Training and Network Organization in Entrepreneurship in Denmark 2010

Transcription

1 Entrepreneurship comprises discovering opportunities and the exploitation of opportunities in existing and new firms. The activity is now institutionalized and supported in society, with a social role for performing the activity, the vocation called the entrepreneur. How does entrepreneurial training shape human capital? Is the human capital partly invested in the creation a network organization around the entrepreneur? Are resources embedded in the network organization, as social capital? Does human capital bring comparative advantages such as income and enhanced social capital? Does the social capital in the network organization bring comparative advantages, such as innovation, exporting and growth-expectations? Has the level of entrepreneurial activity in Denmark declined during the economic recession, and is the Danish level higher or lower than in other societies? Are the cultural and institutional framework conditions in Denmark deteriorating or stable despite the recession, and are Danish conditions better or worse than in other societies? How do the framework conditions shape entrepreneurship, and what are the effects of culture and institutions? These questions are addressed by analyzing data from our surveys in 2010 and preceding years in Denmark and many other countries, gathered mainly in our research program Global Entrepreneurship Monitor, GEM. Our up-to-date surveys and analyses provide leading indicators of current changes in entrepreneurship. THOMAS SCHØT Training and Network Organization in Entrepreneurship in Denmark 2010 Thomas Schøtt studied at the University of Aarhus (cand.scient.), Columbia University (M.A. in statistics, and Ph.D. in sociology) and Yale University (postdoc in organizational research), was Assistant Professor and Associate Professor at the University of Pittsburgh, is now Professor (mso) in the Department of Entrepreneurship and Relationship Management at the University of Southern Denmark, and is also Professor (adjunct) in the Faculty of Entrepreneurship at Tehran University. As the National Team Leader of the Danish GEM-team, he directs the Danish research program affiliated with the Global Entrepreneurship Monitor, where he is a member of the Research Committee and leads the research group on entrepreneurial networks. He teaches entrepreneurship, organizations, methodology and networks among people and organizations. He consults to agencies and international organizations on entrepreneurship, intervention, organizations, clusters and development in local and global regions. He researches entrepreneurship, innovation and network organization, and he has published numerous articles in international journals and several books, including the five research monographs, Entrepreneurship in Denmark 2005; Entrepreneurship in the Regions in Denmark 2006; Growth-Entrepreneurship in Denmark 2007; Education, Training and Networking for Entrepreneurship in Denmark 2008; and Social and Commercial Entrepreneurship in Denmark THOMAS SCHØTT Training and Network Organization in Entrepreneurship in Denmark 2010 studied via Global Entrepreneurship Monitor

2 Training and Network Organization in Entrepreneurship in Denmark 2010 studied via Global Entrepreneurship Monitor Thomas Schøtt

3 Training and Network Organization in Entrepreneurship in Denmark 2010 studied via Global Entrepreneurship Monitor Thomas Schøtt University of Southern Denmark 2010 & Thomas Schøtt Syddansk Universitet Institut for Entreprenørskab og Relationsledelse Engstien Kolding Tel: [email protected] relationsledelse.aspx Layout, sats og tryk: Jørn Thomsen / Elbo A/S, Kolding ISBN: Gengivelse af denne bog eller dele heraf er ikke tilladt ifølge gældende dansk lov om ophavsret.

4 Preface Entrepreneurship comprises discovering opportunities and the exploitation of opportunities in existing and new firms. The activity is now institutionalized and supported in society, with a social role for performing the activity, the vocation called the entrepreneur. How does entrepreneurial training shape human capital? Is the human capital partly invested in the creation a network organization around the entrepreneur? Are resources embedded in the network organization, as social capital? Does human capital bring comparative advantages such as income and enhanced social capital? Does the social capital in the network organization bring comparative advantages, such as innovation, exporting and growth-expectations? Has the level of entrepreneurial activity in Denmark declined during the economic recession, and is the Danish level higher or lower than in other societies? Are the cultural and institutional framework conditions in Denmark deteriorating or stable despite the recession, and are Danish conditions better or worse than in other societies? How do the framework conditions shape entrepreneurship, and what are the effects of culture and institutions? These questions are addressed by analyzing data from our surveys in 2010 and preceding years in Denmark and many other countries, gathered mainly in our research program Global Entrepreneurship Monitor, GEM. This study is a sequel to my five research monographs, Entrepreneurship in Denmark 2005; Entrepreneurship in the Regions in Denmark 2006; Growth-Entrepreneurship in Denmark 2007; Education, Training and Networking for Entrepreneurship in Denmark 2008; and Social and Commercial Entrepreneurship in Denmark This study is the twelfth in the series of annual thematic studies of entrepreneurship in Denmark, with up-to-date analyses covering each year from 1999 through The series is part of the research program Global Entrepreneurship Monitor (GEM), conducted by the international consortium Global Entrepreneurship Research Association (GERA), in which the Danish team is headed by the main author. The Danish team and the consortium have collected most of the data, but the analyses and interpretations are of course the sole responsibility of the author. The study was supported by a grant from the Foundation for Entrepreneurship, Fonden for Entreprenørskab. The University of Southern Denmark through our Department of Entrepreneurship and Relationship Management granted me time and facilities for the research. The study benefitted from discussions with Torben Bager, Kim Klyver, Mette Søgaard Nielsen, Lene Vestergaard, Christian Vintergaard, Mohammad Reza Zali and with our numerous colleagues in GEM/GERA around the world. This publication can also be viewed on the internet at and and further information is at University of Southern Denmark, Winter solstice 2010 Thomas Schøtt Training and Network Organization in Entrepreneurship in Denmark

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6 Table of contents Preface Contents Sammenfatning Summary in Danish PART 1 Chapter 1 Chapter 2 PART 2 INTRODUCTION Introduction: Are training and networking forming human and social capital? Methods for researching entrepreneurship in Denmark and other societies STUDENTS MOVING IN ENTREPRENEURSHIP Chapter 3 Students learning for entrepreneurship in Denmark PART 3 POPULATION AND ITS TRAINING Chapter 4 People s training to start a business: Loose coupling with education Chapter 5 People s training shaped by personal background: Gender, age and education Chapter 6 People returning for further training Chapter 7 Trained youngsters learning Chapter 8 People s competencies enhanced by training Chapter 9 Training shaping an entrepreneurial culture Chapter 10 Entrepreneurial careers and other careers loosely coupled with training Chapter 11 People s income: Gain from training PART 4 ENTREPRENEURS NETWORK ORGANIZATION Chapter 12 Entrepreneurs organizing their own network Chapter 13 Network organization shaped by the entrepreneurs training and background Chapter 14 Network organization promoting innovation, exporting and growth-expectation Training and Network Organization in Entrepreneurship in Denmark

7 PART 5 Chapter 15 Chapter 16 Chapter 17 PART 6 Chapter 18 SOCIETY The changing level of entrepreneurship in Denmark and other societies National conditions for entrepreneurship: Trends in Denmark and comparisons to other societies Effects of framework conditions upon level of entrepreneurship CONCLUSIONS Conclusions: Training and network organization bring comparative advantages Appendix with technical specifications Bibliography National teams in 2010 in Global Entrepreneurship Monitor Training and Network Organization in Entrepreneurship in Denmark 2010

8 Sammenfatning Danish Summary Entreprenørskab betegner den foretagsomme aktivitet der består i at opdage og udnytte forretningsmuligheder ved at starte og drive virksomhed. Det omfatter dermed også intraprenørskab der betegner opdagelse af muligheder undervejs i driften af eksisterende virksomheder og udnyttelsen deraf ved at starte og drive en ny enhed. Aktiviteten opstart kaldes nu ofte iværksætteri, mens aktiviteten drift af virksomhed ofte kaldes ejer-ledelse eller selvstændig erhvervsdrift. Betegnelsen entreprenørskab dækker hermed både iværksætteri og ejerledelse eller selvstændighed. Entreprenørskab er en aktivitet der udføres som en erhvervsbeskæftigelse, der egentlig bør betegnes entreprenør efter det oprindelige franske entrepreneur, der i angelsaksiske samfund er blevet til betegnelsen for denne beskæftigelse. Entreprenør sammenfatter hermed de beskæftigelser, der ofte betegnes iværksætter, ejer-leder og selvstændig erhvervsdrivende. Entreprenørskab er blevet etableret og institutionaliseret som en samfundsinstitution med institutionelle og kulturelle rammer. Den kulturelle værdi, der af samfundet tillægges entreprenørskab, kommer kulturelt til udtryk i prestige af entreprenør som erhvervsbeskæftigelse, i anerkendelse af veludført entreprenant virke og også i undervisning i entreprenørskab. Institutionaliseringen af entreprenørskab foregår også i verdenssamfundet, hvor et verdensomspændende netværk af indflydelsesrige organisationer, centreret omkring OECD, Verdensbanken og Forenede Nationer (især FNs organisation for industriel udvikling UNIDO), rådgiver om rammevilkår der kan fremme entreprenørskab, også i Danmark (OECD 2008). Den verdensomspændende institutionalisering af entreprenørskab er et led i moderniseringen, udviklingen og globaliseringen af menneskeheden. Siden 1990erne er den globale institutionalisering af entreprenørskab også fremmet af en international sammenslutning af forskere, nu formaliseret som Global Entrepreneurship Research Association (GERA), især gennem sammenslutningens forskningsprogram Global Entrepreneurship Monitor (GEM), som dette studie og forfatteren er tilknyttet, som National Team Leader for det danske forskerteam. I forskningsprogrammet Global Entrepreneurship Monitor gennemfører vi hvert år en spørgeskemaundersøgelse af befolkningen i hvert deltagende land og næsten hvert år også en ekspertvurdering af landets rammevilkår (Chapter 2). Op til 2010, siden begyndelsen i 1999, har 83 lande deltaget i et eller flere år. Danmark har deltaget i hvert af de 12 år, så vi opdaterer løbende og ser de aktuelle udviklingstendenser. Ved sammenligninger af mange lande kan vi studere den generelle dynamik i entreprenørskab, som den typisk er i mange lande, især i de højt udviklede lande, og mere specifikt den danske dynamik. Læring, som den kan opnås gennem træning og netværk, er i fokus. Det store spørgsmål er: Training and Network Organization in Entrepreneurship in Denmark

9 Sammenfatning Danish Summary Hvordan ekspanderer læring og entreprenørskab gennem træning og netværk? Spørgsmålet præciseres ved at fokusere på landets befolkning og på entreprenørerne: Hvad er de studerendes læring når de undervises i iværksætteri? Hvordan ekspanderer befolkningen gennem træning deres humane kapital og deres involvering i entreprenørskab? Hvordan investerer entreprenører deres trænings-baserede humane kapital i dannelsen af netværk med ressourcer, som en social kapital? Hvordan bringer denne trænings-baserede sociale kapital komparative fordele til de trænede entreprenør igennem ekspanderende innovation, eksport og vækstforventninger? De studerendes læring og involvering i iværksætteri Træning betegner her undervisning og anden modtagelse og indlæring af viden om at starte en virksomhed. Træning omfatter derfor undervisning de studerende får igennem uddannelser, modtagelse af viden som unge får ved siden af uddannelser, og indlæring som voksne får efter afslutningen af deres uddannelser. At træning kan forekomme i mange kontekster hænger nok sammen med at træning er et ekspanderende fænomen og også med at entreprenørielle kompetencer er mangfoldige. Uddannelserne udgør en søjle af klodser der stables ovenpå hinanden, og læringen i hver klods bygger oven på tidligere læring. Træning i iværksætteri kan også tænkes som moduler, hvor de første moduler indpoder motivation for iværksætteri og senere moduler udvikler kreativitet, og endnu senere moduler indlærer færdigheder. Uddannelse omfatter grundskole, ungdomsuddannelse som enten gymnasial uddannelse eller erhvervsuddannelse, og videregående uddannelse. Unges veje gennem uddannelserne til beskæftigelse illustreres i Figur A. 8 Training and Network Organization in Entrepreneurship in Denmark 2010

10 Sammenfatning Danish Summary Figure A. Veje gennem uddannelser til besk æftigelse Iværksætter eller selvstændig Ansat eller andre beskæftigelser Videregående uddannelse Gymnasial uddannelse Erhvervsuddannelse Grundskole Træning i iværksætteri kan fås undervejs i uddannelserne, og også ved siden af uddannelserne og efter afslutningen af uddannelserne. I surveyet i 2010 spurgte vi enhver (i alderen 15 til 64 år) om deres modtagelse og indlæring af viden om at starte en virksomhed: I din folkeskole, har du der fået nogen undervisning i at starte en virksomhed? De med nogen ungdomsuddannelse spurgtes, hvis den var en erhvervsuddannelse: I din erhvervsuddannelse, har du der fået nogen undervisning i at starte en virksomhed? eller, hvis den var en gymnasial uddannelse: I din gymnasiale uddannelse, har du der fået nogen undervisning i at starte en virksomhed? De med nogen videregående uddannelse spurgtes også: I din videregående uddannelse, har du der fået nogen undervisning i at starte en virksomhed? Enhver spurgtes også: Imens du var under uddannelse, har du da uden for skolen fået nogen træning i at starte en virksomhed? De, der ikke længere var studerende, spurgtes også: Senere hen, efter du sluttede din uddannelse, har du så fået nogen træning eller undervisning i at starte en virksomhed? Training and Network Organization in Entrepreneurship in Denmark

11 Sammenfatning Danish Summary Besvarelserne af disse spørgsmål er basis for redegørelsen for de studerendes træning, Chapter 3, Students learning for entrepreneurship in Denmark. Får mange studerende træning i at starte virksomhed? Ja, halvdelen af de studerende (i alderen 15 år og opefter) har fået træning i at starte virksomhed. De trænede studerende har typisk fået deres træning inden for deres uddannelser, og sjældnere ved siden af uddannelsen. Er studerendes træning tildels en social arv? Ja, træning tenderer til at være nedarvet fra forældrenes uddannelse og erhverv. Studerende hvis fædre fik hverken erhvervsuddannelse eller højere uddannelse er mere tilbøjelige til at trænes end studerende hvis fædre fik erhvervsuddannelse eller højere uddannelse. Studerende hvis forældre har været selvstændigt erhvervsdrivende er mere tilbøjelige til at trænes end studerende uden forældre der har været selvstændigt erhvervsdrivende. Er studerendes træning mest teoretisk eller mest praktisk? De studerendes træning inden for uddannelsen er oftest mere teoretisk end praktisk. Men alligevel øger træningen ofte de studerendes lyst og evner til at starte, synes de. Har trænede studerende oftere entreprenørielle kompetencer end utrænede studerende? Ja, trænede studerende har særlig ofte entreprenørielle kompetencer såsom tillid til egen evne til at starte en virksomhed, årvågenhed for muligheder for at starte, og risikovillighed. Har trænede studerende oftere end utrænede studerende holdninger der udtrykker en iværksætterkultur? Ja, trænede studerende har oftere end utrænede studerende holdninger såsom at en karriere som iværksætter er en god karriere og at medierne ofte bør bringe historier om virksomheder med succes. Har trænede studerende oftere end utrænede studerende til hensigt at blive iværksættere? Ja, trænede studerende har oftere end utrænede studerende en intention om at starte egen virksomhed inden for en overskuelig fremtid. Er trænede studerende oftere end utrænede studerende begyndt som iværksættere? Ja, trænede studerende er oftere end utrænede studerende i gang med deres eget, hvorved de tjener en skilling, så de er begyndt som studenter-iværksættere. Får studenter-iværksættere ofte opbakning fra familien, venner og skolen? Studenter-iværksættere får typisk opbakning fra familie og venner, men sjældnere fra skolen. Befolkningens træning Er befolkningen trænet trænes mange og er træningen knyttet til uddannelse? Ja, knapt halvdelen af folk i alderen 15 til 64 år har fået træning i en eller flere kontekster. De fleste blandt de trænede har modtaget træning inden for uddannelsen, en del har fået træning ved siden af uddannelsen, og en del har fået træning efter afslutningen af deres uddannelse. Kønnet er uden betydning for omfanget af træningen, omend der er lidt forskel på hvor hvert køn får træning. Er træning livslang er trænede særlig tilbøjelige til senere træning? 10 Training and Network Organization in Entrepreneurship in Denmark 2010

12 Sammenfatning Danish Summary Ja, de der fik træning inden for grundskolen er særlig tilbøjelige til også at få træning inden for ungdomsuddannelsen. De der fik træning inden for ungdomsuddannelsen er særlig tilbøjelige til også at få træning inden for videregående uddannelse. De der fik træning inden for uddannelsen er også særlig tilbøjelige til at få træning ved siden af uddannelsen. De der fik træning ved siden af uddannelsen er også særlig tilbøjelige til at få træning senere, efter afslutningen af uddannelsen. Dermed tenderer træning til at blive en livslang proces. Kønnet er uden betydning; kvinder og mænd har lignende tilbøjelighed til at gøre kompetenceudvikling til en livslang proces. Er træning fremmende for lyst og kompetencer til at innovere og starte? Ja, træning fremmer ofte lyst og især kompetencer til innovation og opstart. Lysten og kompetencen til innovation øges lige hyppigt for kvinder og mænd. Lysten og kompetencen til at starte øges hyppigere blandt mænd end blandt kvinder. Er træning til gavn i folks senere jobs? Træning gavner ofte folk i deres nuværende beskæftigelse, selvfølgelig især hvis de er selvstændige erhvervsdrivende, men også hvis de er ansatte. Mænd har hyppigere end kvinder gavn af træningen, både hvis de er selvstændige erhvervsdrivende og hvis de er ansatte. Er træning tæt koblet til iværksætteri og selvstændighed og løst koblet til andre karrierer? Ja, folk med træning er mere tilbøjelige end folk uden træning til at være i færd med at starte, at have til hensigt at starte, og til at eje og lede en etableret virksomhed. Omvendt er trænede mindre tilbøjelige end utrænede til at have andre beskæftigelser. Kønnet er uden betydning for disse koblinger. Giver træning en særlig høj indkomst? Ja, trænede har betydelig højere indkomst end utrænede. Jo mere træning, jo højere er indkomsten, også når vi kontrollerer for andre forhold, såsom køn, alder, uddannelse og beskæftigelse. Kønnet er uden betydning herfor, idet træning øger indkomsten for både kvinder og mænd. Ekspanderer læringen befolkningens involvering i entreprenørskab? Ja, folks uddannelse, træning, kompetence og netværk har hver en effekt på deres erhvervsbeskæftigelse hvorvidt de er entreprenører eller ej. Folk med lang højere uddannelse er særlig tilbøjelige til at blive entreprenører. Trænede folk er oftere entreprenører end utrænede folk, kompetente folk er oftere entreprenører end mindre kompetente folk, og folk der netværker er oftere entreprenører end folk der ikke netværker med en starter (Schøtt 2009). At lang uddannelse, træning, kompetence og netværk fremmer tilbøjeligheden til at blive entreprenør overrasker nok ikke, men det er væsentligt at se at hver bidrager til at ekspandere befolkningens involvering i entreprenørskab. Disse effekter på folks erhvervsbeskæftigelse vises i Figur B. Training and Network Organization in Entrepreneurship in Denmark

13 Sammenfatning Danish Summary Figur B. Folks erhvervsbeskæftigelse formet af deres uddannelse, træning, kompetence og netværk Erhvervsbeskæftigelse Netværk Kompetence Træning Uddannelse Entreprenørens netværksorganisation Hvordan organiserer en entreprenør arbejdet? En entreprenør der har intention om at starte, er i færd med at starte, eller driver en virksomhed afhænger af og bruger mange 12 Training and Network Organization in Entrepreneurship in Denmark 2010

14 Sammenfatning Danish Summary slags ressourcer. En vigtig ressource er viden, både i form af tidligere læring fra uddannelse, træning og erfaring og i form af rådførsel med omgivelserne, både forhåndenværende bekendte og folk der kan opsøges og give råd. Entreprenører får råd fra en snæver eller bred kreds af rådgivere fra forskellige sfærer eller kontaktflader i entreprenørens liv. Entreprenørens relationer med disse rådgivere betegnes entreprenørens netværk af rådgivere, rådgivningsnetværk eller rådførselsnetværk, idet rådførslen er i fokus. Netværket er en organisation rundt om entreprenøren. Det er samlebåndet hvor entreprenøren samler information og andre ressourcer som knyttes sammen i entreprenørens arbejde, men arbejdet er mindre planlagt og mindre systematisk end et samlebånd. Arbejdet er heller ikke som et puslespil, for der mangler brikker og er brikker som ikke matcher andre. Arbejdet følger nok mere de forhåndenværende søms princip, som en bricolage hvor arbejdet bliver en konstruktion der udnytter og kombinerer tilgængelige ressourcer i omgivelserne, netop ressourcer der er i netværket, som derved rummer en social kapital. Netværkets ressourcer er en form for kapital i den udstrækning den kan bringe gavn, et udbytte der overstiger omkostningen, og kan være særlig gavnlig og dermed give en komparativ fordel. Organiseringen af netværket, netværksorganisationen, og måden netværket er organiseret rundt om entreprenøren, har forventeligt konsekvenser for det entreprenørielle foretagende. Denne forståelse af netværksorganiseringen udnytter teorier om organisationer, der kaldes ressourceafhængighedsteori og informationsprocesteori, hvor organisationers præstation betinges af deres evne til at opnå information og andre ressourcer og deres kapacitet til at kombinere og behandle dem effektivt og produktivt. Netværksorganisationen har organisatoriske egenskaber såsom dens størrelse og dens konfiguration af sfærer eller kontaktflader med ressourcer. Størrelsen af netværket omkring en entreprenør er den organisatoriske egenskab som oftest er undersøgt. Størrelse indikerer mængden af information og andre ressourcer som kan opnås. Størrelsen af en entreprenørs netværk har i tidligere undersøgelser vist sig at have en positiv effekt på entreprenørens præstation, især overlevelse, fortjeneste og vækst, og også for innovation, eksport og forventning til vækst (Schøtt 2009). Netværksorganisationen kan også bringe fordele ved andre egenskaber end dens størrelse. Nogle slags relationer og nogle konfigurationer af relationer kan rumme fordele. Social kapital rummes især i netværk med et bredt spektrum af vidt forskellige kontakter, i netværk med svage bånd til kontakter, i netværk med tætte relationer indbyrdes imellem kontakterne, i netværk der giver autonomi og handlefrihed til aktøren i centrum, og i netværk med huller imellem kontakterne. Her fokuserer jeg på netværkets konfiguration af sfærer eller kontaktflader til omgivelserne omkring entreprenøren. Så spørgsmålene er: Hvordan er netværket organiseret? Mere specifikt: Organiserer entreprenører typisk en kreds af rådgivere som er stor eller lille? Hvad er sfærerne eller kontaktfladerne i omgivelserne hvor entreprenøren har sine rådgivere? Hvordan er nogle sfærer eller kontaktflader særlig betydelige eller prominente? Hvordan er kontaktfladers betydningsfuldhed eller sfærers prominens betinget af den nationale kultur? Entreprenører har netværk af vidt forskellig størrelse, viser det sig i undersøgelsen. Training and Network Organization in Entrepreneurship in Denmark

