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11. Glossary 1
Appendix 1
All Locations
22 June 2016 Supported by
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Provided under contract to The Asian Development Bank
By
Brian Barge (Individual Consultant)
with support of
The Evidence Network Inc.
www.theevidencenetwork.com
Report Structure We have created this report as the appendix to the main report, provided separately. In this report we present
our in-depth assessment of the venture support programs in Da Nang, Ho Chi Minh City, and Phnom Penh including the detailed analyses and diagrams.
The Mekong Business Initiative (MBI)
The Evidence Network would like to thank the Australian Government’s Mekong Business Initiative for supporting the preparation of this report. MBI is an advisory facility that
promotes private sector development in Cambodia, the Lao People’s Democratic Republic (Lao PDR), Myanmar, and Vietnam. MBI fosters development of the innovation ecosystem by
supporting business advocacy, alternative finance and innovation. It is supported by the Government of Australia and the Asian Development Bank.
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2
The views expressed in this report are those of the authors and do not necessarily reflect the views and policies of the Government of Australia, or of the Asian Development Bank (ADB) and its Board of Governors and the governments represented by ADB.
ADB and the Government of Australia do not guarantee the accuracy of the data in this report and accept no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB or the Government of Australia in preference to others of a similar nature that are not mentioned.
By making any designation of, or reference to, a particular territory or geographic area, or by using the term “country” in this document, ADB and the Government of Australia do not intend to make any judgments about the legal or other status of any territory or area.
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TableofContents 3
Contents
1.TEN’sMethodology. ..........................................................................................4
2.DescriptionofSample. ......................................................................................5
3.DemographicsoftheRandomSampleofYoungCompanies. .............................8
4.DemographicsoftheParticipantsintheVentureSupportProgramsinAllLocations. ............................................................................................................23
5.UseofServicesbyVentureSupportProgramParticipants. ..............................38
6.ImpactonResourcesandCapabilitiesofVentureSupportProgramParticipants. ..........................................................................................................................44
7.ImpactonPerformanceofVentureSupportProgramParticipants. ..................52
8.PredictorsofSelectionforSupport. .................................................................58
9.PredictorsofCompanyGrowth. .......................................................................62
10.PredictorsofImpact. .....................................................................................71
11.GlossaryofTerms. .........................................................................................93
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4 VietnamandCambodiaImpactAssessment
Figure'8.1'Innova0on'Intermediary'Logic'Model'
©"The"Evidence"Network"
IMPACT'ON'CHANGE"''''ACTIVITIES"
OBJECTIVE'
Na0onal'Compe00veness''''''''''Community,'Regional,'Economic'Development''''''''''Industry'Strength''''''''''Viable'New'Ventures'
INPUTS"
• Knowledgeable'people'• Rela0onships'• Equipment,'facili0es'
• Funding'
• Business,'science'and'technology'knowledge,''
equipment,'facili0es'
• Business,'research,'''technology'rela0onships'
• Design,'tes0ng,'prototyping,'scaleSup,'IP'management,'
licensing'services'
• Plans,'proposals,'projects'• Events,'conferences,'seminars,'mee0ngs'
• Websites,'blogs,'reports,''
directories,'newsleVers'
•'Financing'
Impact'on'Change:''• Products,'services'• Time'to'market'
• Market'share'
• Employment'• Environmental'impact'
• Revenues'• Valua0on'• Investment'
Impact'on'Change:''• Sustainable'wealth'and'jobs'• Environmental'and'health'
care'improvement'
• Increased'community,'''regional,'na0onal,'economic'
and'social'wellness'
RESOURCES'&'CAPABILITIES' PERFORMANCE' SOCIOSECONOMIC'
Impact'on'Change:''• Knowledge,'exper0se'• Opportuni0es'for''''promo0on,'influence'
• Business'and'research''''linkages'
• Access'to'technology''''services'
• Access'to'financing'• Access'to'complementary'''
business'inputs'
1.TEN’sMethodology ThemethodologyemployedbyTheEvidenceNetworkInc.(TEN)isrepresentedinthelogicmodelforinnovationintermediariesshownbelowinFigure1.1.Thelogicmodelillustrateshowinnovationintermediariesworktofulfilltheirmissions,andhowTENmeasurestheirimpact.Theterminnovationintermediarybroadlyencompassesbusinesssupportprogramsthatoperatetofurtherthedevelopmentofbusiness,andincludesexportandinternationalisationsupport.
Asshownatthetopofthefigure,innovationintermediariesexpresstheirobjectivesintermsofenhancingnationalcompetitiveness,advancingregionaleconomicdevelopment,bolsteringindustrystrength,orsupportingviablenewventures.
TEN’slogicmodelexpressestheexpectationthatinnovationintermediaryactivitiescreateshorter-termimpactsoncompanies’resourcesandcapabilities,whichleadtosubsequentimpactsoncompanyperformance,andultimatelyleadtolonger-termimpactsintheformofsocio-economicbenefits,anexpectationthatholdsacrossalltypesofinnovationintermediaries.Detailsofhowinnovationintermediariesachievetheirdesiredimpactsareshowninthelowerpartofthefigure.Knowledge-basedandtangibleinputsleadtoawiderangeofactivitiessuchasprovisionofknowledge,relationships,events,publications,prototypes,equipment,andfacilities.Theactivitiesareexpectedtolead,inturn,totheshorter,medium,andlonger-termimpactsdescribedabove.
Statisticalexaminationsoftherelationshipsbetweentheuseofservicesoffered,impactonresourcesandcapabilities,andimpactsoncompanyperformancemakeitpossibletoassesswhichservicesandimpactsonresourcesandcapabilitiesaresignificantlyrelatedtotheimpactoftheintermediaryoncompanies’performanceinthemarket.
Figure1.1:TEN’sInnovationIntermediaryLogicModel
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2.DescriptionofSample 5
Table2.1ResponseRatebyVentureSupportProgram
2.DescriptionofSample
InJuneof2016,206outof274companiesthathadparticipatedinventuresupportprogramsrespondedtoaweb-basedsurvey.Table2.1providesfurtherdetailsontheresponseratebyprogram.Duringthesameperiodthe309entrepreneursrepresentingarandomsampleofyoungcompaniesoperatinginDaNangwereinterviewed.
WehavebeenaskedtoexcludethosecompaniessupportedbytheDaNangSMEAssociationfromtheanalysissampleonthebasisthatprogrammingoftheDaNangSMEAssociationdifferssubstantivelyfromtheotherventuresupportprograms,andthereforecannotbeconsideredinthesameanalysiscontext.AllanalysesofimpactthereforeexcludetheDaNangSMEAssociationincludingthedescriptionsinAppendix1(AllLocations),andAppendix2(DaNang).Wehave,however,includedthe
1TheBusinessStartupSupportCentre(BSSC)hasapproximately100clients.However,wedonothaveinformationontheresponseratefortheBSSC,astheyprovidedthesurveylinktotheirclientsdirectly.Asaresult,wedonotincludetheBSSCintheoverallresponseratecalculation.
Location Program ProgramSize Invitations Respondents ResponseRate
PhnomPenh
EmergingMarkets 8 7 6 86%
MinistryofCommerce101program 87 83 58 70%
NationalBusinessPlanCompetition 20 14 70%
WeCreate 18 17 14 82%
NOMINetwork 20 10 8 80%
Total 133 137 100 73%
HoChiMinhCity
BusinessStartupSupportCentre 100 10 ArgiBusinessIncubator 17 6 35%
BusinessIncubationandInnovationCentre–NguyenTatThanhUniversity 15 8 5 63%
NongLamUniversity–CenterforTechnologyBusinessIncubation 9 3 33%
SaigonHi-TechPark–IncubationCenter ~20 16 8 50%
InformationTechnologyPark–VietnamNationalUniversityinHCMC ~10 16 11 69%
QuangTrungSoftwareBusinessIncubationCenter 10 9 7 78%
HoChiMinhCityUniversityofTechnology–TechnologicalBusinessIncubator 6 5 83%
Total 141 81 551 56%
DaNang
DaNangBusinessIncubator 8 8 8 100%
CollegeofInformationIncubator 15 15 13 87%
DaNangSMEAssociation 500 33 20 61%
Total 523 56 41 73%
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6 VietnamandCambodiaAppendix
SMEAssociationinouraggregatepresentationsofcompanyandentrepreneurcharacteristics,onthepremisethattheSMEAssociationsupportscompanies(albeitindifferentwaysthantheincubators),andthenumberofrespondentsthatengagedwiththeDaNangSMEAssociationconstitutearelativelysmallportionofthetotalpopulation(20of206respondents).
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3.DemographicsoftheRandomSample 7 7
TheRandomSampleofYoungCompanies
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8 VietnamandCambodiaAppendix
3.DemographicsoftheRandomSampleofYoungCompaniesThissectionofthereportprovidesinformationonthe309entrepreneurs,andcompanyrespondentsfromtherandomsampleofyoungcompaniesoperatinginDaNang.FirmCharacteristicsoftheRandomSampleofYoungCompanies
Theanalysisofthedemographicsoftherandomsampleofyoungcompaniesrevealedthat:• 71%ofcompaniesgeneratelessthan5BVNDinannualrevenues• 74%havenotreceivedfunding• 75%haveoneortwofull-time,paidfounders;80%donothaveanyfull-timeunpaid
founders• 44%havethreetofivefull-timepaidemployees;54%donothaveanyfull-timeunpaid
employees• 75%havesomepercentageofthefoundersoremployeesintheircompanywithdomestic
displacementexperience;88%havenofoundersoremployeesthathavestudiedorworkedoutsideVietnam
• 34%havemorethan65%oftheirfoundersoremployeeseducatedwithcollegeoruniversitydegrees
• 46%donothaveanyfoundersoremployeesthatarefamilymembers• 72%havemodestgrowthplans;15%havehighgrowthplans• 79%donothaveawebsite• 23%operateintheconstructionsector;17%operateintheretailorwholesalesector• 35%werefoundedin2015;13%werefoundedin2016
Webeginbyprovidinginformationaboutthecompanies’annualrevenues,financialsupportreceived,employeedemographics,internationalanddomesticdisplacementexperience,growthplans,yearfounded,industrialsector,andcompanywebsite.Figuresdescribingthesurveyedcompaniesfollow,accompaniedbythecorrespondingsurveyquestions,numberofrespondents(n),andanalysisfindings.
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3.DemographicsoftheRandomSample 9 9
Figure3.1
Whatareyourcompany’sannualrevenues?n=300
Findings:
• 71%ofrespondentsreportedthattheircompanygenerateslessthan5BVNDinannualrevenues.• 21%ofrespondentsreportedthattheircompanyispre-revenue.
Figure3.2
Hasyourcompanyreceivedfunding?n=301
Finding:
• 74%ofrespondentsreportedthattheircompanyhasnotreceivedfunding.
0
20
40Pe
rcen
tageofR
espo
nden
ts
Pre-revenue
<500MVND
500-999MVND
1-4.9BVND
5-9.9BVND
10-19.9BVND
20-49.9BVND
50BVNDormore
AnnualRevenues
0
20
40
60
80
Percen
tageofR
espo
nden
ts
Grant Loan EquityInvestment
CompetitionPrize
NoFunding
FinancialSupport
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10 VietnamandCambodiaAppendix
Figure3.3
Howmanyfull-timepaidfoundersarethereinyourcompany?n=283
Finding:
• 75%ofrespondentsreportedthattheircompanyhasoneortwofull-timepaidfounders.
Figure3.4
Howmanyfull-timeunpaidfoundersarethereinyourcompany?n=173
Finding:
• 80%ofrespondentsreportedthattheircompanydoesnothaveanyfull-timeunpaidfounders.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timePaidFounders
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timeUnpaidFounders
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3.DemographicsoftheRandomSample 11 11
Figure3.5
Howmanyfull-timepaidemployeesarethereinyourcompany?n=290
Findings:
• 44%ofrespondentsreportedthattheircompanyhasthreetofivefull-timepaidemployees.• 35%ofrespondentsreportedthattheircompanyhassixormorefull-timepaidemployees.
Figure3.6
Howmanyfull-timeunpaidemployeesarethereinyourcompany?n=200
Finding:
• 54%ofrespondentsreportedthattheircompanydoesnothaveanyfull-timeunpaidemployees.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timePaidEmployees
0
20
40
60
Percen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timeUnpaidEmployees
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12 VietnamandCambodiaAppendix
Figure3.7
Howmanyfoundersoremployeesinyourcompanyarefamilymembers?n=305
Finding:
• 46%ofrespondentsreportedthattheircompanydoesnothaveanyfoundersoremployeesthatarefamilymembers.
Figure3.8
Howmanyfoundersoremployeeswithcollegeoruniversitydegreesarethereinyourcompany?n=307
Finding:
• 34%ofrespondentsreportedthatmorethan65%ofthefoundersoremployeesintheircompanyhavecollegeoruniversitydegrees.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeesthatareFamilyMembers
0
20
40
Percen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithUniversityDegrees
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3.DemographicsoftheRandomSample 13 13
Figure3.9
Howmanyfoundersoremployeesinyourcompanyhaveworkedoutsidethetownorcitywheretheygrewup?n=301
Finding:
• 75%ofrespondentsreportedthatsomepercentageofthefoundersoremployeesintheircompanyhaveworkedoutsidethetownorcitywheretheygrewup.
Figure3.10
HowmanyfoundersoremployeesinyourcompanyhavestudiedorworkedoutsideVietnam?n=292
Finding:
• 88%ofrespondentsreportedthatnoneofthefoundersoremployeesintheircompanyhavestudiedorworkedoutsideVietnam.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithDomesticDisplacementExperience
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithInternationalDisplacementExperience
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14 VietnamandCambodiaAppendix
Figure3.11
Whatareyourcompany’srevenuegrowthplans?n=307
Findings:
• 72%ofrespondentsreportedthattheircompanyhasmodestgrowthplans.• 15%ofrespondentsreportedthattheircompanyhashighgrowthplans.
Figure3.12
Whenwasyourcompanyfounded?n=301
Findings:
• 35%ofrespondentsreportedthattheircompanywasfoundedin2015.• 13%ofrespondentsreportedthattheircompanywasfoundedin2016.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
Lowergrowth Nogrowth Modestgrowth Highgrowth
CompanyGrowthPlans
0
20
40
Percen
tageofR
espo
nden
ts
2011orearlier 2012 2013 2014 2015 2016
YearFounded
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3.DemographicsoftheRandomSample 15 15
Figure3.13
Inwhatindustrialsectordoesyourcompanybelong?n=309
Findings:
• 23%ofrespondentsreportedthattheircompanyoperatesintheconstructionsector.• 17%ofrespondentsreportedthattheircompanyoperatesintheretailorwholesalesector.
Figure3.14
Doesyourcompanyhaveawebsite?n=308
Finding:
• 79%ofrespondentsreportedthattheircompanydoesnothaveawebsite.
0 20 40PercentageofResponses
ConstructionRetailorWholesale
OtherProfessionalorBusinessServices
TourismHoteloraccommodation
MaterialsorManufacturingTransportationorLogistics
EducationalServicesInformationorCommunicationsHardware
SoftwareFoodProcessing
AgricultureHealth,Medical,orBiotechnology
EntertainmentRestaurantorFoodandBeverageServices
Energy,Mining,orForestryEnvironment
FisheriesorAquaculture
IndustrialSector
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
Yes No
Website
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16 VietnamandCambodiaAppendix
EntrepreneurCharacteristicsoftheRandomSampleofYoungCompanies
Theanalysisoftheentrepreneursoftherandomsampleofyoungcompaniesrevealedthat:• 61%ofentrepreneursare36orolder• 65%aremale• 55%haveacollegeoruniversitycertificate• 92%havenotstudiedorworkedoutsideofVietnam• 88%didnothaveafamilybusiness• 90%hadaninternshipasastudent;ofthosewhohadaninternship,72%wereemployed
byaprivatecompany• 62%hadfiveormoreyearsofworkexperiencepriortofoundingtheircompany• 34%donothaveaFacebookaccount;32%have100–499Facebookfriends
Thissectionprovidesinformationabouttheentrepreneurs’age,gender,levelofeducation,internationalexperience,priorexperienceinfamilybusiness,internshipexperience,priorworkexperience,andFacebooknetwork.Figuresdescribingthesurveyedentrepreneursfollow,accompaniedbythecorrespondingsurveyquestions,numberofrespondents(n),andanalysisfindings.
