iito iibe iicollectedcould iibe
iifrom iiapproximately iia iilarge iisample. iiThe iiquestionnaires iiweredistributed
iidirectly iito iithe iPolice officers and Small Medium Enterprises ownersiiselected iias
iia iistudy iisample. iiThis iimethod iiaided iito iiavoid iibiasand iisafeguard iiin
iiobtaining iiaccurate iiand iivalid iidata.
3.11.2 Interview
The iiresearcher iiused iian iiinterview iiguide iito iicollect iiprimary iidata iifrom
Police officers and Small Medium Enterprises owners iiwhere iithe iiguide
iiwascomposed iiof iiseveral iiquestions iiaiming iiat iiobtaining iiin iidetail
iitherelevantinformation. iiThe iiresearcher iiopted iifor iithis iimethod iibecause iiof
iithe iinatureof iithe iistudy iipopulation, iiwhich iicomposed iiof iiliterate
iirespondents. iiIn iitheinterview, iithe iiresearcher iiconsider iithe stakeholders s
iiwho iiwere involved on crime prevention.
3.12 Reliability iiand iivalidity iiof iidata
3.12.1 Reliability
The iiresearcher iifocused iion iithe iiright iisource iiof iiinformation iito
iiensurereliability iiof iidata. iiThrough iithis iithe iimethodology iiproduced
iiresults,whichwere iiconsistent. iiReliability iiis iiabout iiif iithe iioutcome iifrom
iianexaminationcan iibe iithe iisame iiif iithe iiexploration iiwas iito iibe iidirected
iionce iimore, iitothe iiextent iiquantitative iiresearch iidependability iiis iiconcerned.
iiThe iitarget iiofthe iiexamination iiwas iito iiguarantee iithat iiif iia iilast iiexaminer
iiwould iitakeafter iithe iivery iisame iisystems iias iiportrayed iiby iia iipast iiagent
40
iianddirecteda iisimilar iireview iithink iiabout, iionce iimore, iithe iilast iispecialist
iishouldtouchbase iito iicomparative iidiscoveries iiand iiconclusions, ii(Yin, ii2017).
3.12.2 Validity
Due iito iithe iisignificance iiof iivalidity iifor iithe iidata, iithe iiresearcher
iiensuredthat iithe iidata iiwere iicollected iiusing iia iiwell-designed iidata-
collectinginstrument.To iithe iibest iiof iihis iiknowledge iithe iiresearcher iiprepared
iiawell-structured iiquestionnaire, iiwhich iienabled iito iicapture iiimportant
iiandrelevant iiinformation iito iibe iisubjected iito iianalysis iiat iia iilater iistage.
iiTheinstrument iiused iienabled iithe iiresearcher iito iiperform iihis iistudy iias
iiplannedand iicome iiup iiwith iivalid iiresults.
3.13 Analysis iiand iimanagement iiof iidata
Before iidata iianalysis iithe iiresearcher iisystematically iireviewed, iifiltered,
iiandremoved iithe iicollected iidata iiwhich, iiif iileft iias iithey iiwere iithey
iimightmislead iithe iientire iiresults iior iimake iithem iimeaningless. iiThis iiactivity
iiwasdone iiduring iithe iiprocess iiof iicollecting iidata iiand iiafter iidata iicollection.
Data iiprocessing iiinvolved iia iiset iiof iiactivities iisuch iias iidata iisorting
iiandcleaning, iicategorizing, iidata iicoding iiand iitransferring iicoded iidata
iitotabulations. iiBoth iiquantitative iiand iiqualitative iidata iianalysis iiwas
iiusedduring iithe iianalysis iiof iidata.
Data iimanagement iiis iithe iisystematic iiorganization iiof iia iimass iiof iiraw
iidatacollected iiin iia iimanner iithat iifacilitated iianalysis iiof iidata. iiIt iialso
iiincludesidentifying ii(and iicorrecting) iierrors iiin iithe iidata, iicoding iithe iidata,
iiandstoring iiit iiin iian iiappropriate iiform. iiTherefore, iithe iidata iiwas iiput
iiintosome iisystematic iiform, ii(Kothari, ii2004). iiTo iienable iithis iiprocess iito
iibemore iiaccurate iiand iisimple iithe iiresearcher iiprepared iia iicodebook
iithatdescribed iithe iispecific iidetails iiextracted iifrom iithe iiquestionnaires. ii
41
Data iimanagement iiwas iidone iithroughout iithe iiprocess iiof iidata iianalysis
iiinorder iiguarantee iithe iiresearcher iithat iia iisignificant iipercentage iiof
iithecollected iiinformation iifrom iirespondents iiis iiuseful. iiAlso iiit iiwas iidone
iiaftercollecting iidata iiso iias iito iithoroughly iicheck iithe iidata, iiwhich
iiwereaccidentally iicollected, iiand iithe iiresearcher iidid iinot iinotice iiduring
iitheprocess. iiThe iiwhole iiprocess iiensured iithat iithe iiremaining iidata
iiguaranteedmeaningful, iiaccurate iiand iireliable iiresults. ii ii ii ii
Statistical iiPackage iifor iiSocial iiScientist ii(SPSS) iiSoftware iiVersion
ii23.0andMicrosoft iiExcel iioffice iipackage iiwere iiused iito iianalyze iithe
iidatawherebycorrelation iianalysis iitechniques iiwere iiemployed iito iidetermine
iithe iistrengthof iiassociation iibetween iitwo iivariables. ii ii kjkljllkjk
3.13.1 Assumption for Correlation analysis
Schabenberger and Gotway (2017) underline the assumptions of the correlation
analysis which include; level of measurement, related pairs, absence of outliers,
normality of variables, linearity, and homoscedasticity.
Level of measurement refers to each variable. For a Pearson correlation each
variable should be continuous. If one or both of the variables are ordinal in
measurement, then a Pearson correlation could be conducted instead.
Related pairs; this refers to the pairs of variables. Each participant or observation
should have a pair of values. So if the correlation was between weight and height, then
each observation used should have both a weight and a height value.
Absence of outliers; this refers to not having outliers in either variable. Having an
outlier can skew the results of the correlation by pulling the line of best fit formed by
the correlation too far in one direction or another. Typically, an outlier is defined as a
value that is 3.29 standard deviations from the mean, or a standardized value of less
than ±3.29.
42
Linearity and homoscedasticity; these refer to the shape of the values formed by the
scatterplot. For linearity, a “straight line” relationship between the variable should be
formed. If a line were to be drawn between all the dots going from left to right, the
line should be straight and not curved. Homoscedasticity refers to the distance
between the points to that straight line. The shape of the scatterplot should be tube-like
in shape. If the shape is cone-like, then homoscedasticity would not be met.