15 Sammenfatning Danish Summary Nogle få entreprenører fortæller at de ikke rådfører sig med nogen om deres foretagende, mens andre entreprenører snakker med over et dusin rådgivere. I gennemsnit bruger entreprenører omkring en håndfuld rådgivere. Men entreprenører er meget forskellige fra hinanden i størrelsen af deres netværk. Omgivelserne omkring en entreprenør er ikke en homogen masse af kontakter, men består af forskellige kontaktflader. Undersøgelsen afdækker fem kontaktflader eller sfærer i en entreprenørs netværk: privatsfæren af entreprenørens familie og venner jobsfæren af entreprenørens chef og arbejdskolleger professionelle sfære af revisor, advokat og bankrådgiver markedssfæren af samarbejdspartnere, konkurrenter, leverandører og kunder entreprenørskabssfæren af mentorer, offentlige erhvervsvejledere, investorer, udenlandske kontakter, kontakter der er kommet fra udlandet, forskere og opfindere. Disse fem sfærer eller kontaktflader giver oftest forskellige slags råd. Privatsfæren giver nok oftest støtte og opmuntring, men undertiden nedvurdering og fraråd. Jobsfæren giver nok ofte inspiration og sparring. Den professionelle sfære tilbyder kodificeret viden. Markedssfæren giver nok mest information om forretningsmuligheder. Entreprenørskabssfæren giver nok mest tavs, uformel og ukodificeret viden om entreprenørskabens kunst. Nogle entreprenører rådfører sig mest med privatsfæren, andre entreprenører rådfører sig mest i jobsfæren, andre entreprenører konsulterer mere i den professionelle sfære, andre entreprenører opsøger mest markedssfæren, mens andre entreprenører især rådfører sig med entreprenørskabssfæren. Så for en entreprenør er nogle sfærer særlig prominente, mens andre sfærer er betydningsløse. For en entrenør afhænger prominensen eller betydningsfuldheden af en sfære af den national kontekst. Jo mere rationalistisk-verdslig kulturen er modsat traditionel kultur jo mindre prominent er privatsfæren, og jo mere prominente er jobsfæren, den professionelle sfære, markedssfæren og entreprenørskabssfæren. Fremmes netværksorganiseringen af træning? De organisatoriske egenskaber ved netværket afhænger også af entreprenørens personlige karakteristika. Privatsfæren er særlig prominent for entreprenører i den allertidligste fase, og som er unge og kvinder. Træning øger størrelsen af netværket betydeligt, træning øger betydningsfuldheden af den professionelle sfære og træning øger også prominensen af markedssfæren. Trænede entreprenører investerer dermed deres trænings-baserede humane kapital i skabelsen af social kapital i form af store netværk der rummer værdifulde ressourcer som kan øge deres præstation og bringe komparative fordele. Fremmer netværksorganiseringen innovation, eksport og vækstforventning? Præstationen omfatter entreprenørers innovation, eksport og vækst-forventning. Analyserne viser at præstationer påvirkes af netværksorganiseringen. Størrelse på netværk fremmer eksport og vækst-forventning. Prominens af entreprenørskabssfæren og prominens af markedssfæren fremmer innovation. Ekspansiv entreprenørskab betegner her den entreprenørskab der er særlig innovativ, eksporterende og vækstforventende. Vi vil så sige at entreprenørskab er ekspansiv i den grad den er innovativ, eksporterende og vækstforventende. Ligeledes kalder vi en 14 Training and Network Organization in Entrepreneurship in Denmark 2010

16 Sammenfatning Danish Summary entreprenør ekspansiv i den udstrækning entreprenøren innoverer, eksporterer og forventer vækst. Hvorvidt landets entreprenører er ekspansive afhænger af deres uddannelse, træning, kompetence og netværk, på de måder at entreprenører med lang videregående uddannelse, med træning, med entreprenøriel kompetence, og med store netværk med prominens i markedssfæren og den professionelle sfære tenderer til at være særlig ekspansive. Disse effekter på ekspansivitet afbildes i Figur C. Figur C. Entreprenørers ekspansivitet formet af deres uddannelse, træning, kompetence og netværk Ekspansivitet Netværksorganisering Entreprenøriel kompetence Træning Uddannelse Training and Network Organization in Entrepreneurship in Denmark

17 Sammenfatning Danish Summary Samfundets vilkår for iværksætteri påvirker niveauet i iværksætteriet Danmark og andre lande Hvad er niveauet i entreprenørskab i Danmark? Mere specifikt: Er udviklingstendensen i niveauet opadgående, stabil, eller nedadgående? Hvor højt er niveauet i Danmark sammenlignet med andre udviklede lande? Det danske niveau af iværksætteri i opstartsfasen, målt som voksenbefolkningens rate af iværksættere der er i færd med at starte eller lige har startet en virksomhed, er faldet under krisen og er nu noget lavere end det typisk er for de udviklede lande. Men når vi måler den allertidligste fase, fasen hvor folk har en intention om at starte inden for overskuelig fremtid, så ser vi i Danmark i 2010 en ny stigning i raten af folk der har til hensigt at starte ny virksomhed inden for de næste få år. Denne nylige stigning i intentioner i Danmark kan betragtes som en forløber, en tidlig eller ledende indikator, for en kommende stigning i opstartsraten. Men vilkårene for at omsætte en intention om at starte til handling kan jo være lammende, så derfor skal vi ikke forvente at den stigende interesse udløser en markant ny stigning i iværksætteriet. Hvordan er de nationale rammevilkår for entreprenørskab i Danmark? Mere specifikt: Er kulturelle og institutionelle vilkår i Danmark under forbedring eller forringelse? Hvor gode er vilkårene i Danmark sammenlignet med betingelserne i andre lande? Ved ekspertvurderinger har vi opnået indikatorer på rammevilkår i Danmark og i andre lande igennem de senere år. De 14 rammevilkår omfatter 4 kulturelle vilkår individualisme som en kulturel værdi, prestige af iværksætteren som erhvervsbeskæftigelse, uddannelse og træning i entreprenørskab, befolkningens færdigheder i entreprenørskab samt 10 institutionelle vilkår: mulighederne for entreprenørskab, finansielle ressourcer, regeringspolitik for entreprenørskab, offentlige støtteprogrammer, overførsel af teknologi til erhvervslivet, kommerciel og juridisk infrastruktur, markedets åbenhed for ny virksomhed, den teknisk-fysiske infrastruktur, ophavsrettigheder og patentsystem, samt støtteforanstaltninger til vækst-entreprenørskab. De fleste af rammevilkårene i Danmark er blevet bedre igennem de senere år. Nogle få af vilkårene er stagnerende. Få af vilkårene er alvorligt forringede igennem de senere år, mest adgangen til kapital. Alt i alt er rammen for dansk iværksætteri igennem de senere år blevet mere favorabel. Til trods for forbedringerne, så er vilkårene i Danmark stadig omkring midten i sammenligninger med de andre udviklede lande. De fleste rammevilkår i Danmark er som de typisk er i de udviklede lande, enkelte vilkår er betydeligt bedre i Danmark, og enkelte vilkår er betydeligt ringere i Danmark end typisk blandt de udviklede lande, så alt i alt er rammen i Danmark ret typisk. Hvad er den nationale dynamik i entreprenørskab? Mere specifikt: Hvordan påvirker de kulturelle vilkår hinanden? Hvordan er de institutionelle betingelser relateret til hinanden? Hvad er de særskilte effekter fra de kulturelle og institutionelle rammebetingelser på entreprenørskab? Rammevilkårene i et land påvirker niveauet af iværksætteri i landet betydeligt, viser en statistisk analyse af de udviklede lande. Befolkningens færdigheder fremmes betydeligt af undervisning i iværksætteri, og af værdien af individualisme i landet. Mulighederne for iværksætteri fremmes betydeligt af de mere konkrete institutionelle rammer. Gode 16 Training and Network Organization in Entrepreneurship in Denmark 2010

18 Sammenfatning Danish Summary muligheder i landet koblet med gode færdigheder i befolkningen fremmer niveauet af iværksætteri i samfundet. Den nære sammenhæng mellem rammevilkår og niveauet i iværksætteri illustreres af Danmarks position. Danmarks rammevilkår har været som typisk for udviklede lande (over det seneste årti, som helhed). Den generelle sammenhæng mellem vilkår og niveau, medfører at niveauet i Danmark har været som typisk for udviklede lande. Den tætte kobling mellem rammerne og aktivitetsniveauet illustreres også af USA. USA har haft de bedste rammevilkår, alt i alt, for iværksætteri, ifølge målingerne i GEM (over det seneste årti, som helhed). Disse rammevilkår gør at niveauet i USA har været særdeles højt, et af de højeste blandt de udviklede lande. Training and Network Organization in Entrepreneurship in Denmark

19

20 Chapter 1. Introduction: are training and networking forming human and social capital? Once upon a time, entrepreneurship was considered something people might do if they were gifted and inspired. Success was considered the result of a gift, received at birth, the result of bringing the gift to fruition, and the successful business might bring a glorious reputation to its founder. Failure was often attributed to lack of such a gift, and the failure would bring disrepute to the starter. Considered a matter of gift and inspiration, entrepreneurship did not involve learning. The conception of entrepreneurship changed. Entrepreneurship came to be considered something that can be learned. Learning could come through trial and error in solitude. Success was considered the result of hard work, through a series of trials and errors, conducted in solitude. Considered something learnable by experiencing trials and errors in solitude, entrepreneurship did not involve instruction or learning from others. The conception is changing again. Nowadays, entrepreneurship is considered learnable, both as codified knowledge that can be acquired through formal instruction and education and as tacit knowledge that can be acquired as advice, as know-how and as experiential learning, for example as apprentice in a business. Educators and policy-makers are now busy creating and extending instruction in entrepreneurship, so that more levels and kinds of education will include instruction in entrepreneurship, so that more pupils, students and adults will learn entrepreneurship, so that they will learn more elements of entrepreneurship, not only things like developing a business plan, planning production and targeting sales, but also will learn the very inception of the entrepreneurial process such as nurturing motivation, pursuing interests, generating bold ideas, elaborating sketches and evaluating feasibilities. Entrepreneurship can be conceptualized as the activity that comprises discovering opportunities and the exploitation of opportunities in existing and new firms. The activity is now institutionalized and supported in society, with a social role for performing the activity, the vocation called the entrepreneur (Christensen 2005, Swedberg 2000). It may therefore be fruitful to focus on the people who may become involved and perform the activity and the learning affecting their involvement and performance. I here investigate people s learning through their education in entrepreneurship, their training in starting a business, and their networking through which they may learn, and investigate how people s learning expands their involvement in entrepreneurship and how entrepreneurs learning expands their innovation, exports and expectations for growth. Training creates human capital in the heads and minds of people, who then as entrepreneurs utilize their human capital to pursue, select and nurture Training and Network Organization in Entrepreneurship in Denmark

21 Introduction: Are training and networking forming human and social capital? networks and take advantage of resources embedded in the networks, which thus is a form of capital, social capital (Coleman 1988). The human capital thus goes into the entrepreneurs creation of social capital, from which they may gain a comparative advantage. The monograph is thus about training shaping human capital that goes into the creation of social capital which brings comparative advantages. Before substantive issues are addressed, we consider the methodology: How can we research entrepreneurship? Specifically, Chapter 2 addresses the methodological problem, How are we investigating entrepreneurship at the levels of society, people and performers? Students, as one segment of the population, are in focus in Part 2 of the monograph. Students training and involvement in entrepreneurship in Denmark are examined in Chapter 3. Training to start a firm denotes instruction and other acquisition of knowledge and skills about starting a business. Training of therefore comprises instruction through formal education, receipt of knowledge alongside education (i.e. outside, but during education). Training also refers to learning upon finishing formal education (but that is not considered in Chapter 3 about students, but is considered in the subsequent chapters). Training thus occurs in several contexts, partly because entrepreneurial training is growing and expanding in society and partly because entrepreneurial competencies are so diverse and complex (Bager & Nielsen 2005). Education is like a column of building blocks, where learning in each block builds upon earlier blocks of learning. Training for entrepreneurship can also be considered as modules where the early modules may mainly instill motivation for innovation and for starting a firm, later modules may mainly develop creativity, opportunity-awareness and risk-willingness, and even later modules may mainly teach skills. The questions in Chapter 3 are, Are students frequently trained to start a business? Are students mostly trained within their education or mostly alongside their education? Is training often socially inherited, dependent on their parents education and occupation? Is training in education mainly theoretical or mainly practical? Does training often enhance motivation and competency to innovate and start a firm? Do trained students more often than untrained students have entrepreneurial competencies? Do trained students more often than untrained students have attitudes of an entrepreneurial culture? Are trained students more often than untrained students intending to become entrepreneurs and working independently as student-entrepreneurs? Are student-entrepreneurs supported by family, friends and schools? Having focused on the students as a segment of the population in Denmark, we broaden the perspective in Part 3 to examine the population and its training in entrepreneurship. People in the adult population may be trained like students and may also be trained upon finishing their schooling; in particular, they may get on-the-job-training during more or less formalized apprenticeship. The questions in Chapter 4 are, Are people frequently trained? Is people s training typically coupled with education? 20 Training and Network Organization in Entrepreneurship in Denmark 2010

22 Introduction: Are training and networking forming human and social capital? Training is unlikely to be uniform throughout the population. Likelihood of training may depend on personal background such as gender, age and extent of education. The questions in Chapter 5 are, Are people trained equally frequently in the genders and ages, or does likelihood of training depend on gender and age? Is people s training coupled with education in the same way for the genders and ages, or does coupling depend on gender and age? Is people s extent of training tightly coupled to education, in the way that the more education people have the more training they tend to have. We would expect that training depends on gender in the way that more of the men than of the women have been trained because entrepreneurship is traditionally a male vocation. We would expect that training depends on age in the way that more of the young than of the older have been trained because training in schools has been expanding during recent decades. We would expect training to be coupled to education as a positive correlation, in the way that the more education people have the more training they tend to have. Training to start a business may involve becoming motivated to start, assimilating entrepreneurial cultural orientations, honing awareness of opportunities, becoming able to evaluate ideas, and learning to commit, organize, plan and execute. Training does not in one shot train all these competencies. First people may be trained in some things, and then later return for further training in other things. It is therefore important to examine whether training is typically a once-in-a-lifetime experience, or whether people trained in one context are especially likely to return for further training. The question of whether people trained in one context have high odds of returning for further training in another context is therefore a series of questions, addressed in Chapter 6, Do people trained in one part of their schooling have high odds of becoming trained later in their schooling? Do people trained within education have high odds of becoming trained alongside education? Do people trained within education have high odds of becoming trained upon completion of education? Do people trained alongside education have high odds of becoming trained upon completion of education? We would expect that training begets training in every way, and that the odds for returning for further training are high. The learning from the training is examined, what the trained youngsters have acquired and learnt during their training, and also the benefits of training. The questions in Chapter 7 are, Is training within education mostly theoretical or mostly practical? Does training typically enhance motivation and ability to innovate and start a business? Does training benefit people in their jobs and in some occupations more than in others? From the focus on trained youngsters we again broaden the perspective to the population to examine people s competencies for entrepreneurship, and differences in competencies of trained persons and untrained persons. The questions in Chapter 8 are, Training and Network Organization in Entrepreneurship in Denmark

23 Introduction: Are training and networking forming human and social capital? Are competencies distinguishing entrepreneurs from non-entrepreneurs? Have competencies in the population been changing during the last decade? Are competencies dependent on personal background such as gender, age and education? Are trained persons more competent than untrained persons? We would expect certain competencies to be common among entrepreneurs and far less prevalent among non-entrepreneurs, perhaps even rare, so that the competencies distinguish entrepreneurs from non-entrepreneurs. We would also expect that competencies in the population have been increasing because of the increasing training in entrepreneurship. Competencies expectedly depend on gender in the way that males have more entrepreneurial competencies than women do, partly because males get more training than women do. Competencies expectedly depend on education in the way that highly educated persons have more entrepreneurial competencies than less educated persons. These expected associations are of course merely formulations of hypotheses, which are more or less plausible and which are to be tested here. Training is not just training competencies but is also shaping an entrepreneurial culture. Culture refers to the things that are valued in society, the things that people attach value to. To the extent entrepreneurship is valued in society, the culture is entrepreneurial and society has an entrepreneurial culture. The concept of culture thus applies to society. The culture in a society may change over time, it may become increasingly entrepreneurial. Policies in Denmark and around the world aim at changing the culture, and to make it increasingly and pervasively entrepreneurial. The concept of culture can also be applied more narrowly when things are highly valued in part of society and less valued in another part of society, and we then call this a subculture. Thus, we may possibly find that a society does not have an entrepreneurial culture but has an entrepreneurial subculture. Policies aiming at changing the culture may succeed in creating an entrepreneurial subculture within one part of society, specifically the young generation, but not in other parts of society. The questions in Chapter 9 are, Is the culture in Denmark changing in the direction of an entrepreneurial culture? Is an entrepreneurial subculture prevailing within a gender, specifically among men? Is an entrepreneurial subculture prevailing within an age-group, specifically the young? Is an entrepreneurial subculture prevailing within an educational group, specifically those with vocational secondary education? Is an entrepreneurial subculture prevailing among the trained people? We would expect that the culture in Denmark has become more entrepreneurial in recent years. But we also expect that culture is not uniform, but that there may well be an entrepreneurial subculture among men, in the young generation, among those with vocational secondary education, and among those who have been trained to start a b usiness. Training affects careers. There may be a tight coupling between and education and an occupation. For example, learning to work with electrical installations is a vocational education in the form of apprenticeship with schooling, the learner is an electrician-apprentice who then graduates as a skilled craftsman and becomes an electrician who can be self-employed and work independently in the occupation of electricians 22 Training and Network Organization in Entrepreneurship in Denmark 2010

24 Introduction: Are training and networking forming human and social capital? who are certified by their education. This education and occupation are coupled tightly in so far as the education is a necessary and sufficient condition for the occupation. Another example is the coupling between Ph.D. education and research as an occupation; this education and occupation have a coupling that is tight to the extent most youngsters with this education become researchers and most researchers have this education. Such tight coupling often defines a profession. Entrepreneurship is not a profession in so far as entrepreneurs are not educated or trained in entrepreneurship. Policies, however, are aiming to professionalize entrepreneurship, to tighten the coupling between the entrepreneurial occupation and the entrepreneurial training (Schøtt and Ottósson, 2009). The questions in Chapter 10 are, Do trained people much more frequently than untrained people become entrepreneurs? Do entrepreneurs much more frequently than non-entrepreneurs have training? Training affects careers and, in turn, may have consequences for their income. Training to start a firm often makes the trained persons more motivated and competent to innovate and start a firm, and is often beneficial in work, not only in self-employment but also in employment, as we saw in Chapters 7, 8 and 9. So we would also expect that training often increases income. We hypothesize a tendency that the more training people have received, the higher is their income. Such a tendency has been found in an American study (Charney & Libecap 2000; see also Lepoutre et al 2010). So the question in Chapter 11 is, Does people s training increase their income? Having considered the population and its training, we then focus on the entrepreneurs in Part 4, specifically on the kind of organization they create, a network organization. Entrepreneurs intending to start a business, or starting a business, or running an established business depend on and utilize many kinds of resources. An important resource is knowledge, both in the form of past learning from their education and experience and ongoing in the form of advice from their environment. Entrepreneurs get advice from advisors, a narrow or wide circle of advisors drawn from various spheres in the life of the entrepreneur. The entrepreneur s relations with these advising persons are called the entrepreneur s network of advisors or advice network. The network is an organization around the entrepreneur. It is the assembly-line where the entrepreneur assembles information and other resources that go into the entrepreneurial work, but it is less orderly and planned than an ordinary assembly-line. The assembly is more like bricolage. The organization of this network, the network organization, and the way it is organized around the entrepreneur, is expectedly important and consequential for the entrepreneurial work. The network organization around an entrepreneur has several properties that may be important and consequential. These organizational properties of the network around a person should be conceptualized (Burt et al 1983). The property, that has attracted most attention, is size, size of the network around the person. Size is theorized to be important because it connotes the volume of resources or information that the person may obtain. Such information or resources can bring benefit and is therefore a kind of capital, denoted social capital, and is social because the advantage is reaped in the social environment (Bourdieu 1980, 1986). The person invests in creating and maintaining the network and can mobilize it to bring advantage and reap a profit when the benefit Training and Network Organization in Entrepreneurship in Denmark

25 Introduction: Are training and networking forming human and social capital? exceeds the investment (Coleman 1988). The size of an entrepreneur s network has been found to bring benefit, specifically for survival, profit and growth (Schøtt 2007) and also for innovation, exporting and growth-expectation (Schøtt 2009). The organization of the network, in its qualities apart from size, may also bring advantage. Certain kinds and configurations of relations tend to bring advantage. Social capital may reside in networks that reach across a wide spectrum of kinds of contacts (Lin et al 2008), networks that have weak ties to contacts (Granovetter 1973, 1983), networks that have dense relations among the contacts (Berkman et al 1979, Coleman 1988), networks that confer autonomy on the actor (Coser 1975), and networks that have disconnects or holes among the contacts, rather than being dense (Burt 1992). The organization of the network, and not only its size, will also be examined here. The organization of the network around an entrepreneur will here be conceptualized in terms of the salience of spheres of the environment from where the advisors are drawn. The questions in Chapter 12 are, How is the network organized? What are the spheres in the environment around an entrepreneur which gives advice on the business? How is salience of a sphere shaped by the national culture? The organization of the network around an entrepreneur is partly shaped by characteristics of the country, and partly shaped by characteristics of the entrepreneur. The question of how the network organization is shaped by characteristics of the entrepreneur can be elaborated as a series of specific questions, addressed in Chapter 13, Is size of the network around an entrepreneur dependent on the entrepreneur s training, gender, age, education and phase in the entrepreneurial process? Is salience of each sphere in the network around the entrepreneur affected by the entrepreneur s training, gender, age, education and phase? The network organization is conceptualized as the organization of the work and flow of resources and information around the entrepreneur. This network organization has organizational properties such as size and a department-like configuration in the form of spheres for acquisition of resources. This conceptualization of the network organization draws on the traditions of research on organizations focusing on resource dependency and on information processing, where performance is contingent on acquisition of information and other resources and capacity for processing them. The network organization is conceptualized in terms of size and spheres and we identify five spheres: the private sphere, the job sphere, the professional sphere, the market sphere, and the entrepreneurship sphere where the resource of information is embedded and acquired in the form of advice. This network organization is actually shaped by national culture traditional versus rationalistic-secular and by individual characteristics such as gender, age, education, training and phase of the entrepreneurial endeavor. We also consider the issue of performance and ask how performance is affected by the network organization. The aspects of performance are here innovation, exporting and growth-expectation of the entrepreneurs who are in the phases of starting or operating. Then the issues are how these performance aspects are affected by the organizational properties of the network. Specifically, the questions in Chapter 14 are, 24 Training and Network Organization in Entrepreneurship in Denmark 2010

26 Introduction: Are training and networking forming human and social capital? Is innovation affected by size of the network and salience of the spheres in the network? Is exporting affected by size of the network and salience of the spheres in the network? Is growth-expectation affected by size of the network and salience of the spheres in the network? We might expect that network size enhances each dimension of performance; at least this is the traditional idea about the effect of networking. But, going beyond orthodoxy, we may expect that networking in certain spheres will enhance performance. Specifically, I hypothesize that salience of the entrepreneurial sphere and salience of the market sphere will enhance performance. National entrepreneurship is examined in the last substantive part of the monograph, Part 5. The changing level of entrepreneurship in Denmark and other societies is considered. Chapter 15 addresses the issues, Is the trend in the level of entrepreneurship upward, stable or downward? How does the level in Denmark compare to the levels in other societies? The national conditions for entrepreneurship are examined; we track trends in Denmark and make comparisons to other societies in the national framework of conditions for entrepreneurship. Specifically, Chapter 16 answers the questions, Are cultural and institutional conditions in Denmark improving or deteriorating? How does the framework in Denmark compare to the framework in other societies? Having considered the national level of entrepreneurship and the national framework conditions, we shall examine their dynamics, the effects of framework conditions upon level of entrepreneurship. Specifically, Chapter 17 addresses the questions, How, within a nation, are the cultural conditions affecting one another? How, within a nation, are the institutional conditions interrelated? How are the cultural and institutional conditions affecting entrepreneurship? The conclusions, in Chapter 18, then concern whether and how training and network organization bring comparative advantages for individuals, firms and nations. Before investigating entrepreneurship, we shall first consider how this endeavor can be researched. Training and Network Organization in Entrepreneurship in Denmark