Figure3.15
Whatisyourage?n=302
Finding:
• 61%ofrespondentsreportedthattheyare36yearsoldorolder.
0
20
40
Percen
tageofR
espo
nden
ts
25orunder 26-30 31-35 36-40 41-45 46-50 Over50
Age
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3.DemographicsoftheRandomSample 17 17
Figure3.16
Whatisyourgender?n=308
Finding:
• 65%ofrespondentsreportedthattheyaremale.
Figure3.17
Whatisyourhighestlevelofeducation?n=305
Finding:
• 55%ofrespondentsreportedthattheyhaveacollegeoruniversitycertificate.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
Male Female Prefertonotrespond
Gender
0 20 40 60PercentageofRespondents
Primaryschoolcertificate
Juniorhighschoolcertificate
Somehighschool
Highschoolcertificate
Somecollegeoruniversity
Collegeoruniversitycertificate
Master'sorPhD
LevelofEducation
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18 VietnamandCambodiaAppendix
Figure3.18
HaveyoustudiedorworkedoutsideofVietnam?Pleaseselectallthatapply.n=286
Finding:
• 92%ofrespondentsreportedthattheyhavenotstudiedorworkedoutsideofVietnam.
Figure3.19
Didyourparentsownabusiness?n=304
Finding:
• 88%ofrespondentsreportedthattheirparentsdidnotownabusiness.
0
20
40
60
80
100Pe
rcen
tageofR
espo
nses
NotstudiedorworkedoutsideVietnam Studiedorworkedinaforeigncountry
InternationalExperience
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
Yes No
FamilyBusiness
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3.DemographicsoftheRandomSample 19 19
Figure3.20
Didyouworkinyourparents’business?n=36
Finding:
• Ofthosethatreportedtheirparentsownedabusiness,50%reportedthattheyworkedinthatbusiness.
Figure3.21
Didyouhaveaninternshipasastudent?n=249
Finding:
• 90%ofrespondentsreportedthattheyhadaninternshipasastudent.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
Yes No
WorkinFamilyBusiness
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
Yes No
Internships
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20 VietnamandCambodiaAppendix
Figure3.22
Pleasespecifyyourinternshipemployer?n=225
Finding:
• Ofthoserespondentsthathadaninternship,72%reportedthattheirinternshipemployerwasaprivatecompany.
Figure3.23
Beforefoundingyourcompany,howmuchworkexperiencedidyouhave?n=303
Finding:
• 62%ofrespondentsreportedthattheyhadfiveormoreyearsofworkexperiencepriortofoundingtheircompany.
0 20 40 60 80PercentageofRespondents
Aprivatecompany
Anagencyorgovernmentorganization
Anon-governmentalorganization(NGO)
Auniversity,hospital,orotherNPO
Other
InternshipEmployer
0
20
40
Percen
tageofR
espo
nden
ts
Noworkexperience <5years 5-10years >10years
WorkExperiencePriortoFoundingCompany
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3.DemographicsoftheRandomSample 21 21
Figure3.24
HowmanyFacebookfriendsdoyouhave?n=293
Findings:
• 34%ofrespondentsreportedthattheydonothaveaFacebookaccount.• 32%ofrespondentsreportedthattheyhave100–499Facebookfriends.
0
20
40Pe
rcen
tageofR
espo
nden
ts
NoFacebookaccount
<100friends 100-499friends
500-999friends
1,000ormorefriends
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22 VietnamandCambodiaAppendix
VentureSupportProgramParticipants–AllLocations
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4.DemographicsofProgramParticipants 23 23
4.DemographicsoftheParticipantsintheVentureSupportProgramsinAllLocationsThissectionofthereportprovidesinformationonthe196entrepreneurs,andcompanyrespondentsfromthosecompaniesparticipatingintheventuresupportprogramsoperatinginDaNang,HoChiMinhCity,andPhnomPenh.
FirmCharacteristicsoftheVentureSupportProgramParticipants
Theanalysisofthedemographicsofcompaniesparticipatingintheventuresupportprogramsacrossalllocationsrevealedthat:• 34%companiesarepre-revenue;38%generatelessthan$50KUSDinannualrevenues• 35%receivedfinancialsupport• 53%haveoneortwofull-time,paidfounders• 25%havemorethantenfull-time,paidemployees;25%havethreetofive• 37%haveoneortwofull-time,unpaidemployees• 53%donothaveanyfoundersoremployeesthatarefamilymembers• 61%havemorethan65%ofthefoundersoremployeesintheircompanywithuniversity
degrees• 48%havemorethan65%ofthefoundersoremployeeswithdomesticdisplacement
experience• 54%ofrespondentshavefoundersoremployeeswithinternationaldisplacement
experience• 34%havehighgrowthplans;55%havemodestgrowthplans• 57%werefoundedin2014–2016• 25%operateinthesoftwaresector;18%operateintheinformationorcommunications
hardwaresector• 60%haveawebsite• 71%joinedtheprogramtonetworkwithotherentrepreneurs• 53%firstengagedwiththeirprogramin2015;23%ofrespondentsfirstengagedwith
theirprogramin2016
Webeginbyprovidinginformationaboutthecompanies’annualrevenues,financialsupportreceived,employeedemographics,internationalanddomesticdisplacementexperience,growthplans,yearfounded,industrialsector,companywebsite,reasonsforjoiningtheprogram,andyearoffirstengagement.Figuresdescribingthesurveyedcompaniesfollow,accompaniedbythecorrespondingsurveyquestions,numberofrespondents(n),andanalysisfindings.Foreachmeasurewefirstpresentthefindingsforthewholesampleoftheventuresupportprogramparticipants,followedbythechartsandfindingsforeachoftheparticipatingcities.
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24 VietnamandCambodiaAppendix
Figure4.1
Whatareyourcompany’sannualrevenues?n=170
Findings:
• 34%ofrespondentsreportedthattheircompanyispre-revenue.• 38%ofrespondentsreportedthattheircompanygenerateslessthan$50Kinannualrevenues.
Figure4.2
Hasyourcompanyreceivedfunding?Pleaseselectallthatapply.2n=172
Finding:
• 35%ofresponsesindicatereceiptofoneormoretypesoffinancialsupport.
2Respondentswereaskedtoselectalltypesofapplicablefinancing,thereforethepercentagesadduptoavaluegreaterthan100%.
0
20
40Pe
rcen
tageofR
espo
nden
ts
Pre-revenue <$5K $5-9.9K $10-49.9K $50-249.9K
$250-999.9K
$1millionormore
AnnualRevenues
0
20
40
60
80
Percen
tageofR
espo
nden
ts
Grant Loan EquityInvestment
CompetitionPrize
NoFunding
FinancialSupport
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4.DemographicsofProgramParticipants 25 25
Figure4.3
Howmanyfull-timepaidfoundersarethereinyourcompany?n=134
Findings:
• 53%ofrespondentsreportedthattheircompanyhasoneortwofull-time,paidfounders.• 27%ofrespondentsreportedthattheircompanyhasthreetofivefull-time,paidfounders.
Figure4.4
Howmanyfull-timeunpaidfoundersarethereinyourcompany?n=106
Findings:
• 49%ofrespondentsreportedthattheircompanyhasoneortwofull-time,unpaidfounders.• 21%ofrespondentsreportedthattheircompanyhasthreetofivefull-time,unpaidfounders.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timePaidFounders
0
20
40
60
Percen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timeUnpaidFounders
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26 VietnamandCambodiaAppendix
Figure4.5
Howmanyfull-timepaidemployeesarethereinyourcompany?n=157
Findings:
• 25%ofrespondentsreportedthattheircompanyhasmorethantenfull-time,paidemployees.• 25%ofrespondentsreportedthattheircompanyhasthreetofivefull-timeemployees.
Figure4.6
Howmanyfull-timeunpaidemployeesarethereinyourcompany?n=90
Findings:
• 37%ofrespondentsreportedthattheircompanyhasoneortwofull-time,unpaidemployees.• 19%ofrespondentsreportedthattheircompanyhasthreetofivefull-time,unpaidemployees.
0
20
40Pe
rcen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timePaidEmployees
0
20
40
60
Percen
tageofR
espo
nden
ts
0 1-2 3-5 6-10 >10
Full-timeUnpaidEmployees
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4.DemographicsofProgramParticipants 27 27
Figure4.7
Howmanyfoundersoremployeesinyourcompanyarefamilymembers?n=176
Finding:
• 53%ofrespondentsreportedthatnoneofthefoundersoremployeesintheircompanyarefamilymembers.
Figure4.8
Howmanyfoundersoremployeeswithcollegeoruniversitydegreesarethereinyourcompany?n=176
Finding:
• 61%ofrespondentsreportedthatmorethan65%ofthefoundersoremployeesintheircompanyhaveuniversitydegrees.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeesthatareFamilyMembers
0
20
40
60
80
Percen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithUniversityDegrees
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28 VietnamandCambodiaAppendix
Figure4.9
Howmanyfoundersoremployeesinyourcompanyhaveworkedoutsidethetownorcitywheretheygrewup?n=176
Finding:
• 48%ofrespondentsreportedthatmorethan65%ofthefoundersoremployeesintheircompanyhavedomesticdisplacementexperience.
Figure4.10
Howmanyfoundersoremployeesinyourcompanyhavestudiedorworkedoutsideyourcountry?n=179
Finding:
• 54%ofrespondentsreportedthattheircompanyhasfoundersoremployeeswithinternationaldisplacementexperience.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithDomesticDisplacementExperience
0
20
40
60
Percen
tageofR
espo
nden
ts
0% <35% 35-65% >65%
FoundersorEmployeeswithInternationalDisplacementExperience
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4.DemographicsofProgramParticipants 29 29
Figure4.11
Whatareyourcompany’srevenuegrowthplans?n=173
Findings:
• 34%ofrespondentsreportedthattheircompanyhashighgrowthplans.• 55%ofrespondentsreportedthattheircompanyhasmodestgrowthplans.
Figure4.12
Whenwasyourcompanyfounded?n=178
Findings:
• 57%ofrespondentsreportedthattheircompanywasfoundedin2014–2016.• 35%ofrespondentsreportedthattheircompanywasfoundedin2012orearlier.
0
20
40
60Pe
rcen
tageofR
espo
nden
ts
Lowergrowth Nogrowth Modestgrowth Highgrowth
CompanyGrowthPlans
0
20
40
Percen
tageofR
espo
nden
ts
2012orearlier 2013 2014 2015 2016
YearFounded
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30 VietnamandCambodiaAppendix
Figure4.13
Inwhatindustrialsectordoesyourcompanybelong?Pleaseselectallthatapply.3n=186
Findings:
• 25%ofresponsesindicatecompaniesbelonginthesoftwaresector.• 18%ofresponsesindicatecompaniesbelongintheinformationorcommunications
hardwaresector
Figure4.14
Doesyourcompanyhaveawebsite?n=178
Finding:
• 60%ofrespondentsreportedthattheircompanyhasawebsite.
3Respondentswereaskedtoselectalltypesofapplicablesectors,thereforethepercentagesadduptoavaluegreaterthan100%.
0 20 40PercentageofResponses
SoftwareInformationorCommunicationsHardware
MaterialsorManufacturingRetailorWholesale
OtherAgriculture
ProfessionalorBusinessServicesEducationalServices
TourismRestaurantorFoodandBeverageServices
Health,Medical,orBiotechnologyEnvironment
FoodProcessingConstruction
EntertainmentEnergy,Mining,orForestry
FisheriesorAquacultureHoteloraccommodation
TransportationorLogistics
IndustrialSector
0
20
40
60
80
Percen
tageofR
espo
nden
ts
Yes No
Website
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4.DemographicsofProgramParticipants 31 31
Figure4.15
Whydidyoujoin[Program]?Pleaseselectallthatapply.4n=174
Finding:
• 71%ofresponsesindicatecompaniesjoinedtheprogramtonetworkwithotherentrepreneurs.
Figure4.16
Whatwastheyearofyourcompany’sfirstengagementwith[Program]?n=161
Findings:
• 53%ofrespondentsreportedthattheircompanyfirstengagedwiththeirprogramin2015.• 23%ofrespondentsreportedthattheircompanyfirstengagedwiththeirprogramin2016.
4Respondentswereaskedtoselectalltypesofapplicablereasonsforjoiningtheprogram,thereforethepercentagesadduptoavaluegreaterthan100%.
0 20 40 60 80PercentageofResponses
TonetworkwithotherentrepreneursToaccessbusinesssupportservices
TolearnfromknowledgeablementorsToaccessfunding
ToattendinstructionalsessionsGoodformycompany’sreputation
Toaccessofficeorco-workingspaceGoodformypersonalreputation
Forotherreasons
ReasonsforJoiningtheProgram
0
20
40
60
Percen
tageofR
espo
nden
ts
2009orearlier
2010 2011 2012 2013 2014 2015 2016
YearofFirstEngagement
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32 VietnamandCambodiaAppendix
EntrepreneurCharacteristicsoftheVentureSupportProgramParticipantsinAllLocations
The analysis of the demographics of the entrepreneurs of companies in all locationsparticipatingintheventuresupportprogramsrevealedthat:• 62%ofentrepreneursareinthe26–40yearagecategory;23%are25orunder• 71%aremale• 53%haveacollegeoruniversitycertificate;29%haveamaster’sorPhD• 60%havenotstudiedorworkedinaforeigncountry• 82%didnothaveafamilybusiness• 66%hadaninternshipasastudent;58%ofthosethathadaninternshipwereemployed
byaprivatecompany• 28%hadmorethan10yearsofworkexperiencepriortofoundingtheircompany;21%
hadnone• 35%have1,000ormoreFacebookfriends;53%have100–999Facebookfriends
Thissectionprovidesinformationabouttheentrepreneurs’age,gender,levelofeducation,internationalexperience,priorexperienceinfamilybusiness,internshipexperience,priorworkexperience,andFacebooknetwork.Figuresdescribingthesurveyedentrepreneursfollow,accompaniedbythecorrespondingsurveyquestions,numberofrespondents(n),andanalysisfindings.Foreachmeasurewefirstpresentthefindingsforthewholesampleoftheventuresupportprogramparticipants,followedbythechartsandfindingsforeachoftheparticipatingcities.
Figure4.17
Whatisyourage?n=174
Findings:
• 62%ofrespondentsreportedthattheyareinthe26–40yearagecategory.• 23%ofrespondentsreportedthattheyareinthe25orunderagecategory.
0
20
40
Percen
tageofR
espo
nden
ts
25orunder 26-30 31-35 36-40 41-45 46-50 Over50
Age
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4.DemographicsofProgramParticipants 33 33
Figure4.18
Whatisyourgender?n=174
Finding:
• 71%ofrespondentsreportedthattheyaremale.
Figure4.19
Whatisyourhighestlevelofeducation?n=174
Findings:
• 53%ofrespondentsreportedthattheyhaveacollegeoruniversitycertificate.• 29%ofrespondentsreportedthattheyhaveamaster’sorPhD.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
Male Female Prefertonotrespond
Gender
0 20 40 60PercentageofRespondents
Primaryschoolcertificate
Juniorhighschoolcertificate
Somehighschool
Highschoolcertificate
Somecollegeoruniversity
Collegeoruniversitycertificate
Master'sorPhD
LevelofEducation
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34 VietnamandCambodiaAppendix
Figure4.20
HaveyoustudiedorworkedoutsideofVietnam?Pleaseselectallthatapply.5n=174
Finding:
• 60%ofrespondentsreportedthattheyhavenotstudiedorworkedinaforeigncountry.
Figure4.21
Didyourparentsownabusiness?n=173
Finding:
• 82%ofrespondentsreportedthattheirparentsdidnotownabusiness.
5Respondentswereaskedtoselectallapplicableresponses,thereforethepercentagesadduptoavaluegreaterthan100%.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
Notstudiedorworkedinaforeigncountry
Studiedinaforeigncountry Workedinaforeigncountry
InternationalExperience
0
20
40
60
80
100
Percen
tageofR
espo
nden
ts
Yes No
FamilyBusiness
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4.DemographicsofProgramParticipants 35 35
Figure4.22
Didyouworkinyourparents’business?n=30
Finding:
• 70%ofrespondentsthatreportedthattheirparentsdoownabusinessdonotworkinthatbusiness.