3.13.2 Qualitative iidata iianalysis ii
The iiresearcher iialso iiemployed iia iiqualitative iidata iianalysis, iiwhich
iiinvolvedthe iiidentification, iiexamination, iiand iiinterpretation iiof iipatterns iiand
iithemesin iitextual iidata iiand iidetermines iihow iithese iipatterns iiand iithemes
iihelpedanswer iithe iiresearch iiquestions iiat iihand. iiThe iiresearch iiemployed
iiinterviewmethod iias iia iiqualitative iidata iicollection iimethod, iiwhich iiinvolved
iiaskingquestions iito iirespondents, iilistening iito iiand iirecording iianswers iifrom
iianindividual iion iia iistructured iiformat iiand iiin iian iiin iidepth iimanner.
3.14 iiEthical iiConsideration
According iito iiKothari i(2004), iiEthical iiConsideration iiis iithe iiway iiaresearcher
iidepicts iihow iihe iior iishe iiguarantees iiethical iiissues iior iinecessityis
iimaintained iiin iithe iistudy.To iiensure iiethical iiconduct iiof iithe iistudy
iitheresearcher iiobtained iia iiletter iifrom iiMzumbe iiUniversity iiprior iito iithe
iistudyas iiauthorization iito iiconduct iithe iistudy Ilala Municipality. iiThe
iiresearcherensured iiconfidentiality iiof iidata iicollected iiis iimaintained iifor
iiherrespondents. iiThe iirespondents iiwere iimore iiopen iiand iifree iito iirespond
iitothe iiresearcher iiwith iino iifear iiof iibeing iimisinterpreted iior iiabused. I
43
CHAPTER FOUR
DATA PRESENTATION, ANALYSIS AND DISCUSSION
4.1. iiIntroduction
Thischapterextrapolatesdatacollectedduringithestudyinrelationtoresearchquestionsan
dobjectives.Theistudyfocusedionitheeffects of crime prevention against small and
medium business enterprises at Ilala Municipality, Dar-es-salaam.
Itisiseparatedintofivemainsections,whichfocusionaddressingthegeneralandspecific
iiresearch iiobjectives.Section iione iicentered iion iidemographic iiand iibackground
iicharacteristics iiof iithe iirespondents, iisection iitwo iexamine the relationship
between crime prevention and the growth of small and medium enterprises, section
threedetermine the types of crimes affecting small and medium businesses in Ilala
Municipality, whereas section four examine strategies for crime prevention in small
and medium businesses in Ilala Municipalityiiwhile iisection iifive iifocuses iionassess
the contribution of crime prevention strategies in the growth of small and medium
businesses.
4.2 Demographic characteristics of the respondents
This shows a conceptual of the nature of the population and composition that the
researcher used in collecting data. The demographics characteristics of the respondents
were grouped in two groups depending on the nature of the sample of the study. The
first group indicates the demographic characteristics of the SMEs owners of Ilala
Municipality, which includes gender of respondents, age of the respondents and the
education level of the respondents and business experience, while the second group
indicates the demographic characteristics of the Police officers from Ilala Police
Centre.
44
Table 4.1: Characteristics of the respondents
Source: Field data, (2019).
Type of respondent Characteristics of the
respondents
Parameters Frequency Percentage
SMEs owners at Ilala
Municipality
Age 25-35 years 28 30
36-45 years 41 45
46 years and above 23 25
Total 92 100=(N=120)
Sex Male 69 75
Female 23 25
Total 92 100=(N=120)
Business experience Below ii5 iiyears 29 32
6-10 iiyears. 40 43
11-15 iiyears. ii ii 14 15
16 iiyears iiand iiabove 9 10
92 100=(N=120)
Educational level Primary education 16 17
Secondary education 44 48
Bachelor degree 25 27
Masters degree 7 8
Total 92 100=(N=120)
Police officers at Ilala
Police Centre
Age 25-35 years 16 33
36-45 years 26 54
46 years and above 6 13
Total 48 100=(N=55)
Sex Male 36 75
Female 12 25
Total 48 100=(N=55)
Name of the department Crime preventation unit
department
17 35
Criminal Investigation
department
11 23
Cyber crime department 6 13
General duty
department
14 29
Total 48 100=(N=55)
45
4.2.1 Demographic characteristics of the respondents (SMEs owners from Ilala
Municipality)
4.2.1.1 Age of respondents
Based on the age of SMEs owners from Ilala Municipality, Table 4.1 above indicates
that 28(30%) of the respondents were aged between 25 to 35 years, while 41(45%)
respondents were aged between 36 to 45 years whereas 23(25%) of the respondents
were aged between 46 and above.
4.2.1.2 Gender status of respondents
Based on the gender status of SMEs owners from Ilala Municipality, Table 4.1 above
indicates that 69(75%) of the respondents were male, while 23(25)% of the
respondents were female.
4.2.1.3 Business experience
Based on the age of SMEs owners from Ilala Municipality, Table 4.1 above indicates
that 29(32%) of the respondents had a business experience below 5 years, 40(43%) of
the respondents had a business experience between 6 to 10 years, whereas 40(43%) of
the respondents had a business experience between 11 to 15 years while 9(10%) of the
respondents had a business experience between 16 and above.
4.2.1.4 Education levels of the respondents
The study sample of the SMEs owners from Ilala Municipality contained with
respondents who had different levels of education including primary education,
secondary education, bachelor degree and master’s degree whereby, 16(17%) of the
respondents had primary education level, 44(48%) of the respondents had secondary
education level, whereas 25(27%) of the respondents had bachelor degree education
level, while 7(8%) of the respondents had masters degree education.
46
4.2.2 Demographic characteristics of the respondents (Police officers at Ilala
Police Centre)
4.2.2.1 Age of respondents
Based on the age of Police officers at Ilala Police Centre, Table 4.1 above indicates
that 16(33%) of the respondents were aged between 25 to 35 years, while 26(54%)
respondents were aged between 36 to 45 years whereas 6(13%) of the respondents
were aged between 46 and above.
4.2.2.2 Gender status of respondents
Based on the gender status of Police officers at Ilala Police Centre, Table 4.1 above
indicates that 36(75%) of the respondents were male, while 12(25%) of the
respondents were female.
4.2.2.3 Departments where the respondents belong
The study sample of the Police officers at Ilala Police Centre contained with
respondents who belonged from different departments including Crime preventation
unit department, Criminal Investigation department, Cyber crime department and
General duty department whereby, 17(35%) of the respondents belonged from Crime
preventation unit department, 11(23%) of the respondents belonged from Criminal
Investigation department, whereas 6(13%) of the respondents belonged from Cyber
crime department, while 14(29%) of the respondents belonged from General duty
department.