27

28 Chapter 2. Methods for researching entrepreneurship in Denmark and other societies How can we research entrepreneurship? More specifically, this chapter addresses the methodological problem, How are we investigating entrepreneurship at the levels of society, people, and performers? Entrepreneurship is conceptualized as an activity that is institutionalized with a supportive framework in society, and with a social role for performing the activity, the entrepreneur. Research therefore focuses on the performers of the activity and the framework of conditions affecting their performance. To understand why Denmark has its level of activity of entrepreneurship, we compare Denmark to other societies, that is, we compare their activities and we compare their frameworks, in order to see how the activity is shaped by its framework. Individuals are compared to one another, and societies are compared to one another. This requires comparable data on individuals and comparable data on societies. Global Entrepreneurship Monitor surveys Data on societies and people are gathered in the research program Global Entrepreneurship Monitor conducted by the Global Entrepreneurship Research Association, which maintains an informative homepage (GERA 2007; Reynolds et al., 2005). GEM has so far been in full operation for 12 years, 1999 through 2010, and a total of 83 countries or societies have participated. Denmark has participated in each of the 12 years, but most countries have participated in only some of the years. The 83 participating countries or societies include 39 developed societies: Australia, Austria, Belgium, Bosnia and Herzegovina, Canada, Croatia, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hong Kong, Hungary, Iceland, Ireland, Israel, Italy, Japan, Latvia, Macedonia, the Netherlands, New Zealand, Norway, Poland, Portugal, Puerto Rico, Romania, Russia, South Korea, Serbia, Singapore, Slovenia, Spain, Sweden, Switzerland, Taiwan, the United Kingdom and the United States. The survey has also been conducted in 44 developing societies: Algeria, Angola, Argentina, Azores, Bolivia, Brazil, Chile, China, Colombia, Costa Rica, Dominican Republic, Ecuador, Egypt, Ghana, Guatemala, India, Indonesia, Iran, Jamaica, Jordan, Kazakhstan, Malaysia, Mexico, Myanmar, Pakistan, Palestine (West Bank and Gaza), Panama, Peru, Philippines, Saudi Arabia, South Africa, Syria, Thailand, Tonga, Trinidad and Tobago, Tunisia, Turkey, Uganda, United Arab Emirates, Uruguay, Vanuatu, Venezuela, Yemen and Training and Network Organization in Entrepreneurship in Denmark

29 Methods for researching entrepreneurship in Denmark and other societies Zambia. Results are robust with respect to a slightly different classification of developed versus developing countries, but, of course, for many other purposes a continuum is more informative, for example that mapped in the World Values Survey (Inglehart and Wenzel 2005). The performers of entrepreneurial activities are identified and investigated in a survey of the adult population. In Denmark we have in each of the 12 years from 1999 to 2010 conducted a national probability sample survey of the adult population, with a new sample each year, pooling them for a total of respondents interviewed on the telephone. Weighting the respondents enhances the validity of these surveys (weights, based on gender, age and region, are used mainly in the analyses in Chapters 15 and 17). The questionnaire asks the adults about their involvement in entrepreneurship, so as to identify entrepreneurs (used in Chapter 15), and about their values (used in Chapter 9). The entrepreneurs are asked about their experiences and characteristics of their enterprises (used in Chapter 15). In 2010 we included young people down to age 15 and asked about schooling and training (used in Chapters 3-13). In the years I added questions measuring entrepreneurs networking (used in Chapters 12-14). Similar surveys have been conducted around the world, asking the same questions everywhere, and pooled into a total of far more than one million respondents interviewed in the years 1999 to 2010 in the 83 countries or societies. The conditions affecting entrepreneurship have been measured, in 2009 and preceding years, in Denmark and in the other countries participating in GEM that year. The framework conditions in a country are rated by a panel of experts usually comprising about 40 experts in the country. The panel rates several conditions, so each condition is scored. Thereby we create a time series for each framework condition in Denmark so as to track changes (Chapter 16), to understand dynamics in the country, and to offer indicators for policy-making. We also compare conditions in Denmark to conditions in other countries in order to estimate effects of conditions upon entrepreneurship (Chapter 17), and also to offer comparative indicators for policy-making. The coupling between entrepreneurship and its conditions, especially policies, differs between developed countries and developing countries. In a typical developed society there is a tight coupling between entrepreneurship and policy, whereas the coupling is far looser in a typical developing society (Schøtt and Jensen 2009). Therefore, it is often most informative to examine the two kinds of societies separately, and to compare Denmark to the other developed societies. However, comparing widely different countries, such as Denmark and Iran as I am currently pursuing, can yield an understanding of how entrepreneurship is affected by national culture traditionalism versus rationalism-secularism and how entrepreneurship affects development. Registry data Entrepreneurship can also be investigated through data from registries. Registries are compiled by Statistics Denmark on persons, firms and people s work in firms (Danmarks Statistik 2005). The registry data on persons cover the lives of people. The Danish registries of individuals are very rich and unique, better than registries in most other countries, so they enable original and detailed analyses of, for example, the processes 28 Training and Network Organization in Entrepreneurship in Denmark 2010

30 Methods for researching entrepreneurship in Denmark and other societies leading into the entrepreneurial vocation, out of it, and switches (Erhvervs- og Boligstyrelsen, 2002). The national registries of individuals are rather idiosyncratic to each country, and have apparently not been used for individual-level comparisons among people in different nations. The registry data on firms cover the evolution of firms. The Danish registries of firms are also better than registries in most other countries, so they allow analyses of the growth of firms in Denmark (Erhvervs- og Byggestyrelsen, 2008). The national registries of firms are rather idiosyncratic to each country, but are nevertheless used for comparisons among countries (Eurostat 2005; Hoffmann et al, 2005; OECD 2008). Registry-based measures of entrepreneurial activity are fairly highly correlated with our TEArate (Schøtt, 2005b). But, of course, the differences among countries in registration reduce validity of the comparisons among countries. Our adult population survey has some distinct advantages over registry data. First, our survey is up-to-date and provides up-to-date leading indicators on entrepreneurship. Second, our survey goes beyond the behavior and investigates, for example, people s intentions to become entrepreneurs, their motivations, and their expectations. Third, our survey is conducted around the world, using the same method everywhere, so as to enable valid comparisons. Having now reviewed our methods, we can embark on our analyses of entrepreneurship in society. Training and Network Organization in Entrepreneurship in Denmark

31

32 Chapter 3. Students learning for entrepreneurship in Denmark This first substantive chapter considers students training and involvement in entrepreneurship in Denmark. Training to start a firm denotes instruction and other acquisition of knowledge and skills about starting a business. Training of therefore comprises instruction through formal education, receipt of knowledge alongside education (i.e. outside but during education). Training also refers to learning upon finishing formal education, but that is not considered in this chapter about students, but is considered in subsequent chapters. Training thus occurs in several contexts, partly because entrepreneurial training is growing and expanding in society and partly because entrepreneurial competencies are so diverse and complex (Bager & Nielsen 2005). Education is like a column of building blocks, where learning in each block builds upon earlier blocks of learning. Training for entrepreneurship can also be considered as modules where the early modules may mainly instill motivation for innovation and for starting a firm, later modules may mainly develop creativity, opportunity-awareness and risk-willingness, and even later modules may mainly teach skills. The questions in this chapter are, Are students frequently trained to start a business? Are students mostly trained within their education or mostly alongside their education? Is training often socially inherited, dependent on their parents education and occupation? Is training in education mainly theoretical or mainly practical? Does training often enhance motivation and competency to innovate and start a firm? Do trained students more often than untrained students have entrepreneurial competencies? Do trained students more often than untrained students have attitudes of an entrepreneurial culture? Are trained students more often than untrained students intending to become entrepreneurs and working independently as student-entrepreneurs? Are student-entrepreneurs supported by family, friends and schools? These questions will be answered by analyzing data on a sample of 331 students, namely the students among the 2000 persons interviewed in our GEM population survey in 2010 (described in Chapter 2 on methods for researching entrepreneurship). The 2000 interviewed persons are a fairly representative sample of the population age 15-64, so the interviewed students are a fairly representative sample of the population of students age 15 and older. The findings in this chapter can therefore be generalized to the population of students in Denmark. Training and Network Organization in Entrepreneurship in Denmark

33 Students learning for entrepreneurship in Denmark Education: Primary, Secondary and Tertiary Education in Denmark comprises mainly: Primary education now called grundskole and earlier called folkeskole. Primary education is for youth up to about age 16 (most finish primary education upon grade 9). Secondary education now called ungdomsuddannelse. Upon finishing their primary education, most youngsters continue for secondary education, while they are about age years, in one of two tracks, general secondary education called gymnasial uddannelse vocational secondary education called erhvervsuddannelse. Tertiary education called videregående uddannelse. Upon their graduation from vocational secondary education or general secondary education, many youngsters continue, when they are about 20 years old, for tertiary education, either for a few years for a professional education around a baccalaureate level, for some years around a master s level, or for more years around a doctoral level. Youngster may leave any education for jobs in occupations such as entrepreneurs or employees, Figure 3.1 Figure 3.1. Pathways through education Tertiary education General secondary education Vocational secondary education Primary education Respondents in our survey were asked a series of questions around their training within education and alongside education. Most of the questions are not usually in our annual GEM-survey, but are adapted from questions crafted, pretested and validated by our colleagues abroad (and we are especially grateful to José Ernesto Amoros for sharing his questionnaire with us). The interviewees are asked, Are you currently a pupil in primary education, or have you finished your primary education? Within your primary education, have you received any instruction in starting a new business? 32 Training and Network Organization in Entrepreneurship in Denmark 2010

34 Students learning for entrepreneurship in Denmark The respondents who had finished their primary education were then asked about their secondary education: Following your primary education, have you completed vocational education or completed general education, or are you currently studying in vocational education or studying in general education? The respondents who had completed vocational education or were studying vocational education were then asked: Within your vocational education, have you received any instruction in starting a new business? The respondents who had completed general secondary education or were studying general secondary education were asked: Within your general education, have you received any instruction in starting a new business? The respondents who had complete secondary education were then asked: Following that education, have you completed a tertiary education, or are you currently studying for tertiary education? The respondents who had completed tertiary education or were studying tertiary education were asked: Within your further education, have you received any instruction in starting a new business? The respondents who had received any instruction in starting a business within their education were then asked: When you think back upon the instruction that you during your education received in starting a business, did this instruction give you more desire to create something new? When you think back upon the instruction that you during your education received in starting a business, did this instruction give you more desire to start a business? Still thinking back on the instruction in starting a business, did this instruction make you more competent to create something new? Still thinking back on the instruction in starting a business, did this instruction make you more competent to start a business? Was what you learnt from the instruction in starting a business mostly theoretical or mostly practical? All respondents were asked: During your education, did you outside school get any training in starting a business? The respondents who were studying (whether in primary, secondary or tertiary education) were asked whether they are entrepreneurs: Alongside your education, are you currently working for yourself, that is, making a product that you sell or providing a service that you get payment for? The respondents who answered, yes, that they are entrepreneurs, were also asked: Is your school supporting you in your work for yourself? Are your parents supporting you in your work for yourself? Are your friends supporting you in your work for yourself? When you compare yourself to others, who like you are working for themselves, do you then think that you are as successful as they are, or less successful, or more successful than they are? Training and Network Organization in Entrepreneurship in Denmark

35 Students learning for entrepreneurship in Denmark The respondents who were studying were also asked about their parents education and work: Has your father taken a vocational education, or a higher education, or has he not taken any vocational or higher education? Has your mother taken a vocational education, or a higher education, or has she not taken any vocational or higher education? Have any of your parents been self-employed? Training of students thus refers to their training obtained within school or alongside school (and not training they may get later in life, upon finishing school). Students training within and alongside education The first issues are, Are students frequently trained to start a business? Are students mostly trained within their education or mostly alongside their education? Almost half of the students age 15 or older have received some training in starting a firm, Table 3.1. Typically, the training is within the school rather than alongside their education. Table 3.1. Students training, with place of training (n=331 students) All students Untrained students 57% Trained students 43% Total 100% Trained students by place of training: Trained within school 38% Trained alongside school 13% Training tends to be inherited The next issue is whether students training often is socially inherited, dependent on their parents education and occupation. Whether students are trained or not depend on their fathers education, Table 3.2 (the differences are statistically significant, with p-value.02 in an anova F-test). Students whose fathers have neither vocational nor higher education are more likely to be trained than other students. Students mothers education seem to matter much less (the differences are not statistically significant; in reality there may be differences, but the sample is insufficient to discern them with reasonable confidence). 34 Training and Network Organization in Entrepreneurship in Denmark 2010

36 Students learning for entrepreneurship in Denmark Table 3.2. Students training, by parents education (n=251 students) Vocational education Father s education Higher education Neither vocational nor higher education Vocational education Mother s education Higher education Neither vocational nor higher education Untrained 62% 62% 40% 58% 62% 51% students Trained 38% 38% 60% 42% 38% 49% students Total 100% 100% 100% 100% 100% 100% Students training depends on the parents occupation, Table 3.3. Students with a selfemployed parent are more likely to be trained than students without a self-employed parent (the difference is statistically significant, with p-value.02 in a one-sided t-test). The difference may be in training within education (although the p-value is.11 in the one-sided t-test and thus not marginally significant) and also in training outside education (the p-value is.08 in the one-sided t-test and thus marginally significant). Table 3.3. Students training, by parents occupation (n=262 students) Parents occupation Self-employed Not self-employed Untrained students 50% 63% Trained students 50% 37% Total 100% 100% Trained students according to place of training: Trained within education 42% 34% Trained alongside education 16% 10% In short, students training evidently depends on their fathers education, but there is no strong evidence that training also depend on mothers education. Students training also depends on their parents occupation, in the way that their likelihood of training is enhanced if the parents are self-employed. In these ways training tends to be socially inherited. Students competencies and attitudes The training that students receive within their education may contain theoretical learn- Training and Network Organization in Entrepreneurship in Denmark

37 Students learning for entrepreneurship in Denmark ing and practical exercises. But where is the emphasis, is the training within education mainly theoretical or mainly practical? For by far most students, the training they have received within their education has been mostly theoretical, Table 3.4. But there is undoubtedly a division of labor, in so far as the training that is given alongside education and afterwards is more practical. Table 3.4. Practical versus theoretical training within education (n=125 trained students) Training within education is mostly practical 10% Training equally practical and theoretical 30% Training within education is mostly theoretical 61% Total 100% Training within education often aims both at motivating the students and at enhancing their skills. One way of evaluating the training is thus by asking the trained students about their learning, does training often enhance motivation and competency to innovate and start a firm? Desire as well as competency to innovate and to start have typically been enhanced, Table 3.5. Table 3.5. Trained students change in desire and competence to innovate and to start a business (about 120 trained students) Desire to innovate enhanced 67% Desire to start a business enhanced 59% Competency to innovate enhanced 66% Competency to start a business enhanced 55% The effect of training may also be ascertained by comparing trained students to untrained students (although the difference cannot be attributed to the training only). So the issue is whether trained students more often than untrained students have entrepreneurial competencies, Table 3.6. Trained students more frequently than untrained students have skills (the difference is statistically significant, with p-value.0001 in a onetailed t-test). Trained students are also more often aware of opportunities (the difference is statistically significant, with p-value.04 in a one-tailed test). Trained students more often know someone who is starting a new business the difference is statistically significant, with p-value.0002 in a one-tailed test). But trained students are not significantly more often risk-willing (the p-value is.16 in a one-tailed test). 36 Training and Network Organization in Entrepreneurship in Denmark 2010

38 Students learning for entrepreneurship in Denmark Table 3.6. Competencies of students, by training (about 300 students) Trained Untrained Skills 41% 15% Opportunity awareness 56% 46% Risk-willingness 65% 59% Know someone starting 57% 37% Training may also affect students cultural attitudes toward entrepreneurship, so the question is whether trained students more often than untrained students have attitudes of an entrepreneurial culture (although, again, a difference should not be attributed solely to the training), Table 3.7. Trained students more frequently than untrained students want the media to be favorable (the difference is statistically significant, with p- value.004 in a one-tailed t-test). Trained students more frequently appear to consider a career in entrepreneurship to be good (the difference is marginally significant, with p- value.10 in a one-tailed t-test). But, surprisingly, trained students do not more often than untrained students want the occupation of the entrepreneur to have high status. Also surprisingly, trained students do not especially often think that inequality among people in standard of living is ok (the difference is not statistically significant, with p- value.17 in the one-tailed test). Table 3.7. Attitudes of students, by training (about 300 students) Trained Untrained Student wants media to be favorable 73% 58% Student thinks career in entrepreneurship good 93% 89% Student wants occupation to have high status 51% 52% Student thinks inequality in living standards is ok 68% 63% Students becoming entrepreneurs Training is provided for the purpose of promoting entrepreneurship, most concretely by turning more youngsters into entrepreneurs. So the question is whether trained students more often than untrained students are intending to become entrepreneurs and more are working independently as student-entrepreneurs? Indeed, trained students more frequently than untrained students intend to start a business, Table 3.8 (the difference is statistically significant, with p-value.006 in a one-tailed t-test). Moreover, trained students have more frequently started to work independently (the difference is statistically significant, with p-value.002 in a one-tailed test). Training and Network Organization in Entrepreneurship in Denmark

39 Students learning for entrepreneurship in Denmark Table 3.8. Students who have started or intend to start, according to training (about 280 students) All students Trained Untrained Started to work independently 15% 23% 9% Intending to start a business 9% 14% 5% Student-entrepreneurs support from family, friends and school Often entrepreneurs have been considered lone wolves, very independent and self-propelling. In fact, however, they network with a broad range of others for resources. Adult entrepreneurs network extensively with family, friends and colleagues at work. So we ask whether the student-entrepreneurs are supported by their family, friends and schools? Indeed, the student-entrepreneurs are usually supported by their family and by their friends, but not so often by their schools, Table 3.9. Table 3.9. Support for independently working students Supported by family 93% Supported by friends 95% Supported by school 34% The above analyses of students training and involvement in entrepreneurship lead to the following conclusions. Roughly half of the students (age 15 and older) have been trained to start a firm. Mostly they have been trained within their education, and less often alongside their education. Training tends to be socially inherited, that is, training depends on the parents education and occupation, namely in the ways that students whose fathers had neither vocational nor higher education are more likely to get training that students whose fathers have a vocational education or a higher education, and students with self-employed parents are more likely to get training than students whose parents are employees. The training provided within education is typically mostly theoretical, rather than practical. Still, the training tends to enhance both motivation and ability to innovate and start a business. Trained students, more often than untrained students, have entrepreneurial competencies. Trained students also especially often have attitudes of an entrepreneurial culture. Trained students, more often than untrained students, intend to become entrepreneurs. Trained students also more often start to work independently, and thereby they become student-entrepreneurs. The student-entrepreneurs are usually supported by both family and friends, but less often by their schools. From focusing on students we shall broaden our perspective to consider people generally. 38 Training and Network Organization in Entrepreneurship in Denmark 2010

40 Chapter 4. People s training to start a business: Loose coupling with education The previous chapter focused narrowly on students. This chapter broadens the perspective to consider all people in the general population, and examines their training to start a business. This chapter therefore expands upon the previous chapter, with some repetition. Training to start a firm denotes instruction and other acquisition of knowledge and skills about starting a business. Training of therefore comprises instruction through formal education, receipt of knowledge alongside education (i.e. outside but during education), and also learning upon finishing formal education. Training thus occurs in several contexts, partly because entrepreneurial training is growing and expanding in society and partly because entrepreneurial competencies are so diverse and complex (Bager & Nielsen 2005). Education is like a column of building blocks, where learning in each block builds upon earlier blocks of learning. Training for entrepreneurship can also be considered as modules where the early modules may mainly instill motivation for innovation and for starting a firm, later modules may mainly develop creativity, opportunity-awareness and risk-willingness, and even later modules may mainly teach skills, especially on-the-job-training during more or less formalized apprenticeship upon finishing formal schooling. The questions in this chapter are, Are people frequently trained? Is people s training typically coupled with education? These questions will be answered by analyzing our GEM-survey in year 2010 of a sample of 2000 persons age years in Denmark. Education: Primary, Secondary and Tertiary To examine how training is coupled with education in Denmark, we first outline the educational system. Education comprises mainly: Primary education now called grundskole and earlier called folkeskole. Primary education is for youth up to about age 16 (most finish primary education upon grade 9) Secondary education now called ungdomsuddannelse. Upon finishing their primary education, most youngsters continue for secondary education, while they are about age years, in one of two tracks, general secondary education called gymnasial uddannelse vocational secondary education called erhvervsuddannelse Training and Network Organization in Entrepreneurship in Denmark

41 People s training to start a business: Loose coupling with education Tertiary education called videregående uddannelse. Upon their graduation from vocational secondary education or general secondary education, many youngsters continue, when they are about 20 years old, for tertiary education, either for a few years for a professional education around a baccalaureate level, for some years around a master s level, or for more years around a doctoral level Youngster may leave any education for jobs in occupations such as entrepreneurs or employees, Figure 4.1. Figure 4.1. Pathways through education to occupations Entrepreneur Employee or other occupation Tertiary education General secondary education Vocational secondary education Primary education Every respondent in the population of persons, age years, was asked about their education and training: Are you currently a pupil in primary education, or have you finished your primary education? Within your primary education, have you received any instruction in starting a new business? Respondents who had finished their primary education were also asked about secondary education: Following your primary education, have you completed vocational education or completed general education, or are you currently studying in vocational education or studying in general education? 40 Training and Network Organization in Entrepreneurship in Denmark 2010

42 People s training to start a business: Loose coupling with education Respondents who were currently in or had finished vocational secondary education were also asked: Within your vocational education, have you received any instruction in starting a new business? Respondents who were currently in or had finished general secondary education were also asked: Within your general education, have you received any instruction in starting a new business? Respondents who had completed vocational or general secondary education were asked about tertiary education: Following that education, have you completed a further education, or are you currently studying for further education? Respondents who were currently in or had finished tertiary education were also asked: Within your further education, have you received any instruction in starting a new business? Respondents who had completed tertiary education were also asked: Was this further education less the 3 years, between 3 and 4 years, or longer than 4 years? Every respondent was also asked: During your education, did you outside school get any training in starting a business? Respondents who had finished their education and were no longer studying were also asked: Later, after you finished your education, have you gotten any training or instruction in starting a business? A person may thus receive training in up to five contexts: within primary education within secondary education within tertiary education alongside education, that is, outside school while being educated, after finishing education. A person s extent of training is crudely indicated by the number of contexts in which the person is trained. It is of course interesting how many people receive any training, but it is especially interesting whether many people have a greater extent of training, whether they return for training and receive training in several contexts, Table 4.2. Most people in the population have not received any training. Many have received training in one context (26%). Rather many have received training in more than one context (15%). Training and Network Organization in Entrepreneurship in Denmark

43 People s training to start a business: Loose coupling with education Table 4.2. Training of the population, by number of contexts of training (2010; year olds) No training 58% Training in 1 context 26% Training in 2 contexts 11% Training in 3 contexts 3% Training in 4 contexts 1% Training in 5 contexts.1% Total 100% N respondents 2000 Whether persons are trained or untrained of course depends on their level of education, Table 4.3 (the differences in percentages are statistically significant, with p-value.0001 in the chi-square test). Few of the people (age 15-64) with only primary education have been trained. More of the people with secondary education as their highest education have been trained. Almost half of the people with tertiary education have been trained. A person s extent of training is crudely indicated by the number of contexts in which the person is trained. The number of contexts in which people have been trained of course also depends on their training, Table 4.3 (the differences among the averages are statistically significant; the p-value is.0001 in the anova F-test). People with only primary education have been trained in at most three contexts (namely in primary school, alongside primary school, and upon leaving primary school as their highest level of education), and their mean number of contexts of training is only.2. People with secondary education as their highest level of education have been trained in more contexts, on average. People with tertiary education have been trained in up to five contexts, and on average they have been trained in.7 contexts. So people s extent of training depends on their education in the way that the more educated they are the more extensive they tend to be trained. Table 4.3. Training of persons, by their highest education (2010; age year olds) Primary education General secondary education Vocational secondary education Tertiary education Untrained 86% 58% 55% 53% Trained 14% 42% 45% 47% Total 100% 100% 100% 100% Mean contexts N persons Training and Network Organization in Entrepreneurship in Denmark 2010