Figure4.23
Didyouhaveaninternshipasastudent?n=169
Finding:
• 66%ofrespondentsreportedthattheyhadaninternshipasastudent.
0
20
40
60
80Pe
rcen
tageofR
espo
nden
ts
Yes No
WorkinFamilyBusiness
0
20
40
60
80
Percen
tageofR
espo
nden
ts
Yes No
Internships
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36 VietnamandCambodiaAppendix
Figure4.24
Pleasespecifyyourinternshipemployer.n=110
Finding:
• 58%ofrespondentsthatreportedtheyhadaninternshipasastudentspecifiedaprivatecompanyastheiremployer.
Figure4.25
Beforefoundingyourcompany,howmuchworkexperiencedidyouhave?n=169
Findings:
• 28%ofrespondentsreportedthattheyhadmorethan10yearsofworkexperiencepriortofoundingtheircompany.
• 21%ofrespondentsreportedthattheyhadnoworkexperiencepriortofoundingtheircompany.
0 20 40 60 80PercentageofResponses
Aprivatecompany
Anagencyorgovernmentorganization
Anon-governmentalorganization(NGO)
Auniversity,hospital,orotherNPO
Other
InternshipEmployer
0
20
40
Percen
tageofR
espo
nden
ts
Noworkexperience <5years 5-10years >10years
WorkExperiencePriortoFoundingCompany
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4.DemographicsofProgramParticipants 37 37
Figure4.26
HowmanyFacebookfriendsdoyouhave?n=171
Findings:
• 35%ofrespondentsreportedthattheyhave1,000ormoreFacebookfriends.• 53%ofrespondentsreportedthattheyhave100–999Facebookfriends.
0
20
40Pe
rcen
tageofR
espo
nden
ts
NoFacebookaccount
<100friends
100-499friends
500-999friends
1000ormorefriends
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38 VietnamandCambodiaAppendix
5.UseofServicesbyVentureSupportProgramParticipants
94%ofcompaniesacrossall locationsusedtheprogramsupportservices (27%high intensityofuse,38%moderateintensityofuse,29%lowintensityofuse).
Theventuresupportprogramsprovidecompanieswithasetofsupportservicesintendedtoenablecompaniestogrowandsucceed.ThesesupportservicesaredescribedingreaterdetailinTable5.1.
Table5.1SupportServicesOffered
Location Program SupportServicesOffered
PhnomPenh
EmergingMarkets
- Provisionofmanagement,financial,andlegaladvice
- Mentorshipandguidance- Facilitationoffinancing- Analyticalsupport
MinistryofCommerce101program
- Mentorshipandcoaching- Bootcampentranceprogram- Facilitationoffinancing- Networkingandevents- Promotionopportunities
NationalBusinessPlanCompetition
- Workshopsandtrainingprograms- Leadershipcamp- Networkingandevents- Onlinelearningforum
WECREATE
- Businessbuildingprograms- Facilitationoffinancing- Networkingandevents(workshops,training,etc.)
- Mentorshipandcoaching
NOMINetwork - Technicaltraining- Improvedmarketaccess
DaNang
DaNangBusinessIncubator
- Mentorshipandcoaching- Facilitationoffinancing- Prototypedevelopmentsupport- Networkingandevents
CollegeofInformationIncubator
- Mentorshipandcoaching- Facilitationoffinancing- Provisionoftraining- Networkingandevents
DaNangSMEAssociation
- Regulatoryguidance- Assistancewithbusinessregistration,taxprocedures,andcontractdisputeresolution
- Networkingandevents
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5.UseofServices 39 39
Table5.1(Continued) Location Program SupportServicesOffered
HoChiMinhCity
AgriBusinessIncubator - AccesstofacilitiesandequipmentBusinessIncubationandInnovationCenter–NguyenTatThanhUniversity
- Networkingandevents- Workshops- Mentorshipandcoaching
NongLamUniversity–CenterforTechnologyBusinessIncubation
- Researchandtransferadvancedtechnologyonagriculture,forestryandfishery,environmentandnaturalresources
- Organizingtechnicaltrainingcoursesforstudents,techniciansandextensionstaff
- Demonstrationprojects- Scientificandtechnologyservices(e.g.,information,consultancy,technologytransfer)
SaigonHi-TechPark–IncubationCenter
- Mentorshipandcoaching- Facilitationoffinancing
InformationTechnologyPark–VietnamNationalUniversityinHCMC
- Mentorshipandcoaching- Facilitationoffinancing- Networkingandevents
QuangTrungSoftwareBusinessIncubationCenter
- Accesstofacilitiesandequipment- Businessdevelopmentservices
HoChiMinhCityUniversityofTechnology–TechnologicalBusinessIncubator
- Networkingandevents- Trainingprogram- Facilitationoffinancing
BusinessStartupSupportCentre
- Mentorshipandcoaching- Training- Provisionandfacilitationoffinancing- Tradepromotion- Networkingandevents- Accesstofacilitiesandequipment
Respondentswereaskedtoratethesupportservicesoftheventuresupportprogramsintermsoftheirintensityofuse.Alloftheventuresupportprogramsarecategorizedaseitherfull-time,(thatis,provisionoffull-timeMentoring,Networking,Instruction,Workingspace,Accesstofunding,andBusinesssupportservices),ortrainingprograms.Intermsoffull-timeprograms,respondentswereaskedtoindicatetheirintensityofuseofservicesonafour-pointscalefrom‘didnotuse’(codedas1)to‘highintensity’(codedas4).Intermsoftrainingprograms,respondentswereaskedtoindicatetheirdegreeofparticipationintrainingsessionsonafour-pointscalefrom‘didnotparticipate’(codedas1)to‘fullyparticipated’(codedas4).Forfull-timeprograms,thecombinedintensityofuseofsupportservicesvariableiscalculatedastheaverageofMentoring,Networking,Instruction,Workingspace,Accesstofunding,andBusinesssupportservices.Fortrainingprograms,thecombinedintensityofuseofsupportservicesvariableiscalculatedbasedonthedegreeofparticipationintrainingsessions.Figure5.1showsacomparisonoftheintensityofuseresponsesgivenforfull-timeandtrainingprograms,foreachoftheventuresupportprograms.
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40 VietnamandCambodiaAppendix
0" 20" 40" 60" 80" 100"
Other&Programs&
Ministry&of&Commerce&101&
Da&Nang&SME&Associa;on&
WeCreate&
College&of&Informa;on&Incubator&
Informa;on&Technology&Park&
Business&Startup&Support&Centre&
Na;onal&Business&Plan&Compe;;on&
Da&Nang&Business&Incubator&
Saigon&HiFTech&Park&
NOMI&Network&
Percentage&of&Respondents&
High&Intensity&of&Use& Moderate&Intensity&of&Use& Low&Intensity&of&Use& Did&Not&Use&
Figure5.1Figure5.2showstheresponsesgiven,andthenumberofresponses(‘n’)fortheuseoffull-timesupportservices,andtrainingprograms.
Finding:
• 94%ofrespondentsreportedthattheircompanyusedtheprogramsupportservices(27%highintensityofuse,38%moderateintensityofuse,29%lowintensityofuse).
Figure5.2
Pleaseassessyourcompany’sintensityofuseoftheprogramsupportservices.n=173;Average=7.2
0
20
40
60
Percen
tageofR
espo
nden
ts
Didnotuse Lowintensity Moderateintensity Highintensity
IntensityofUseofServices
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5.UseofServices 41 41
SatisfactionwithSupportServices
93% of companies across all locations were satisfied with the program support services (30%highlysatisfied,63%somewhatsatisfied).
Respondentswhocompletedthesurveywereaskedabouttheirdegreeofsatisfactionwiththesupportservicesprovidedbytheventuresupportprograms.Figure5.3showstheresponsesgiven,andthenumberofresponses(‘n’)forthequestion.
Finding:
• 93%ofrespondentsreportedthattheyweresatisfiedwiththeprogramsupportservices(30%highlysatisfied,63%somewhatsatisfied).
Figure5.3
Towhatdegreeareyousatisfiedwiththeservicesprovided?n=101:Average=6.1
0
20
40
60
80
Percen
tageofR
espo
nden
ts
Notsatisfied Somewhatsatisfied Highlysatisfied
SatisfactionwithServices
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42 VietnamandCambodiaAppendix
PredictorsofIntensityofUseofSupportServices
Tobetterunderstandthecharacteristicsandbehavioursofsupportedcompaniesthatusedsupportservicesinallcities,weconductedstatisticalexaminationsoftherelationshipsbetweenintensityofuseofservices,andpredictorsoftheintensityofuse6.
Weconsiderfourtypesofpredictorsoftheintensityofuseofservicesasindependentvariables:
• Companyattributes(C)
• Entrepreneurattributes(E)
• Satisfactionwithservicesprovidedbyventuresupportprograms7
• Reasonstojoinintheventuresupportprograms(R)8
Fromthisanalysiswefindthatcompaniesthatjoinedintheventuresupportprogramsforthepurposeofnetworkingandlearning(e.g.mentors,instructionalsessions)aremorelikelytousethesupportserviceswithahigherintensity,whilecompaniesthatjoinedintheprogramsforaccesstoofficespacearelesslikelytousethesupportservicesorusetheserviceswithalowerintensity.Thisfindingindicatesthattheventuresupportprogramsaremoreattractivetoentrepreneursandcompaniesforthepurposesofnetworkingandlearningcomparedtoaccesstoofficespace.
Additionally,intheparagraphbelow,wepresentdetailsthatshowcompanieswithplansformodestgrowthorsustainedoperations,companiesthathavelessemployeeswithinternationaldisplacementexperience,andcompaniesthatfoundedbyentrepreneurswithmoreFacebookfriendsaremorelikelyusethesupportserviceswithhigherintensity.
Model1belowregressescompanyattributes,entrepreneurattributes,satisfactionvariables,andreasonstojoinintheprogramsagainstintensityofuseservices.DetailsonModel1maybefoundinTable2below.
Specifically,Model1explains25%ofthevarianceinthedependentvariable,Intensityofuseofservices.Model1showsthatNetworking,andLearningaresignificantlyassociatedwithIntensityofuseofservices(significantatthe95%confidencelevel,andatthe90%confidencelevelrespectively),indicatingthatcompaniesthatjoinedintheprogramsfornetworkingandlearningpurposeandmorelikelytousesupportserviceswithahigherintensity.Moreover,AccesstoofficespaceissignificantandnegativelyassociatedwithIntensityofuseofservices(significantatthe95%confidencelevel),indicatingthatcompaniesthatjoinedintheprogramsforaccesstoofficespacearelesslikelytousesupportservicesoruseserviceswithalowerintensity.Ofthecompanyattributesvariables,Growthplan,andInternationaldisplacementexperienceofemployeearesignificantlyandnegativelyassociatedwithIntensityofuseofservices(bothsignificantatthe90%confidencelevel),indicatingthatcompanieswithplansformodestgrowthorsustainedoperations,andcompaniesthathavelessemployeesthathaveinternationaldisplacementexperiencearemorelikelytousetheserviceswithahigherintensity.Oftheentrepreneurattributesvariables,FacebookfriendsissignificantlyassociatedwithIntensityofuseofservices(significantatthe95%confidencelevel),indicatingthatcompaniesthatfoundedbyentrepreneurswithmoreFacebookfriendsaremorelikelytouseserviceswithahigherintensity.
6CompaniesthatengagedwiththeDaNangSMEAssociationareexcludedfromtheanalysissample.7Respondentswereaskedtoindicatetheirsatisfactionwiththeservicesprovidedbytheventuresupportprogramsonathree-pointscalefrom‘Notsatisfied’(codedas0)to‘Highlysatisfied’(codedas2).8Weincludefivedummyvariablesasreasonstojoinintheprograms:1)Networking,2)Accesstoofficespace,3)Learning,4)Accesstofunding,and5)Businesssupportservices.
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5.UseofServices 43 43
Table5.2PredictorsofIntensityofUseofSupportServices9
VariableModel1
IntensityofUseofServicesC:Age C:Size C:Growthplan -αC:Fundingreceived($) C:Internationaldisplacementofemployees -αC:Domesticdisplacementofemployees C:Employeesthatarefamilymembers C:Employeesthathaveuniversitydegrees C:Website E:Age E:Gender(male) E:Parentsthatownabusiness E:Levelofeducation E:Workexperience(years) E:Internationalexperience E:Facebookfriends +αSatisfactionwithservices R:NetworkingR:AccesstoofficespaceR:LearningR:AccesstofundingR:Businesssupportservices
+*-*+α
ModelCharacteristics TotalN 138AdjustedR2 .25F(dof) ***(20)
dof=Degreesoffreedomα=p<.1,*=p<.05,**=p<.01,***=p<.001
9CompaniesthatengagedwiththeDaNangSMEAssociationareexcludedfromtheanalysissample.
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44 VietnamandCambodiaAppendix
6.ImpactonResourcesandCapabilitiesofVentureSupportProgramParticipantsANoteAboutStatisticalSignificance
Instatistics,confidencelevelstellushowlikelyitisthatapatterninthedataisduetochance.Forexample,inouranalysis,whenwepresentfindingsthatare‘significantatthe95%confidencelevel’,weareexplainingthatthepatternweseeinthedata(thefindingwepresent)hasa95%likelihoodofbeingtrue,andonlya5%(100%-95%)likelihoodofbeingduetochance.Higherconfidencelevels(e.g.,99%)meanthepatterninthedataismorelikelytrue,andnotduetochance.
Overallcompanyrespondentsacrossall locationsattributedthegreatestaverage impacttotheventuresupportprogramsonimprovementstotheircompanies’BusinessexpertiseandBusinessnetworkexpansion,andlowerimpactonimprovementstoKnowledgeofcustomerneeds.The average impact of the venture support programs on the resources and capabilities ofcompaniesacrossalllocationsisgreaterforcompaniesthatwerefoundedin2016,have35%ormoreoftheirfoundersandemployeeswithdomesticdisplacementexperience,havelessthan35%oftheirfoundersoremployeesthatarefamilymembers,havemorethan65%oftheir foundersoremployeeswithuniversitydegrees,arepre-revenue,orhaverevenuesoflessthan$50KUSD,andhavereceivedfinancing.The average impact of the venture support programs on the resources and capabilities ofcompanies across all locations is also greater for companies with entrepreneurs that areyoungerthan25,hadan internship,aremale,haveahighschoolcertificate,orhavetakensome,orcompletedcollegeoruniversity,anddidnothaveanyworkexperience,orhadlessthanfiveyearsofworkexperiencepriortofoundingthecompany.Further, theaverage impactoncompanies’ resourcesandcapabilitiesacrossall locations isgreaterforcompaniesthatusedthesupportserviceswith‘moderate’or‘high’intensity.
Followingourlogicmodelapproachforassessmentofimpact,theventuresupportprogramsachieveimpactoncompanyperformancebyhelpingtoimprovecompanies’resourcesandcapabilities.Thisimprovementtotheresourcesandcapabilitiesofcompaniesisthedirectimpactoftheventuresupportprograms,achievedthroughthevarioussupportservicesavailabletocompanies.Table6.1showsthethreeresourcesandcapabilitiesimpactmeasuresthatwereselectedusingTEN’smethodologytoassesstheventuresupportprograms’impactonimprovementstocompanies’resourcesandcapabilities10.Forconvenience,explanatoryexamplesmayalsobefoundinTable6.1. 10CompaniesthatengagedwiththeDaNangSMEAssociationwereexcludedfromtheanalysissample.
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6.ImpactonCapabilities 45 45
Table6.1ResourcesandCapabilitiesImpactMeasuresandAssociatedExamples
ImpactMeasure ExamplesBusinessexpertise • Businessmodels,orbusinessplans,marketingand
salesstrategies,stakeholderrelations,financingstrategies,orcorporategrowthstrategies
• Newmarketingororganizationalmethodsinbusinesspractices,workplaceorganization,orexternalrelations
• Expansionofthescaleofoperations,diversificationintonewproductlines,orexpansionofindustrialorgeographicmarkets
Businessnetworkexpansion • Accesstocustomers,suppliers,manufacturers,businesspartners,serviceproviders,channeltomarketpartners,orotherrelevantbusinessesinFinlandorabroad
• Accessto,orbetterunderstandingof,industrialknowledge,newdevices,products,orservices
• Accesstokeypersonsinlargecompanies
Knowledgeofcustomerneeds • Knowledgeofcustomerneeds• Knowledgeofhowtoaccesscustomers,domestically,
orabroadFigure6.1showstheaverageimpactresponsesforthethreeresourcesandcapabilitiesimpactmeasures.11Readingclockwise,wecanseethattheaverageimpactsonresourcesandcapabilitiesareattheupperendofthe‘alittle’impactrangeonimprovementstoallthreeresourcesandcapabilitiesmeasures.Thissuggeststhattheventuresupportprogramshavesimilaraverageimpactonimprovementstocompanies’abilitytomakegainbusinessexpertise,expandtheirbusinessnetworks,andlearnabouttheircustomers.