4.3 Findings iiby iispecific iiresearch iiquestions
4.3.1 Response iion iithe iirelationship iibetween crime prevention iiand the
growth of SMEs
The researcher sought to examine the relationship between crime prevention and the
growth of SMEs. The descriptive analysis were conducted whereby the descriptive
47
statistic results as indicated in the Table 4.2 were obtained while showing the list of
variables including increase of increase number of customers, increases on sales,
reduce costs of doing business, boost workers’ morale, and encourage SMEs owners
to stay in the business as variables showing the existing relationship between crime
prevention and the growth of SMEs.
Table 4.2Descriptive statistics
N Sum Mean Std. Deviation
Statistic Statistic Statistic Std. Error Statistic
Boost workers’ morale 92 433.00 5.1838 .07707 .68936
Encourage SMEs to continue with business 92 440.00 5.5056 .06689 .59837
Reduce costs of doing business 92 435.00 5.4194 .07431 .66463
Increase number of customers 92 426.00 5.3188 .08527 .76271
Increases sales 92 419.00 5.2325 .09126 .81625 Valid N (listwise) 92
Source: Field data (2019)
The descriptive results in the table 4.2 indicate the description/comparison of means
and whereby increase boost workers’ morale, encourage SMEs to continue with
businessreduce costs of doing business, increase number of customers andincreases
sales. Encourage SMEs to continue with businessvariable having an average of 5.5056,
Reduce costs of doing business variable having an average of 5.4194, increase number
of customersvariable having an average of 5.3188, Increases sales variable having an
average 5.2325, while boost workers’ morale variable having an average of 5.1838.
While in the description/comparison of standard deviation the results indicate that
Increases sales variable had a standard deviation of 0.81625, increase number of
customers had a standard deviation of 0.76271, Boost workers’ morale variable had a
standard deviation of 0.68936 whereas reduce costs of doing business variable had a
standard deviation of 0.66463, while encourage SMEs to continue with business
variable had a standard deviation of 0.59837.
Therefore as increases sales variable data having a higher standard deviation compared
to the rest of variables, these results entail that the increases sales variable data is more
48
spread out or dispersed than increase number of customers, boost workers’ morale,
reduce costs of doing business and encourage SMEs to continue with business.
Respondents were asked the extent to which the SMEs owners have realized the effect
of crime preventation on the growth of SMEs. From the findings in the Table 4.1
below, it is evident that the SMEs owners have moderately realized a wide collection
of effect arising from the crime preventation activities especially in terms of increasing
boost workers’ morale, encourage SMEs to continue with business, reduction costs of
doing business, increasing number of customers andincreasing sales to SMEs of Ilala
Municipality. The findings of this research are concurrent with the findings of Islam,
(2014) who found that crime prevention is very essential to SMEs since it has
significant impact on the improvement of SMEs in terms of cost reduction and the
increase sales.
Correlation analysis
In the line of the result obtained by the descriptive analysis, the researcher also sought
to examine the relationship between crime prevention and the growth of SMEs through
the application correlation analysis technique. The correlation analysis was conducted
whereby the results as indicated in the Table 4.3 were obtained while showing how
each variable correlate with the crime prevention while checking whether such
relationship is either positive correlation, negative correlation or no correlation
between variables representing the effect of crime prevention such as increase number
of customers, increases on sales, reduce costs of doing business, boost workers’
morale, and encourage SMEs owners to stay in the business and the growth of SMEs
which is dependent
49
Table 4.3 Correlations
Source: Field data (2019)
The results were presented in a matrix such that, the correlations were replicated to
determine the Pearson correlation coefficient, its significance value and the sample
size that the calculation was based on. This result revealed that the Pearson correlation
coefficient, r =0.941, r=0.974 and r=0.915, r=0.864 and that is statistically significant
(p=0.000).
Discussion of the Pearson correlation results
A Pearson correlation was run to determine the relationship among encouraging SMEs
to continue with business, reduce costs of doing business, increase number of
customers, increases sales and boost workers’ morale and were statistically significant
(r =0.941, r=0.974, r=0.915, r=0.864,p=0.000). Therefore based on the results obtained
it can concluded that encourage SMEs to continue with business, reduce costs of doing
business, increase number of customers, increases sales and boost workers’ morale
have strong statistically significant linear relationship (p=0.000). It can also be
Boost
workers’
morale
Encourage
SMEs to
continue with
business
Reduce
costs of
doing business
Increase number
of customers
Increases sales
Boost workers’
morale
Pearson Correlation 1 .941** .974** .915** .864**
Sig. (1-tailed) .000 .000 .000 .000
N 92 92 92 92 92
Encourage SMEs
to continue with
business
Pearson Correlation .941** 1 .933** .871** .840**
Sig. (1-tailed) .000 .000 .000 .000
N 92 92 92 92 92
Reduce costs of
doing business
Pearson Correlation .974** .933** 1 .949** .895**
Sig. (1-tailed) .000 .000 .000 .000
N 92 92 92 92 92
Increase number
of customers
Pearson Correlation .915** .871** .949** 1 .974**
Sig. (1-tailed) .000 .000 .000 .000
N 92 92 92 92 92
Increases sales
Pearson Correlation .864** .840** .895** .974** 1
Sig. (1-tailed) .000 .000 .000 .000
N 92 92 92 92 92
**. Correlation is significant at the 0.01 level (1-tailed).
50
concluded that the direction of the relationship among the identified variables
(encourage SMEs to continue with business, reduce costs of doing business, increase
number of customers, increases sales and boost workers’ morale) implying that these
variables tend to result together in improving growth of SMEs at Ilala Municipality as
a result of crime prevention in particular. Therefore the magnitude or strength of the
association/relationship is absolute strong.
The coefficient of the above correlation analysis, which is (r =0.941) shows that there
is positive correlation between crime prevention and growth of SMEs in terms of
encouraging SMEs to continue with business. This means that changes in crime
prevention will correlate with changes growth of SMEs in terms of encouraging SMEs
to continue with business. The coefficient r=0.974 shows that there is positive
correlation between crime preventation and growth of SMEs in terms of reducing costs
of doing business. This means that changes in crime prevention will correlate with
changes growth of SMEs in terms of increase on sales growth, whereas the coefficient
r=0.915 shows that there is positive correlation between crime preventation and
growth of SMEs in terms of increasing number of customers. This means that changes
in crime prevention will correlate with changes in the growth of SMEs in terms of
increasing number of customers, while the coefficient r=0.864 shows that there is
positive correlation between crime preventation and growth of SMEs in terms of the
increases of sales. This means that changes in crime prevention will correlate with
changes the growth of SMEs in terms of the increase of sales. Therefore it can be
concluded that crime preventation and growth of SMEs are strongly correlated in terms
of encouraging SMEs to continue with business, reduce costs of doing business,
increase number of customers, increases sales and boost workers’ morale. In addition,
with regards to Sig (2-Tailed), conclusion can be drawn that there is statistically
significant correlation between crime prevention and the growth of SMEs.