44 People s training to start a business: Loose coupling with education We can look closer at the context in which people have been trained, Table 4.4. Most typically, people have been trained within their education, as part of their education. Less typically, people have been trained alongside their education, and also to some extent, people have been trained after finishing their education. Training within education has rarely been in primary school, but most often in vocational secondary education. Training has fairly often been in general secondary education and fairly often in tertiary education. Table 4.4. Training of the population, and coupling with education (2010; year olds) Percent of the category within the population Untrained 58% of the population Trained 42% of the population Trained in each context: Trained upon completion of education 11% of those who finished education Trained alongside education 9% of the population Trained within education 34% of the population Trained within education, by education: Trained in primary education 6% of the population Trained in vocational secondary 38% of those with vocational secondary education education 22% of those with general secondary Trained in general secondary education education Trained in tertiary education 26% of those with tertiary education The above analyses of people s training show that less than half of the population (age years) is trained. Training has been acquired mostly within education, and a substantial portion of people has been trained in more than one context. This account of training in the population as a whole ignores differences among segments of the population. Likelihood of training, however, may depend on personal background. Differences in training according to gender and according to age will be considered next. Training and Network Organization in Entrepreneurship in Denmark

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46 Chapter 5. People s training shaped by personal background: gender, age and education Training in the population as a whole was examined in the preceding chapter, ignoring differences among segments of the population. Likelihood of training, however, may depend on personal background. This chapter examines differences in training according to gender, age and extent of education. The questions in this chapter are, Are people trained equally frequently in the genders and ages, or does likelihood of training depend on gender and age? Is people s training coupled with education in the same way for the genders and ages, or does coupling depend on gender and age? Is people s extent of training tightly coupled to education, in the way that the more education people have the more training they tend to have. We would expect that training depends on gender in the way that more of the men than of the women have been trained because entrepreneurship is traditionally a male vocation. We would expect that training depends on age in the way that more of the young than of the older have been trained because training in schools has been expanding during recent decades. We would expect training to be coupled to education as a positive correlation, in the way that the more education people have the more training they tend to have. These questions will be answered by analyzing our GEM-survey in year 2010 of a sample of 2000 persons age years in Denmark, the same data used in the preceding chapter for examining the population as a whole. Training differs between the two genders, Table 5.1, but the gender differences are mostly small. More of the men than of the women appear to have been trained, but the apparent difference is not statistically significant. The men have been trained in.65 contexts, on average, and the women have been trained in.58 contexts, on average, and this difference is significant (with p-value.05 in the one-tailed t-test), so men have been trained more than women. Among those with completed education, more of the men than of the women appear to have been trained after they completed their education, but this apparent difference is not statistically significant. More men than women have been trained alongside their education (this difference is statistically significant; the p- value is.004). Men and women are equally often trained within the schools. The more significant gender differences occur in training within the educational levels. More women than men are trained in primary school and especially in vocational secondary schooling (both differences are statistically significant; the p-values are less than.05). Conversely, more men than women are trained in general secondary school- Training and Network Organization in Entrepreneurship in Denmark

47 People s training shaped by personal background: gender, age and education ing and especially in tertiary education (both differences are statistically significant; the p-values are less than.05). Table 5.1. Training of the population, by gender (2010; year olds) Women Men Untrained 60% of women 57% of men Trained 40% of women 43% of men Trained in each context: Trained upon completing education 10% of women with completed educ 12% of men with completed educ Trained alongside 7% of women 10% of men education Trained within education 34% of women 34% of men Trained within education, by education: Trained within primary 7% of women 5% of men education Trained in vocational secondary educ 45% of women with vocational sec ed 34% of men with vocational sec ed Trained in general secondary education 20% of women with general sec educ 26% of men with general sec educ Trained in tertiary education 22% of women with tertiary education 31% of men with tertiary education Training also depends on age, Table 5.2. Young persons have more frequently been trained than older people (the association with age is highly significant). But not in every context. Apparently young persons have less frequently received training upon completion of education than older persons have, but this is of course simply because the young persons have not yet completed or just completed their education. More interestingly, many more of the young persons have received training alongside their education and, even more of the young ones have been trained within their education (these differences are quite significant). That almost half of the young persons contrasted with less than a quarter of the older persons have received training within education demonstrates the comprehensive expansion of training in education that has occurred in the most recent decades. The increase in training has occurred at all levels of education, training has spread like wild-fire in primary education, in vocational secondary education and in general secondary education, whereas there is more inertia in tertiary education. 46 Training and Network Organization in Entrepreneurship in Denmark 2010

48 People s training shaped by personal background: gender, age and education Table 5.2. Training of the population, by age (2010) Young (15-29 years) Midaged (30-49 years) Older (50-64 years) Untrained 51% of young 59% of midaged 69% of old Trained 49% of young 41% of midaged 31% of old Trained in each context: Trained upon completing educ 9% of young with completed education 11% of midaged with completed education 12% af old with completed education Trained alongside 11% of young 7% of midaged 8% of old education Trained within education 44% of young 33% of midaged 21% of old Trained within education, by education: Trained in primary education 9% of young 5% of midaged 2% of old Trained in vocational sec ed Trained in general sec ed Trained in tertiary education 55% of young with vocational sec educ 26% of young with general sec educ 32% of young with tertiary education 35% of midaged with vocational sec educ 23% of midaged with general sec educ 24% of midaged with tertiary education 28% of old with vocational sec educ 9% of old with general sec educ 21% of old with tertiary education The above analyses indicate that training is associated with education, age and gender. Highly educated persons are trained more often and more extensively than less educated persons. Young persons have received training more frequently than older persons. Men have been trained more than women. Is training affected by gender, also when holding age and education constant? Is training affected by age, also when gender and education are equal? Is training affected by education, also when gender and age are controlled for? These distinct and separate effects are discerned in a statistical model where training is regressed on gender, age and education (this regression is reported in the Appendix in Table A5.1). We find that all three effects are significant. Gender affect training in the way that men are more trained than women, age has a negative effect on training, and education has a positive effect on training, when the other conditions are held constant. The effect of gender is the smallest effect, and the effect of education is the strongest effect. These effects are drawn as arrows in Figure 5.3. The thickness of each arrow indicates the strength of the effect, and the dotted arrow shows the negative effect. Training and Network Organization in Entrepreneurship in Denmark

49 People s training shaped by personal background: gender, age and education Figure 5.3. Training affected by gender, age and education Gender Age Training Education The analyses in this chapter show that training to some degree is shaped by personal background characteristics, namely gender, age and education. Gender affects training in the way that men get more training than women, also when controlling for age and education, but this gender effect is rather small. Age affects training in the way that young are more trained than older, also when holding gender and education constant, and this age effect is stronger than the gender effect. Education affects training, in the way that the more education people get the more training they tend to get. This effect of education is stronger than the effects of age and gender. 48 Training and Network Organization in Entrepreneurship in Denmark 2010

50 Chapter 6. People returning for further tr aining Training to start a business may involve becoming motivated to start, assimilating entrepreneurial cultural orientations, honing awareness of opportunities, becoming able to evaluate ideas, and learning to commit, organize, plan and execute. Training does not in one shot train all these competencies. First people may be trained in some things, and then later return for further training in other things. It is therefore important to examine whether training is typically a once-in-a-lifetime experience, or whether people trained in one context are especially likely to return for further training. The question of whether people trained in one context have high odds of returning for further training in another context is therefore a series of questions, Do people trained in primary education have high odds of becoming trained in general secondary education? Do people trained in primary education have high odds of becoming trained in vocational secondary education? Do people trained in general secondary education have high odds of becoming trained in tertiary education? Do people trained in vocational secondary education have high odds of becoming trained in tertiary education? Do people trained within education have high odds of becoming trained alongside education? Do people trained within education have high odds of becoming trained upon completion of education? Do people trained alongside education have high odds of becoming trained upon completion of education? We would expect that training begets training in every way, and that the odds for returning for further training are high. These questions can be answered by analyzing the data on the 2000 persons, age years old, surveyed in 2010 in our annual GEM survey of the population in Denmark, as described in the earlier chapter on methods for researching entrepreneurship. The questionnaire asked about training within each educational level and also training alongside education and training upon completion of education. The questions are quoted in the preceding chapters. Training within general secondary education depends on training within primary education, Table 6.1 (the association is significant; the p-value is.0001 in the chi-square test). Students in general secondary education have odds.92 of being trained in general secondary education if they were trained in primary education (the odds are defined as the probability.48 of trained divided by the probability.52 of being untrained in gen- Training and Network Organization in Entrepreneurship in Denmark

51 People returning for further training eral secondary education). But their odds of being trained in general secondary education is lower, only.27, if they were not trained in primary education. So those trained in primary education have odds of being trained in general secondary education which are.92/.27 or 3.4 times the odds of those who were not trained in primary school. That this ratio between the two odds exceeds 1 shows that people trained in primary education have especially high odds of becoming trained in general secondary education. Training within vocational secondary education depends on training within primary education, Table 6.2 (the association is significant; the p-value is.0001). Those trained in primary education have odds of being trained in vocational secondary education which are 5.0 times the odds of those who were not trained in primary school. This odds ratio shows that people trained in primary education have especially high odds of becoming trained in vocational secondary education. Training within tertiary education depends on training within general secondary education, Table 6.3 (the association is significant; the p-value is.0001). Those trained in general secondary education have odds of being trained in tertiary education which are 5.0 times the odds of those who were not trained in general secondary school. This odds ratio shows that people trained in general secondary education have especially high odds of becoming trained in tertiary education. Training within tertiary education depends on training within vocational secondary education, Table 6.4 (the association is significant; the p-value is.0001). Those trained in vocational secondary education have odds of being trained in tertiary education which are 8.3 times the odds of those who were not trained in vocational secondary school. This odds ratio shows that people trained in vocational secondary education have especially high odds of becoming trained in tertiary education. Training alongside education depends on training within education, Table 6.5 (the association is significant; the p-value is.0001). Those trained within education have odds of being trained alongside education which are 2.5 times the odds of those who were not trained within school. This odds ratio shows that people trained within education have especially high odds of becoming trained alongside education. Training upon completion of education depends on training within education, Table 6.6 (the association is significant; the p-value is.001 in the one-sided test). Those trained within education have odds of being trained upon finishing education which are 1.6 times the odds of those who were not trained within school. This odds ratio shows that people trained within education have especially high odds of becoming trained also upon finishing their education. Training upon completion of education depends on training alongside education, Table 6.7 (the association is significant; the p-value is.0001). Those trained alongside education have odds of being trained upon finishing education which are 13.9 times the odds of those who were not trained alongside school. This odds ratio shows that people trained alongside their education have especially high odds of becoming trained also upon finishing their education. 50 Training and Network Organization in Entrepreneurship in Denmark 2010

52 People returning for further training Table 6.1. Training within general secondary education, dependent on training within primary education Primary education Trained (n=60) Untrained (n=1008) General secondary Trained 48% 21% education Untrained 52% 79% Odds 48/52=.92 21/79=.27 Odds ratio.92/.27 = 3.4 Table 6.2. Training within vocational secondary education, dependent on training within primary education Primary education Trained (n=39) Untrained (n=611) Vocational secondary Trained 74% 36% education Untrained 26% 64% Odds 74/26=2.8 36/64=.56 Odds ratio 2.8/.56 = 5.0 Table 6.3. Training within tertiary education, dependent on training within general secondary education General secondary education Trained (n=169) Untrained (n=678) Tertiary education Trained 45% 19% Untrained 55% 81% Odds 45/55=.82 19/81=.23 Odds ratio.82/.23 = 3.6 Table 6.4. Training within tertiary education, dependent on training within vocational secondary education Vocational secondary education Trained (n=86) Untrained (n=106) Tertiary education Trained 60% 15% Untrained 40% 85% Odds 60/40=1.5 15/85=.18 Odds ratio 1.5/.18 = 8.3 Training and Network Organization in Entrepreneurship in Denmark

53 People returning for further training Table 6.5. Training alongside education, dependent on training within education Training alongside education Training within education Trained (n=682) Untrained (n=1318) Trained 14% 6% Utrained 86% 94% Odds 14/86=.16 6/94=.064 Odds ratio.16/.064 = 2.5 Table 6.6. Training upon completion of education, dependent on training within education Training upon finishing education Training within education Trained (n=682) Untrained (n=1318) Trained 12% 8% Utrained 88% 92% Odds 12/88=.14 8/92=.087 Odds ratio.14/.087 = 1.6 Table 6.7. Training upon completion of education, dependent on training alongside education Training upon finishing education Training alongside education Trained (n=139) Untrained (n=1607) Trained 51% 7% Untrained 49% 93% Odds 51/49=1.04 7/91=.075 Odds ratio 1.04/.075 = 13.9 These analyses all show that people who are trained in one context are especially likely to return for further training in another context. Training is neither a one-shot experience and then avoided nor something that occurs at random, but is something like a spiral of returning, training begetting training, with a recurrence of training at a higher level. From this account of the contexts of people s training to start a business, we turn toward examining the content of the training, what the trained youngsters have acquired and learnt during their training. 52 Training and Network Organization in Entrepreneurship in Denmark 2010

54 Chapter 7. Trained youngsters learning The preceding chapters considered the contexts of people s training to start a business. This chapter examines the content of the training, what the trained youngsters have acquired and learnt during their training, and also the benefits of training. The questions are Is training within education mostly theoretical or mostly practical? Does training typically enhance motivation and ability to innovate and start a business? Does training benefit people in their jobs and in some occupations more than in others? The questions are answered by analyzing the data on the 832 trained persons among those interviewed in our GEM survey of the population age years old in Denmark in 2010 (as described in Chapter 2 on methods for investigating entrepreneurship). Firstly, is training within education mostly theoretical or mostly practical? Persons who had received training within their educations were asked about the kind of instruction, Was what you learnt from the instruction in starting a business mostly theoretical or mostly practical? Training within education is typically theoretical rather than practical, Table 7.1. But there is undoubtedly a division of labor among training within education, training alongside education and training upon completion of education, which is typically practical. Table 7.1. Theoretical and practical learning from training within education Percent of those with training within education Mostly theoretical training 69% Equally theoretical and practical 22% Mostly practical training 9% Total 100% Respondents with training within education 667 Training expectedly enhances both motivation and skills, and both for innovative work and for starting a new business. So the persons who had received training within their educations were asked about motivations and competencies, Training and Network Organization in Entrepreneurship in Denmark

55 Trained youngsters learning When you think back upon the instruction that you during your education received in starting a business, did this instruction give you more desire to create something new? When you think back upon the instruction that you during your education received in starting a business, did this instruction give you more desire to start a business? Still thinking back on the instruction in starting a business, did this instruction make you more competent to create something new? Still thinking back on the instruction in starting a business, did this instruction make you more competent to start a business? Both motivation and competency for innovation as well as for starting have typically been enhanced by the training, Table 7.2. Table 7.2. Effect of training in education upon motivation and competency for innovation and upstart Percent of those with training within education Enhanced motivation for innovation (n=645) 50% Enhanced competency for innovation (n=645) 58% Enhanced motivation for upstart (n=658) 43% Enhanced competency for upstart (n=655) 60% Training refers to training to start a business, as we say explicitly and repeatedly in our interview with each respondent, but such training may be useful more broadly than just for starting a firm. The skills may be more or less useful for the occupations that people pursue. So the persons who had received training were all asked, When you think about the instruction or training in starting a business, which you have received during your life, is that beneficial for what you are now occupied with? About half of the trained people consider their training to be beneficial in their current occupation, Table 7.3. Table 7.3. Benefit from training for current occupation Training benefits occupation 46% Training does not benefit occupation 54% Total 100% Respondents with training 708 We would of course expect the training to be beneficial most frequently to entrepreneurs, and less often to be beneficial to other occupations, Table 7.4 (the differences are significant; the p-value is.0001 in the chi-square test). Indeed, training typically benefits entrepreneurs. Less typically, but also quite often, does training benefit employees, and also other occupations. This suggest that training also benefits employees creative endeavors within existing organizations, intrapreneurship. Intrapreneurship will expect- 54 Training and Network Organization in Entrepreneurship in Denmark 2010

56 Trained youngsters learning edly become a focus in our GEM research program in 2011, so we will expectedly also investigate the effects on intrapreneurship from training. Table 7.4. Benefit from training for current occupation, dependent on occupation Entrepreneurs Employees Other occupations Training benefits occupation 68% 42% 23% Training does not benefit occupation 32% 58% 77% Total 100% 100% 100% Respondents with training The analyses of the content of the training, what people acquire and learn during training, and also its usefulness, have shown that training within education is typically theoretical and not practical (practical learning is probably more frequently acquired in training upon completion of education), that training typically enhances motivation and ability to innovate and start a business, and that training frequently benefits people in their jobs, especially in entrepreneurial occupation but often also in employment and other occupations. Training and Network Organization in Entrepreneurship in Denmark

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58 Chapter 8. People s competencies enhanced by tr aining Trained youngsters learning was examined in the preceding chapter. This chapter broadens the perspective to the population and examines people s competencies for entrepreneurship, and differences in competencies of trained persons and untrained persons. The questions are, Are competencies distinguishing entrepreneurs from non-entrepreneurs? Have competencies in the population been changing during the last decade? Are competencies dependent on personal background such as gender, age and education? Are trained persons more competent than untrained persons? We would expect certain competencies to be common among entrepreneurs and far less prevalent among non-entrepreneurs, perhaps even rare, so that the competencies distinguish entrepreneurs from non-entrepreneurs. We would also expect that competencies in the population have been increasing because of the increasing training in entrepreneurship. Competencies expectedly depend on gender in the way that males have more entrepreneurial competencies than women do, partly because males get more training than women do. Competencies expectedly depend on education in the way that highly educated persons have more entrepreneurial competencies than less educated persons. These expected associations are of course merely formulations of hypotheses, which are more or less plausible and which are to be tested here. The questions will be answered, and the hypotheses tested, by analyzing data from our annual GEM-surveys of the population in Denmark from year 2000 to year 2010, and especially our survey in year 2010, as described in Chapter 2 on methods for researching entrepreneurship. Competencies here comprises four personal qualities, upstart-competency, the competency to start a firm; opportunity-awareness, the perception of opportunities for starting; risk-willingness, the willingness to start without fear of failure; and role-modeling, knowing someone who has started who may serve as a role-model. Upstart-competency is measured in our survey by asking all respondents, Do you have the knowledge, skill and experience required to start a new business? Opportunity-awareness is queried by asking, In the next six months will there be good opportunities for starting a business in the area where you live? Risk-willingness is operationalized by the question, Would fear of failure prevent you from starting a business? Training and Network Organization in Entrepreneurship in Denmark

59 People s competencies enhanced by training Role-modeling is reported by asking, Do you know someone personally who started a business in the past 2 years? These four competencies are more frequent among entrepreneurs than non-entrepreneurs, Table 8.1. The three kinds of entrepreneurs the intending entrepreneurs, the starting entrepreneurs, and the owner-managers far more frequently than the others the non-entrepreneurs have competency to start, are aware of opportunities for starting, are willing to take risks, and know someone who is starting and can serve as a role-model (all four competences differ significantly among the occupations; the p-values are all less than.0001). So these competencies are far more prevalent among entrepreneurs and distinguish them from the non-entrepreneurs. Table 8.1. Competencies of entrepreneurs and non-entrepreneurs (2010, years old) Intending entrepreneurs Starting entrepreneurs Owningmanaging Nonentrepreneurs Upstart-competency 72% 82% 79% 32% Opportunityawareness 60% 70% 56% 44% Risk-willingness 72% 80% 73% 59% Role-modeling 74% 71% 63% 39% These competencies have changed in the adult population during the decade, Table 8.2. Upstart competency dropped in , and then increased again in Opportunity-awareness also dropped in , and then increased again in Riskwillingness also dropped in and increased again in Role-modeling seem to have dropped in 2009 and then stayed constant in The drop in all four competencies around can be explained by the economic crisis during these years, a crisis that hit entrepreneurship severely by cutting the up-start rate to half. Table 8.2. Competencies in the adult population (18-64 years old), annually up to Upstart-competency 41% 37% 37% 40% 38% 36% 36% 32% 35% 41% Opportunityawareness 47% 46% 51% 42% 49% 66% 65% 71% 62% 34% 46% Risk-willingness 71% 70% 71% 69% 73% 59% 60% 75% 57% 57% 65% Role-modeling 50% 42% 51% 45% 50% 46% 43% 44% 44% 42% 42% 58 Training and Network Organization in Entrepreneurship in Denmark 2010

60 People s competencies enhanced by training Genders differ in their competencies, Table 8.3. Upstart-competency, opportunityawareness, risk-willingness and role-modeling are all more frequent among men than among women (all four differences are statistically significant; the p-values are less than.001). Table 8.3. Competencies in the population, by gender (2010, years old) Women Men Upstart-competency 31% 50% Opportunity-awareness 42% 51% Risk-willingness 61% 69% Role-modeling 35% 48% Competencies also differ among the age-groups, Table 8.4. Up-start-competency is more frequent among older than among younger persons (this positive association with age is statistically significant). Opportunity-awareness appears to be associated with age, but the association is not statistically significant. Risk-willingness is more frequent among older than among younger persons (this positive association with age is statistically significant). Conversely, role-modeling is more frequent among young than among older persons (this negative association with age is statistically significant). Thus, in short, different competencies are variously positively related, negatively related and unrelated to age. Table 8.4. Competencies in the population, by age (2010) Young (15-29 years) Midaged (30-49 years) Older (50-64 years) Upstart-competency 31% 44% 47% Opportunity-awareness 50% 47% 43% Risk-willingness 56% 52% 69% Role-modeling 49% 47% 31% Educational level also matter for competencies, Table 8.5. Upstart-competency is most frequent among those whose highest level of education is a vocational secondary education (the differences among the four groups are statistically significant; the p-value is.0001 in the anova F-test). Opportunity-awareness is highest among those whose highest education is a tertiary education or general secondary education (the differences are statistically significant; the p-value is.0001). Risk-willingness is highest in among those whose highest education is primary education or vocational secondary education (the differences are statistically significant; the p-value is.007). Role-modeling is most frequent among those with tertiary education (the differences are statistically significant; Training and Network Organization in Entrepreneurship in Denmark

61 People s competencies enhanced by training the p-value is.0001). Thus, in short, different competencies are variously related to educational level. Table 8.5. Competencies in the population, by education (2010) Primary education General secondary education Vocational secondary education Tertiary education Upstart-competency 32% 28% 48% 41% Opportunityawareness 37% 50% 41% 52% Risk-willingness 68% 57% 66% 59% Role-modeling 31% 40% 43% 49% Training also matter for the competencies, Table 8.6. Upstart-competency, opportun ityawareness and role-modeling are all more prevalent among trained than among un - trained persons (each difference is statistically significant; with p-value less than.0001). Trained and untrained persons, however, do not differ significantly in risk-willingness. Table 8.6. Competencies in the population, by training (2010) Trained Untrained Upstart-competency 53% 31% Opportunity-awareness 52% 44% Risk-willingness 62% 61% Role-modeling 56% 36% The four kinds of competencies tend to go hand in hand with one another, in the way that if a person has one kind of competency, then the person also often has the other kinds of competency, and, conversely, if a competency is lacking then also the other competencies often lack. The four competencies thus correlate with one another positively. However, they correlate only weakly, the correlation coefficients are only.13 on average (with Cronbach s alpha.37). That the four measures correlate positively means that it is conceptually sensible to subsume them under one concept, entrepreneurial competency. But that they correlate only weakly with one another also means that entrepreneurial competency is not a one-dimensional concept, but is actually multidimensional. Entrepreneurial competency can be measured by an index that combines the four measurements, just as their average. This index correlates rather highly with each of the four measures, and can be used for further analyses. Entrepreneurial competency is related most clearly, in the above analyses, to gender in the way that men more often than women claim competency and to training in the 60 Training and Network Organization in Entrepreneurship in Denmark 2010