11Forresourcesandcapabilities,impactismeasuredonascaleof0to10usingthefollowingweights:‘Noimpact’0,‘alittle’impact5.0,‘alot’ofimpact10.
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46 VietnamandCambodiaAppendix
Figure6.1AverageImpactoftheVentureSupportProgramsonCompanies’Resourcesand
Capabilities
Wealsoseektounderstandthedistributionofscoresaroundtheaveragesreportedabovetovalidatetheimportanceofthethreeresourcesandcapabilitiesimpactmeasures.Wedeterminedthepercentageofrespondentswhoreportedpositiveimpactontheircompany’sresourcesandcapabilities(i.e.,‘ALot’ofimpact,or‘ALittle’impact).Figure6.2showsthepercentageofcompaniesthatattributedpositiveimpactforthethreeresourcesandcapabilitiesimpactmeasures.WeseeinFigure6.2thatwhilethetotalpercentageofpositiveimpactisapproximatelyequal,moreclientsattributed‘ALot’ofimpactontheirKnowledgeofcustomerneedsmeasure.
BusinessExper,se
KnowledgeofCustomerNeeds
BusinessNetworkExpansion
AllLoca,ons
NoImpact ALi>leImpact ALotofImpact
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6.ImpactonCapabilities 47 47
Figure6.2PercentageofCompaniesAttributingPositiveImpact
ontheirResourcesandCapabilitiesRespondentsfromalllocationsreportedthefollowingimpactsonimprovementstotheircompanies’resourcesandcapabilitiestobe‘ALot’,or‘ALittle’:
• Knowledgeofcustomerneeds(85%positiveimpact)(29%‘ALot’,56%‘ALittle)
• Businessexpertise(84%positiveimpact)(34%‘ALot’,50%‘ALittle)
• Businessnetworkexpansion(84%positiveimpact)(26%‘ALot’,58%‘ALittle)
Thefrequencydistributionsthatfollow,Figures6.3to6.5showimpactresponsesforthethreeresourcesandcapabilitiesimpactmeasures,togetherwiththecorrespondingsurveyquestions,numberofrespondents,andaverageimpactscores(outof10).
n=133
n=132
n=134
0 20 40 60 80 100
BusinessExper1se
BusinessNetworkExpansion
KnowledgeofCustomerNeeds
PercentageofRespondents
"ALiEle" "ALot"
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48 VietnamandCambodiaAppendix
Figure6.3
Asaconsequenceof[Program],hasyourcompany’sbusinessexpertiseincreased?n=157;Average=6.0
Figure6.4
Asaconsequenceof[Program],hasyourcompany’sbusinessnetworkincreased?n=156;Average=5.5
Figure6.5
Asaconsequenceof[Program],hasyourcompany’sknowledgeofcustomerneedsincreased?n=157;Average=5.7
0
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BusinessExpertise
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BusinessNetworkExpansion
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6.ImpactonCapabilities 49 49
Impactoftheventuresupportprogramsoncompanyresourcesandcapabilitieswasfurtheranalyzedwithrespecttocompanyinformation,entrepreneurinformation,andintensityofuseofsupportservices.TheVentureSupportPrograms’Impact:CompanyAttributesAllLocationsFromtheinformationsegmentedbycompanyattributes,foralllocations,wefindthat:
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforthosethatwerefoundedin2016,comparedtothosethatwerefoundedin2015orearlier(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforthosewith35%or
moreoftheirfoundersoremployeeswithdomesticdisplacementexperience,comparedtothosewithlessthan35%(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswithless
than35%oftheirfoundersoremployeesthatarefamilymembers,comparedtothosewith35%ormore(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswith
morethan65%oftheirfoundersoremployeesthathaveuniversitydegrees,comparedtothosewith65%orless(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompaniesthatare
pre-revenue,orhaverevenuesoflessthan$50K,comparedtothosewithrevenuesof$50Kormore(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompaniesthat
receivedfinancing,comparedtothosethatdidnotreceivefinancing(significantatthe99%confidencelevel).
TheVentureSupportPrograms’Impact:EntrepreneurAttributesFromtheinformationsegmentedbyentrepreneurattributes,foralllocations,wefindthat:
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswithentrepreneursthatare25orunder,comparedtothosewithentrepreneursthatareolderthan25(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswithentrepreneursthataremale,comparedtothosewithentrepreneursthatarefemale(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswith
entrepreneursthathaveahighschoolcertificate,orhavetakensome,orcompleted,collegeoruniversity,comparedtothosewithentrepreneursthathaveamaster’sorPhD(significantatthe99%confidencelevel).
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50 VietnamandCambodiaAppendix
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswith
entrepreneursthathadaninternship,comparedtothosewithentrepreneursthatdidnothaveaninternship(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswith
entrepreneursthatdidnothaveanyworkexperience,orhadlessthanfiveyearsofworkexperiencepriortofoundingthecompany,comparedtothosewithentrepreneursthathadfivetotenyearsofexperience(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompanieswith
entrepreneursthathavenotstudiedorworkedinaforeigncountry,comparedtothosewithentrepreneursthathavestudiedorworkedinaforeigncountry(significantatleastatthe95%confidencelevel).
TheVentureSupportPrograms’Impact:IntensityofUseofServicesFromtheinformationsegmentedbyintensityofuseofthesupportservicesprovidedbytheventuresupportprograms,foralllocations,wefindthat:
• Theaverageimpactoncompanies’resourcesandcapabilitiesisgreaterforcompaniesthatusedthesupportserviceswithmoderateorhighintensitycomparedtocompaniesthatusedtheserviceswithlowintensity,ordidnotusetheservices(significantatthe99%confidencelevel).
Figure6.6comparestheaverageimpactattributedbyrespondentsontheircompanies’resourcesandcapabilitiesagainstintensityofuseofeachoftheindividualsupportservices.Wecanseethatingeneral,averageimpactonresourcesandcapabilitiesincreaseswiththeintensityofuseofeachsupportservice.
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6.ImpactonCapabilities 51 51
Figure6.6
2"
4"
6"
8"
10"
Low"Intensity"of"Use"or"Did"Not"Use" Moderate"or"High"Intensity"of"Use"
Weighted"Av
erage"Im
pact"
Mentoring) Networking) Instruc1onal)Sessions)
Working)Space) Access)to)Funding) Business)Support)Services)
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52 VietnamandCambodiaAppendix
7.ImpactonPerformanceofVentureSupportProgramParticipants
Overall,theanalysisindicatesthattheaverageimpactoftheventuresupportprogramswashighest in terms of improvements to companies’ Change in employment, and Change inannual revenues measures, and lower in terms of improvements to companies’ Fundingreceivedmeasure.The average impact of the venture support programs on improvements to companyperformanceishigherforcompaniesthatfirstengagedwiththeprogramsin2014orearlier,werefoundedin2014orearlier,generaterevenues,havemodestorhighgrowthplans,andhavereceivedfinancing.The average impact of the venture support programs on improvements to companyperformance isalsohigher for companieswithentrepreneurs thatare25orunder,donothaveafamilybusiness,didnothaveanyworkexperiencepriortofoundingthecompany,andhavenotstudiedorworkedinaforeigncountry.Further, theaverage impactoncompanies’performance is greater for those thatused thesupportserviceswithanyintensity,comparedtothosethatdidnotusethesupportservices.
Followingourlogicmodelapproachforassessmentofinnovationimpacts,theventuresupportprogramsachievelong-termimpactsintheformofsocio-economicbenefitsbyhelpingcompaniestoimprovetheirperformance.Measuringimpactoncompanies’performanceisimportantbecauseitcorrespondstotheventuresupportprograms’missionandprovidesthehardevidencethatstakeholdersseek.However,companyperformancedependsonanumberoffactorsandsotoassessimpactonperformanceweconsiderboththechangeincompanyperformanceandthedegreetowhichthechangeisattributabletotheventuresupportprograms.Companyperformanceimprovementsoccurasaconsequenceoftheimpactthattheventuresupportprogramshaveonimprovingcompanies’resourcesandcapabilities.Table9.1showsthethreeperformanceimpactmeasuresthatwereselectedtoassesstheventuresupportprograms’impactoncompanyperformance.12
Table7.1PerformanceMeasures
• Changeinannualrevenues• Changeinemployment• Fundingreceived
12CompaniesthatengagedwiththeDaNangSMEAssociationwereexcludedfromtheanalysissample.
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7.ImpactonPerformance 53 53
Figure7.1showstheaverageimpactresponsesforthethreeperformanceimpactmeasures.13Readingclockwise,wecanseethattheaverageimpactsonperformanceareatthelowendofthe‘alittle’impactrangeonimprovementstotheChangeinannualrevenuesmeasure,atthetopendofthe‘noimpact’rangeonimprovementstotheChangeinemploymentmeasure,andatthemiddleofthenoimpactmeasurefortheFundingreceivedmeasure.Thissuggeststhatamongthethreecompanyperformanceimpactmeasures,theventuresupportprogramshavethegreatestaverageimpactonimprovementstocompanies’abilitytoincreasetheirannualrevenues.
Figure7.1AverageImpactoftheVentureSupportProgramsonCompanies’Performance
Wetestedforsignificantdifferencesamongthemeasures,andfoundthatcompaniesattributedhigherimpactstotheventuresupportprogramsintermsoftheChangeinannualrevenues,andChangeinemploymentmeasures,comparedtotheFundingreceivedperformancemeasure(significantatthe99%confidencelevel).Wealsoseektounderstandthedistributionofscoresaroundtheaveragesreportedabovetovalidatetheimportanceofthethreeperformanceimpactmeasures.Wedeterminedthepercentageofrespondentswhoreportedpositiveimpactontheircompany’sperformance(i.e.,‘ALot’ofimpact,or‘ALittle’impact).
13Forperformance,impactismeasuredonascaleof0to10usingthefollowingweights:‘Noimpact’0,‘alittle’impact5.0,‘alot’ofimpact10.
ChangeinAnnualRevenues
ChangeinEmployment
FundingReceived
AllLoca9ons
NoImpact ALi<leImpact ALotofImpact
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54 VietnamandCambodiaAppendix
Figure7.2showsthepercentageofcompaniesthatattributedpositiveimpactforthethreeperformanceimpactmeasures.WeseeinFigure7.2thatagreaterpercentageofcompaniesattributepositiveimpactontheirChangeinannualrevenuesmeasure.
Figure7.2PercentageofCompaniesAttributingPositiveImpactontheirPerformance
Respondentsfromalllocationsreportedthefollowingimpactsonimprovementstotheircompanies’performancetobe‘ALot’,or‘ALittle’,andinthecaseofFundingreceived,‘Asignificantamount’,or‘Asmallamount’:
• Changeinannualrevenues(57%positiveimpact)(9%‘ALot’,48%‘ALittle)
• Changeinemployment(46%positiveimpact)(10%‘ALot’,36%‘ALittle)
• Fundingreceived(20%positiveimpact)(6%‘Asignificantamount’,14%‘Asmallamount’)
Thefrequencydistributionsthatfollow,Figures7.3to7.5showimpactresponsesforthethreeperformanceimpactmeasures,togetherwiththecorrespondingsurveyquestions,numberofrespondents,andaverageimpactscores(outof10).
n=72
n=88
n=30
0 20 40 60
FundingReceived
ChangeinEmployment
ChangeinAnnualRevenues
PercentageofRespondents
"ALiCle" "ALot" "ASmallAmount" "ASignificantAmount"
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7.ImpactonPerformance 55 55
Figure7.3
Asaconsequenceof[Program],haveyourcompany’sannualrevenuesincreased?n=155;Average=3.3
Figure7.4
Asaconsequenceof[Program],hasyourcompany’snumberofemployeesincreased?n=154;Average=2.9
Figure7.5
Asaconsequenceof[Program],hasyourcompanyreceivedfunding?n=155;Average=1.3
0
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56 VietnamandCambodiaAppendix
Impactoftheventuresupportprogramsoncompanyperformancewasfurtheranalyzedwithrespecttocompanyinformation,entrepreneurinformation,andintensityofuseofsupportservices.TheVentureSupportPrograms’Impact:CompanyAttributesFromtheinformationsegmentedbycompanyattributes,foralllocations,wefindthat:
• Theaverageimpactoncompanies’performanceisgreaterforcompaniesthatfirstengagedin2014orearlier,comparedtothosethatfirstengagedin2015or2016(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompaniesthatwerefoundedin2014orearlier,comparedtothosethatwerefoundedin2015or2016(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompaniesthatgenerate
revenues,comparedtothosethatdonotgeneraterevenues(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompanieswithmodestorhigh
growthplans,comparedtothosethathavelowerornogrowthplans(significantatthe99%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompaniesthathavereceivedfinancing,comparedtothosethathavenotreceivedfinancing(significantatthe95%confidencelevel).
TheVentureSupportPrograms’Impact:EntrepreneurAttributesFromtheinformationsegmentedbyentrepreneurattributes,foralllocations,wefindthat:
• Theaverageimpactoncompanies’performanceisgreaterforcompanieswithentrepreneursthatare25orunder,comparedtothosewithentrepreneursthatare36orolder(significantatleastatthe95%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompanieswithentrepreneurs
thatdonothaveafamilybusiness,comparedtothosewithentrepreneursthathaveafamilybusiness(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompanieswithentrepreneursthatdidnothaveanyworkexperiencepriortofoundingthecompany,comparedtothosewithentrepreneursthathadtenyearsorlessofexperience(significantatthe95%confidencelevel).
• Theaverageimpactoncompanies’performanceisgreaterforcompanieswithentrepreneurs
thathavenotstudiedorworkedinaforeigncountry,comparedtothosewithentrepreneursthathavestudiedinaforeigncountry(significantatthe99%confidencelevel).
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7.ImpactonPerformance 57 57
Figure7.6comparestheaverageimpactattributedbyrespondentsontheircompanies’performanceagainstintensityofuseofeachoftheindividualsupportservices.Wecanseethatingeneral,averageimpactonperformanceincreaseswiththeintensityofuseofeachsupportservice.
Figure7.6
0"
2"
4"
6"
Low"Intensity"of"Use"or"Did"Not"Use" Moderate"or"High"Intensity"of"Use"
Weighted"Av
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pact"
Mentoring) Networking) Instruc1onal)Sessions)
Working)Space) Access)to)Funding) Business)Support)Services)
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58 VietnamandCambodiaAppendix
8.PredictorsofSelectionforSupport
Smallercompanies,companiesthathavemoreemployeeswithdisplacementexperience,andcompaniesthathaveawebsitearemorelikelytobeselectedforprogramsupport.
Additionally,companiesthatfoundedbyyoungerentrepreneurs,thatfoundedbyentrepreneurswithahigherlevelofeducation,andthatfoundedbyentrepreneurswithmoreFacebookfriendsaremorelikelytobeselectedforprogramsupport.
WhichCompaniesAreMoreLikelytobeSupported?
ThissectionconsidersthequestionofwhichcompaniesaremorelikelytobeselectedforADBsupportprograms.Therefore,logisticregressionwasusedtoexaminetherelationshipsbetweenprogramsupportandpredictorsofselectionforsupport.14
Forstatisticalanalysis,weincludeprogramsupportasthedependentvariable:
• Programsupport(y/n):indicateswhetherornotacompanyhasbeenselectedforADBsupportprograms.
Weconsidertwokindsofpredictorsasindependentvariables:
• Companyattributes,and• Entrepreneurattributes.
Inthefollowingsectionswedescribeourmeasures,andshowtheresultsoflogisticregressions.
14NotethatforthisanalysistheDaNangSMEAssociationwasincludedwiththerandomsampleofyoungcompanies.Intheinterestofcompleteness,wehavererunthisparticularanalysis,excludingtheDaNangSMEAssociationentirely.Theresultswereinconsequentialanddidnotyieldanysignificantchanges.