51
4.3.2 Response on the types of crimes affecting small and medium businesses at
Ilala Municipality
The researcher sought to examine the types of crimes affecting small and medium
businesses at Ilala Municipality. The respondents were asked to identify five types of
crimes and examine the extent in which each type of crime affects the growth of SMEs.
The results of the indicates that among the five types of crimes affecting small and
medium businesses at Ilala Municipality include all burglary, vandalism, cyber crime,
all fraud, all theft, and assaults and threats. In the line of the given identified types of
crime affecting the growth SMEs at Municipality, the reseach also sought to examine
in what extent in each types of identified crime affects growth of SMEs. The results
are graphically presented on the Figure 4.1 as follows;
Source: Field data (2019)
Figure 4.1 Response on the extent of types of crimes affecting the growth of SMEs
at Ilala Municipality
Figure 4.1 indicates that 15 respondents represent 16% of the total respondents
indicates that all burglary as a type of crime affects the growth of SMEs, 11
respondents represent 12% of the total respondents indicates that vandalism as a type
52
of crime affects the growth of SMEs, 3 respondents represent 3% of the total
respondents indicates that cyber crime as a type of crime affects the growth of SMEs,
12 respondents represent 13% of the total respondents indicates that all fraud as a type
of crime affects the growth of SMEs, where as 33 respondents represent 36% of the
total respondents indicates that all theft as a type of crime affects the growth of SMEs
while 18 respondents represent 20% of the total respondents indicates that assaults and
threats as type of crimes affects the growth of SMEs. This result of the study entails
that majority of SMEs owners are mostly affected by theft crimes compared to other
type of crimes.
In the line the of the given findings, the researcher also sought examine the type of
crimes that are regularly reported at Ilala Police centre by SMEs owners. This question
was asked by way of questionnaire and it was addressed by the Police officers.
4.3.2.1 Response on type of crimes that are regularly reported at Ilala Police
centre by SMEs owners
The researcher also sought examine the type of crimes that are regularly reported at
Ilala Police centre by SMEs owners. This question was asked by way of questionnaire
and it was addressed by the Police officers while considering sample size of 48 police
officer of Ilala Police centre. The results are graphically presented on the Figure 4.2 as
follows;
53
Source: Field data (2019)
Figure 4.2 Response on type of crimes that are regularly reported at Ilala Police
centre by SMEs owners
Figure 4.2 indicates that 7 respondents represent 15% of the total respondents
confirmed that vandalism crimes are regularly reported to the police by SMEs owners,
3 respondents represent 6% of the total respondents confirmed that cyber crimes are
regularly reported to the police by SMEs owners, 9 respondents represent 19% of the
total respondents confirmed that fraud crimes are regularly reported to the police by
SMEs owners, 27 respondents represent 56% of the total respondents confirmed that
theft crimes are regularly reported to the police by SMEs owners, where as 2
respondents represent 4% of the total respondents confirmed that assaults and threats
crimes are regularly reported to the police by SMEs owners. These results of the study
entail that theft is the type crime that is mostly regularly reported by SMEs owners at
Ilala Police Centre, while the least type of crimes reported at Ilala Police centre are
assaults and threats.
54
In the line of the given findings of the study, it was also revealed in the study by
Shanmugam, Haat and Ali (2012) who reported that the level of fraud incidence as
reported by owners is still at a very low level and the overall cost incurred is still within
expectation. However, there is a question of whether the low reported rate of fraud is
due to adequate preventive actions currently employed by owners, or whether the
owners are reluctant to reveal the truth in order to portray their efficiency and
effectiveness in running their businesses.
In connection to the given study findings, it was revealed in the study by Taylor (2002)
that crime surveys of businesses have revealed that while crimes such as burglary,
robbery and other type of theft tend to be reported to police, other crimes such as fraud
and assault and threats are likely to go unreported to police. The study emphasized that
an understanding why some crimes are reported and others are not is essential to
encouraging business proprietors to report crime, which in turn is essential for
improving the accuracy of police crime data.
In the line of the obtaining study findings, the researcher also sought to identify how
could SMEs owner respond to crimes, the impacts when crimes are not reported to the
police, whether crime prevention officers visit the SMEs owners and evaluate their
physical and procedural security measures, whether the crime prevention officers
conduct a security survey towards SMEs owners and whether crime prevention
officers advise the SMEs owners against crime occurance.
These questions originate from a set of Interview guide questions as was addressed by
Commanding officer (C.O) of Crime Prevention Unit department as indicated below;
Question one: How could SMEs owner respond to crimes?
Response one:“As Police officers, we always advise the SMEs owners on how to
respond to crimes whereby in order for SMEs owners to prevent their business from
crime they should have a strong relationship with law enforcement officers whereby
55
in case a criminal comes by to stake out their shops, they might be deterred by the
presence of the police.”
Question two:What are the impacts when crimes are not reported to the police?
Response two: “When crimes go unreported, crime statistics become skewed,
meaning law enforcement can’t accurately allocate its limited manpower. Worse, if no
one speaks up, the person who committed the crime might become a repeat offender.”
Question three: Could crime prevention officers visit the SMEs owners and evaluate
their physical and procedural security measures?
Response three: “Yes the crime prevention officers have a tendency of visiting the
SMEs owners and evaluate their physical and procedural security measures. These
officers would inform the SMEs owner or manager on how their particular business
may be most susceptible to crime, and factors that may be making their business an
attractive target to prospective criminals.”
Question four: Does the crime prevention officers conduct a security survey towards
SMEs owners?
Response four: “Yes! Crime prevention officers always conduct a security survey
towards SMEs owners presented at Ilala Municipality. Following the survey, the
officers could complete the survey by offering specific suggestions on how the business
could lower the potential for their business and its employees to become crime victims.
Howeverall information discussed during the survey should be kept strictly
confidential.”
56
Question five:Does crime prevention officers advise the SMEs owners against crime
occurance?
Response five: “Yes! Crime prevention officers often advise the SMEs owners against
crime occurance whereby SME owners can take an active role in reducing criminal
opportunity in and around their business property by participating in a variety of
crime prevention initiatives, such as “Ulinzi shirikishi program”
4.3.3 Response on the strategies for crime prevention towards SMEs
The researcher sought to examine the strategies for crime prevention towards
SMEs.The descriptive analysis were conducted whereby the descriptive statistic
results as indicated in the Table 4.4 were obtained while showing the list of variables
including surveillance cameras, burglar alarms, use of locks, key control, keeping
minimal cash on hand and security guards or guard dogs as variables representing
strategies for crime prevention towards SMEs.