62 People s competencies enhanced by training way that trained persons more often than untrained persons report to be entrepreneurially competent. It is harder to say from the above how competency tends to relate to age and education. The effects upon entrepreneurial competency from each of the four characteristics training, education, gender and age can be ascertained in a statistical model, a linear regression of competency on the four characteristics. This regression is reported in the Appendix as Table A8.1. The analysis shows that each of the four has a distinct and separate and substantial effect on competency, also when the other three are held constant. Training has the largest effect, being trained greatly promotes competency. Gender also matters much, in the way that men much more than women report competency. Education has a substantial effect, in the way that the more education people have, the more competent they tend to be. Age also has an effect, in the way that older persons tend to be more competent than younger persons. These effects are illustrated in Figure 8.1 where the thickness of an arrow represents the magnitude of the effect. Figure 8.1. Entrepreneurial competency affected by training and also by gender, age and education Training Education Competency Gender Age In short, the above analyses of entrepreneurial competency in the population show that entrepreneurial competency is multidimensional, encompassing at least four aspects upstart-competency, opportunity-awareness, risk-willingness and role-modeling which are distinct. Peoples entrepreneurial competency is greatly strengthened by training, and also promoted by education, apart from training. Competency is also affected by age, in the way that older tend to be more competent than younger people. Competency is also related to gender, in the way that men more than women report competency. Training and Network Organization in Entrepreneurship in Denmark

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64 Chapter 9. Training shaping an entrepreneurial culture Culture refers to the things that are valued in society, the things that people attach value to. To the extent entrepreneurship is valued in society, the culture is entrepreneurial and society has an entrepreneurial culture. The concept of culture thus applies to society. The culture in a society may change over time, it may become increasingly entrepreneurial. Policies in Denmark and around the world aim at changing the culture, and to make it increasingly and pervasively entrepreneurial. The concept of culture can also be applied more narrowly when things are highly valued in part of society and less valued in another part of society, and we then call this a subculture. Thus, we may possibly find that a society does not have an entrepreneurial culture but has an entrepreneurial subculture. Policies aiming at changing the culture may succeed in creating an entrepreneurial subculture within one part of society, specifically the young generation, but perhaps not in other parts of society. The questions are, Is the culture in Denmark changing in the direction of an entrepreneurial culture? Is an entrepreneurial subculture prevailing within a gender, specifically among men? Is an entrepreneurial subculture prevailing within an age-group, specifically the young? Is an entrepreneurial subculture prevailing within an educational group, specifically those with vocational secondary education? Is an entrepreneurial subculture prevailing among the trained people? We would expect that the culture in Denmark has become more entrepreneurial in recent years. But we also expect that culture is not uniform, but that there may well be an entrepreneurial subculture among men, in the young generation, among those with vocational secondary education, and among those who have been trained to start a business. These issues will be addressed by analyzing data from our annual GEM-surveys in the population in Denmark in the years 2003 to 2010, as described in Chapter 2 on methods for investigating entrepreneurship. Culture will here be examined as the values attached to four aspects of entrepreneurship, value of a career as entrepreneur; value of status achieved by success; value of inequality; and value of stories in the media. The culture in society is the extent to which these values prevail in the population. Training and Network Organization in Entrepreneurship in Denmark

65 Training shaping an entrepreneurial culture Or, more specifically, to the extent these values prevail, the culture in society is an entrepreneurial culture. The population s valuation of a career as entrepreneur is indicated in our survey by asking people to serve as informants about the population, Do you think that, in Denmark, most people consider starting a new business a desirable career choice? The population s valuation of status achieved by success is indicated in our survey by asking people to serve as informants about the population, Do you think that, in Denmark, those successful at starting a new business have a high level of status and respect? The population s valuation of inequality is indicated in our survey by asking people to serve as informants about the population, Do you think that, in Denmark, most people would prefer that everyone had a similar standard of living? The population s valuation of stories in the media is indicated in our survey by asking people to serve as informants about the population, In Denmark, do the public media often report stories about successful new businesses? The population s value attached to a career as entrepreneur is measured by the percentage of Yes-answers to the first question. The population s value attached to status based on success is measured by the percentage of Yes-answers to the second question. The population s value attached to inequality is measured by the percentage No-answers to the third question. The population s value attached to stories in the media is measured by the percentage of Yes-answers to the fourth question. Culture in Denmark has changed over the years, Table 9.1. However, the culture has changed in some specific ways only. The value attached by the population to a career as entrepreneur has remained rather constant over the years. Also the value attached by the population to status based on success has been fairly stable over the years. I had expected these two values to have become more pervasive in society. Inequality among people in standard of living has changed in an interesting manner. The population increasingly valued inequality, notably from to the years around 2006 but then decreasingly valued inequality toward That is, inequality became increasingly valued when the economy was flourishing and incomes tended to increase, but inequality became decreasingly valued when the crisis hit Danish society and hit the low income people especially much so that inequality actually continued to widen. It thus seems that the population increasingly valued inequality in times of economic upturn, but decreasingly valued inequality in times of downturn. 64 Training and Network Organization in Entrepreneurship in Denmark 2010

66 Training shaping an entrepreneurial culture Table 9.1. Entrepreneurial culture in the adult population (18-64 years old), annually up to Value of a career as entrepreneur 51% 50% 44% 52% 56% 57% 47% Value of status achieved by success 75% 73% 73% 74% 79% 76% 75% Value of inequality 44% 39% 50% 55% 52% 51% 47% Value of stories in the media 52% 55% 30% 33% 36% 32% 26% To examine subcultures we cannot let our respondents serve as informants about values in Denmark as a whole. Instead, we asked the respondents about their own values. A person s valuation of a career as entrepreneur was indicated in our survey in 2010 by asking for their own attitude, Do you consider starting a new business a desirable career choice? A person s valuation of status achieved by success was indicated by asking for their own attitude, Do you think that those successful at starting a new business ought to be get a high level of status and respect? A person s valuation of inequality was indicated by asking for their own attitude, Do you prefer that everyone in this country should have a similar standard of living? A person s valuation of stories in the media was indicated by asking for their own attitude, Do you think that the public media should often report stories about successful new businesses? The person s own value attached to a career as entrepreneur is measured by a Yesanswer to the first question. The person s own value attached to status based on success is measured by a Yes-answer to the second question. The person s own value attached to inequality is measured by a No-answer to the third question. The person s own value attached to stories in the media is measured by a Yes-answer to the fourth question. These cultural attitudes enable us to examine whether entrepreneurial subcultures exist, distinguishing one group of people from another group. We may expect that an entrepreneurial subculture prevails among men, but not so much among women. So we examine the cultural attitudes within each gender, Table 9.2. Men and women seem to differ in the value they attach to the career as an entrepreneur, namely in the way that the career seems more often valued by men than by women (the difference is marginally significant; the p-value is.08). Men and women also differ in the value they attach to inequality in living standards, inequality is more frequently valued by men than by women (the difference is statistically significant; the p- value is.0005). But men and women do not differ significantly in the value they attach to status based on success as an entrepreneur. Also, the genders do not differ in the value they attach to having the media report stories about entrepreneurial success. In short, entrepreneurial culture is more prevalent among men than among women, but the gender difference is only small, and we cannot say that there is an entrepreneurial subculture distinguishing the genders. Training and Network Organization in Entrepreneurship in Denmark

67 Training shaping an entrepreneurial culture Table 9.2. Entrepreneurial culture within each gender (15-64 year olds; 2010) Women Men Value of a career as entrepreneur 86% 89% Value of status based on success 54% 54% Value of inequality 38% 46% Value of stories in the media 70% 68% Does an entrepreneurial subculture prevail within an age-group, distinguishing it from the others? Specifically, we may expect that an entrepreneurial subculture prevails among the young people because they have been targeted by policies promoting entrepreneurship, especially coupled with education. So we examine the cultural attitudes within each age-group, Table 9.3. All age-groups attach high value to the career as an entrepreneur, without significant differences among the age-groups. Likewise, the agegroups do not differ significantly in the value they attach to status based on success. But they differ in attaching value to inequality, older more often than younger people value inequality (the differences among the age-groups is significant; the p-value is.0002 in the anova F-test). Likewise, older more often than younger people value that the media reports stories of entrepreneurial successes (the differences among the age-groups is significant; the p-value is.0001). In short, and contrary to my expectation, entrepreneurial culture prevails in some of its aspects more among older than among younger people. Table 9.3. Entrepreneurial culture within each age-group (2010) Young (15-29 years) Mid-age (30-49 years) Older (50-64 years) Value of a career as entrepreneur 89% 88% 86% Value of status based on success 53% 54% 57% Value of inequality 36% 46% 44% Value of stories in the media 62% 71% 77% Is there an entrepreneurial subculture within an educational level, distinguishing it from other educational levels? Specifically, we might expect an entrepreneurial subculture to prevail among people with vocational secondary education because they have a tradition of becoming self-employed craftsmen. So we examine the cultural attitudes within each educational level, for those whose highest education is at that level, Table 9.4. The educational levels, however, do not differ significantly in their evaluation of entrepreneurial culture (for none of the four attitudes are the differences among the educational groups significant; the four p-values all exceed.10). So we cannot conclude that educational level significantly influences cultural attitudes toward entrepreneurship. 66 Training and Network Organization in Entrepreneurship in Denmark 2010

68 Training shaping an entrepreneurial culture Table 9.4. Entrepreneurial culture within each educational group (15-64 year olds; 2010) Primary education General secondary education Vocational secondary education Tertiary education Value of a career as entrepreneur 85% 89% 89% 87% Value of status achieved by 52% 57% 49% 56% success Value of inequality 39% 43% 60% 44% Value of stories in the media 66% 72% 68% 69% Is there an entrepreneurial subculture among the persons who have been trained to start a business? There was no entrepreneurial subculture distinguishing men from women, or distinguishing one age-group from others, or distinguishing one educational level from others, but if there is a contrast somewhere, we should expect to find it between the trained and the untrained. So we examine the cultural attitudes of the trained and the untrained, Table 9.5. The trained more often than the untrained value the career an entrepreneur, value inequality, and also value stories in the media (all three differences are significant, with p-value less than.02 in a one-sided test). The trained and the untrained are rather equal in their evaluation of status based on success. Table 9.5. Entrepreneurial culture among trained and among untrained (15-64 year olds; 2010) Trained Untrained Value of a career as entrepreneur 90% 86% Value of status based on success 53% 55% Value of inequality 48% 39% Value of stories in the media 73% 67% The four cultural attitudes tend to go hand in hand with one another, in the way that if a person has one of the cultural attitudes, then the person also often has the other cultural attitudes, and, conversely, if an attitude is lacking then also the other attitudes often lack. The four cultural attitudes thus correlate with one another positively. However, they correlate only weakly, the correlation coefficients are only.07 on average (with Cronbach s alpha.22), and an exploratory factor model suggest more than one factor. That the four measures correlate positively means that it is conceptually sensible to subsume them under one concept, entrepreneurial culture. But that they correlate only weakly with one another also means that entrepreneurial culture is not a one-dimensional concept, but is actually multidimensional. Entrepreneurial culture may be indicated by an index that combines the four mea- Training and Network Organization in Entrepreneurship in Denmark

69 Training shaping an entrepreneurial culture surements, just as their average. This index correlates positively with each of the four measures, and may be used for further analyses. Entrepreneurial culture was variously related, in the above analyses, to training, education, gender and age, but it was hard to see how culture, on the whole, was related to each of the four. The effects upon entrepreneurial culture from each of the four characteristics training, education, gender and age can be ascertaining in a statistical model, a linear regression of the index of culture on the four characteristics. This regression is reported in the Appendix as Table A9.1. The analysis shows that neither gender nor education is significantly related to culture. Age and training are significantly related to culture. Age is related to culture in the way that older people more than younger people have assimilated the entrepreneurial culture. Training is related to culture in the way that trained people more than untrained people subscribe to the entrepreneurial culture. The effects of training and age are similar, and both effects are small. These effects are illustrated in Figure 9.1 where the thickness of an arrow represents the magnitude of the effect. The lack of significant effects from gender and education is symbolized by the absence of arrows. Figure 9.1. Entrepreneurial culture affected by training and age Training Education Culture Gender Age In short, the above analyses of entrepreneurial competency in the population show that entrepreneurial culture is multidimensional, encompassing at least four values the value of a career as entrepreneur, the value of status based on success, the value of inequality and the value of stories in the media and these four values are quite distinct. Peoples assimilation of entrepreneurial culture is on the whole not systematically related to gender and neither to education. The value attached to entrepreneurial cul- 68 Training and Network Organization in Entrepreneurship in Denmark 2010

70 Training shaping an entrepreneurial culture ture is promoted by training, and also increases with age, but the effects of training and age are small. Entrepreneurial culture is thus rather homogenously spread out across various segments of the population, i.e. across both genders, across educational levels, and fairly much across ages and also fairly much across trained and untrained people. Training and Network Organization in Entrepreneurship in Denmark

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72 Chapter 10. Entrepreneurial careers and other careers loosely coupled with tr aining The may be a tight coupling between and education and an occupation. For example, learning to work with electrical installations is a vocational education in the form of apprenticeship with schooling, the learner is an electrician-apprentice who then graduates as a skilled craftsman and becomes an electrician who can be self-employed and work independently in the occupation of electricians who are certified by their education. This education and occupation are coupled tightly in so far as the education is a necessary and sufficient condition for the occupation. Another example is the coupling between Ph.D. education and research as an occupation; this education and occupation have a coupling that is tight to the extent most youngsters with this education become researchers and most researchers have this education. Such tight coupling often defines a profession. Entrepreneurship is not a profession in so far as entrepreneurs are not educated or trained in entrepreneurship. Policies, however, are aiming to professionalize entrepreneurship, to tighten the coupling between the entrepreneurial occupation and the entrepreneurial training (Schøtt and Ottósson, 2009). The questions here are Do trained people much more frequently than untrained people become entrepreneurs? Do entrepreneurs much more frequently than non-entrepreneurs have training? The questions can be answered by analyses of data from our GEM-survey in 2010 of 2000 persons, age years, as described in Chapter 2 on methods for researching entrepreneurship. Occupation depends on training, Table Trained persons are much more likely than untrained persons to become entrepreneurs (the difference is statistically significant; the p-value is.0001 in the one-sided test). Trained persons chance or odds of becoming entrepreneurs are.28, whereas untrained persons odds of becoming entrepreneurs are much lower, only.15. So trained persons odds of becoming entrepreneurs are 1.9 times the odds that untrained persons become entrepreneurs. So training almost doubles the chance or odds of becoming entrepreneurs. How occupation depends on training can be examined in more detail, Table Trained persons are more likely to become entrepreneurs of various kinds, i.e. to be engaged in starting, to be intending to start, and to be owning-managing a firm (the two first differences are highly significant and the third is marginally significant). Training and Network Organization in Entrepreneurship in Denmark

73 Entrepreneurial careers and other careers loosely coupled with training Table Occupation, dependent on training Trained Untrained Entrepreneur 22% 13% Non-entrepreneur 78% 87% Odds 22/78=.28 13/87=.15 Odds ratio.28/.15=1.9 Table Occupation, dependent on training Trained Untrained Currently engaged in starting 8% 5% Intending to start (and not engaged in 8% 4% starting) Owning and managing a firm (and not 8% 6% intending/engaged) Employed full-time (and not entrepreneur) 46% 48% Employed part-time (and not entrepreneur) 8% 8% Other occupations (and not entrepreneur) 22% 30% Total 100% 100% N respondents The question can be turned around, Are entrepreneurs much more frequently trained than non-entrepreneurs? More than half of the entrepreneurs are trained, Table 10.3, and the chance or odds that an entrepreneur is trained are 1.2. Fewer than half of the non-entrepreneurs are trained, and the odds that a non-entrepreneur is trained are only.64. So entrepreneurs odds of being trained are 1.9 times the odds that non-entrepreneurs are trained (this odds ratio equals the odds ratio above, in Table 10.1). How various occupations recruit trained and untrained persons can be examined in some detail, Table In the three entrepreneurial occupations 48% or more are trained, whereas in the non-entrepreneurial occupation fewer are trained, 43% or fewer. Table Training, according to occupation Entrepreneur Non-entrepreneur Trained 54% 39% Untrained 46% 61% Odds 54/46=1.2 39/61=.64 Odds ratio 1.2/.64= Training and Network Organization in Entrepreneurship in Denmark 2010

74 Entrepreneurial careers and other careers loosely coupled with training Table Training, according to occupation Engaged in starting Intending to start (and not engaged in starting) Owning and managing a firm (and not intending/ engaged) Employed full-time (and not entrepreneur) Employed part-time (and not entrepreneur) Other occupations (and not entrepreneur) Trained 55% 62% 48% 41% 43% 34% Untrained 45% 38% 52% 59% 57% 66% Total 100% 100% 100% 100% 100% 100% N respondents The odds ratio of 1.9 expresses the association between training and occupation, the coupling between training and occupation in entrepreneurship. To the extent the odds ratio exceeds 1, the coupling is tight. There is a coupling between training and entrepreneurship, but the coupling is not tight; rather, the coupling is loose. The odds that a trained person is an entrepreneur are nearly twice the odds that an untrained person is an entrepreneur. In other words, the odds that an entrepreneur is trained are nearly twice the odds than a non-entrepreneur is trained. Training and Network Organization in Entrepreneurship in Denmark

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76 Chapter 11. People s income: gain from tr aining Training to start a firm often makes the trained persons more motivated and competent to innovate and start a firm, and is often beneficial in work, not only in self-employment but also in employment, as we saw in Chapters 7, 8 and 9. So we would also expect that training often increases income. We hypothesize a tendency that the more training people have received, the higher is their income. Such a tendency has been found in an American study (Charney & Libecap 2000; see also Lepoutre et al 2010). So the question here is, Does people s training increase their income? This question can be answered by analyzing data on the employed and the self-employed or entrepreneurs among our 2000 interviewed persons age years in our GEM-survey in the year 2010 (so we ignore people in other occupations such as students, unemployed, retired persons and homemakers). In our survey we asked the respondents about their own annual gross-income, i.e. income before taxes. We also asked the respondents whether they had received training in starting a firm in each of the following five contexts: primary school, secondary school, tertiary school, alongside their schooling, and upon finishing their education (Chapter 4). So amount on training can be indicated by the number of contexts in which they received training, a scale from 0 to 5. Causality, that training really is a cause of income, cannot be proven, so causality is interpreted when we find statistical association. There is, however, some evidence that training really causes increases in entrepreneurial competences (Coduras et al 2010), and since competences undoubtedly are causes of income, we can reasonable interpret associations as cause-and-effect. Incomes can be compared among people without any training and people with training in one or more contexts, Table The tendency is for people with training in several contexts to earn more than people with no or little training. Training correlates positively with income; the correlation is positive,.07 (this correlation coefficient is statistically significant; the p-value is.004 in the one-tailed test). Table Income (annually, in kroner), by training Untrained Trained in 1 context Trained in 2 contexts Trained in 3 contexts Trained in 4 contexts Income, average N respondents This association between training and income, however, does not measure the dis- Training and Network Organization in Entrepreneurship in Denmark

77 People s income: gain from training tinct effect of training because other characteristics are ignored. Income does not only depend on training but also on many other characteristics such as gender, age, education and occupation. To better distinguish the separate effect of training from effects of other characteristics, we perform an analysis that controls for other characteristics, i.e. holds other things constant, so that we can estimate the distinct effect from training. For this we use a multiple linear regression, in which each effect is ascertained. The results in the linear regression are shown a little later. The results can be illustrated first. Training has a significant effect on income which is positive, trained people tend to have higher income than people without training, as we expected. This positive effect is shown by an arrow in Figure Age has an effect on income which is also positive, older people tend to have higher income than younger people, as is well-known. This positive effect is also shown by an arrow in Figure Gender also matters for income, in the way that income tends to be higher for men than for women, as is also well-known. This effect is also shown by an arrow. Employment also affects income, as is also well-known. Full-time employees and part-time employees can be compared to the self-employed. Full-time employees have lesser income than the self-employed, and this lesser income of full-time employees is shown by an arrow, that is dotted because their income is lesser, the effect is negative. Similarly, part-time employees have lesser income than the self-employed, and this lesser income of part-time employees is also shown by a dotted arrow. Education also affects income, as is also well-known. People with primary education as their highest level, people with vocational secondary education and people with vocational secondary education can be compared to people with tertiary education. People with primary education have lesser income than people with tertiary education, drawn as a dotted arrow. People with vocational secondary education have lesser income than people with tertiary education, drawn as a dotted arrow. People with general secondary education have lesser income than people with tertiary education, drawn as a dotted arrow in Figure Training and Network Organization in Entrepreneurship in Denmark 2010

78 People s income: gain from training Figure Income affected by training, gender, age, education and occupation Employed full-time Employed part-time Training Gender Income Age Primary education Vocational secondary ed General secondary ed These effects of education, occupation, gender and age are all well-known. Education, occupation, gender and age are included in the analysis here, because their inclusion enables us to estimate the separate effect of training. The effect of training is the effect that training has on income when education, occupation, age and gender are constant. The important result is that training has a separate effect that is significant and positive, training increases the income. The analysis also enables us to estimate the amount, in kroner annually, that training yields. Figure 11.1 summarizes the regression shown in Table An effect is ascertained by its regression-coefficient. A significant and positive coefficient indicates an effect that increases income, drawn as a solid arrow. A significant and negative coefficient indicates an effect that reduces income, drawn as a dotted arrow. Training has a coefficient that is statistically significant and positive (the p-value is.003 in the one-tailed test), so training has an effect that is positive. The coefficient is 14000, which means that each additional context of training increases income by kroner, the model estimates. So, compared to untrained people, people trained in one context tend to earn kroner more, people trained in two contexts tend to earn kroner more, people trained in three contexts tend to earn kroner more, people trained in four contexts tend to earn kroner more, and people trained in five contexts are predicted to earn kroner more. This additional income is distinct for training, and cannot be due to the other characteristics gender, age, education and occupation which are held constant or controlled for. Gender has its own consequence for income (the coefficient is statistically signifi- Training and Network Organization in Entrepreneurship in Denmark

79 People s income: gain from training cant, with p-value listed in the table). To be a man, compared to being a woman, entails an additional income of kroner (holding constant the other characteristics, namely training, age, education and occupation). Age also has its distinct consequence for income (the coefficient is statistically significant, with p-value listed in the table). The higher the age, the higher the income tends to be (holding constant the other characteristics, namely training, gender, education and occupation). Education has separate effects on income (holding constant the other characteristics). We compare the educational levels to one another, and use tertiary education as our frame of reference against which we compare the other educational levels. The least educated people, whose highest education is a primary education, earn much less, kroner less than those with tertiary education. Those with general secondary education as their highest education, earn kroner less than those with tertiary education. Those with vocational secondary education tend to earn kroner less than those with tertiary education. Occupation also has separate effects on income (controlling for the other characteristics). We compare the occupations to one another, and use self-employment as our frame of reference against which we compare the other occupations. Full-time employment entails an income that tends to be kroner below the income of the self-employed. Part-time employment entails an income that is estimated to be kroner less than the income of the self-employed. 78 Training and Network Organization in Entrepreneurship in Denmark 2010

80 People s income: gain from training Table Income affected by training and also by gender, age, education and occupation Linear multiple regression. Income is the person s annual gross-income, i.e. before taxes, in kroner. For occupation, self-employment or entrepreneur is the frame of reference that each other occupation is compared to. For education, tertiary education is the frame of reference that each other level of education is compared to. N = 1273 respondents who are self-employed or employed full-time or part-time (ignor ing other occupations). R 2 =.23 Independent Measurement Regression P-value variable coefficient Training number of contexts with training Gender woman 0; man Age Logarithm of years Education: Primary education Primary education 1 ; otherwise General sec. ed. General sec. ed. 1; otherwise Vocational sec. ed. Vocational sec. ed. 1; otherwise Occupation: Employed full-time Full-time employed 1; otherwise Employed part-time Part-time employed 1; otherwise Constant The distinct effects of gender, age, education and occupation are not surprising, they are fairly well-known. The new and important result in this analysis is that training has a distinct effect on income. Training affects income in a positive direction, it increases income the more training people receive, the more income they tend to get and the effect is actually quite substantial. Training and Network Organization in Entrepreneurship in Denmark