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8.PredictorsofSelectionforSupport 59
DependentVariables
Programsupportisincludedasthedependentvariable:
• Programsupport(y/n):IndicateswhetherornotacompanyhasbeensupportedbyADBprograms.Itisabinaryvariablewithavalueof1ifacompanyhasbeensupportedand0otherwise.
IndependentVariables
Weincludecompanyattributes,andentrepreneurattributesasindependentvariables:
Companyattributes
• Companyage:Indicatesthecompany’sageinyearsasof2016(allcompaniesformedpriorto2012wereconsideredtobeformedin2012).
• Size:Respondentswereaskedtoindicatetheirannualrevenuesonaseven-pointscalefrom‘pre-revenue’(codedaszero)to‘$1millionormore’(codedas$1.5million).Themid-pointvalueswereusedfortheannualrevenuesresponses.Respondentswerealsoaskedtoindicatethenumberoffounders,andnumberofemployees,includingfull-timeandpart-timefoundersandemployees(actualnumber).Thenumberoffoundersandemployeesandthemid-pointvaluesfortheannualrevenuesresponsesweremultipliedtogetanindicatorofcompanysize.
• Growthplan:Companiesthathaveaclearandambitiousgrowthplanareexpectedtohavegreatermotivationandconfidenceinimprovedcompanyperformance.Respondentswereaskedtoindicatetheircompany’sgrowthplanaseither‘lowergrowthplan’(codedaszero),‘nogrowthplan’(codedas1),‘modestgrowthplan’(codedas2),or‘highgrowthplan’(codedas3).
• Fundingreceived($):Respondentswereaskedtoindicatetheamountoffunding(e.g.grant,loan,equityinvestments,orcompetitionprize)thattheircompaniesreceivedinactualvalues($).
• Displacementexperienceofemployees:Respondentswereaskedtoindicatehowmanyfoundersandemployeeshaveworkedorstudiedoutsidethetownorcitywheretheygrewuponafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).Respondentswerealsoaskedtoindicatehowmanyfoundersandemployeesintheircompanieshaveworkedorstudiedoutsidehomecountryonafour-pointscalefrom‘none’(codedas2)to‘morethan65%’(codedas8).DomesticdisplacementexperienceandinternationaldisplacementexperiencewereaddedtogethertocalculatetheDisplacementexperienceofemployeesvariable.
• Employeesthatarefamilymembers:Respondentswereaskedtoindicatehowmanyfoundersandemployeesintheircompaniesarefamilymembersonafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).
• Employeesthathaveuniversitydegrees:Respondentswereaskedtoindicatehowmanyfoundersandemployeesintheircompanieshavecollegeoruniversitydegreesonafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).
• Website:Respondentswereaskedtoindicateiftheircompanieshaveawebsite.Ifitabinaryvariablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
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60 VietnamandCambodiaAppendix
EntrepreneurAttributes
• Entrepreneurage:Entrepreneurswereaskedtoindicatetheirageonaseven-pointscalefrom‘25orunder’(codedas1)to‘over50’(codedas7).
• Gender(male):Entrepreneurswereaskedtoindicatetheirgender.Itisabinaryvariablewithavalueof1iftheentrepreneurismaleand0otherwise.
• Parentsthatownabusiness:Entrepreneurswereaskedtoindicateiftheirparentsownabusiness.Itisabinaryvariablewithavalueof1iftheentrepreneur’sparentsownabusinessand0otherwise.
• Levelofeducation:Entrepreneurswereaskedtoindicatetheirhighestlevelofeducationonaseven-pointscalefrom‘primaryschoolcertificate’(codedas1)to‘MastersorPhD’(codedas7).
• Workexperience:Entrepreneurswereaskedtoindicatetheirworkexperiencebeforefoundingacompanyonafour-pointscalefrom‘noexperience’(codedas0)to‘morethan10years’(codedas15).
• Internationalexperience:Entrepreneurswereaskedtoindicateiftheyhaveworkedorstudiedinaforeigncountry.Itisabinaryvariablewithavalueof1iftheentrepreneurhadinternationalexperienceand0otherwise.
• Website:Entrepreneurswereaskedtoindicateiftheircompanieshaveawebsite.Itisabinaryvariablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
• Facebookfriends:EntrepreneurswereaskedtoindicatetheirFacebookfriendsonafive-pointscalefrom‘noFacebookaccount’(codedas0)to‘morethan1,000friends’(codedas1,500).
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8.PredictorsofSelectionforSupport 61
LogisticRegressionModelResults
Logisticregressionwasusedtoassesswhichcompanyattributes,andentrepreneurattributesarepredictorsofselectionforsupport.Table6.1presentslogisticregressionagainstprogramsupport,basedonthesampleofallcompanies.InTable8.1Model1,whichincludesthecompanyattributesandentrepreneurattributes,explains40%ofthevarianceinthedependentvariable,Programsupport.Ofthecompanyattributesvariables,SizeissignificantlyandnegativelyassociatedwithProgramsupport(significantatthe90%confidencelevel),indicatingthatsmallercompaniesaremorelikelytobesupportedbyprograms.DisplacementexperienceofemployeesissignificantlyassociatedwithProgramsupport(significantatthe99.9%confidencelevel),indicatingthatcompaniesthathavemoreemployeeswithdomesticandinternationaldisplacementexperiencearemorelikelytobesupportedbyprograms.WebsiteissignificantlyassociatedwithProgramsupport(significantatthe99%confidencelevel),indicatingthatcompaniesthathaveawebsitearemorelikelytobesupportedbyprograms.Oftheentrepreneurattributesvariables,EntrepreneurageissignificantlyandnegativelyassociatedwithProgramsupport(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatfoundedbyyoungerentrepreneursaremorelikelytobesupportedbyprograms.Moreover,Levelofeducation,andFacebookfriendsaresignificantlyassociatedwithProgramsupport(significantatthe90%confidencelevel,andatthe99.9%confidencelevel),indicatingthatcompaniesthatfoundedbyentrepreneurswithahigherlevelofeducationandhavemoreFacebookfriendsaremorelikelytobesupportedbyprograms.
Table8.1:LogisticRegressionAgainstProgramSupport
VariableModel1
ProgramSupport(y/n)C:Age C:Size -αC:GrowthPlan C:Fundingreceived($) C:Displacementexperienceofemployees +***C:Employeesthatarefamilymembers C:Employeesthathaveuniversitydegrees C:Website +**E:Age -***E:Gender(male) E:Parentsthatownabusiness E:Levelofeducation +αE:Workexperience(years) E:Internationalexperience E:Facebookfriends +***ModelCharacteristics TotalN 393AdjustedR2 .40Chi2(dof) ***(15)dof=Degreesoffreedomα=p<.1,*=p<.05,**=p<.01,***=p<.001
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62 VietnamandCambodiaAppendix
9.PredictorsofCompanyGrowth
Withregardtounsupportedcompanies,oldercompanies,companiesthathaveawebsite,companiesfoundedbyolderentrepreneurs,andcompaniesfoundedbyentrepreneurswithahigherlevelofeducationaremorelikelytogrowintermsofannualrevenues.Additionally,companiesthathaveanambitiousgrowthplan,companiesthatreceivedmorefinancialsupport,companiesthathaveawebsite,andcompaniesfoundedbyentrepreneurswhoseparentsownabusinessaremorelikelytogrowintermsofnumberoffoundersandemployees.
Withregardtosupportedcompanies,oldercompanies,companiesthatfoundedbyolderentrepreneurs,andcompaniesthatfoundedbymaleentrepreneursaremorelikelytogrowintermsofannualrevenues.Additionally,oldercompanies,companiesthathavemoreemployeesthatarefamilymembers,companiesthatfoundedbyolderentrepreneurs,andcompaniesthatfoundedbymaleentrepreneursaremorelikelytogrowintermsofnumberoffoundersandemployees.
WhichCompaniesAreMoreLikelytoGrowinSize?
Thissectionconsidersthequestionofwhichcompaniesaremorelikelytogrowintermsofannualrevenuesandemployment.Therefore,weconductstatisticalexaminationsoftherelationshipsbetweenthecompanygrowthinsizeandpredictorsofthisgrowthinsize.15
Forthestatisticalexaminations,weincludetwosizeindicatorsasdependentvariables:
• Annualrevenues,and• Numberoffoundersandemployees.
Weconsiderthreekindsofpredictorsasindependentvariables:
• Companyattributes,• Entrepreneurattributes,and• Whetherornotthecompanyhasbeensupportedbyprograms.
Inthefollowingsectionswedescribeourmeasures,andshowtheresultsoflinearregressionsagainstAnnualrevenues,andNumberoffoundersandemployees.Specifically,wereportregressionresultsonsupportedcompanies,youngcompaniesfromarandomsample,andall16companiesrespectively.
15CompaniesthatengagedwiththeDaNangSMEAssociationwereexcludedfromtheanalysissample.16Allcompaniesincludebothsupportedcompanies,andtherandomsampleofyoungcompanies.
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9.PredictorsofCompanyGrowth 63
DependentVariables
WeincludeAnnualrevenues,andNumberoffoundersandemployeesasdependentvariables:
• Annualrevenues17:Respondentswereaskedtoindicatetheirannualrevenuesonaseven-pointscalefrom‘pre-revenue’(codedaszero)to‘$1millionormore’(codedas$1.5million).Themid-pointvalueswereusedfortheannualrevenuesresponses.
• Numberoffoundersandemployees:Respondentswereaskedtoindicatethenumberoffounders,andnumberofemployees,includingfull-timeandpart-timefoundersandemployees(actualnumber).Thetotalnumberoffounders(bothfull-timeandpart-time)andemployees(bothfull-timeandpart-time)weresummedupasNumberoffoundersandemployeesvariable.
IndependentVariables
Weincludecompanyattributes,entrepreneurattributes,andprogramsupportasindependentvariables:
Companyattributes
• Age:Indicatesthecompany’sageinyearsasof2016(allcompaniesformedpriorto2012wereconsideredtobeformedin2012).
• Growthplan:Companiesthathaveaclearandambitiousgrowthplanareexpectedtohavegreatermotivationandconfidenceinimprovedcompanyperformance.Respondentswereaskedtoindicatetheircompany’sgrowthplanaseither‘lowergrowthplan’(codedaszero),‘nogrowthplan’(codedas1),‘modestgrowthplan’(codedas2),or‘highgrowthplan’(codedas3).
• Fundingreceived($):Respondentswereaskedtoindicatetheamountoffunding(e.g.grant,loan,equityinvestments,orcompetitionprize)thattheircompaniesreceivedinactualvalues($).
• Displacementexperienceofemployees:Respondentswereaskedtoindicatehowmanyfoundersandemployeeshaveworkedorstudiedoutsidethetownorcitywheretheygrewuponafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).Respondentswerealsoaskedtoindicatehowmanyfoundersandemployeesintheircompanieshaveworkedorstudiedoutsidehomecountryonafour-pointscalefrom‘none’(codedas2)to‘morethan65%’(codedas8).DomesticdisplacementexperienceandinternationaldisplacementexperiencewereaddedtogethertocalculatetheDisplacementexperienceofemployeesvariable.
• Employeesthatarefamilymembers:Respondentswereaskedtoindicatehowmanyfoundersandemployeesintheircompaniesarefamilymembersonafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).
• Employeesthathaveuniversitydegrees:Respondentswereaskedtoindicatehowmanyfoundersandemployeesintheircompanieshavecollegeoruniversitydegreesonafour-pointscalefrom‘none’(codedas1)to‘morethan65%’(codedas4).
• Website:Respondentswereaskedtoindicateiftheircompanieshaveawebsite.Ifitabinaryvariablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
17AnnualrevenuesinVNDhavebeenconvertedtoUSD.
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64 VietnamandCambodiaAppendix
EntrepreneurAttributes
• Entrepreneurage:Entrepreneurswereaskedtoindicatetheirageonaseven-pointscalefrom‘25orunder’(codedas1)to‘over50’(codedas7).
• Gender(male):Entrepreneurswereaskedtoindicatetheirgender.Itisabinaryvariablewithavalueof1iftheentrepreneurismaleand0otherwise.
• Parentsthatownabusiness:Entrepreneurswereaskedtoindicateiftheirparentsownabusiness.Itisabinaryvariablewithavalueof1iftheentrepreneur’sparentsownabusinessand0otherwise.
• Levelofeducation:Entrepreneurswereaskedtoindicatetheirhighestlevelofeducationonaseven-pointscalefrom‘primaryschoolcertificate’(codedas1)to‘MastersorPhD’(codedas7).
• Workexperience:Entrepreneurswereaskedtoindicatetheirworkexperiencebeforefoundingacompanyonafour-pointscalefrom‘noexperience’(codedas0)to‘morethan10years’(codedas15).
• Internationalexperience:Entrepreneurswereaskedtoindicateiftheyhaveworkedorstudiedinaforeigncountry.Itisabinaryvariablewithavalueof1iftheentrepreneurhadinternationalexperienceand0otherwise.
• Website:Entrepreneurswereaskedtoindicateiftheircompanieshaveawebsite.Itisabinaryvariablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
• Facebookfriends:EntrepreneurswereaskedtoindicatetheirFacebookfriendsonafive-pointscalefrom‘noFacebookaccount’(codedas0)to‘morethan1,000friends’(codedas1,500).
Programsupport
• Programsupport(y/n):IndicatedwhetherornotacompanywassupportedbyADBprograms.Itisabinaryvariablewithavalueof1ifthecompanywassupportedand0otherwise.
LinearRegressionModelResults
Linearregressionwasusedtoassesswhichcompanyattributes,andentrepreneurattributesaresignificantlyrelatedtothecompanies’annualrevenuesandnumberoffoundersandemployees.Regressionwasalsousedtoexaminetherelationshipsbetweenprogramsupportandcompanies’growthinsize.
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9.PredictorsofCompanyGrowth 65
ModelResultsofaRandomSampleofYoungCompanies
Models1and2showninTable9.1belowregresscompanyattributesandentrepreneurattributesagainstAnnualrevenuesandNumberoffoundersandemployeesrespectively,basedonthesampleofunsupportedcompanies.Model1,whichincludesboththecompanyattributesandentrepreneurattributes,explains15%ofthevarianceinthedependentvariable,Annualrevenues.InModel1,CompanyageandWebsitearesignificantlyassociatedwithAnnualrevenues(significantatthe99%confidencelevel,andatthe99.9%confidencelevelrespectively),indicatingthatoldercompanies,andcompaniesthathaveawebsitearemorelikelytoachievegrowthintermsofannualrevenues.Oftheentrepreneurattributesvariables,EntrepreneurageandLevelofeducationaresignificantlyassociatedwithAnnualrevenues(significantatthe90%confidencelevel,andatthe95%confidencelevel),indicatingthatcompaniesthatfoundedbyolderentrepreneurs,andentrepreneurswithahigherlevelofeducationaremorelikelytogrowintermsofannualrevenues.Model2,whichincludesboththecompanyattributesandentrepreneurattributes,explains12%ofthevarianceinthedependentvariable,Numberoffoundersandemployees.InModel2,Growthplan,Financialsupport,andWebsitearesignificantlyassociatedwithNumberoffoundersandemployees(significantatthe90%confidencelevel,atthe99%confidencelevel,andatthe99%confidencelevelrespectively),indicatingthatcompanieswithanambitiousgrowthplan,companiesthathavereceivedmorefinancialsupport,andcompaniesthathaveawebsitearemorelikelytogrowintermsofnumberoffoundersandemployees.Oftheentrepreneurattributesvariables,ParentsownabusinessissignificantlyassociatedwithNumberoffoundersandemployees(significantatthe99%confidencelevel),indicatingthatcompaniesthatfoundedbyentrepreneursthattheirparentsownabusinessaremorelikelytogrowintermsofnumberoffoundersandemployees.AdjustedR2arelessthan.25,suggestingtheseresultsbeinterpretedandusedwithcaution.