Table 4.4 Descriptive statistics
N Sum Mean Std. Deviation
Statistic Statistic Statistic Std. Error Statistic
Surveillance cameras 92 406.00 5.0793 .04358 .38980
Burglar alarms
92 412.00 5.1450 .03543 .31698
Use of Locks
92 407.00 5.0925 .04217 .37728
Key control
92
389.00 4.8563 .08221 .73537
Keeping minimal cash on hand
92 291.00 3.6356 .08130 .72714
Security guards or guard dogs
92 414.00 5.1713 .03111 .27830
Valid N (listwise)
92
Source: Field data (2018)
57
The descriptive results in the table 4.4 indicate the description/comparison of means
and whereby Security guards or guard dogs variable were little over greater on average
than Surveillance cameras, Burglar alarms, Use of Locks, Key control, Keeping
minimal cash on hand. Security guards or guard dogs variable having an average of
5.1713, Burglar alarms variable having an average of 5.1450, Use of Locks variable
having an average of 5.0925, Surveillance cameras variable having an average 5.0793,
Key control variable having an average of 4.8563, while Keeping minimal cash on
hand variable having an average of 4.6250.
While in the description/comparison of standard deviation the results indicate that Key
control variable had a standard deviation of 0.73537, Keeping minimal cash on hand
variable had a standard deviation of 0.72714, Surveillance cameras variable had a
standard deviation of .38980, Use of Locks variable had a standard deviation of
0.37728, whereas Burglar alarms variable had a standard deviation of 0.31698, while
Security guards or guard dogs variable had a standard deviation of 0.27830. Therefore
as Key control variable data having a higher standard deviation compared to the rest
of variables, these results entail that the Key control variable data is more spread out
or dispersed than Surveillance cameras, Burglar alarms, Use of Locks, Keeping
minimal cash on hand and Security guards or guard dogs.
Interpretation of the standard deviation
Standard deviation shows how much variation or dispersion exists from the average
(mean), or expected value. More precisely, it is a measure of the average distance
between the values of the data in the set and the mean. A low standard deviation
indicates that the data points tend to be very close to the mean; while a high standard
deviation indicates that the data points are spread out over a large range of values. A
useful property of standard deviation is that, unlike variance, it is expressed in the same
units as the data.
58
In statistics, the standard deviation is the most common measure of statistical
dispersion. However, in addition to expressing the variability of a population, standard
deviation is commonly used to measure confidence in statistical conclusions.
In the line of the obtaining study findings, the researcher also sought to examine
consequences, which are likely to occur when crimes are not highly prevented, How
far does SMEs owners prevent their business from different kinds of crimes and to
determine the crime prevention strategies that SMEs consider more effective.
These questions originate from a set of Interview guide questions as was addressed by
of the SMEs owners as indicated below;
Question oneWhat are the consequences likely to occur when crimes are not highly
prevented??
Response one:“While estimating costs associated with business crime can be difficult,
it is clear that the impact and costs of crime committed within and against businesses
are not shared by that sector alone. Increased expenditures on the criminal justice
system for the taxpayer, higher prices for the consumer, lost revenue for government,
higher insurance premiums for clients, increased fear in the community, job losses for
employees, increased closures affecting the viability of surrounding businesses.”
Question two: How far do you prevent your business from different kinds of crimes?
Response two: “According to my business experience, with regard to security
strategies, I have been always securing my business premises by strengthen doors, fit
window locks and install security lighting. Since each can deter burglars, because
most burglaries are unplanned. However, my access points are vulnerable, therefore
I had to CCTV cameras. Also have an alarm system, which is fitted in my business
premise.”
Question three: What are the crime prevention strategies that you consider more
effective?
59
Response three:“With regard to the crime preventation strategies, there are a number
of strategies that SMEs owners adopt to prevent their business against criminals,
whereas for my experience I have been adopted different strategies including but not
limited to Surveillance cameras, Burglar alarms, Use of Locks, Key control, Keeping
minimal cash on hand, Security guards or guard dogs, Alarm systems, Employee
securing training and Equipment tagging. Among these strategies I have observed that
Security guards or guard dogs strategy was the most effective strategies to prevent my
business from criminals.”
Question four: What Small Medium Enterprises Owners can bring to well planned
crime prevention?
Response four:“Supporting social crime prevention measures, reducing
opportunities for crime through situational crime prevention and environmental
design, helping to strengthen community capacity and helping to prevent recidivism
by assisting in the reintegration of offenders.”
4.3.4 Response on the contribution of crime preventation on the growth of
SMEs
The researcher sought to examine contribution of crime preventation on the growth of
SMEs. The descriptive analysis were conducted whereby the descriptive statistic
results as indicated in the Table 4.5 were obtained while showing the list of variables
including Enhance safety of customers, Enhance confidence in business, Minimize
robbery and burglary risk, Minimize fraud risk and Minimize the theft risk as variables
showing the contribution of crime preventation on the growth of SMEs.
Table 4.5Descriptive statistics
N Sum Mean Std. Deviation
Statistic Statistic Statistic Std. Error Statistic
Enhance safety of customers
92
418.00
5.2238
.01844
.16496
60
Enhance confidence in business 92 415.00 5.1844 .02859 .25576
Minimize robbery and burglary risk 92 410.00 5.1188 .05072 .45370
Minimize fraud risk 92 406.00 5.0794 .04358 .38980
Minimize the theft risk 92 402.00 5.0269 .05507 .49259
Valid N (listwise) 92
Source: Field data (2019)
The descriptive results in the table 4.5 indicate the description/comparison of means
and whereby Enhance safety of customers variable were little over greater on average
than Enhance confidence in business, Minimize robbery and burglary risk, Minimize
fraud risk and Minimize the theft risk. Enhance safety of customersvariable having an
average of 5.2238, Enhance confidence in business variable having an average of
5.1844, Minimize robbery and burglary risk variable having an average of 5.1188,
Minimize fraud risk variable having an average 5.0794, while Minimize the theft risk
variable having an average of 5.0269.
While in the description/comparison of standard deviation the results indicate that
Minimize the theft risk variable had a standard deviation of 0.49259, Minimize robbery
and burglary riskvariable had a standard deviation of 0.45370, Minimize fraud risk
variable had a standard deviation of 0.38980, whereas Enhance confidence in business
variable had a standard deviation of 0.25576, while Enhance safety of customers
variable had a standard deviation of 0.16496. Therefore as Minimize the theft risk
variable data having a higher standard deviation compared to the rest of variables,
these results entail that the Minimize the theft risk variable data is more spread out or
dispersed than Enhance safety of customers, Enhance confidence in business,
Minimize robbery and burglary risk, and Minimize fraud risk.