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82 Chapter 12. Entrepreneurs organizing their own net work Entrepreneurs intending to start a business, or starting a business, or running an established business depend on and utilize many kinds of resources. An important resource is knowledge, both in the form of past learning from their education and experience and ongoing in the form of advice from their environment. Entrepreneurs get advice from advisors, a narrow or wide circle of advisors drawn from various spheres in the life of the entrepreneur. The entrepreneur s relations with these advising persons are called the entrepreneur s network of advisors or advice network. The network is an organization around the entrepreneur. It is the assembly-line where the entrepreneur assembles information and other resources that go into the entrepreneurial work, but it is less orderly and planned than an ordinary assembly-line. The assembly is more like bricolage. The organization of this network, the network organization, and the way it is organized around the entrepreneur, is expectedly important and consequential for the entrepreneurial work. The network organization around an entrepreneur has several properties that may be important and consequential. These organizational properties of the network around a person should be conceptualized (Burt et al 1983). The property, that has attracted most attention, is size, size of the network around the person. Size is theorized to be important because it connotes the volume of resources or information that the person may obtain. Such information or resources can bring benefit and is therefore a kind of capital, denoted social capital, and is social because the advantage is reaped in the social environment (Bourdieu 1980, 1986). The person invests in creating and maintaining the network and can mobilize it to bring advantage and reap a profit when the benefit exceeds the investment (Coleman 1988). The size of an entrepreneur s network has been found to bring benefit, specifically for survival, profit and growth (Schøtt 2007) and also for innovation, exporting and growth-expectation (Schøtt 2009). The organization of the network, in its qualities apart from size, may also bring advantage. Certain kinds and configurations of relations tend to bring advantage. Social capital may reside in networks that reach across a wide spectrum of kinds of contacts (Lin), networks that have weak ties to contacts (Granovetter 1973, 1983), networks that have dense relations among the contacts (Berkman et al 1979, Coleman 1988), networks that confer autonomy on the actor (Coser 1975), and networks that have disconnects or holes among the contacts, rather than being dense (Burt 1992). The organization of the network, and not only its size, will also be examined here. The organization of the network around an entrepreneur will here be conceptualized in terms of the salience of spheres of the environment from where the advisors are drawn. The questions are, Training and Network Organization in Entrepreneurship in Denmark

83 Entrepreneurs organizing their own network How is the network organized? What are the spheres in the environment around an entrepreneur which gives advice on the business? How is salience of a sphere shaped by the national culture? How is salience of a sphere shaped by the characteristics of the entrepreneur and the business? How is the network affecting innovation, exporting and growth-expectations? This chapter answers the first three questions, and the last two questions will be answered in the next chapters. The questions are addressed by data collected along with the GEM population surveys in the three years 2008 to Those intending to start, or starting, or owning-managing were asked whether they received advice from a wide range of others. A total of 747 networks were surveyed; comprising 104 respondents intending to start who reported their network in 2010 (in the preceding years this kind of entrepreneur was not asked to report the network), 197 respondents engaged in starting who reported their network in , and 446 respondents intending to start who reported their network in There are several common research techniques for identifying and measuring the network around a person (Lin et al 2008). One technique is to use a name-generator, first asking the person to name those who are important for the person, and then ask about their attributes and their relations to the person and one another (Burt 1985). Another technique is to use a position-generator, first asking the person whether they have direct contact with some people holding certain positions in society. Yet, another technique is to use a resource-generator, first asking the person whether certain resources can be obtained from some people around the person. These techniques tend to be rather costly in terms of the time they require during an interview. My challenge was to construct a very short set of questions that would yield informative responses, and that could be asked together with the ordinary questions in the GEM adult population survey identifying entrepreneurs of three kinds: those intending to start, those engaged in starting and those owning-managing a firm. The technique, that I constructed, may be called the role-generator technique, because it asks the respondent whether they are advised by people playing certain roles. The list of roles used here is based on earlier research (especially Schøtt 1987) and was expanded in discussions in early 2008 with GEM-colleagues around the world, and the list used in 2008 was slightly modified for 2009 and The entrepreneurs were asked whether or not they received advice from each advisor on a list of possible advisors, Table Training and Network Organization in Entrepreneurship in Denmark 2010

84 Table Questions asked persons intending to start, starting or owning-managing Persons intending to start a business were asked, Various people may give advice on your ideas for starting a business. Have you received advice from Persons currently starting a business were asked, Various people may give advice on your new business. Have you received advice from Persons owning and managing a business were asked, Various people may give advice on your business. During the last year, have you received advice from Percentage of the entrepreneurs using the advisor your spouse or life-partner? 44% your parents? 20% other family or relatives? 24% friends? 51% current work-colleagues? 41% a current boss? 20% a bank? 25% a lawyer? 22% an accountant? 44% a firm that you collaborate with? * 35% a firm that you compete with? * 15% a supplier? ** 27% a customer? ** 39% someone who is starting a business? 20% someone with much business experience? 50% a public advising services for business? 15% a possible investor? 15% a researcher or inventor? 11% someone in another country? 21% someone who has come from abroad?*** 12% someone with expertise on what you do?**** 58% earlier work-colleagues?**** 32% an earlier boss?**** 17% * For respondents intending to start, this was worded... you might.... ** For respondents intending to start, this was worded A possible.... *** Asked only in 2009 and **** Asked only in Training and Network Organization in Entrepreneurship in Denmark

85 Entrepreneurs organizing their own network The most used kind of advisor was someone with expertise on what you do, followed by friends and someone with much business experience, i.e. a mentor, Table The least used kind of advisor is a researcher or inventor and also someone who has come from abroad. Size of the network around an entrepreneur Entrepreneurs have networks of different sizes, Table Some report that they did not get advice from anybody, and some reported to use up to 16 advisors (of the 20 possible kinds of advisors). On average, the entrepreneurs used about 5 advisors. But the entrepreneurs actually differ very much from one another in the sizes of their networks. 84 Training and Network Organization in Entrepreneurship in Denmark 2010

86 Entrepreneurs organizing their own network Table Entrepreneurs, by size of their network ( ; N= 510 entrepreneurs) Percent of the entrepreneurs 0 advisor 10% 1 advisor 9% 2 advisors 6% 3 advisors 11% 4 advisors 11% 5 advisors 9% 6 advisors 10% 7 advisors 8% 8 advisors 8% 9 advisors 5% 10 advisors 4% 11 advisors 2% 12 advisors 4% 13 advisors 1% 14 advisors 1% 15 advisors 1% 16 advisors.4% 17 advisors 0% 18 advisors 0% 19 advisors 0% 20 advisors 0% Total 100% Mean 5.3 advisors Standard deviation 3.7 advisors Coefficient of variation.70 Size is partly the result of the background of the entrepreneur as will be examined in the next chapter. Size has consequences that will also be examined in a later chapter (Chapter 14). First we shall conceptualize another property of the network, a sphere. Spheres in the network around an entrepreneur The environment around an entrepreneur is not homogenous, but is more or less divided into somewhat distinct and separate spheres. An often distinguished sphere is the family sphere comprising ancestors and descendent, relatives in between ancestors and descendent, and some joined by marriage. The sphere itself is not homogenous and we speak about close family and more distant relatives, indicating that it has no definite Training and Network Organization in Entrepreneurship in Denmark

87 Entrepreneurs organizing their own network boundary. Such spheres are sources of resources for the entrepreneur. The resources in one sphere may be unique to that sphere. The family, for example, typically provides emotional support and also inertia and constraint. Discerning spheres is a task for investigation. Entrepreneurs often use advisors from the same sphere, as we shall see below. The use of advisors is not random; rather, advisors come in bundles, and some tend to be used alongside one another. A bundle of advisors, who tend to be used concurrently or alongside one another, often come from the same sphere in the environment around the entrepreneur. This tendency opens up for discerning spheres by several statistical techniques (Burt & Schøtt 1985). One informative technique for detecting such clustering is factor analysis, exploratory factor analysis. Concurrent use of advisors can be detected by factor analyzing the use of advisors by the entrepreneurs; each factor is a sphere of advisors who tend to be used alongside one another. This exploratory factor analysis guides us to distinguish spheres in a network of relations around an entrepreneur. First we analyze the data set on all the entrepreneurial networks. In all years we asked about the use of 19 kinds of advisors (the 19 listed first in Table 12.1). These 19 variables are analyzed by an exploratory factor analysis, using a model with rotation. The analysis yielded five eigenvalues exceeding 1 and thus identified five factors (we also performed exploratory factor analyses with a four-factor model and with a six-factor model, but they did not guide us to more promising conceptualizations). A clearly distinct factor comprises the four advisors: Spouse, parents, other family and friends (their factor loadings are.58,.72,.68 and.53, respectively). These four advisors are drawn from a sphere that can appropriately be conceptualized as the private sphere. Another rather distinct factor includes the two advisors: Work colleagues and boss (their factor loadings are.76 and.85). These two advisors are drawn from a sphere that can appropriately be conceptualized as the job sphere. Another clearly distinct factor comprises the three advisors: Bank, lawyer, accountant (their factor loadings are.68,.70 and.80, respectively). These three advisors are drawn from a sphere that can appropriately be conceptualized as the professional sphere. Another clearly distinct factor comprises the four advisors: Collaborator, competitor, supplier and customer (their factor loadings are.62,.67,.68 and.57, respectively). These four advisors are drawn from a sphere that can appropriately be conceptualized as the market sphere. Yet another factor comprises the six advisors: someone in another country, a starter, possible investor, public advising service, researcher/inventor, and business mentor with much experience (their factor loadings are.51,.62,.46,.51,.63 and.34). The business mentor has the same factor loading also on the factor called the market sphere, but for conceptualizing and theorizing about spheres of relations, it appears less promising to group the business mentor with the market sphere and more promising to group the business mentor with other advisors that are specific to entrepreneurship. These six advisors: possible investor, public advising service, researcher/inventor, starter, business mentor with much experience, and somebody abroad are drawn from a sphere that can appropriately be conceptualized as the entrepreneurship sphere. The salience of 86 Training and Network Organization in Entrepreneurship in Denmark 2010

88 Entrepreneurs organizing their own network this sphere correlates positively with knowing someone who has recently started (as measured in the GEM population survey) and this correlation is higher than the correlation with any of the other sphere, so this also justifies conceptualizing this sphere as the entrepreneurship sphere. Each of these five distinct classes among the 19 kinds of advisors was then analyzed by a one-factor model. Their factor loadings all exceed.5, marked by an asterix * in Table Three more kinds of advisors were asked about in the survey in 2008, namely earlier work colleagues, earlier boss, and somebody with expertise on the product being made by the entrepreneur. Their classifications are detected in an exploratory factor analysis of the 22 variables measured in This exploratory factor analysis of the 2008 data reveals a factor comprising the four advisors: earlier work colleagues and earlier boss, current work colleagues and current boss. These four variables were then subjected to a one-factor model, yielding satisfactory loadings also for earlier boss and earlier work colleagues (both.6), marked by ** in Table This classification further justifies conceptualizing this factor as the job sphere. The exploratory factor analysis of the 2008 data also shows that the advisor who is an expert on the product can be included with the six kinds of advisors in the entrepreneurship sphere. A one-factor model of these 7 variables in the 2008 data yields a factor loading of.6 for the expert on the product, marked by ** in Table One more kind of advisor was asked about in the surveys in , namely somebody from abroad. The classification of this advisor is detected in an exploratory factor analysis of the 20 relations measured in This analysis reveals that this advisor somebody from abroad can be included with the six kinds of advisors in the entrepreneurship sphere. A one-factor model of these 7 variables in the data yields a factor loading of.7 for somebody from abroad, marked by *** in Table Training and Network Organization in Entrepreneurship in Denmark

89 Entrepreneurs organizing their own network Table One-factor model of each sphere Sphere Advisor Loadings Private sphere Spouse*.6 Parents *.7 Other family *.7 Friends *.6 Job sphere Work colleagues *.8 Boss *.8 Earlier work colleagues **.6 Earlier boss **.6 Professional sphere Bank *.7 Lawyer *.8 Accountant *.8 Market sphere Collaborator *.7 Competitor *.7 Supplier *.8 Customer *.7 Entrepreneurship sphere Starter *.6 Business mentor with much experience *.6 Public advising service *.4 Possible investor *.6 Researcher or inventor *.5 Somebody in another country *.6 Somebody from abroad ***.7 Expert on product **.6 * Estimated in a one-factor model of the data from all the entrepreneurs in all three years. ** Estimated in a one-factor model of the data from the entrepreneurs in year *** Estimated in a one-factor model of the data from the entrepreneurs in years Training and Network Organization in Entrepreneurship in Denmark 2010

90 Entrepreneurs organizing their own network These spheres are likely to give different kinds of advice. The private sphere is likely to give support or discouragement. The job sphere may serve as sounding board. The professional sphere offers codified knowledge. The market sphere may provide information about business opportunities. The entrepreneurial sphere may convey tacit knowledge about entrepreneurship. Some entrepreneurs get advice mainly from the private sphere, other entrepreneurs seek more in the job sphere, other entrepreneurs search more in the professional sphere, other entrepreneurs rely more on the market sphere, while yet other entrepreneurs more pursue the entrepreneurial sphere. These five spheres in the network around an entrepreneur are analyzed in the following. Salience of a sphere in the network around an entrepreneur An entrepreneur may utilize one sphere especially much and may draw especially little on another sphere. One sphere has high salience and the other sphere has low salience in the network around the entrepreneur. This conceptualization of salience is similar to the conceptualization of prominence (and especially the concept of power, rather than the concept of centrality, in the tradition of analyzing social networks; Burt 1973). The concept of salience can here be operationalized as follows. Salience of a sphere around an entrepreneur is defined as the proportion of the possible advisors within the sphere who are used, divided by the proportion of all the 20 possible advisors who are used, in the most recent survey (and if the entrepreneur has no advisor, salience will be considered minimal, namely 0). For example, if the entrepreneur uses 2 advisors in the private sphere (out of the 4 possible advisors in this sphere), and in the network altogether uses 7 advisors (out of the 20 possible advisors), then the salience of the private sphere in the network is (2/4)/ (7/20) which is about 1.4. Salience of each sphere in a network varies among networks, as indicated in Table Table Salience of each sphere ( ; 510 networks) Minimum Maximum Mean Standard deviation Coefficient of variation Private sphere Job sphere Professional sphere Market sphere Entrepreneurship sphere Training and Network Organization in Entrepreneurship in Denmark

91 Entrepreneurs organizing their own network High salience of one sphere does not imply low salience of another sphere. The salience of one sphere is not strongly correlated with the salience of another sphere, typically. The strongest correlation is between salience of the private sphere and salience of the entrepreneurship sphere. Their correlation is negative, -.26, so an entrepreneur whose private sphere is salient is typically only weakly oriented toward the entrepreneurship sphere. Because saliences of the five spheres vary rather independent of one another, each sphere can be analyzed by itself. The next chapters examine how the network around the entrepreneur is consequential for the work and how the network is shaped by characteristics of the entrepreneur. Here we briefly consider how the network is shaped by characteristics of the country. Salience of a sphere shaped by national culture Salience of a sphere in the network around an entrepreneur is likely to differ from entrepreneurs in one society to entrepreneurs in another society, in so far as the society provides the context and framework conditions for entrepreneurial endeavors. Salience of a sphere is likely to depend on the national culture of the country, the human development of the country, and the economy of the country. The major areas of human concern, from religion to politics to economic and social life, in most countries around the world have been mapped in the World Values Survey (Inglehart and Wenzel, 2005). That study revealed that most variation among countries in a wide range of religious-political-economic-social orientations can be accounted for by one dimension of culture: Secular-rationalism versus traditionalism Secular-rationalism versus traditionalism is the major dimension of culture. In the words of Inglehart, The Traditional/Secular-rational values dimension reflects the contrast between societies in which religion is very important and those in which it is not. A wide range of other orientations are closely linked with this dimension. Societies near the traditional pole emphasize the importance of parent-child ties and deference to authority, along with absolute standards and traditional family values, and reject divorce, abortion, euthanasia, and suicide. These societies have high levels of national pride, and a nationalistic outlook. Societies with secular-rational values have the opposite preferences on all of these topics. ( ) Secular-rationalism versus traditionalism in a country is measured in the World Values Survey of humankind on a numerical scale on which a country scores negative to the extent the culture is traditional and positive to the extent the culture is secular-rational ( base_111 ) The networks around entrepreneurs were surveyed in 2008 in 5 countries (Schøtt et al 2010) and in the same and other countries in 2009, so we obtained data on networks in 14 countries, and analyzed the salience of spheres in each country (Schøtt et al 2010). The salience of the private sphere is related to the culture, especially to the secularrationalistic value. The private sphere is less salient where the secular-rationalistic value prevails. The private sphere appears more salient where tradition is valued. The im- 90 Training and Network Organization in Entrepreneurship in Denmark 2010

92 Entrepreneurs organizing their own network portance family-ties in peoples every-day lives in traditional culture is well-known (Freeman et al, 1990). This can be examined more precisely: Salience of the private sphere correlates negatively and very strongly with the prevalence of secular-rationalistic culture. In other words, the more traditional the culture is, the more salient is the private sphere. Salience of the job sphere, salience of the professional sphere, salience of the market sphere and salience of the entrepreneurship sphere correlate positively and strongly with secular-rationalistic culture. In other words, the more traditional the culture is, the less salient these four spheres will be. For an entrepreneur, the salience of each sphere thus depends on national context. Specifically, the more secular-rationalistic (and less traditional) the culture is, the less salient the private sphere, the more salient the job sphere, the professional sphere, the market sphere, and the entrepreneurship sphere. The spheres and other properties of the network around an individual depend not only on characteristics of the national but also on characteristics of the individual, as will be examined in the next chapter. Training and Network Organization in Entrepreneurship in Denmark

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94 Chapter 13. Network organization shaped by the entrepreneur s training and background The organization of the network around an entrepreneur is partly shaped by characteristics of the country, as examined in the preceding chapter, and partly shaped by characteristics of the entrepreneur as will be examined in this chapter. The network organization has properties such as size of the network around the entrepreneur, and salience of each sphere in the network, namely salience of the private sphere, salience of the job sphere, salience of the professional sphere, salience of the market sphere, and salience of the entrepreneurship sphere, as these spheres were identified in the preceding chapter. The question of how the network organization is shaped by characteristics of the entrepreneur can thus be elaborated as a series of specific questions, Is size of the network around an entrepreneur dependent on the entrepreneur s training, gender, age, education and phase in the entrepreneurial process? Is salience of each sphere in the network around the entrepreneur affected by the entrepreneur s training, gender, age, education and phase? These questions can be answered by analyzing the data on the entrepreneurs identified in the GEM-surveys in Denmark , the data also analyzed in the preceding chapter. Size of the network affected by gender, age, education, training and phase Does the entrepreneur s gender affect the size of the network around the entrepreneur? No, analyses show that female and male entrepreneurs get advice from the same number of advisors in their environment. Also when holding other conditions constant, is there no significant effect of gender upon size of the network. Does the entrepreneur s age affect the size of the network? No, there is no substantial association between age and size of the network. Specifically, when controlling for other conditions, there is no significant effect of age upon size of the network. Does the entrepreneur s education affect the size of the network? No, there is no significant association between level of education and size of the network. Also when taking other conditions into consideration, is there no significant effect of education upon size of the network. Training of the entrepreneur affects the size of the network, Table The trained entrepreneurs use 30% of the possible advisors on our list whereas the untrained entrepreneurs use only 19% of the possible advisors on our list (that numbered 22 in our Training and Network Organization in Entrepreneurship in Denmark

95 Network organization shaped by the entrepreneur s training and background survey in 2008 and 20 in our surveys in , as described in the preceding chapter). The trained entrepreneurs have networks that, on average, are larger than the networks around entrepreneurs who have not received training in starting a firm (the difference is statistically significant; the p-value is.0001 in the t-test). That trained entrepreneurs network more extensively is understandable, because training often includes learning that networking is useful, learning to pursue networks, and beginning to network with potentially informative advisors (Schøtt 2009). Table Average size of the networks around entrepreneurs, by training Trained Untrained Size of the network 30% 19% N entrepreneurs Phase of the entrepreneurial process also affects the size of the network, Table 13.2 (the differences are statistically significant; the p-value is.02 in the anova F-test). Those intending to start a firm network less that those engaged in starting or those owningmanaging a firm. It is to be expected that persons in this very early phase network less; indeed, they often have not yet identified suppliers, competitors and customers. Although these early-stage entrepreneurs network less than those in later stages, it is actually important that they network so much. They organize a sizeable network and utilize it before they even engage in starting the firm itself. Organizing the start of a firm thus begins well before engaging in starting the firm itself; rather, organizing the start includes forming a network organization around the entrepreneur. Table Average size of the networks around entrepreneurs, by phase Intending Starting Owning-managing Size of the network 23% 30% 28% N entrepreneurs The effects upon size of the network from each of training, education, gender, age and phase can be ascertained in a regression analysis. The regression is shown in the Appendix in Table A13.1. The results are summarized here in Figure Training has an effect on size of the network, which is significant, positive and substantial, also when holding the other conditions constant. The more training entrepreneurs get, the larger will their network be. This effect is shown by the arrow in Figure Education, age and gender have no significant effects on the size of the network. More precisely, each has no separate effect, also when the other conditions are constant. Their lack of significant effects is illustrated by the absence of arrows. 94 Training and Network Organization in Entrepreneurship in Denmark 2010

96 Network organization shaped by the entrepreneur s training and background Phase affects the size of the network. Entrepreneurs in the intending phase and entrepreneurs in the operating phase can be compared to entrepreneurs in the starting phase. Entrepreneurs in the phase of intending have smaller networks than entrepreneurs in the starting phase. This is shown by an arrow that is dotted because these entrepreneurs have smaller networks, a negative effect. Entrepreneurs in the operating phase have networks that are not significantly different, on the whole, from the networks of starting entrepreneurs. This lack of difference is illustrated by the absence of an arrow. Figure Size of network, affected by the entrepreneurs training, education, age, gender and phase Training Education Size of network Age Gender Phase of intending Phase of operating Salience of each sphere, affected by gender, age, education, training and phase How is the salience of each sphere in the network around an entrepreneur affected by the entrepreneur s characteristics, such as gender, age, education, training and phase in the formation of a firm? Gender affects the salience of spheres, we should expect. Expectedly, the private sphere is more salient to female entrepreneurs than to male entrepreneurs. Conversely, we should expect the job sphere to be more salient for male entrepreneurs than for female entrepreneurs. In fact, salience of several spheres differs between the genders, Table The private sphere is actually much more salient for female than for male entrepre- Training and Network Organization in Entrepreneurship in Denmark

97 Network organization shaped by the entrepreneur s training and background neurs, on average (the difference between the two means is statistically significant; the p-value is.0004 in the one-tailed t-test). Conversely, the job sphere is actually more salient for men than for women (the difference is significant; the p-value is.03 in the onetailed test). There is no significant gender difference in salience of the professional sphere, salience of the market sphere, and salience of the entrepreneurship sphere. Table Salience of each sphere in the networks around entrepreneurs, by gender; mean for each gender Women Men Salience of the private sphere Salience of the job sphere Salience of the professional sphere Salience of the market sphere.8.8 Salience of the entrepreneurship sphere.7.7 N entrepreneurs Training affects the salience of spheres, we may reasonably expect. Training often intends to promote networking in spheres considered useful for the enterprise, notable the professional sphere, the market sphere and the entrepreneurship sphere, and to reduce an otherwise strong reliance on advice from the private sphere, Table The private sphere appears less salient for trained entrepreneurs than for untrained entrepreneurs (the difference is not statistically significant). The professional sphere is much more salient for trained entrepreneurs than for untrained entrepreneurs. Also the market sphere is more salient for trained than for untrained entrepreneurs, as expected. But, unexpectedly and surprisingly, the entrepreneurship sphere is not more salient for trained entrepreneurs than for untrained entrepreneurs. Table Salience of each sphere in the networks around entrepreneurs, by training Trained Untrained Salience of the private sphere Salience of the job sphere.9.6 Salience of the professional sphere Salience of the market sphere.8.6 Salience of the entrepreneurship sphere.6.6 N entrepreneurs Phase affects the salience of spheres, we expect. In the earliest phase, those intending to start a firm will typically not yet network with potential collaborators, potential com- 96 Training and Network Organization in Entrepreneurship in Denmark 2010