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66 VietnamandCambodiaAppendix
Table9.1ModelResultsofaRandomSampleofYoungCompanies
Variables
Model1AnnualRevenues
Model2FoundersandEmployees
C:Age +** C:Growthplan +αC:Fundingreceived($) +**C:Displacementexperienceofemployees C:Employeesthatarefamilymembers C:Employeesthathaveuniversitydegrees C:Website +*** +**E:Age +α E:Gender(male) E:Parentsthatownabusiness +**E:Levelofeducation +* E:Workexperience(years) E:Internationalexperience E:Facebookfriends ModelCharacteristics TotalN 270 268AdjustedR2 .15 .12F(dof) ***(14) ***(14)
dof=Degreesoffreedomα=p<.1,*=p<.05,**=p<.01,***=p<.001Tofurtherexplorethecompanyattributesandentrepreneurattributesoftherandomsampleofyoungcompanies,wepresentthedescriptivestatisticsandcorrelationstableinTable9.2.Foreachvariable,thetableprovides:correlationwithothervariables,thenumberofobservations(N),itsmean,standarddeviation,minimumvalue,andmaximumvalue.Herewereportthepertinentcorrelationresults:
• Oldercompaniesaremorelikelytohaveawebsite,andtobefoundedbyolderentrepreneurs.• Largercompaniesaremorelikelytobefoundedbyentrepreneursthattheirparentsowea
business.• Companieswithanambitiousgrowthplanaremorelikelytohaveawebsite,andfoundedby
youngerentrepreneurs.• Companiesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikely
tohavemoreemployeeswithdomesticdisplacementexperience,andtobefoundedbyentrepreneursthathavestudiedorworkedinaforeigncountry.
• Companiesthathavemoreemployeeswithdomesticdisplacementexperiencearemorelikelytohavemoreemployeeswithuniversitydegrees,andtobefoundedbyentrepreneurswithmoreyearsofworkingexperience.
• Companiesthathavemoreemployeesthatarefamilymembersaremorelikelytobefoundedbyentrepreneurswithalowerlevelofeducation.
• Companiesthathavefeweremployeeswithdomesticdisplacementexperiencearemorelikelytousesupportserviceswithahigherintensity.
• Companiesthathavemoreemployeeswithuniversitydegreesaremorelikelytohaveawebsite,andtobefoundedbyentrepreneurswithahigherlevelofeducation.
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9.PredictorsofCompanyGrowth 67
• Youngerentrepreneursaremorelikelytohaveahigherlevelofeducation,andtohavemoreFacebookfriends.
• EntrepreneursthathaveahigherlevelofeducationaremorelikelytohavemoreFacebookfriends.
• EntrepreneurswithmoreyearsofworkexperiencearemorelikelytohavefewerFacebookfriends.
Allcorrelationfindingsreportedabovearesignificantatthe99%confidencelevel.
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68
VietnamandCam
bodiaAppendix
Table9.2DescriptiveStatisticsandCorrelationsTableoftheRandom
SampleofYoungCom
panies
1.
2.3.
4.5.
6.7.
8.9.
10.11.
12.13.
14.15.
16.
1.C:Age
2.C:Size
3.C:Grow
thplan
4.C:Fundingreceived($)
5.C:Internationaldisplacementofem
ployees
6.C:Dom
esticdisplacementofem
ployees
+**
7.C:Em
ployeesthatarefamilym
embers
+*
8.C:Employeesthathaveuniversitydegrees
+*
+**+**
9.C:Website
+**+*
+**+*
+**
10.E:Age+**
-**
+*
-*
11.E:G
ender(male)
+*
-*-*
12.E:Parentsthatownabusiness
+**
13.E:Levelofeducation
+*
+*-**
+**
-**
+*
14.E:W
orkexperience(years)
+*
+*
+**
+**
+*+*
15.E:Internationalexperience
+**
16.E:Facebookfriends
+*
+*+*
-**
+**
-**
N
301289
307309
292301
305307
308309
306304
305303
309293
Mean
3.033.2M
2.99
9.8K2.34
2.321.81
2.82.21
4.09.66
.125.40
7.39.15
316.7Standarddeviation
1.5321.5M
.61
41.4K1.03
1.01.93
1.02.41
1.56.48
.331.00
5.20.36
418.2Minim
um
10
10
11
11
01
00
20
00
Maxim
um
63.3x10
84450.0K4
44
41
81
17
151
1500
*=p<.05,**=p<.01
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9.PredictorsofCompanyGrowth 69
ModelResultsofSupportedCompanies
Models3and4showninTable9.3belowregresscompanyattributesandentrepreneurattributesagainstAnnualrevenuesandNumberoffoundersandemployeesrespectively,basedonthesampleofsupportedcompanies.Model3,whichincludesboththecompanyattributesandentrepreneurattributes,explains21%ofthevarianceinthedependentvariable,Annualrevenues.InModel3,CompanyageissignificantlyassociatedwithAnnualrevenues(significantatthe99%confidencelevel),indicatingthatoldercompaniesaremorelikelytoachievegrowthintermsofannualrevenues.Oftheentrepreneurattributesvariables,EntrepreneurageandGender(male)aresignificantlyassociatedwithAnnualrevenues(significantatthe99.9%confidencelevel,andatthe95%confidencelevel),indicatingthatcompaniesthatfoundedbyolderandmaleentrepreneursaremorelikelytoachievegrowthintermsofannualrevenues.Model4,whichincludesboththecompanyattributesandentrepreneurattributes,explains18%ofthevarianceinthedependentvariable,Numberoffoundersandemployees.InModel4,Companyage,andEmployeesthatarefamilymembersaresignificantlyassociatedwithNumberoffoundersandemployees(bothsignificantatthe95%confidencelevel),indicatingthatoldercompanies,andcompaniesthathaveahigherproportionofemployeesthatarefamilymembersaremorelikelytogrowintermsofnumberoffoundersandemployees.Oftheentrepreneurattributesvariables,EntrepreneurageandGender(male)aresignificantlyassociatedwithNumberoffoundersandemployees(bothsignificantatthe95%confidencelevel),indicatingthatcompaniesthatfoundedbyolderandmaleentrepreneursaremorelikelytogrowintermsofnumberoffoundersandemployees.
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70 VietnamandCambodiaAppendix
Table9.3ModelResultsofSupportedCompanies
Variable
Model3AnnualRevenues
Model4FoundersandEmployees
C:Age +** +*C:Growthplan C:Fundingreceived($) C:Displacementexperienceofemployees C:Employeesthatarefamilymembers +*C:Employeesthathaveuniversitydegrees C:Website E:Age +*** +*E:Gender(male) +* +*E:Parentsthatownabusiness E:Levelofeducation E:Workexperience(years) E:Internationalexperience E:Facebookfriends ModelCharacteristics TotalN 147 146AdjustedR2 .21 .18F(dof) ***(14) ***(14)
dof=Degreesoffreedomα=p<.1,*=p<.05,**=p<.01,***=p<.001
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10.PredictorsofImpact 71
10.PredictorsofImpact
Theimpactoncompanies’resourcesandcapabilitiesismoststronglyassociatedwithimpactoncompanyperformance.
Additionally,oldercompanies,companiesthatwithanambitiousgrowthplan,companiesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.
Moreover,companiesthatfoundedbyentrepreneurswithahigherlevelofeducation,andcompaniesthatfoundedbyentrepreneurswhoseparentsdidnotownabusinessaremorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.
HowSupportProgramsAchieveImpactonCompanyPerformance
InthissectionweconsiderthequestionofhowSupportProgramshaveachievedthisimpact.Itisexpected,asindicatedbyTEN’slogicmodel,thatinnovationintermediaryactivitiesandservicescreateshorter-termimpactsoncompanies’resourcesandcapabilities,whichleadtosubsequentimpactsoncompanyperformance.Therefore,weconductstatisticalexaminationsoftherelationshipsbetweentheSupportProgram’simpactoncompanyperformanceandpredictorsofthatimpact.
Forthestatisticalexaminations,weselectedfourmeasuresofimpactoncompanyperformanceasdependentvariables:
• ImpactonAnnualrevenues,• ImpactonEmployment,• ImpactonFundingreceived,and• Indirectimpactfactor18.
Weconsideredthreekindsofpredictorsofimpactonthedependentvariables:
• Companyattributesandentrepreneurattributesthatweincludedascontrolvariables,• ThedegreeofuseofsupportservicesofferedbytheSupportPrograms,and• Thenatureanddegreeofimpactoncompanies’resourcesandcapabilities.
Inthefollowingsectionswedescribeourmeasures,andshowtheresultsoflinearregressionsagainstimpactonAnnualrevenues,impactonEmployment,impactonFundingreceived,andindirectimpactfactorrespectively.Additionally,wealsopresentregressionresultsagainstimpactoncompanies’resourcesandcapabilities.19
18Indirectimpactfactorvariablewascalculatedusingfactoranalysisbasedonimpactonannualrevenues,
impactonemployment,andimpactonfundingreceived.19CompaniesthatengagedwiththeDaNangSMEAssociationwereexcludedfromtheanalysissample.
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72 VietnamandCambodiaAppendix
ControlVariables
Wecontrolledforsixteencompanyattributesandentrepreneurattributesthatmayaffecta
respondent’sassessmentoftheimpactoftheSupportProgramsontheirAnnualrevenues,Employment,andFundingreceivedperformance:
CompanyAttributes
• Companyage:Indicatesthecompany’sageinyearsasof2016(allcompaniesformedpriorto
2012wereconsideredtobeformedin2012).
• Size:Respondentswereaskedtoindicatetheirannualrevenuesonaseven-pointscalefrom
‘pre-revenue’(codedaszero)to‘$1millionormore’(codedas$1.5million).Themid-point
valueswereusedfortheannualrevenuesresponses.Respondentswerealsoaskedto
indicatethenumberoffounders,andnumberofemployees,includingfull-timeandpart-time
foundersandemployees(actualnumber).Thenumberoffoundersandemployeesandthe
mid-pointvaluesfortheannualrevenuesresponsesweremultipliedtogetanindicatorof
companysize.
• Growthplan:Companiesthathaveaclearandambitiousgrowthplanareexpectedtohave
greatermotivationandconfidenceinimprovedcompanyperformance.Respondentswere
askedtoindicatetheircompany’sgrowthplanaseither‘lowergrowthplan’(codedaszero),
‘nogrowthplan’(codedas1),‘modestgrowthplan’(codedas2),or‘highgrowthplan’(coded
as3).
• Fundingreceived($):Respondentswereaskedtoindicatetheamountoffunding(e.g.grant,
loan,equityinvestments,orcompetitionprize)thattheircompaniesreceivedinactualvalues
($).
• Internationaldisplacementexperienceofemployees:Respondentswerealsoaskedtoindicatehowmanyfoundersandemployeesintheircompanieshaveworkedorstudied
outsidehomecountryonafour-pointscalefrom‘none’(codedas2)to‘morethan65%’
(codedas8).
• Domesticdisplacementexperienceofemployees:Respondentswereaskedtoindicatehowmanyfoundersandemployeesintheircompanieshaveworkedorstudiedoutsidethetownor
citywheretheygrewuponafour-pointscalefrom‘none’(codedas1)to‘morethan65%’
(codedas4).
• Employeesthatarefamilymembers:Respondentswereaskedtoindicatehowmany
foundersandemployeesintheircompaniesarefamilymembersonafour-pointscalefrom
‘none’(codedas1)to‘morethan65%’(codedas4).
• Employeesthathaveuniversitydegrees:Respondentswereaskedtoindicatehowmany
foundersandemployeesintheircompanieshavecollegeoruniversitydegreesonafour-point
scalefrom‘none’(codedas1)to‘morethan65%’(codedas4).
• Website:Respondentswereaskedtoindicateiftheircompanieshaveawebsite.Ifitabinary
variablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
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10.PredictorsofImpact 73
EntrepreneurAttributes
• Entrepreneurage:Entrepreneurswereaskedtoindicatetheirageonaseven-pointscalefrom
‘25orunder’(codedas1)to‘over50’(codedas7).
• Gender(male):Entrepreneurswereaskedtoindicatetheirgender.Itisabinaryvariablewithavalueof1iftheentrepreneurismaleand0otherwise.
• Parentsthatownabusiness:Entrepreneurswereaskedtoindicateiftheirparentsownabusiness.Itisabinaryvariablewithavalueof1iftheentrepreneur’sparentsownabusiness
and0otherwise.
• Levelofeducation:Entrepreneurswereaskedtoindicatetheirhighestlevelofeducationonaseven-pointscalefrom‘primaryschoolcertificate’(codedas1)to‘MastersorPhD’(codedas
7).
• Workexperience:Entrepreneurswereaskedtoindicatetheirworkexperiencebeforefoundingacompanyonafour-pointscalefrom‘noexperience’(codedas0)to‘morethan10
years’(codedas15).
• Internationalexperience:Entrepreneurswereaskedtoindicateiftheyhaveworkedorstudiedinaforeigncountry.Itisabinaryvariablewithavalueof1iftheentrepreneurhad
internationalexperienceand0otherwise.
• Website:Entrepreneurswereaskedtoindicateiftheircompanieshaveawebsite.Itisa
binaryvariablewithavalueof1ifthecompanyhasawebsiteand0otherwise.
• Facebookfriends:EntrepreneurswereaskedtoindicatetheirFacebookfriendsonafive-pointscalefrom‘noFacebookaccount’(codedas0)to‘morethan1,000friends’(codedas1,500).
IntensityofUseofSupportServices
Useofsupportservices:Respondentswereaskedtoratethesupportservicesoftheventuresupportprogramsintermsoftheirintensityofuse.Alloftheventuresupportprogramsare
categorizedaseitherfull-time(thatis,provisionoffull-timeMentoring,Networking,Instruction,
Workingspace,Accesstofunding,andBusinesssupportservices),ortrainingprograms.Intermsof
full-timeprograms,respondentswereaskedtoindicatetheirintensityofuseofservicesonafour-
pointscalefrom‘didnotuse’(codedas1)to‘highintensity’(codedas4).Intermsoftraining
programs,respondentswereaskedtoindicatetheirdegreeofparticipationintrainingsessionsona
four-pointscalefrom‘didnotparticipate’(codedas1)to‘fullyparticipated’(codedas4).
RegressionVariablesWeconductedcorrelationsandlinearregressionanalysestoexplainhowimpactoncompany
resourcesandcapabilities,andperformanceisachieved.Table10.1showsallthevariablesincluded
intheregressions.Toreducecomplexity,afactoranalysiswasusedtoconsolidatemeasuresof
impact.Asshowninthetablebelow,thethreeimpactonresourcesandcapabilitiesmeasureswere
reducedtoonefactor:Directimpact.Thethreeimpactoncompanyperformancemeasureswere
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74 VietnamandCambodiaAppendix
reducedtoonefactor:Indirectimpact.AllcompositefactorsofimpactmeasuresarereliableasindicatedbytheCronbachalphas.20
Table10.1RegressionVariables
TypeofMeasures Measures RegressionVariables
IntensityofUse
• Mentoring• Networking• Instruction• Workingspace• Accesstofunding• Businesssupportservices• Degreeofparticipationintraining
sessions
Useofsupportservices21
Independentimpactmeasures
Impacton:• Businessexpertise• Businessnetworkexpansion• Knowledgeofcustomerneeds
Directimpact(Cronbach’sAlpha=.91)
Impactonperformancemeasures
Impacton:
• ChangeinannualrevenuesImpacton:
• ChangeinemploymentImpacton:
• Fundingreceived
ImpactonannualrevenuesImpactonemploymentImpactonfundingreceived
Impacton:• Changeinannualrevenues• Changeinemployment• Fundingreceived
Indirectimpactfactor(Cronbach’sAlpha=.93)
Controls
• Yearfounded• Annualrevenues• Numberofemployees• Companygrowthplan• Financialsupport($)
CompanyageSizeGrowthplanFundingreceived
20Cronbach’salphaisameasureofinternalconsistency.21Forfull-timeprograms,UseofsupportservicevariableiscalculatedastheaverageofMentoring,Networking,Instruction,Workingspace,Accesstofunding,andBusinesssupportservices.Fortrainingprograms,Useofsupportservicevariableiscalculatedbasedonthedegreeofparticipationintrainingsessions.