Interpretation of the standard deviation
Standard deviation shows how much variation or dispersion exists from the average
(mean), or expected value. More precisely, it is a measure of the average distance
61
between the values of the data in the set and the mean. A low standard deviation
indicates that the data points tend to be very close to the mean; while a high standard
deviation indicates that the data points are spread out over a large range of values. A
useful property of standard deviation is that, unlike variance, it is expressed in the same
units as the data.
In statistics, the standard deviation is the most common measure of statistical
dispersion. However, in addition to expressing the variability of a population, standard
deviation is commonly used to measure confidence in statistical conclusions.
In the line of the obtaining study findings, the researcher also sought to examine how
far does crime preventation contributes to the growth of your business.These questions
originate from a set of Interview guide questions as was addressed by of the SMEs
owners as indicated below;
Question six: How far does crime preventation contributes to the growth of your
business?
Response six:“For my business experience, I can say that the impact of crime
prevention on my business and the communities in which they are located can be
substantial. It can contribute the SMEs to attract customers, recruit and retain
employees, boost workplace morale and ensure the productivity of employees, and in
some cases, for the SME owners to stay in business.”
62
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATIONS
6.1Introduction
This section presents a summary, conclusion and recommendations onthe effects of
crime prevention against small and medium business enterprises at Ilala Municipality,
Dar-es-salaam while based on the findings discussed in the previous chapter.
6.2 Summary of the findings based on the research questions
6.2.1 Summary of the findings based on the the relationship between crime
prevention and the growth of SMEs
Based on the findings of the study, it can be summarized that the direction of the
relationship among the identified variables (increase on number of customers,
increases on sales, reduce costs of doing business, boost workers’ morale, and
encourage SMEs owners to stay in the business are positively correlated) implying that
these variables tend to result together in representing the magnitude of growth of
SMEs. Therefore the magnitude or strength of the association/relationship between
crime prevention and the growth of SMEs is absolute strong.
6.2.2 Summary of the findings based on the the types of crimes affecting small
and medium businesses
Based on the findings of the study as analyzed by descriptive analysis, it can be
summarized that among the five identified types crimes affecting small and medium
businesses at Ilala Municipality, which include all burglary, vandalism, cyber crime,
all fraud, all theft, and assaults and threats.
63
6.2.3 Summary of the findings based on the on the strategies for crime
prevention towards SMEs
Based on the findings of the study as analyzed by the descriptive analysis, it can be
summarized that among the strategies for crime prevention towards SMEs that were
used by the SMEs owners include surveillance cameras, burglar alarms, use of locks,
key control, keeping minimal cash on hand and security guards or guard dogs.
6.2.3 Summary of the findings based on the the contribution of crime
preventation on the growth of SMEs
Based on the findings of the study as analyzed by descriptive analysis, it can be
summarized that crime prevention contributes on the growth of SMEs in terms of
enhancing safety of customers, enhancing confidence in business, minimizing robbery
and burglary risk, minimizing fraud risk and minimizing the theft risk.
6.3 Conclusion of the study
This section has condensed the study findings summarized and discussed from the
previous chapter respectively. The findings of the study were generally compared to
the earlier studies whereby comparisons and distinctions were acknowledged. Future
research opportunities and suggestions were discovered and argued with respect to the
findings of the study.
The study concluded that the direction relationship among the identified variables
(increase on number of customers, increases on sales, reduce costs of doing business,
boost workers’ morale, and encourage SMEs owners to stay in the business are
positively correlated). These results entail that there is a strong relationship between
crime preventation and the growth of SMEs.
With respect to the types of crimes affecting SMEs at Ilala Municipality, the study also
concluded that among the types crime include but not limited to all burglary,
vandalism, cyber crime, all fraud, all theft, and assaults and threats. The study further
revealed that theft as the type of crime was found to be mostly regularly reported by
64
SMEs owners at Ilala Police Centre, while the least type of crimes reported at Ilala
Police centre were assaults and threats.
The study also concludes that among the strategies for crime prevention towards SMEs
that were used by the SMEs owners include surveillance cameras, burglar alarms, use
of locks, key control, keeping minimal cash on hand and security guards or guard dogs.
It was determined that the Among these strategies, Security guards or guard dogs
strategy was found to be the most effective strategies to prevent my business from
criminals.
With regard to the contribution of the contribution of crime preventation on the growth
of SMEs, the study concluded that crime prevention contributes on the growth of
SMEs in terms of enhancing safety of customers, enhancing confidence in business,
minimizing robbery and burglary risk, minimizing fraud risk and minimizing the theft
risk.
The study further established that crime preventation is significant as it contributes to
the growth of SMEs by attracting customers, recruit and retain employees, boost
workplace morale and ensure the productivity of employees, and in some cases, for
the SME owners to stay in business.
6.4 Recommendations of the study
In the light of the summary of the findings of this study and the conclusion above, the
following are the recommendations drained from the study, which are put forward with
the view of the effect of crime preventation towards the growth of SMEs at Ilala
Municipality. Among the efforts that crime prevention stakeholders need to consider
in order to prevent crimes occurance include the following;
6.4.1 Recommendations to the management of Ilala Police centre
By considering the findings of the study, it is recommended to the management of Ilala
Police centre that since there is significant relationship between crime prevention and
65
the growth of SMEs, then management of Ilala Police centre needs to ensure that the
police officers undertake their duty of conducting survey to different business premises
and advise SMEs and the commuinty effectively on how to prevent their business from
being attacked by criminals.
6.4.2 Recommendation to SMEs owners
This study recommends that SMEs owners should understand that,the policemen can
get along with them at any time to discuss trends in local crime and not after a crime
has take place. They would give them both information specific to their business and
general advice about how to handle robberies.
Also it is recommended that SMEs owners should understand that Crime Prevention
is the responsibilityof every business owner. Therefore they should work with the
police to secure their businesses. Small Business Crime Prevention strategies must
remain vigil and fluid; their adopted crime strategies must change as the crimes
change.
6.4.4 Recommendations for further research
This research study provides an opportunity for further research as they have been
identified from the presented and discussed research findings. However the limitations
of this study create a number of opportunities for further research whereby the
following areas for further research were discovered.
The researcher recommends that, since the study has used a case study design
considering the nature of scope and limited to only SMEs belonged at Ilala
Municipality however the findings of the study will not be necessarily applicable to
the rest of the Mucipality in Dar es Salaam and in Tanzania at large. Therefore more
studies should be conducted on the subject matter while taking a case of different
SMEs belonged from different Municipality in order to compare/contrast if the
findings obtained pertaining the same study topic will be either consistent or
inconsistent.