98 Network organization shaped by the entrepreneur s training and background petitors, potential suppliers and potential customers, so the market sphere will not yet be very salient. Likewise, we would not expect much networking with the professional sphere or the entrepreneurship sphere. Rather, those intending to start will still rely extensively on advice from the private sphere. Moreover, this phase is when the family is deciding on important steps toward starting. Salience of the spheres varies across the phases, Table The private sphere is most salient in the earliest phase, as expected (the differences are significant; the p-value is.0001 in the anova F-test). The job sphere is most salient in the starting phase (the differences are significant; the p-value is.05). The professional sphere becomes increasingly salient during the phases (the big differences are statistically significant; with p- value.0001). The market sphere is least salient in the earliest stage, as expected (the differences are significant; the p-value is.03). The entrepreneurship sphere is most salient in the starting phase, as we should expect (the differences are significant; the p- value is.0001). Table Salience of each sphere in the networks around entrepreneurs, by phase Intending Starting Operating Salience of the private sphere Salience of the job sphere Salience of the professional sphere Salience of the market sphere Salience of the entrepreneurship sphere N entrepreneurs Age has some association with salience, but this is of course intertwined with the phases, so the association with age should be ascertained when controlling for phase, as is done in the regressions below. Education seems not to be associated with salience, as we also see in the regressions below. Is salience of a sphere affected by each characteristic while holding the other characteristics constant? How salience of a sphere is affected simultaneously by several characteristics, such as gender, age, education, training and phase, is ascertained by a statistical model, a linear regression of salience on these characteristics. The regression analyses are detailed in the Appendix, as Tables A13.2, A13.3, A13.4 and A13.5. The results are summarized in Figure 13.2 Salience of the job sphere is not significantly affected by any of the characteristics, training, education, gender, age and phase. The lack of any effect is shown by the absence of any arrow to salience of the job sphere in Figure Salience of the professional sphere is enhanced by training. Trained entrepreneurs Training and Network Organization in Entrepreneurship in Denmark

99 Network organization shaped by the entrepreneur s training and background are networking more than untrained entrepreneurs are with people in the professional sphere. This positive effect is illustrated by an arrow in Figure Salience of the professional sphere is also affected by phase. The intending phase and the operating phase can be compared to the starting phase. The professional sphere is much less salient to entrepreneurs in the intending phase than to entrepreneurs in the starting phase. This is illustrated by an arrow that is dotted because their salience is less, a negative effect. Salience of the market sphere is also enhanced by training. Salience of the market sphere is also affected by phase, in the way that the market sphere is less salient for intending entrepreneurs than for starting entrepreneurs. Salience of the private sphere is affected by gender in the way that the private sphere is less salient for male entrepreneurs than for female entrepreneurs. Salience of the private sphere is also affected by age, in the way that the private sphere is less salient for older than for younger entrepreneurs. Salience of the private sphere is also affected by phase, in the way that the private sphere is more salient for intending entrepreneurs than for starting entrepreneurs. Salience of the entrepreneurship sphere is affected by phase in the way that the entrepreneurship sphere is less salient for intending entrepreneurs than for starting entrepreneurs, and also in the way that the sphere is less salient for operating entrepreneurs than for starting entrepreneurs. 98 Training and Network Organization in Entrepreneurship in Denmark 2010

100 Network organization shaped by the entrepreneur s training and background Figure Effects upon salience of each sphere from training and other characteristics Training Job sphere Education Professional sphere Gender Market sphere Age Intending phase Private sphere Entrepreneurship sphere Operating phase The analyses in this chapter have shown how the network organization is shaped by attributes of the entrepreneurs. Size of the network is greatly enhanced by training. Size of the network is also affected by the phase, in the way that the network is smaller in the intending phase than in the starting phase. Training enhances salience of the professional sphere and of the market sphere. The private sphere is especially salient for entrepreneurs who are females, young and in the intending phase. Having now examined conditions shaping the network organization, the next task is to examine consequences of the network organization. Training and Network Organization in Entrepreneurship in Denmark

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102 Chapter 14. Network organization promoting innovation, exporting and grow th-expectation The network organization is conceptualized as the organization of the work and flow of resources and information around the entrepreneur. This network organization has organizational properties such as size and a department-like configuration in the form of spheres for acquisition of resources. This conceptualization of the network organization draws on the traditions of research on organizations focusing on resource dependency and on information processing, where performance is contingent on acquisition of information and other resources and capacity for processing them. The preceding two chapters presented this conceptualization of the network organization in terms of size and spheres and identified five spheres: the private sphere, the job sphere, the professional sphere, the market sphere, and the entrepreneurship sphere where the resource of information is embedded and acquired in the form of advice. This network organization was found to be shaped by national culture traditional versus rationalistic-secular and by individual characteristics such as gender, age, education, training and phase of the entrepreneurial endeavor. We now turn to the issue of performance and ask how performance is affected by the network organization. The aspects of performance are here innovation, exporting and growth-expectation of the entrepreneurs who are in the phases of starting or operating (those intending to start were not asked about performance). Then the issues are how these performance aspects are affected by the organizational properties of the network. Specifically, the questions here are, Is innovation affected by size of the network and salience of the spheres in the network? Is exporting affected by size of the network and salience of the spheres in the network? Is growth-expectation affected by size of the network and salience of the spheres in the network? We might expect that network size enhances each dimension of performance; at least this is the traditional idea about the effect of networking. But, going beyond orthodoxy, I may expect that networking in certain spheres will enhance performance. Specifically, I hypothesize that salience of the entrepreneurial sphere and salience of the market sphere will enhance performance. These questions can be answered by analyzing the data on starting and operating entrepreneurs identified in our GEM population surveys in the period , which were analyzed in the preceding two chapters. The entrepreneurial endeavor is innovative to the degree the endeavor markets product that are new, the production uses new technology and the entrepreneur is the only producer. There we measure innovation by asking the entrepreneur to what extent the Training and Network Organization in Entrepreneurship in Denmark

103 Network organization promoting innovation, exporting and growth-expectation products or services are new to the customers, to what extent the entrepreneur is the only provider, and to what extent new technology is used in the production, and the three measures are then combined into an index of innovation. Exporting is measured by asking how many of the customers are abroad. The percentage of customers abroad is then transformed logarithmically. Growth-expectation is measured by first asking how many persons work for the enterprise at present, and how many are expected to work for the firm in five years. Then both counts are transformed logarithmically, and then growth-expectation is measured by the difference between the two logged counts (log of future size minus log of present size). Networking affecting innovation, exporting and growth-expectation Innovation correlates with size and salience of some spheres, Table As expected, the correlation between innovation and size is positive (and significant as shown in the table). As also expected, the correlation between innovation and salience of the entrepreneurship sphere is also positive (and significant as shown in the table). As also expected, the correlation between innovation and salience of the market sphere is also positive (and significant; with p-value.04 when the test is one-sided). Innovation correlates negatively with salience of the professional sphere. However, when controll - ing for other things, then there is no significant association between innovation and salience of the professional sphere. A better analysis of the effects on innovation from each network property, while controlling for other things, is provided later in the chapter. Exporting correlates with size and salience of some spheres, Table As expected, the correlation between exporting and size is positive (and significant as shown in the table). As also expected, the correlation between exporting and salience of the entrepreneurship sphere is also positive (and significant as shown in the table). Exporting correlates negatively with salience of the professional sphere. However, when controlling for other things, then there is no significant association between exporting and salience of the professional sphere. A better analysis of the effects on exporting from each network property, while controlling for other things, is provided later in this chapter. Growth-expectation correlates with size and salience of some spheres, Table As expected, the correlation between growth-expectation and size is positive (and significant as shown in the table). As also expected, the correlation between growth-expectation and salience of the entrepreneurship sphere is also positive (and significant as shown in the table). A better analysis of the effects on growth-expectation from each network property, while controlling for other things, is provided later. 102 Training and Network Organization in Entrepreneurship in Denmark 2010

104 Network organization promoting innovation, exporting and growth-expectation Table Correlations of innovation with network properties (N = 532 networks) Correlation with P-value innovation Size of the network Salience of the private sphere Salience of the job sphere Salience of the professional sphere Salience of the market sphere Salience of the entrepreneurship sphere Table Correlations of exporting with network properties Correlation with P-value exporting Size of the network Salience of the private sphere Salience of the job sphere Salience of the professional sphere Salience of the market sphere Salience of the entrepreneurship sphere Table Correlations of growth-expectation with network properties Correlation with P-value growthexpectation Size of the network Salience of the private sphere Salience of the job sphere Salience of the professional sphere Salience of the market sphere Salience of the entrepreneurship sphere The correlations offer a first indication of how network organization is associated with performance. However, when we just look at a correlation we are ignoring other things. A better analysis of the effect of the network on performance should hold other things constant, especially characteristics of the entrepreneur and the enterprise. The separate effects of the network on performance, holding other things constant, are estimated in Training and Network Organization in Entrepreneurship in Denmark

105 Network organization promoting innovation, exporting and growth-expectation a linear regression. The regression analyses are reported in the Appendix in Tables A14.1, A14.2 and A14.3. The results are summarized here in Figure Growth-expectation is affected positively by size of the network, as a separate effect, that is significant and substantial, also when holding constant the other network properties and characteristics of the entrepreneur and the enterprise. This positive effect is illustrated by an arrow in Figure 14.1 Exporting is affected positively by size of the network, as a distinct effect that is significant and substantial, also when controlling for the other network properties and characteristics of the entrepreneur and the enterprise. This positive effect on exporting is illustrated by an arrow in Figure 14.1 Innovation is affected positively by salience of the market sphere and is also affected positively by salience of the entrepreneurship sphere. These two separate effects are significant and substantial, also when holding constant the other network properties and characteristics of the entrepreneur and the enterprise. These two positive effects on innovation are also illustrated by arrows in Figure All four effects in the figure are of similar magnitude. Figure Effects of network properties on innovation, exporting and growth-expectation Size of the network Growth expectation Private sphere salience Job sphere salience Exporting Professional sphere sal. Market sphere salience Entrepreneurship sphere Innovation The question of whether and how the network organization affects performance can now be answered. Size of the network enhances exporting and growth-expectation, and salience of the market sphere and salience of the entrepreneurship sphere promote innovation. 104 Training and Network Organization in Entrepreneurship in Denmark 2010

106 Chapter 15. The changing level of entrepreneurship in Denmark and other societies What is the level of entrepreneurial activity in Denmark? More specifically, this chapter addresses the issues, Is the trend upward, stable or downward? How does the level in Denmark compare to the levels in other societies? Entrepreneurial activity is not a single circumscribed activity but is often seen as an activity with a lifecycle that unfolds in phases as rather distinct activities (Schøtt 2006a:16-17, 56-63, 2007a:22-24, 29-31, 2008:17, 2009, 2010). We distinguish six specialized activities: prospecting or intending to start a new business in the foreseeable future starting a business, actively, such as by looking for facilities and financing new business operation, paying salary or compensation, but not yet for long established business operation, paying salary or compensation for long discontinuing or closing the business investing in a business The last activity, though, is not part of the lifecycle of entrepreneurship. These activities are performed by the entrepreneur. The six specialized activities entails a typology of six specialized entrepreneurs: prospective starter starter owner-manager of a new business owner-manager of an established business ex-owner-manager investor These specialized roles tend to be sequential, but may also overlap. To investigate entrepreneurial activity, we identify the entrepreneurs in the adult population by our GEM-survey (Chapter 2; Reynolds et al., 2005; Schøtt 2006a:20-23; 2007a:24-28; 2008:17-19; 2009; 2010). The prospective starters in entrepreneurship are those who answer Yes to the following question, Are you, alone or with others, expecting to start a new business, including any type of selfemployment, within the next three years? The starters in entrepreneurship are those answering Yes to either of the following two questions, Are you, alone or with others, currently trying to start a new business, including any selfemployment or selling any goods or services to others? Training and Network Organization in Entrepreneurship in Denmark

107 The changing level of entrepreneurship in Denmark and other societies Are you, alone or with others, currently trying to start a new business or a new venture for your employer an effort that is part of your normal work? A starter, furthermore, is also required to report to be actively starting and to be an owner of the startup. The owner-managers in entrepreneurship are those answering Yes to the following question, Are you, alone or with others, currently the owner of a company you help manage, selfemployed, or selling any goods or services to others? Owner-managers are also asked when salary or compensation was first paid to owners so as to distinguish between new and established businesses. The cutoff is set at 3½ years (year of the survey and three preceding years). The ex-owner-managers in commercial entrepreneurship are those answering Yes to the following question, Have you, in the past twelve months, shut down, discontinued or quit a business you owned and managed, any form of self-employed, or selling goods or services to anyone (not counting a business that was sold)? The investors are those answering Yes to the following question, Have you, in the past three years, personally provided funds for a new business started by someone else (excluding any purchases of stocks or mutual funds)? A person may of course play more than one of the above six specialized roles. Here we focus on the early phases of entrepreneurship. We ignore discontinuations and investing (Schøtt, 2008). The level of each entrepreneurial activity in Denmark in a year can be estimated by the prevalence or rate of the so-identified entrepreneurs in our surveyed sample of the adult population, Table 15.1 (observations are weighted, thereby enhancing validity). An entrepreneur may of course be more than one specialized kind of entrepreneur, and thus be included more than once in the counts, so the total rate of entrepreneurship of several kinds is somewhat less than the sum of the rates of the above specialized kinds of entrepreneurship. The rate of prospective starters was evidently at a low in during the economic crisis, Table Indeed the rate of prospective starters in 2009 was down to half of the rate two years earlier, and about a third of the rate five years earlier. The rate of prospective starters increased again in 2010, a considerable increase, climbing up to a level a little below that before the economic crisis. This indicator of people s intentions is a leading indicator, it is ahead of the actual event of starting new businesses, and this leading indicator entails a rather optimistic prediction. People s interesting in becoming entrepreneurs has thus regained momentum, but whether they turn their increased interest into actually starting will be seen only in the next few years. The rate of starters actively trying to start was increasing up to 2006, but evidently declined during the economic crisis. In 2009 the rate of starters was down to about half of the rate three years earlier. Apparently the rate is starting to climb again in 2010, but the increase is so small that it is not statistically significant. The rate of starters may well increase within the next few years because our leading indicator, the rate of prospective starters, began a substantial increase in The rate of operating new businesses also declined during the economic crisis. In 106 Training and Network Organization in Entrepreneurship in Denmark 2010

108 The changing level of entrepreneurship in Denmark and other societies 2009 the rate of new-business owner-managers was down to two thirds of the rate two years earlier. This decline, which we documented earlier (Schøtt 2009), was subsequently reconfirmed by counts of registrations of new businesses (Erhvervs- og Byggestyrelsen 2009). Apparently the rate is starting to climb again in 2010, but the increase is so small that it is not statistically significant. The rate of operating new businesses may well increase in a few years because our leading indicator, the rate of prospective starters, began a substantial increase in An overall measure of entrepreneurial activity in the early phase is the so-called TEA-rate (Total Entrepreneurial Activity, albeit this is less than the totality) which is the rate of starters and new-business owner-managers (and thus a bit less than the sum of their two rates). This TEA-rate correlates highly with other measures of entrepreneurial activity, such as registrations of new businesses (Schøtt 2005b). The TEA-rate shows that entrepreneurship in the early phase declined during the economic crisis. In 2009 the TEA-rate was down to two thirds of the TEA-rate two years earlier. Apparently the rate is starting to climb again in 2010, but the increase is so small that it is not statistically significant. The rate of starters and new-business owner-managers may well increase in the next few years because our leading indicator, the rate of prospective starters, began a substantial increase in Another measure of entrepreneurial activity is the upstart-rate, the rate of new-business owner-managers relative to all owner-managers, i.e. the percentage of owner-managers who are new. This rate is similar to the measure of entrepreneurial activity based on registries, namely the percentage of firms that are newly founded (Erhvervs- og Byggestyrelsen 2009). The upstart-rate seems to have been stable in the years up to 2008, but then declined in In conclusion, by any of our several measures, the level of commercial entrepreneurial activity in Denmark declined during the economic crisis and the level in 2010 is less than the level was just a few years before. However, the leading indicator of interest in pursuing entrepreneurial activity, the rate of prospective starters, has increased substantially in 2010, and predicts, albeit with much uncertainty, an increase in rates of starting new businesses in the next few years. Training and Network Organization in Entrepreneurship in Denmark

109 The changing level of entrepreneurship in Denmark and other societies Table R ates of entrepreneurship in Denmark Annually 2002 to Prospective Percent 9.0% 7.3% 9.9% 9.0% 8.2% 7.7% 7.4% 3.8% 7.5% starters of adults Starters Percent 3.6% 3.0% 2.5% 2.4% 2.9% 2.3% 2.3% 1.6% 1.8% of adults New-business Percent 3.1% 3.3% 2.8% 2.4% 2.8% 3.1% 2.3% 2.0% 2.2% ownermanagers of adults Starters and new-business ownermanagers Percent of adults (TEA) 6.5% 5.9% 5.3% 4.8% 5.3% 5.4% 4.4% 3.6% 3.8% New-business ownermanagers Percent of ownermgrs 36% 37% 36% 34% 34% 34% 34% 30% 28% Has entrepreneurial activity in other countries also declined? For this we consider the change in the rate of starters and new-business owner-managers (the commonly used TEArate) in the various developed countries, Table 15.2 (showing the percentage change from the mean of TEA in 2006 and 2007, weighing 2006 twice as much as 2007, to mean of TEA in 2008, 2009 and 2010, weighing 2009 twice as much as 2008, and weighing 2010 three times as much as 2008). The largest declines in entrepreneurial activity have been occurring in Hong Kong, Portugal, Australia, Serbia, Spain and Denmark, followed by Croatia, Italy and USA. Conversely, there have actually been considerable increases in entrepreneurial activity in many other countries, despite the economic recession. Evidently, the economic recession hit especially hard in Denmark. This decline in activity in Denmark has also been felt by those who started or operated business around 2009 when we asked them about their perceptions. Danish entrepreneurs reported that the global economic crisis made it harder to start, worsened business opportunities and reduced their growth-expectations. The Danish entrepreneurs experienced such hardships more often than entrepreneurs in other countries (Schøtt et al, 2010). 108 Training and Network Organization in Entrepreneurship in Denmark 2010

110 The changing level of entrepreneurship in Denmark and other societies Table Percentage change in rate of starters and new-business owner-managers (TEA) from to Countries with largest decline and countries with largest increase Hong Kong -63% Portugal -50% Australia -35% Serbia -32% Spain -32% Denmark -28% Croatia -27% Italy -20% USA -17%... Belgium 21% Hungary 22% Netherlands 29% Sweden 32% France 33% Latvia 61% Where does this bring Denmark in comparison to other developed countries in the level of entrepreneurial activity? The commonly used measure for comparisons is the TEArate, Table Entrepreneurial activity in Denmark is at a level that is a third of the level in New Zealand and half of the level in USA. Indeed, Denmark is much below the middle among the developed countries, with 26% of the other developed countries below Denmark. On all the other measures of entrepreneurial activity, Denmark is also below the middle. Denmark was hovering somewhere around the middle among the developed countries for several years before the economic crisis hit in 2008, but since 2008 Denmark has dropped well below the middle (Hancock et al, 2001, 2002, 2003, 2004; Schøtt, 2006a, 2007, 2008, 2009, 2010; Warhuus 2000). Training and Network Organization in Entrepreneurship in Denmark

111 The changing level of entrepreneurship in Denmark and other societies Table R ates of entrepreneurship in developed societies. Countries with highest rates, countries with lowest rates, USA and Denmark , weighted toward 2010 Prospective starters Percent of adults Starters Percent of adults New-business ownermanagers Percent of adults Starters and new-business owner-managers (TEA) Percent of adults New-business ownermanagers Percent of ownermanagers 49% Russia 36% Macedonia 9% New Zealand 8% New Zealand 15% New Zealand 31% Serbia 8% Iceland 5% S.Korea 11% Iceland 44% Singapore 27% Taiwan 6% 5% Macedonia 11% Macedonia 44% Czech Republic New Zealand 13% USA 58 percentile rank 6% USA 92 percentile rank 4% USA 84 percentile rank 10% USA 89 percentile rank 38% USA 76 percentile rank 7% Denmark 18 percentile rank 2% Denmark 13 percentile rank 2% Denmark 34 percentile rank 5% Denmark 26 percentile rank 33% Denmark 47 percentile rank 6% 2% Sweden 2% Austria 3% Belgium 23% Austria Netherlands 5% Russia 2% Puerto 1% France 3% Japan 20% Greece Rico 5% Japan 2% Japan 1% Belgium 3% Puerto Rico 19% Japan The gloomy rates are consistent with the recent official report Iværksætterindeks 2010 (Erhvervs- og Byggestyrelsen, 2010). However, the official report is based mainly on trends in the past in numbers of registrations of businesses, and is thus most similar to our rates of new-business owner-managers as percent of owner-managers, and both their counts of registrations and our survey counting new-business owner-managers as a population rate or as a rate of owner-managers are showing a decline in the most recent years. The past trends shown in the official report thus reconfirm the trends that were already revealed and documented by our GEM-surveys in recent years (Schøtt, 2006a, 2007, 2008, 2009, 2010). But, going beyond the counts based on historical registries, our GEM surveys offer a leading indicator which can better reveal current changes, and this entails a more optimistic prediction. 110 Training and Network Organization in Entrepreneurship in Denmark 2010

112 Chapter 16. National conditions for entrepreneurship: trends in Denmark and comparisons to other societies How are the national conditions for commercial entrepreneurship in Denmark? More specifically, this chapter answers the questions, Are cultural and institutional conditions in Denmark improving or deteriorating, or are they stable during the economic recession? How does the framework in Denmark compare to the framework in other societies? Entrepreneurship does not exist in a vacuum. Entrepreneurship is an activity that is organized in society and is shaped by conditions prevailing in the society. Entrepreneurial activity in society flourishes under some conditions and vanishes under other conditions (Morrison 2000; Shane 1992, 1993). The conditions in society shaping entrepreneurship are denoted the framework conditions in the society. The framework conditions are subject to intervention by the authorities in society, indeed, in recent decades they have become a focus for policy-making (Schøtt and Jensen 2008). Some framework conditions are in the culture of society, notably in its values and knowledge. Other framework conditions are in the social institutions of society, notably in its supportive arrangements, mobilization and allocation of resources, and regulation of the market. The framework conditions in society are numerous and only partly discerned, and their effects are even less known. Here we examine 14 framework conditions in society, namely 4 cultural conditions and 10 institutional conditions, Figure 16.1 Training and Network Organization in Entrepreneurship in Denmark

113 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Figure Framework of culture and institutions in society CULTURE Education in entrepreneurship during schooling Skills in entrepreneurship in the population Individualism as a value in culture Esteem of the vocation of entrepreneur ENTREPRENEURSHIP INSTITUTIONS Financial resources for entrepreneurship Government policies for entrepreneurship Public programs for entrepreneurship Technology transfer to entrepreneurship Commercial and legal infrastructure Internal market openness to new firms Physical infrastructure for new firms Intellectual property rights Support for growth-entrepreneurship Opportunities for business These conditions are measured in each country participating in GEM. A national panel of experts on commercial entrepreneurship in the country is surveyed and assesses each condition on a scale from a low of 1 to a high of 5 (Chapter 2; Schøtt, 2006a:20-21, 64-95; 2007:33-49; 2008:21-32; 2009; 2010). Almost annual assessments of conditions in Denmark and other countries enable us to track changes over time in Denmark and to compare Denmark to other countries (the framework conditions in Denmark were measured annually in the years up to 2009, but were not measured in 2010). The measures of framework conditions, in so far as they affect future commercial entrepreneurship, are actually leading indicators of entrepreneurial activity. In this chapter, we shall examine each condition, track its changes in Denmark and 112 Training and Network Organization in Entrepreneurship in Denmark 2010