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10.PredictorsofImpact 75
Table10.1(Continued)TypeofMeasures Measures RegressionVariables
Controls • Proportionoffoundersandemployeeswithint’ldisplacementexperience
Internationaldisplacement
experienceofemployees
• Proportionoffounderandemployees
withdomesticdisplacementexperience Domesticdisplacement
experienceofemployees
• Proportionoffoundersandemployees
thatarefamilymembers Employeesthatarefamily
members
• Proportionoffoundersandemployees
thathaveuniversitydegrees Employeesthathaveuniversity
degrees
• Website Website
• Entrepreneurage Entrepreneurage
• Gender Gender(male)
• Familybusiness Parentsthatownabusiness
• Highestlevelofeducation Levelofeducation
• Workexperiencebeforefoundingthe
company Workexperience(years)
• Entrepreneurshaveworkedorstudiedin
aforeigncountry Internationalexperience
• NumberofFacebookfriends Facebookfriends
DescriptiveStatistics
Table10.2presentsadescriptivestatisticsandcorrelationstable.Foreachvariable,thetable
provides:correlationwithothervariables,thenumberofobservations(N),itsmean,standard
deviation,minimumvalue,andmaximumvalue.Herewereportthepertinentcorrelationresults:
DirectImpact• Younger,maleentrepreneurs,withalowerlevelofeducation,andcompaniesthathaveused
theventuresupportprogramserviceswithgreaterintensityaremorelikelytoattribute
impactontheirresourcesandcapabilities.
IndirectImpact• Youngerentrepreneurs,andcompaniesthathaveattributedgreaterimpactontheirresources
andcapabilitiesaremorelikelytoattributeimpactontheirperformance.
CompanyandEntrepreneurAttributes• Oldercompaniesaremorelikelytobelargerinsize,tohaveawebsite,andtobefoundedby
olderentrepreneurs.
• Youngercompaniesaremorelikelytousesupportserviceswithahigherintensity.
• Companieswithoutgrowthplan,orwithalowergrowthplanaremorelikelytousesupport
serviceswithahigherintensity.
• Companiesthatfoundedbyolderentrepreneursaremorelikelytoreceiveagreateramount
offinancialsupport.
• Companiesthathavemoreemployeeswithinternationaldisplacementexperiencearemore
likelytohavemoreemployeeswithdomesticdisplacementexperience,tobefoundedby
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76 VietnamandCambodiaAppendix
entrepreneurswithahigherlevelofeducation,andtobefoundedbyentrepreneurswithinternationalexperience.
• Companiesthathavemoreemployeeswithdomesticdisplacementexperiencearemorelikelytohaveawebsite,tobefoundedbymaleentrepreneurs,andtobefoundedbyentrepreneursthathavestudiedorworkedinaforeigncountry.
• Companiesthathavefeweremployeeswithdomesticdisplacementexperiencearemorelikelytousesupportserviceswithahigherintensity.
• Companiesthathavemoreemployeeswithuniversitydegreesaremorelikelytobefoundedbymaleentrepreneurs.
• Olderentrepreneursaremorelikelytohaveahigherlevelofeducation,tohavemoreyearsofworkexperience,andtohavestudiedorworkedinaforeigncountry.
Allcorrelationfindingsreportedabovearesignificantatthe99%confidencelevel.
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10.PredictorsofImpact
77
Table10.2DescriptiveStatisticsandCorrelationsTableofSupportedCompanies 22
1.
2.3.
4.5.
6.7.
8.9.
10.11.
12.13.
14.15.
16.17.
18.19.
1.C:Age
2.C:Size+**
3.C:Grow
thplan
4.C:Fundingreceived($)
5.C:Internationaldisplacement
6.C:Dom
esticdisplacement
+*+*
+**
7.C:Fam
ilymem
bers+*
8.C:Universitydegrees
-*
+*
-*
9.C:W
ebsite+**
+*
+**
10.E:Age+**
+**+*
+*
11.E:Gender(m
ale)
+**
+**
12.E:Parentsthatownabusiness
-**
13.E:Levelofeducation
+**
+*+**
14.E:W
orkexperience(years)
+*+*
+*
+*
+**
+**
15.E:Internationalexperience
+**
+**
+**
+**
+**
16.E:Facebookfriends
-*
-*
17.Supportservices-**
-**
-**
+*
+*
18.Directimpactfactor
-**
+*
-**
+**
19.Indirectim
pactfactor
-*
+**
N
162157
157176
163160
160160
162158
155157
158153
158157
157156
152Mean
2.991.1M
3.23
7.5K1.90
3.021.65
3.41.56
2.66.70
.186.10
6.38.39
812.12.99
.08.05
Standarddeviation1.54
3.3M
.6922.9K
1.001.15
.89.84
.501.43
.46.38
.725.83
.49566.9
.81.98
1.01Minim
um
10
10
11
11
01
00
40
00
1-2.03
-1.02Maxim
um
527.0M
4
200.0K44
44
17
11
715
11500
41.64
3.34*=p<.05,**=p<.01
22Com
paniesthatengagedwiththeDaN
angSMEAssociationareexcludedfrom
theanalysissample.
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78VietnamandCambodiaAppendix
LinearRegressionModelResults
AsindicatedbyTEN’slogicmodelforinnovationintermediaries,theachievementofimpactsoncompanyperformancedependsontheachievementofshorter-termimpactsoncompanies’resourcesandcapabilities,whichinturn,dependsontheSupportProgram’sactivities.LinearregressionwasusedtoexaminetherelationshipsbetweentheuseofsupportservicesofferedbytheSupportPrograms,impactonresourcesandcapabilities,andimpactoncompanyperformance.RegressionwasalsousedtoassesswhichservicesandimpactonresourcesandcapabilitiesaresignificantlyrelatedtotheimpactoftheSupportProgramsoncompanies’performance.Wealsocontrolledforcompanyattributesandentrepreneurattributesthatmayaffectcompanies’assessmentoftheimpactoftheSupportProgramsontheirperformance.DetailsonfivemodelsmaybefoundinTable10.3below.Model1regressescontrolvariables,andintensityofuseofsupportservicesagainstdirectimpactoncompanies’resourcesandcapabilities.Models2,3,4,and5regresscontrolvariables,intensityofuseofsupportservices,andtheindependentimpactfactoragainstimpactoncompanyperformancemeasures.Model1,whichincludescontrolvariablesandintensityofuseofsupportservices,explains37%ofthevarianceinthedependentvariable,Directimpactfactor.Model1showsthatUseofservicesissignificantlyassociatedwithDirectimpactfactor(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatusedsupportserviceswithahigherintensityaremorelikelytoattributetheSupportProgramswithimpactonresourcesandcapabilities.Ofthecompanyattributesvariables,Domesticdisplacementexperienceofemployees,andEmployeesthathaveuniversitydegreesaresignificantlyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel,andatthe90%confidencelevelrespectively),indicatingthatcompaniesthathavemoreemployeeswithdomesticdisplacementexperience,andcompaniesthathavemoreemployeeswithuniversitydegreesaremorelikelytoattributetheSupportProgramswithimpactonresourcesandcapabilities.Oftheentrepreneurattributesvariables,EntrepreneurageissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatwerefoundedbyyoungerentrepreneursaremorelikelytoattributetheSupportProgramswithimpactonresourcesandcapabilities.Inaddition,LevelofeducationissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithalowerlevelofeducationaremorelikelytoattributetheSupportProgramswithimpactonresourcesandcapabilities.Moreover,WorkexperienceissignificantlyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithmoreyearsofworkexperiencearemorelikelytoattributetheSupportProgramswithimpactonresourcesandcapabilities.Model2,depictedinFigure10.1,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains27%ofthevarianceinthedependentvariable,Indirectimpactfactor.Model2showsthatDirectimpactfactorissignificantlyassociatedwithIndirectimpactfactor(significantatthe99.9%confidencelevel),indicatingthatcompaniesreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.Ofthecompanyattributesvariables,Companyage,Growthplan,andInternationaldisplacementexperienceofemployeesaresignificantlyassociatedwithIndirect
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10.PredictorsofImpact 79
impactfactor(significantatthe95%confidencelevel,atthe99%confidencelevel,andatthe95%confidencelevelrespectively),indicatingthatoldercompanies,companieswithanambitiousgrowthplan,andcompaniesthathavemoreemployeesthathaveinternationaldisplacementexperiencearemorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.Oftheentrepreneurattributesvariables,ParentsthatownabusinessissignificantlyandnegativelyassociatedwithIndirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswhoseparentsdonotownabusinessaremorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.Inaddition,LevelofeducationissignificantlyassociatedwithIndirectimpactfactor(significantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithahigherlevelofeducationaremorelikelytoattributetheSupportProgramswithimpactoncompanyperformance.
Figure10.1Model2–ImpactonIndirectImpact
Model3,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains34%ofthevarianceinthedependentvariable,impactonAnnualrevenues.Model3showsthatDirectimpactfactorissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheSupportProgramswithimpactontheirannualrevenues.Ofthecompanyattributesvariables,Companyage,Growthplan,andInternationaldisplacementexperienceofemployeesaresignificantlyassociatedwithimpactonAnnualrevenues(significantatthe99.9%confidencelevel,atthe99%confidencelevel,andatthe95%confidencelevelrespectively),indicatingthatoldercompanies,companieswithanambitiousgrowthplan,andcompaniesthathavemoreemployeesthathaveinternationaldisplacementexperiencearemorelikelytoattributetheSupportProgramswithimpactonAnnualrevenues.Additionally,EmployeesthathaveuniversitydegreesissignificantlyandnegativelyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesthathavefeweremployeeswithauniversitydegreearemorelikelytoattributetheSupportProgramswithimpactontheirannualrevenues.Oftheentrepreneurattributesvariables,Parentsthatowna
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80VietnamandCambodiaAppendix
businessissignificantlyandnegativelyassociatedwithimpactonannualrevenues(significantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswhoseparentsdonotownabusinessaremorelikelytoattributetheSupportProgramswithimpactonAnnualrevenues.Inaddition,LevelofeducationissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe99%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithahigherlevelofeducationaremorelikelytoattributetheSupportProgramswithimpactonAnnualrevenues.Moreover,InternationalexperienceissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneursthatstudiedorworkedinaforeigncountryaremorelikelytoattributetheSupportProgramswithimpactonAnnualrevenues.Model4,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains13%ofthevarianceinthedependentvariable,impactonEmployment.Model3showsthatDirectimpactfactorissignificantlyassociatedwithimpactonEmployment(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheSupportProgramswithimpactontheiremployment.Ofthecompanyattributesvariables,Growthplan,andEmployeesthatarefamilymembersaresignificantlyassociatedwithimpactonEmployment(significantatthe99%confidencelevel,andatthe90%confidencelevelrespectively),indicatingthatcompanieswithanambitiousgrowthplan,andcompaniesthathavemoreemployeesthatarefamilymembersaremorelikelytoattributetheSupportProgramswithimpactontheiremployment.Model5,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains13%ofthevarianceinthedependentvariable,impactonFundingreceived.Model3showsthatDirectimpactfactorissignificantlyassociatedwithimpactonFundingreceived(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheSupportProgramswithimpactontheirfundingreceived.Ofthecompanyattributesvariables,DomesticdisplacementexperienceofemployeesissignificantlyandnegativelyassociatedwithimpactonFundingreceived(significantatthe99%confidencelevel),indicatingthatcompaniesthathavefeweremployeeswithdomesticdisplacementexperiencearemorelikelytoattributetheSupportProgramswithimpactontheirfundingreceived.Oftheentrepreneurattributesvariables,Parentsthatownabusiness,andWorkexperiencearesignificantlyandnegativelyassociatedwithimpactonFundingreceived(significantatthe99%confidencelevel,andatthe95%confidencelevelrespectively),indicatingthatcompaniesthatwerefoundedbyentrepreneurswhoseparentsdonotownabusiness,andbyentrepreneurswithlessworkexperiencearemorelikelytoattributetheSupportProgramswithimpactontheirfundingreceived.
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10.PredictorsofImpact
81
Table10.3LinearRegressionsofAllSupportPrograms
Variable
Model1
Directim
pactfactor
Model2
Indirectimpact
factor
Model3
Impactonannualrevenues
Model4
Impacton
employm
ent
Model5
Impactonfundingreceived
C:Age
+*+***
C:Size
C:Grow
thplan
+**+**
+**
C:Fundingreceived($)
C:Internationaldisplacementofem
ployees
+*+*
C:Domesticdisplacem
entofemployees
+*
-**C:Em
ployeesthatarefamilym
embers
+ α
C:Em
ployeesthathaveuniversitydegrees+ α
-*
C:Website
E:Age
-**
E:G
ender(male)
E:Parentsthatow
nabusiness
-**- α
-**
E:Levelofeducation-**
+ α+**
E:Workexperience(years)
+*
-*E:Internationalexperience
-*
E:Facebookfriends
UseofServices
+***
DirectIm
pactFactor
+***+***
+***+***
ModelCharacteristics
TotalN
147
149147
149149
AdjustedR2
.37.27
.34.13
.20F(dof)
***(17)***(18)
***(18)**(18)
***(18)dof=Degreesoffreedom
α=p<.1,*=p<.05,**=p<.01,***=p<.001
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82VietnamandCambodiaAppendix
LinearRegressionModelResultsbyCityofSupportPrograms
Wealsoconductindividualregressionanalysesbydifferentcitiesofsupportprograms.Specifically,thefollowingsectionwillreportregressionmodelresultsonMinistryofCommerce101(MOC)program,PhnomPenhprograms,andHoChiMingCityprogramsrespectively23.Model6regressescontrolvariables,andintensityofuseofsupportservicesagainstdirectimpactoncompanies’resourcesandcapabilities,basedonsampleofMinistryofCommerce101program.Models7,8,9,and10regresscontrolvariables,intensityofuseofsupportservices,andthedirectimpactfactoragainstimpactoncompanyperformancemeasures,basedonsampleofMinistryofCommerce101program.DetailsonthefivemodelsmaybefoundinTable10.4.Model6,whichincludescontrolvariablesandintensityofuseofsupportservices,explains31%ofthevarianceinthedependentvariable,Directimpactfactor.Model6showsthatUseofservicesissignificantlyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatusedsupportserviceswithahigherintensityaremorelikelytoattributetheMOCprogramwithimpactonresourcesandcapabilities.Ofthecompanyattributesvariables,FundingreceivedissignificantlyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatreceivedmorefinancialsupportaremorelikelytoattributetheMOCprogramwithimpactontheirresourcesandcapabilities.Oftheentrepreneurattributesvariables,Entrepreneurage,andLevelofeducationaresignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe90%confidencelevel,andatthe99%confidencelevelrespectively),indicatingthatcompaniesthatwerefoundedbyyoungerentrepreneurs,andthatfoundedbyentrepreneurswithalowerlevelofeducationaremorelikelytoattributetheMOCprogramwithimpactontheirresourcesandcapabilities.Moreover,Workexperience,andFacebookfriendsaresignificantlyassociatedwithDirectimpactfactor(significantatthe99%confidencelevel,andatthe95%confidencelevelrespectively),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithmoreyearsofworkexperience,andthatfoundedbyentrepreneursthathavemoreFacebookfriendsaremorelikelytoattributetheMOCprogramwithimpactonresourcesandcapabilities.Model7,depictedinFigure10.2,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains27%ofthevarianceinthedependentvariable,Indirectimpactfactor.Ofthecompanyattributesvariables,FundingreceivedissignificantlyassociatedwithIndirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatreceivedmorefinancialsupportaremorelikelytoattributetheMOCprogramwithimpactoncompanyperformance.Oftheentrepreneurattributesvariables,EntrepreneurageissignificantlyandnegativelyassociatedwithIndirectimpactfactor(significantatthe90%confidencelevel),indicatingthat
23WedidnotconductindividualregressionanalysisforDaNangprogramsduetodatapaucity.
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10.PredictorsofImpact 83
companiesthatfoundedbyyoungerentrepreneursaremorelikelytoattributetheMOCprogramwithimpactoncompanyperformance.