66
In addition to the given areas for further research, the researcher also suggests that
another study need to be conducted while focusing on exploring the extent to which
crime prevention has an impact to community. There appears to be no systematic
research, which estimates the consequences of crime for business viability, though this
would be most useful. It is clear, however, that crime can be a very significant cost.
However it should be considered that crime may not only lead some businesses to fail,
but may also lead others to relocate. Therefore the activities pertaining crime
preventation should be considered not only by SMEs owners but also the entire
community in order ensure attractive and safety business environment.
67
REFERENCES
American Educational Research Association, American Psychological Association, &
National Council on Measurement in Education (1999). Standards for
educational and psychological testing. Washington, D.C.: American
Educational Research Association.
Bressler, M. (2009). The Impact of Crime on Business: A Model for Prevention,
Detection & Remedy. Journal of Management & Marketing Research, Volume
2, 85-96.
Bressler, M. S. (2009). The impact of crime on business: A model for prevention,
detection & remedy. Journal of management and Marketing Research, 2(1),
12-20.
Burrows, J. & Hopkins, M. 2005. Business and crime in Tilley. Handbook of crime
prevention and community safety. Devon, Willan Publishing.
Capobianco, L. (2005): Sharpening the Lens: Private Sector Involvement in Crime
Prevention. A Background Paper for International Centre for Prevention of
Crimes (ICPC).
Crowe, T. D., & Fennelly, L. J. (2013). Crime prevention through environmental
design. Amsterdam: Elsevier.
Dictionary, C. (2008). Cambridge advanced learner’s dictionary. Recuperado de:
https://dictionary. cambridge. org/es/diccionario/ingles/blended-learning.
Dictionary, M. E. (2008). For Advanced Learners of American English.
Felson, M., & Boba, R. L. (Eds.). (2010). Crime and everyday life. Sage.
Gbetnkom, D. (2012). Corruption and small and medium-sized enterprise growth in
Cameroon. Inclusive Growth in Africa: Policies, Practice, and Lessons Learnt,
37-58.
68
Guidelines for the Prevention of Crime ECOSOC Resolution 2002/13, Annex accessed
athttps://www.unodc.org/documents/justice-and-prison reform/crime
prevention /resolution_2002-13.pdf on 08th May 2019.
Guidelines for the Prevention of Crime, ECOSOC Resolution 2002/13 accessed at
HYPERLINK "https://www.unodc.org/unodc/en/justice-and-prison"
\hhttps://www.unodc.org/unodc/en/justice-and-prison
reform/CrimePrevention.html
Gupta M., Gupta D., (2011): Research Methodology. PHI Learning Pvt. Ltd., India.
Hendrickson, D. (2017). List of Three Crimes That Affect Businesses. Retrieved May
17, 2019, from HYPERLINK "https://smallbusiness.chron.com/list-three-
crimes-affect-businesses-64360.html" \hhttps://smallbusiness.chron.com/list-
three-crimes-affect-businesses-64360.html
Ilala municipal comprehensive Health Plan 2002/3; Dar es Salaam region profile 1999;
Environmental Profile for Dar es salaam City.
Islam, A. (2014). Economic growth and crime against small and medium sized
enterprises in developing economies. Small Business Economics, 43(3), 677-
695.ISSN: 1941-3408.
Islam, A. (2014). Economic growth and crime against small and medium sized
enterprises in developing economies. Small Business Economics, 43(3), 677-
695.
Kilimyi. N. (2013): Challenges facing small and medium enterprises in developing
countries.
Kushnir, (2010). A universal definition of small enterprises: A procrustean bed for
SMEs
69
Law Handbook, (2017). Legal services Commission of South australia. Legal Help for
all South Australians.
Levisohn, B. (2009). Experts Say Fraud Likely to Rise. Business Week Online.
January 12, 2009: 14-14. Available from: Business Source Complete, Ipswich,
MA.
Mfaume, R. and Leonard, W. (2004). Small Business Entrepreneurship in Dar es
Salaam -Tanzania: Exploring Problems and Prospects for Future Development.
School of Public Administration, Mzumbe University, Tanzania.
Mfaume, R. M., & Leonard, W. (2004). Small business entrepreneurship in Dar es
Salaam-Tanzania: Exploring problems and prospects for future development.
Michael, M. (2014). Assessing Crime Prevention by Tanzania Police Force: A Case
of Chamwino-Dodoma (Doctoral dissertation, The Open University of
Tanzania).
Mohamed, N. (2015). A Study on Prevention, Detection, and Remedy of Crimes in
Business. City University College of Ajman.
Motta, V. (2017). The impact of crime on the performance of small and medium-sized
enterprises: Evidence from the service and hospitality sectors in Latin
America. Tourism Economics, 23(5), 993-1010.
Motta, V. (2017). The impact of crime on the performance of small and medium-sized
enterprises: Evidence from the service and hospitality sectors in Latin
America. Tourism Economics, 23(5), 993-1010.
Motta, V. (2017). The impact of crime on the performance of small and medium-sized
enterprises: Evidence from the service and hospitality sectors in Latin
America. Tourism Economics, 23(5), 993-1010.
70
Mundia, L., Matzin, R., Mahalle, S., Hamid, M. H., & Osman, R. S. (2016).
Contributions of sociodemographic factors to criminal behavior. Psychology
research and behavior management, 9, 147–156. doi:10.2147/PRBM.S95270
N’Guilla Sow, A., Basiruddin, R., Mohammad, J., & Abdul Rasid, S. Z. (2018). Fraud
prevention in Malaysian small and medium enterprises (SMEs). Journal of
Financial Crime, 25(2), 499-517.
P.E. Petrakis, P.C. Kostis, 2012. The role of knowledge and trust in SMEs. Journal of
knowledge Economy, DOI.
Sachdeva, J., K., Business Research Methodology, Himalaya Publications,
2010,(pp.109,141).
Shanmugam, J. K., Haat, M. H. C., & Ali, A. (2012). An exploratory study of internal
control and fraud prevention measures in SMEs. Small, 100, 18-2.
Shanmugam, J. K., Haat, M. H. C., & Ali, A. (2012). An exploratory study of internal
control and fraud prevention measures in SMEs. Small, 100, 18-2.
Short, J. (1980). An Investigation of the Relationship between Crime and Business
Crime.
Sifuna, F. M. (2018). The Impact of Crime on Business Performance in Kenya: A Case
of Small Scale and Micro Enterprises in Garissa Town.
Sitharam, S., & Hoque, M. (2016). Factors affecting the performance of small and
medium enterprises in KwaZulu-Natal, South Africa. Problems and
perspectives in Management, 14(2), 277-288.
Small and Medium Enterprise Development Policy, 2002. Tanzania
Statistical abstract, 2011. Tanzania National Bureau of Statistics.
71
Taylor, N. (2002). Under-reporting of crime against small businesses: attitudes toward
police and reporting practices. Policing & Society, 13(1), 79-89.
The Citizen Newspaper, 2017: Tanzania: How Ilala Municipality Grapples With
Problem of Vendors.
Tilley, N. (1993). The prevention of crime against small businesses: The Safer Cities
experience (p. 45). London: Home Office.
U.S. Bureau of Justice Statistics: Cybercrime against Businesses, 2005.
Wikipedia online reference HYPERLINK
"http://en.wikipedia.org/wiki/Ponzi_scheme"
\hhttp://en.wikipedia.org/wiki/Ponzi_scheme.
Zaben, S. (2004). United Nations Office on Drugs and Crime. Retrieved April 17,
2019,fromhttps://www.unodc.org/unodc/en/justice-and-prison-
reform/CrimePrevention.html
72
APPENDICES
Appendix (i) Research questionnaire
Research questionnaires for the SMEs owners from Ilala Municipality
Dear Participants
I iiamMohamed Ally Salumiia iistudent iiofMaster of Business Administration in
Corporate Management of Mzumbe University,iiDar iies iiSalaam Campus. i iI
iiam iiconducting iia iiresearch iiwith iithe iiaim iiof iiidentifying ii“The Effects of
Crime Prevention on Small and Medium Business Enterprises” iias iipart iiof iimy
iiMasters iiDissertation iirequirement. iiThis iiis iipurely iifor iiacademic iipurposes
iiand iiany iiinformation iiyou iiprovide iiwill iinot iibe iidisclosed iiand iia iihigh
iilevel iiof iiconfidentiality iiwill iibe iimaintained.
Kindly iicircle iiin iithe iiappropriate iispace iior iifill iiin iithe iiblanks
PART iiA: iiDEMOGRAPHIC iiINFORMATION
1. iiYour iiGender;
a) Male.
b) Female.
2. iiYour iiAge; ii
a) 25-35.
b) 36-45.
c) 46 iiand iiabove.
73
3. iiHow iilong iihave iiyou iibeen doing business?
a) Below ii5 iiyears.
b) 6- ii10 iiyears.
c) 11 ii-15 iiyears. ii ii
d) 16 iiyears iiand iiabove.
PART iiB: iiRelationship iibetween crime prevention and the growth of SMEs
4. Examine the relationship between crime prevention and the growth of SMEs?
Consider the following list of variables stand for the growth of SMEs.
1) Boost workers’ morale
2) Encourage SMEs to continue with business
3) Reduce costs of doing business
4) Increase number of customers
5) Increases sale
PART iiC: Types of crimes prevalent to small and medium businesses in Ilala
Municipality
5. What are the types of crimes prevalent to small and medium businesses in Ilala
Municipality?
PART iiD: Strategies for crime prevention in small and medium businesses
6. What are strategies for crime prevention that adopted in the small and medium
businesses?
74
PART E: To what extent crime prevention strategies contribute to the growth of
SMEs
7. Please iishow iito iiwhatextent crime prevention strategies contribute to the growth
of SMEs?
S/N To what extent crime
prevention strategies
contribute to the growth of
SMEs
Very
iiLarge
iiExtent
ii(5)
Large
iiExtent
ii(4)
Small
iiExtent
ii(3)
Very
iiSmall
iiExtent
ii(4)
No
iiExtent
ii(1)
1. Surveillance cameras
2. Burglar alarms
3. Use of Locks
4. Key control
5. Keeping minimal cash on
hand
6. Security guards or guard
dogs
PART iiF: Contribution of crime prevention on the growth of SMEs CO
8. To what extent crime prevention contributes to the growth of SMEs?
S/
N
To what extent crime
prevention contributes to
the growth of SMEs
Very
iiLarge
iiExtent
ii(5)
Large
iiExtent
ii(4)
Small
iiExten
t ii(3)
Very
iiSmall
iiExtent
ii(4)
No
iiExte
nt ii(1)
1. Enhance safety of customers
2. Enhance confidence in
business
3. Minimize robbery and
burglary risk
4. Minimize fraud risk
5. Minimize the theft risk
Thank iiyou iivery iimuch iifor iiyour iicooperation iiand iiassistance iiin
iianswering iithese iiquestions
75
Appendix (ii) Research questionnaire
Research questionnaires for the Police officers from Ilala Police Centre
Dear Participants
I iiamMohamed Ally Salumiia iistudent iiofMaster of Business Administration in
Corporate Management of Mzumbe University,iiDar iies iiSalaam Campus. i iI
iiam iiconducting iia iiresearch iiwith iithe iiaim iiof iiidentifying ii“The Effects of
Crime Prevention on Small and Medium Business Enterprises” iias iipart iiof iimy
iiMasters iiDissertation iirequirement. iiThis iiis iipurely iifor iiacademic iipurposes
iiand iiany iiinformation iiyou iiprovide iiwill iinot iibe iidisclosed iiand iia iihigh
iilevel iiof iiconfidentiality iiwill iibe iimaintained.
Kindly iicircle iiin iithe iiappropriate iispace iior iifill iiin iithe iiblanks
PART iiA: iiDEMOGRAPHIC iiINFORMATION
1. iiYour iiGender;
c) Male.
d) Female.
2. iiYour iiAge; ii
d) 25-35.
e) 36-45.
f) 46 iiand iiabove.
3. Working experience J
e) Below ii5 iiyears.
f) 6- ii10 iiyears.
g) 11 ii-15 iiyears. ii ii
h) 16 iiyears iiand iiabove.
76
4. ii iiWhich iiDepartment iiare iiyou iiworking?
a) Crime preventation unit department,
b) Criminal investigation department,
c) Cyber crime department
d) General duty department
5. Among the following types of crimes which one is mostly often reported to the
police by the SMEs owner from Ilala Municipality?
Types of crimes Tick ( )
Vandalism
Cyber crime
All fraud
All theft
Assault and threats
77
Appendix (iii) Interview guide questions
Interview guide questions for the Small Medium Enterprises Owners at Ilala
Munipacility
1. What Small Medium Enterprises Owners can bring to well planned crime
prevention?
2. How far does crime preventation contributes to the growth of your business?
3. What are the consequences likely to occur when crimes are not highly prevented??
4. How far do you prevent your business from different kinds of crimes?
5. What are the crime prevention strategies that you consider more effective?
78
Appendix (iv) Interview guide questions
Interview guide questions for the Police officers from Ilala Police Centre
1. How could SMEs owner respond to crimes?
2. What are the impacts when crimes are not reported to the police?
3. Could crime prevention officers visit the SMEs owners and evaluate their physical
and procedural security measures?
4. Does the crime prevention officers conduct a security survey towards SMEs
owners?
5. Does crime prevention officers advise the SMEs owners against crime occurance?
i