Figure10.2Model7–ImpactonIndirectImpact
Model8,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains30%ofthevarianceinthedependentvariable,impactonAnnualrevenues.Model8showsthatDirectimpactfactorissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheMOCprogramwithimpactontheirannualrevenues.Ofthecompanyattributesvariables,FundingreceivedissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesthatreceivedmorefinancialsupportaremorelikelytoattributetheMOCprogramwithimpactonAnnualrevenues.Oftheentrepreneurattributesvariables,Entrepreneurageissignificantlyandnegativelyassociatedwithimpactonannualrevenues(significantatthe90%confidencelevel),indicatingthatcompaniesthatfoundedbyyoungerentrepreneursaremorelikelytoattributetheMOCprogramwithimpactonAnnualrevenues.Model9,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains21%ofthevarianceinthedependentvariable,impactonEmployment.Ofthecompanyattributesvariables,FundingreceivedissignificantlyassociatedwithimpactonEmployment(significantatthe90%confidencelevel),indicatingthatcompaniesthatreceivedmorefinancialsupportaremorelikelytoattributetheMOCprogramwithimpactontheiremployment.Oftheentrepreneurattributesvariables,WorkexperienceandFacebookfriendsaresignificantlyassociatedwithimpactonemployment
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(bothsignificantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithmoreworkexperience,andthatwerefoundedbyentrepreneurswithmoreFacebookfriendsaremorelikelytoattributetheMOCprogramwithimpactontheiremployment.Model10,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,doesnotexplainthevarianceinthedependentvariable,impactonFundingreceived.NoneoftheindependentvariablesissignificantinModel10.
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10.PredictorsofImpact
85
Table10.4LinearRegressionsoftheMinistryofCom
merce101Program
Variable
Model6
Directim
pactfactor
Model7
Indirectimpact
factor
Model8
Impactonannualrevenues
Model9
Impacton
employm
ent
Model10
Impactonfundingreceived
C:Age
C:Size
C:Grow
thplan
C:Fundingreceived($)+*
+*+*
+ α
C:Internationaldisplacementofem
ployees
C:Domesticdisplacem
entofemployees
C:Em
ployeesthatarefamilym
embers
C:Em
ployeesthathaveuniversitydegrees
C:Website
E:Age
- α- α
- α
E:G
ender(male)
E:Parentsthatow
nabusiness
E:Levelofeducation-**
E:Workexperience(years)
+**
+ α
E:Internationalexperience
E:Facebookfriends
+*
+ α
UseofServices
+*
DirectIm
pactFactor
+*
ModelCharacteristics
TotalN
43
4747
4848
AdjustedR2
.31.27
.30.21
-.06F(dof)
**(8)**(8)
**(8)**(8)
(8)dof=Degreesoffreedom
α=p<.1,*=p<.05,**=p<.01,***=p<.001
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86 VietnamandCambodiaAppendix
DetailsonthefivemodelsbasedonsampleofthePhnomPenhprogramsmaybefoundinTable10.5below.Model11regressescontrolvariables,andintensityofuseofsupportservicesagainstdirectimpactoncompanies’resourcesandcapabilities,.Models12,13,14,and15regresscontrolvariables,intensityofuseofsupportservices,andthedirectimpactfactoragainstimpactoncompanyperformancemeasures,basedonsampleofthePhnomPenhprograms.Model11,whichincludescontrolvariablesandintensityofuseofsupportservices,explains43%ofthevarianceinthedependentvariable,Directimpactfactor.Model11showsthatUseofservicesissignificantlyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatusedsupportserviceswithahigherintensityaremorelikelytoattributethePhnomPenhprogramswithimpactonresourcesandcapabilities.Ofthecompanyattributesvariables,GrowthplanissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompanieswithamodestgrowthplanorwithnogrowthplanaremorelikelytoattributethePhnomPenhprogramswithimpactontheirresourcesandcapabilities.Oftheentrepreneurattributesvariables,LevelofeducationissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithalowerlevelofeducationaremorelikelytoattributethePhnomPenhprogramswithimpactontheirresourcesandcapabilities.Moreover,WorkexperienceissignificantlyassociatedwithDirectimpactfactor(significantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithmoreyearsofworkexperiencearemorelikelytoattributethePhnomPenhprogramswithimpactonresourcesandcapabilities.Model12,depictedinFigure10.3,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains26%ofthevarianceinthedependentvariable,Indirectimpactfactor.Model12showsthatDirectimpactfactorissignificantlyassociatedwithIndirectimpactfactor(significantatthe99.9%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributethePhnomPenhprogramswithimpactoncompanyperformance.Ofthecompanyattributesvariables,Companyage,andInternationaldisplacementexperienceofemployeesaresignificantlyassociatedwithIndirectimpactfactor(significantatthe90%confidencelevel,andatthe99%confidencelevel),indicatingthatoldercompanies,andcompaniesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikelytoattributethePhnomPenhprogramswithimpactoncompanyperformance.Moreover,EmployeesthathaveuniversitydegreesissignificantlyandnegativelyassociatedwithIndirectimpactfactor(significantatthe95%confidencelevel),indicatingthatcompaniesthathavelessemployeeswithauniversitydegreearemorelikelytoattributethePhnomPenhprogramswithimpactoncompanyperformance.
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10.PredictorsofImpact 87
Figure10.3Model12–ImpactonIndirectImpact
Model13,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains30%ofthevarianceinthedependentvariable,impactonAnnualrevenues.Model13showsthatDirectimpactfactorissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe99.9%confidencelevel),indicatingthatcompaniesreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributethePhnomPenhprogramswithimpactontheirannualrevenues.Ofthecompanyattributesvariables,Companyage,Growthplan,andInternationaldisplacementexperienceofemployeesaresignificantlyassociatedwithimpactonAnnualrevenues(allsignificantatthe90%confidencelevel),indicatingthatoldercompanies,companieswithanambitiousgrowthplan,andcompaniesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikelytoattributethePhnomPenhprogramswithimpactonAnnualrevenues.Moreover,EmployeesthathaveuniversitydegreesissignificantlyandnegativelyassociatedwithimpactonAnnualrevenues,indicatingthatcompaniesthathavefeweremployeeswithauniversitydegreearemorelikelytoattributethePhnomPenhprogramswithimpactonAnnualrevenues.Oftheentrepreneurattributesvariables,Levelofeducationissignificantlyassociatedwithimpactonannualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesthatfoundedbyentrepreneurswithahigherlevelofeducationaremorelikelytoattributethePhnomPenhprogramswithimpactonAnnualrevenues.Model14,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains18%ofthevarianceinthedependentvariable,impactonEmployment.Model14showsthatDirectimpactfactorissignificantlyassociatedwithimpactonEmployment(significantatthe99%confidencelevel),indicatingthatcompaniesreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributethePhnomPenhprogramswithimpactontheiremployment.Ofthecompanyattributesvariables,Companyage,andInternational
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88 VietnamandCambodiaAppendix
displacementexperienceofemployeesaresignificantlyassociatedwithimpactonEmployment(significantatthe95%confidencelevel,andatthe99%confidencelevelrespectively),indicatingthatoldercompanies,andcompaniesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikelytoattributethePhnomPenhprogramswithimpactontheiremployment.Oftheentrepreneurattributesvariables,Levelofeducationissignificantlyassociatedwithimpactonemployment(significantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithahigherlevelofeducationaremorelikelytoattributethePhnomPenhprogramswithimpactontheiremployment.Model15,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains35%ofthevarianceinthedependentvariable,impactonFundingreceived.Model15showsthatDirectimpactfactorissignificantlyassociatedwithimpactonFundingreceived(significantatthe95%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributethePhnomPenhprogramswithimpactontheirfundingreceived.Ofthecompanyattributesvariables,Size,andInternationaldisplacementexperienceofemployeesaresignificantlyassociatedwithimpactonFundingreceived(significantatthe99.9%confidencelevel,andatthe90%confidencelevelrespectively),indicatingthatoldercompanies,andcompaniesthathavemoreemployeeswithinternationaldisplacementexperiencearemorelikelytoattributethePhnomPenhprogramswithimpactontheirfundingreceived.
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10.PredictorsofImpact
89
Table10.5LinearRegressionsofthePhnomPenhProgram
sVariable
Model11
Directim
pactfactor
Model12
Indirectimpact
factor
Model13
Impactonannualrevenues
Model14
Impacton
employm
ent
Model15
Impactonfundingreceived
C:Age
+ α+ α
+*
C:Size
+***
C:Grow
thplan-*
+ α
C:Fundingreceived($)
C:Internationaldisplacementofem
ployees
+**+ α
+**+ α
C:Domesticdisplacem
entofemployees
C:Em
ployeesthatarefamilym
embers
C:Em
ployeesthathaveuniversitydegrees
-*-*
C:Website
E:Age
E:G
ender(male)
E:Parentsthatow
nabusiness
E:Levelofeducation-*
+*
+ α
E:Workexperience(years)
+ α
E:Internationalexperience
-*
E:Facebookfriends
UseofServices
+*
DirectIm
pactFactor
+***+***
+**+*
ModelCharacteristics
TotalN
65
6969
7271
AdjustedR2
.43.26
.30.18
.35F(dof)
***(13)**(13)
**(13)*(13)
***(13)dof=Degreesoffreedom
α=p<.1,*=p<.05,**=p<.01,***=p<.001
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90 VietnamandCambodiaAppendix
DetailsoffivemodelsbasedonsampleoftheHCMCprogramsmaybefoundinTable10.6.Model16regressescontrolvariables,andintensityofuseofsupportservicesagainstdirectimpactoncompanies’resourcesandcapabilities.Models17,18,19,and20regresscontrolvariables,intensityofuseofsupportservices,andthedirectimpactfactoragainstimpactoncompanyperformancemeasures,.Model16,whichincludescontrolvariablesandintensityofuseofsupportservices,explains39%ofthevarianceinthedependentvariable,Directimpactfactor.Model16showsthatUseofservicesissignificantlyassociatedwithDirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatusedsupportserviceswithahigherintensityaremorelikelytoattributetheHCMCprogramswithimpactonresourcesandcapabilities.Ofthecompanyattributesvariables,SizeissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe95%confidencelevel),indicatingthatsmallercompaniesaremorelikelytoattributetheHCMCprogramswithimpactontheirresourcesandcapabilities.Oftheentrepreneurattributesvariables,EntrepreneurageissignificantlyandnegativelyassociatedwithDirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatwerefoundedbyyoungerentrepreneursaremorelikelytoattributetheHCMCprogramswithimpactontheirresourcesandcapabilities.Moreover,WorkexperienceissignificantlyassociatedwithDirectimpactfactor(significantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithmoreyearsofworkexperiencearemorelikelytoattributetheHCMCprogramswithimpactonresourcesandcapabilities.Model17,depictedinFigure10.4,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains29%ofthevarianceinthedependentvariable,Indirectimpactfactor.Model17showsthatDirectimpactfactorissignificantlyassociatedwithIndirectimpactfactor(significantatthe99%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheHCMCprogramswithimpactoncompanyperformance.
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10.PredictorsofImpact 91
Figure10.4Model17–ImpactonIndirectImpact
Model18,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,explains46%ofthevarianceinthedependentvariable,impactonAnnualrevenues.Model18showsthatDirectimpactfactorissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe99%confidencelevel),indicatingthatcompaniesthatreportedhigherimpactonresourcesandcapabilitiesaremorelikelytoattributetheHCMCprogramswithimpactontheirannualrevenues.Ofthecompanyattributesvariables,CompanyageissignificantlyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatoldercompaniesaremorelikelytoattributetheHCMCprogramswithimpactonAnnualrevenues.Oftheentrepreneurattributesvariables,Levelofeducation,andWorkexperiencearesignificantlyassociatedwithimpactonannualrevenues(bothsignificantatthe90%confidencelevel),indicatingthatcompaniesthatwerefoundedbyentrepreneurswithahigherlevelofeducation,andthatwerefoundedbyentrepreneurswithmoreyearsofworkexperiencearemorelikelytoattributetheHCMCprogramswithimpactonAnnualrevenues.Moreover,InternationalexperienceissignificantlyandnegativelyassociatedwithimpactonAnnualrevenues(significantatthe95%confidencelevel),indicatingthatcompaniesthatwerefoundedentrepreneursthathavenotstudiedorworkedinaforeigncountryaremorelikelytoattributetheHCMCprogramswithimpactontheirannualrevenues.Model19,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,onlyexplains7%ofthevarianceinthedependentvariable,impactonEmployment.NoneoftheindependentvariablesaresignificantinModel19.Model20,whichincludescontrolvariables,intensityofuseofsupportservices,anddirectimpactfactorvariable,onlyexplains5%ofthevarianceinthedependentvariable,impactonFundingreceived.NoneoftheindependentvariablesaresignificantinModel20.
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Table10.6LinearRegressionsoftheHCMCProgramsVariable
Model16Directimpactfactor
Model17Indirectimpactfactor
Model18Impactonannualrevenues
Model19Impacton
employment
Model20Impactonfundingreceived
C:Age +* C:Size -* C:Growthplan C:Fundingreceived($) C:Internationaldisplacementofemployees
C:Domesticdisplacementofemployees
C:Employeesthatarefamilymembers
C:Employeesthathaveuniversitydegrees
C:Website E:Age -** E:Gender(male) E: Parents that own abusiness
E:Levelofeducation +α E:Workexperience(years) +α +α E:Internationalexperience -α E:Facebookfriends Useofservices +** Directimpactfactor +** +** ModelCharacteristics TotalN 48 48 48 48 48AdjustedR2 .39 .29 .46 .07 .05F(dof) **(9) **(9) ***(9) (9) (9)dof=Degreesoffreedomα=p<.1,*=p<.05,**=p<.01,***=p<.00
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11.Glossary 93
11.GlossaryofTerms
Term DescriptionConfidencelevel Usedtodescribethereliabilityofacalculationorestimate.Ahigherconfidencelevel
indicatesamorereliableestimate.
Impactonresourcesandcapabilities
Improvements,withinashorttimeframe,toresourcesandcapabilities.TENexaminesimprovementstoresourcesandcapabilitiesasoutcomesofserviceofferingsfrominnovationintermediaries,suchasimprovedbusinesslinkages.
Distribution Thearrangementofthefrequencyofoccurrencearoundaparticularvalue.
Frequencydistribution Agraphicalrepresentationoftheoccurrenceofeachvaluewithinarangeofvalues.TENoftenusesthistooltorepresentthefrequencyofdifferentanswersinresponsetoaparticularsurveyquestion.
Impactonperformance Achangeinperformanceresultingfromchangesinresourcesandcapabilities.TENinvestigateschangesincompanyperformancemetricsattributabletoservicesprovidedbyinnovationintermediariesthatincreasecompanies’capacitytoperform.Forexample,changeinemployment.
Innovationintermediary Amemberofaclassoforganizationswithcommongoalsincludingthesupportofinnovation.TENworkswithinnovationintermediaries,rangingfromsmalleconomicdevelopmentorganizationstolargeandsophisticatedresearchinstitutes,whoseektomaketheirclientsmoreinnovative,intheinterestsoffacilitatingincreasesintheirviability,profitability,internationalpresence,orothermanifestationsoftheirsuccess.
Logicmodel Arepresentationoftherelationshipsbetweentheinputs,outputsandoutcomesofaprogram.TEN'sinnovationintermediarylogicmodelillustrateshowinnovationintermediariesworktofulfilltheirmissions,andhowTENmeasurestheirimpact.
Primarydata Datacollecteddirectlyfromasourcebythepersonororganizationconductingtheresearch.TENcollectsprimarydatafrominnovationintermediariesandtheirclientcompaniesthroughanestablishedsurveymethodology.
Privatefinancing Financingfromanindividualoraprivateinstitutionsuchasloansorangelinvestment.
R&D Researchanddevelopment.Companiesmayinvestinresearchanddevelopmentactivitieswiththegoalofimprovingordevelopingproductsorprocedures.
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94 VietnamandCambodiaAppendix
Resourcesandcapabilities Factorsdescribingacompany’scapacitytoperform,forexample,strategicandoperationalknowledge.
Significance Thelikelihoodthataresultorrelationshipiscausedbysomethingotherthanmererandomchance.Thestatisticalsignificancerepresentstheprobabilitythatrandomchancecouldexplaintheresult.Ingeneral,a5%orlowerp-valueisconsideredtobestatisticallysignificant.
SME Smallandmediumsizedenterprises,asdefinedbytheCanadianTradeCommissionerService,arecategorizedbysize.Smallenterpriseshavelessthan$10millioninannualsalesandlessthan50employeesintheservicesectororlessthan100employeesinthemanufacturingsector.Medium-sizedenterpriseshavelessthan$50millioninannualsalesand101to500employees.
TEN TheEvidenceNetworkInc.isanindependentthirdpartycompanythatspecializesinimpactassessmentfororganizationsthatsupportinnovation.
Timetomarket Theelapsedtimebetweentheinitialconceptstageofproductdevelopmentandwhentheproductisavailableforsale.