114 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies compare Denmark to other developed countries, and then, in the next chapter, we shall estimate effects of the conditions upon commercial entrepreneurial activity. Education for entrepreneurship as a cultural framework condition shaping entrepreneurship Education here refers to the formal instruction, all the way up through higher education, which provides knowledge and skills for performing the entrepreneurial role (Schøtt 2006a:68; 2007a:35; 2008:29; 2009; 2010). This kind of education in entrepreneurship in Denmark is assessed almost annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, teaching in primary and secondary education encourages creativity, self-sufficiency, and personal initiative. In Denmark, teaching in primary and secondary education provides adequate instruction in market economic principles. In Denmark, teaching in primary and secondary education provides adequate attention to entrepreneurship and new firm creation. In Denmark, colleges and universities provide good and adequate preparation for starting up and growing new firms. In Denmark, the level of business and management education provide good and adequate preparation for starting up and growing new firms. In Denmark, the vocational, professional, and continuing education systems provide good and adequate preparation for starting up and growing new firms. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the six statements for a measure for the year. With measurement taken in recent years we can track recent changes in the extent of education for entrepreneurship. The extent of entrepreneurial education in Denmark has changed, Table The conveyance of entrepreneurial knowledge and skills has tended to increase over the years (for specific educational initiatives, see Erhvervs- og Byggestyrelsen 2008: 69-71). Table Education for entrepreneurship in Denmark Annually from 2002 to Where does this entrepreneurial education bring Denmark in comparison to other countries? The entrepreneurial content in education is likewise assessed in the other countries participating in GEM. In the years from 2002 to 2010, the framework conditions have been assessed in 39 other developed countries listed in Chapter 2. A summary measure that reduces year-to-year fluctuations as well as emphasizes the most re- Training and Network Organization in Entrepreneurship in Denmark

115 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies cent time is a weighted average, weighing the second year (2003) of measurement twice as much as the first year (2002), the third year (2004) three times as much as the first year, and so on up to the most recent year (2010), that is weighted nine times as much as the first year. This weighted average is used for comparing the framework conditions among the developed countries, Table 16.2 (and similar tables in the rest of this chapter). Entrepreneurial education is more extensive in several developed countries, notably Singapore, Latvia and Taiwan. Among the developed countries, Denmark is a little below the middle, 58% of the other developed countries are above and 42% of the others are below. Table Education for entrepreneurship. The three countries with most education, the three countries with least, and Denmark , weighted toward 2010 Singapore 3.0 Latvia 2.9 Taiwan 2.8 Denmark percentile rank Sweden 2.2 Greece 2.1 Japan 1.9 In short, although the entrepreneurial content in education in Denmark has been expanding considerably, it is still less than typical for the developed countries. Skills for the entrepreneurial vocation Skills refer to the skills of the entrepreneurial vocation, which prevail in the population, and encompass techniques for starting and organizing a firm, understanding markets and managing growth (Schøtt, 2006a:70, 2007a:36, 2008:30, 2009, 2010; Schøtt and Ottósson 2009). Skills are acquired not only through formal education, but also through experience, training and networking (Bager and Nielsen, 2009; Schøtt 2006b, 2007e, 2008a, 2008b, 2009, 2010; Schøtt and Christensen 2005; Schøtt and Klyver 2006). Moreover, skills are transferred from existing firms when entrepreneurs move to start new firms (Schøtt 2005d, Schøtt and Jensen 2007). The skills of the population in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, many people know how to start and manage a high-growth business. In Denmark, many people know how to start and manage a small business. 114 Training and Network Organization in Entrepreneurship in Denmark 2010

116 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In Denmark, many people have experience in starting a new business. In Denmark, many people can react quickly to good opportunities for a new business. In Denmark, many people have the ability to organize the resources required for a new business. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the five statements for a measure for the year. With measurement taken in recent years, we can track recent changes in entrepreneurial skills in the population. The skills in the population in Denmark have changed, Table The skills have tended to increase steadily and considerably over time. Table Skills for the entrepreneurial vocation in Denmark Annually from 2002 to Where does this level of skills bring Denmark in comparison to other countries? Skills are assessed likewise in other countries. Skills are more extensive in many societies, notably in Iceland, Hong Kong and Israel, Table Among the developed countries, Denmark is a little above the middle, with 39% of the others above and 61% of the others below. Table Skills for the entrepreneurial vocation The three countries with most skills, the three countries with least, and Denmark , weighted toward 2010 Iceland 3.6 Hong Kong 3.4 Israel 3.1 Denmark percentile rank Sweden 2.0 France 1.8 Japan 1.6 In short, entrepreneurial skills have increased in the population in Denmark, and they are now a little above the typical for the developed countries. Training and Network Organization in Entrepreneurship in Denmark

117 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Individualism as a value in culture Values refer to what is appreciated in society, what is considered good (Schøtt, 2006a:64, 2007a:33, 2008:28, 2009, 2010). Our culture of modernity values the individual as an actor that is not only capable of taking action, and acting alone, by own effort, but also taking responsibility for acting alone and finding ways to act and to gain by acting (Weber, 1930; Inglehart and Welzel 2005). Modernity thus has a value that we briefly can call individualism, in contrast to collectivism, valuing the collectivity and the collective good (Mueller and Thomas 2000; Nakata and Sivakumar 1996; Thomas and Mueller 2000; Tiessen 1997). Denmark is in many ways a highly modern society but is actually also rather collectively oriented. The value attached to individualism in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, the national culture is highly supportive of individual success achieved through own personal efforts. In Denmark, the national culture emphasizes self-sufficiency, autonomy, and personal initiative. In Denmark, the national culture encourages entrepreneurial risk-taking. In Denmark, the national culture encourages creativity and innovativeness. In Denmark, the national culture emphasizes the responsibility that the individual (rather than the collective) has in managing his or her own life. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the five statements for a measure for the year. With measurement taken in recent years, we can track recent changes in the value attached to individualism. The value attached to individualism in Denmark has changed, Table Individualism has tended to become more highly valued over time. Table Cultural value of individualism in Denmark Annually from 2002 to How does the value attached to individualism in Denmark compare to its value in other countries? Individualism is assessed likewise in other countries. Several societies are highly individualistic, notably USA, Israel and Hong Kong, Table Among the developed countries, Denmark is slightly above the middle, 37% of the others are more individualistic, and 63% of the others are less individualistic. 116 Training and Network Organization in Entrepreneurship in Denmark 2010

118 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Cultural value of individualism The three countries with most individualistic values, the three countries with least individualistic values, and Denmark , weighted toward 2010 USA 4.1 Israel 4.0 Hong Kong 4.0 Denmark percentile rank Japan 2.2 France 1.2 Portugal 2.0 In short, there has been a considerable increase in the cultural value attached to individualism in Denmark over time. Denmark has become more individualistic than is typical among the developed countries. Cultural esteem of the entrepreneurial vocation Esteem refers to the cultural prestige of the vocation or role of the entrepreneur among the vocations in society, as this prestige motivates people to pursue this vocation rather than other occupations (Schøtt, 2006a:66, 2007a:34, 2008:28-29, 2009, 2010). Esteem of the entrepreneurial vocation in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, the creation of new ventures is considered an appropriate way to become rich. In Denmark, most people consider becoming an entrepreneur as a desirable career choice. In Denmark, successful entrepreneurs have a high level of status and respect. In Denmark, you will often see stories in the public media about successful entrepreneurs. In Denmark, most people think of entrepreneurs as competent, resourceful individuals. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the five statements for a measure for the year. With measurement taken in recent years, we can track changes in the cultural esteem of the entrepreneurial vocation. The esteem of the entrepreneurial vocation in Denmark has been changing, Table The esteem has increased considerably over time. Training and Network Organization in Entrepreneurship in Denmark

119 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Esteem in Denmark Annually from 2002 to Where does this esteem bring Denmark in comparison to other countries? Esteem is assessed similarly in the other countries participating in GEM. Esteem of the entrepreneurial vocation is much higher in several other developed societies, notably in Israel, Taiwan and USA, Table Among the developed countries, Denmark is notably above the middle, 42% of the others are above and 58% of the others are below. Table Esteem accorded the entrepreneurial vocation The three countries with highest esteem, the three countries with lowest, and Denmark , weighted toward 2010 Israel 4.4 Taiwan 4.3 USA 4.2 Denmark percentile rank Slovakia 2.9 Japan 2.9 Czech Republic 2.8 In short, the esteem of the entrepreneurial vocation has been increasing much in Denmark, and Denmark now esteems the entrepreneurial vocation notably higher than typical among the developed countries. Cultural framework In the above, we examined four specific cultural framework conditions: education offered for entrepreneurship, skills of the population, individualism as a cultural value, and esteem of the entrepreneurial occupation. These four cultural framework conditions all tended to increase, so the cultural framework has improved overall. The cultural framework can be indicated by an index computed as the mean of the four specific measures, Table The index of the cultural framework has increased considerably, that is, the cultural framework has improved over the years and entrepreneurial culture has become pervasive in Denmark. 118 Training and Network Organization in Entrepreneurship in Denmark 2010

120 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Entrepreneurial culture in Denmark (mean of four specific conditions) Annually from 2002 to ,3 2,4 2,5 2,6 2,8 2,9 2,8 3,2 Where does this entrepreneurial culture bring Denmark in comparison to other countries? Entrepreneurial culture is assessed similarly in the other countries participating in GEM, also as the mean of the four measures of specific cultural conditions. Entrepreneurial culture is more prevalent in several other developed societies, notably in Taiwan, Hong Kong, Israel, Iceland and USA, Table Among the developed countries, Denmark is a little above the middle, 39% of the others are above and 61% of the others are below. Table Entrepreneurial culture The countries with most pervasive entrepreneurial culture, the countries with least, and Denmark , weighted toward 2009 Taiwan 3.5 Hong Kong 3.5 Israel 3.5 Iceland 3.5 USA 3.5 Denmark percentile rank Bosnia 2.5 Portugal 2.4 Sweden 2.4 France 2.3 Japan 2.2 In short, the cultural framework in Denmark has improved considerably over the years, also in recent years despite the economic recession, entrepreneurial culture is now pervasive in Denmark, and Denmark now has more of an entrepreneurial culture than most other developed countries. Having examined the cultural framework, we turn to examine a series of institutional framework conditions. Training and Network Organization in Entrepreneurship in Denmark

121 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Institutional framework conditions: Financial resources for entrepreneurship Financial resources refer to the availability of funding for entrepreneurship (Schøtt, 2006:76, 2007:39, 2008:22, 2009, 2010). Each year, in Denmark, the financial resources are assessed by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, there is sufficient equity funding available for new and growing firms. In Denmark, there is sufficient debt funding available for new and growing firms. In Denmark, there are sufficient government subsidies available for new and growing firms. In Denmark, there is sufficient funding available from private individuals (other than founders) for new and growing firms. In Denmark, there is sufficient venture capitalist funding available for new and growing firms. In Denmark, there is sufficient funding available through initial public offerings (IPOs) for new and growing firms. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the six statements for a measure for the year. With measurement taken in recent years we can track recent changes in financial resources for entrepreneurship. The availability of funding in Denmark has fluctuated over the years, Table Resources seem to have been declining in the most recent years, from 2007 to 2009, that is, since the economic recession began. Table Financial resources in Denmark Annually from 2002 to Where does this availability of resources for entrepreneurship bring Denmark compared to other countries. Availability is also measured in the other countries participating in GEM, Table Among the developed countries, Singapore, Canada and Taiwan have greatest availability. Denmark is in the middle, with 53% of the others below. 120 Training and Network Organization in Entrepreneurship in Denmark 2010

122 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Financial resources The three countries with most financial resources, the three countries with least financial resources, and Denmark , weighted toward 2010 Singapore 3.3 Canada 3.3 Taiwan 3.2 Denmark percentile rank Russia 2.2 Macedonia 2.1 Poland 1.8 In short, availability of resources has been decreasing in the most recent years. Denmark is in the middle among the developed countries. Government policies toward entrepreneurship Government policies toward entrepreneurship refer to the policies that the national government and more local public authorities decide and implement (Schøtt, 2006a:78, 2007a:40, 2008:23, 2009, 2010). Government policies in Denmark are measured annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, Government policies (e.g., public procurement) consistently favor new firms. In Denmark, the support for new and growing firms is a high priority for policy at the national government level. In Denmark, the support for new and growing firms is a high priority for policy at the local government level. In Denmark, new firms can get most of the required permits and licenses in about a week. In Denmark, the amount of taxes is NOT a burden for new and growing firms. In Denmark, taxes and other government regulations are applied to new and growing firms in a predictable and consistent way. In Denmark, coping with government bureaucracy, regulations, and licensing requirements it is not unduly difficult for new and growing firms. Government policies in Denmark have been changing, Table During the decade, policies have become more favorable. Training and Network Organization in Entrepreneurship in Denmark

123 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Government policies in Denmark Annually from 2002 to Where do these favorable policies bring Denmark compared to other countries? Government policies have been measured also in the other countries participating in GEM, Table Among the developed countries, government policies are more favorable especially in Singapore, Iceland and Finland. Denmark is near the top, with 84% of the other countries having less favorable policies. Table Government policies The three countries with most favorable government policies, the three countries with least supportive policies, and Denmark , weighted toward 2010 Singapore 3.6 Iceland 3.3 Finland 3.3 Denmark percentile rank Italy 1.9 Bosnia 1.8 Hungary 1.8 In short, government policies in Denmark have become more supportive, and Denmark is among the countries with most favorable policies. Public programs for entrepreneurship Public program refer to the programs that are publicly available, and mostly supported by funds from the public, channeled through national and more local administrations (Schøtt, 2006a:80, 2007a:41, 2008:23-24, 2009, 2010). The adequacy of the public programs in Denmark are assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, a wide range of government assistance for new and growing firms can be obtained through contact with a single agency. In Denmark, science parks and business incubators provide effective support for new and growing firms. In Denmark, there are an adequate number of government programs for new and growing businesses. 122 Training and Network Organization in Entrepreneurship in Denmark 2010

124 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In Denmark, the people working for government agencies are competent and effective in supporting new and growing firms. In Denmark, almost anyone who needs help from a government program for a new or growing business can find what they need. In Denmark, government programs aimed at supporting new and growing firms are effective. Adequacy of public programs in Denmark has been changing a little, Table Adequacy of the public programs has apparently been increasing most recently. Table Public programs for entrepreneurship in Denmark Annually from 2002 to Where is Denmark positioned compared to other countries in terms of supportive public programs? Public programs are likewise assessed in other countries, Table Among the developed countries, public programs are more supportive in some countries, notably Germany, Austria and Taiwan. Denmark has very supportive programs, only 16% of the other countries have more supportive programs, whereas 84% of the others have less supportive programs. That Denmark has very supportive public programs is hardly surprising, as Denmark is still a welfare society, with welfare extending to public support for private business, especially under the current right-wing government. Table Public programs for entrepreneurship The three countries with most supportive public programs, the three countries with least, and Denmark , weighted toward 2010 Germany 3.5 Austria 3.5 Taiwan 3.4 Denmark percentile rank Hungary 2.2 Russia 2.1 Bosnia 1.9 In short, the supportiveness of public programs in Denmark has been increasing most recently, and public programs are more supportive than in by far most countries. Training and Network Organization in Entrepreneurship in Denmark

125 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Technology transfer to entrepreneurship Technology transfer denotes the movement of technological knowledge from public research institutions to entrepreneurship (Schøtt, 2006a:82, 2007a:42, 2008:24, 2009, 2010). The extent of technology transfer in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, new technology, science, and other knowledge are efficiently transferred from universities and public research centers to new and growing firms. In Denmark, new and growing firms have just as much access to new research and technology as large, established firms. In Denmark, new and growing firms can afford the latest technology. In Denmark, there are adequate government subsidies for new and growing firms to acquire new technology. In Denmark, the science and technology base efficiently supports the creation of world-class new technology-based ventures in at least one area. In Denmark, there is good support available for engineers and scientists to have their ideas commercialized through new and growing firms. Technology transfer in Denmark has been changing over the years, Table Technology transfer has steadily increased over time. Table Technology transfer in Denmark Annually from 2002 to Where does the increase bring Denmark, in comparison to other countries? Technology is measured likewise in many other countries, Table Among the developed countries, technology transfer is especially extensive in Taiwan, Switzerland and Singapore. Denmark is a little above the middle, with 59% of the other countries below Denmark in technology transfer. 124 Training and Network Organization in Entrepreneurship in Denmark 2010

126 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Technology transfer The three countries with most technology transfer, the three countries with least, and Denmark , weighted toward 2010 Taiwan 3.3 Switzerland 3.3 Singapore 3.0 Denmark percentile rank Russia 2.1 Bosnia 1.9 Poland 1.9 In short, technology transfer has been increasing in Denmark, and Denmark is a little above the middle among the developed countries in the extent of technology transfer. Commercial and legal infrastructure for entrepreneurship Commercial and legal infrastructure refers to the availability and affordability of high quality services of commercial, legal and professional kinds (Schøtt, 2006a:84, 2007a:43, 2008:24-25, 2009, 2010). The infrastructure in Denmark is measured annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, there are enough subcontractors, suppliers, and consultants to support new and growing firms. In Denmark, new and growing firms can afford the cost of using subcontractors, suppliers, and consultants. In Denmark, it is easy for new and growing firms to get good subcontractors, suppliers, and consultants. In Denmark, it is easy for new and growing firms to get good, professional legal and accounting services. In Denmark, it is easy for new and growing firms to get good banking services (checking accounts, foreign exchange transactions, letters of credit, and the like). The infrastructure in Denmark has changed over the years, Table The availability increased up to 2006, but since 2006 availability of infrastructure has been decreasing. Training and Network Organization in Entrepreneurship in Denmark

127 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Commercial and legal infrastructure in Denmark Annually from 2002 to How does Denmark compare to other countries? The infrastructure is also measured in the other countries participating in GEM, Table The availability is higher in several countries, notably in Canada, Israel and Belgium. Among the developed countries, Denmark is about the middle, with 53% of the others below. Table Commercial and legal infrastructure The three countries with most commercial and legal infrastructure, the three countries with least, and Denmark , weighted toward 2010 Canada 3.7 Israel 3.7 Belgium 3.6 Denmark percentile rank Bosnia 2.7 South Korea 2.5 Japan 2.2 In short, availability of commercial and legal services in Denmark has been decreasing in the most recent years, and Denmark is in the middle among the developed countries. Internal market openness Openness of the internal market refers to the ease of entry into the market for new firms (Schøtt, 2006a:86, 2007a:44, 2008:25, 2009, 2009, 2010). The openness of the internal market in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, the markets for consumer goods and services change dramatically from year to year. In Denmark, the markets for business-to-business goods and services change dramatically from year to year. In Denmark, new and growing firms can easily enter new markets. In Denmark, the new and growing firms can afford the cost of market entry. In Denmark, new and growing firms can enter markets without being unfairly blocked by established firms. 126 Training and Network Organization in Entrepreneurship in Denmark 2010

128 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In Denmark, the anti-trust legislation is effective and well enforced. The openness in Denmark has changed over the years, Table Over the decade, the internal market has become a little more open. Table Internal market openness in Denmark Annually from 2002 to How open is the internal market in Denmark in comparison to other countries? The openness is assessed in the other countries participating in GEM, Table Many countries are far more open, notably Taiwan, South Korea and Iceland. Among the developed countries, Denmark is notably below the middle, with 42% of the other societies less open. Table Internal market openness The three countries with widest internal market openness, the three countries with narrowest, and Denmark , weighted toward 2010 Taiwan 3.5 South Korea 3.3 Iceland 3.2 Denmark percentile rank Spain 2.5 Portugal 2.4 France 2.4 In short, although the internal market in Denmark has become a little more open over the years, it remains notably below the middle compared to other developed countries. Physical infrastructure for entrepreneurship Physical infrastructure encompasses facilities for transportation and communication, their availability and affordability and speed of obtaining them (Schøtt, 2006a:88, 2007a:45, 2008:25-26, 2009, 2010). Physical infrastructure in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, Training and Network Organization in Entrepreneurship in Denmark

129 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In Denmark, the physical infrastructure (roads, utilities, communications, waste disposal) provides good support for new and growing firms. In Denmark, it is not too expensive for a new or growing firm to get good access to communications (phone, Internet, etc.). In Denmark, a new or growing firm can get good access to communications (telephone, internet, etc.) in about a week. In Denmark, new and growing firms can afford the cost of basic utilities (gas, water, electricity, sewer). In Denmark, new or growing firms can get good access to utilities (gas, water, electricity, sewer) in about a month. The physical infrastructure in Denmark has changed over the years, Table The physical infrastructure improved up to 2006, but since 2006 the physical infrastructure has apparently been declining a little. Table Physical infrastructure in Denmark Annually from 2002 to How is the physical infrastructure in Denmark compared to other countries? The physical infrastructure is assessed likewise in the other countries participating in GEM, Table The physical infrastructure is better in some societies, notably Hong Kong, Singapore and Switzerland. Among the developed countries, Denmark is far above the middle, with 79% of the others below. 128 Training and Network Organization in Entrepreneurship in Denmark 2010

130 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Physical infrastructure The three countries with most physical infrastructure, the three countries with least, and Denmark , weighted toward 2010 Hong Kong 4.7 Singapore 4.6 Switzerland 4.5 Denmark percentile rank Puerto Rico 3.0 Italy 2.9 Poland 2.9 In short, the physical infrastructure in Denmark has apparently been declining in most recent years, but Denmark remains much above the middle among the developed countries. Intellectual property rights Intellectual property rights refer to the establishment of private ownership of knowledge (Schøtt, 2006a:90, 2007a:46, 2008:26, 2009, 2010). This property right in Denmark is assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, the Intellectual Property Rights (IPR) legislation is comprehensive In Denmark, the Intellectual Property Rights (IPR) legislation is efficiently enforced. In Denmark, the illegal sales of pirated software, videos, CDs, and other copyrighted or trademarked products is not extensive. In Denmark, new and growing firms can trust that their patents, copyrights, and trademarks will be respected. In Denmark, it is widely recognized that inventors rights for their inventions should be respected. The rights in Denmark have been changing over the years, Table The rights expanded considerably up to 2007, but since 2007 the rights have apparently been declining. Training and Network Organization in Entrepreneurship in Denmark

131 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Intellectual property rights in Denmark Annually from 2002 to Where do these intellectual property rights bring Denmark in comparison to other countries? Rights are assessed likewise in the other countries participating in GEM. Rights are more extensive in Switzerland, Australia and Singapore, Table Denmark is among the developed countries with very extensive rights, as 84% of the other countries have less comprehensive rights. Table Intellectual property rights The three countries with most protective intellectual property rights, the three countries with least, and Denmark , weighted toward 2010 Switzerland 4.2 Australia 4.2 Singapore 4.1 Denmark percentile rank Serbia 2.3 Russia 2.1 Bosnia 1.9 In short, the intellectual property rights in Denmark have apparently been declining in the most recent years, but Denmark remains among the developed countries with the most extensive rights. Support for growth-entrepreneurship National support for growth-entrepreneurship refers to policies and programs specifically designed to support high-growth firms (Schøtt, 2006a, 2007b, 2008:21-22, 2009, 2010). The institutional support for growth-entrepreneurship in Denmark is assessed by asking experts to ascertain truthfulness of each of the following statements, In Denmark, there are many support initiatives that are specially tailored for highgrowth entrepreneurial activity. In Denmark, policy-makers are aware of the importance of high-growth entrepreneurial activity. 130 Training and Network Organization in Entrepreneurship in Denmark 2010

132 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In Denmark, people working in entrepreneurship-support-initiatives have sufficient skills and competence to support high-growth firms. In Denmark, potential for rapid growth is often used as a selection criterion when choosing recipients of entrepreneurship support. In Denmark, supporting rapid firm-growth is a high priority in entrepreneurship policy. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the five statements for a measure for the year. With measurement taken in recent years we can track recent changes in support for growth-entrepreneurship. Support for growth-entrepreneurship in Denmark has been increasing in recent years, Table This assessment is consistent with the changes in entrepreneurship policy and implementations, such as the establishment of advisory services specifically tailored for growth-oriented firms (Erhvervs- og Byggestyrelsen, 2007). Table Support for growth-entrepreneurship in Denmark Annually 2005 to Where does this bring Denmark compared to other countries? Support for growth-entrepreneurship is also assessed in the other countries participating in GEM by the same questions to a national panel of experts there, Table Ireland, Taiwan and Singapore are more supportive of growth-entrepreneurship. Denmark is near the top, with 92% of the other countries below. Table Support for growth-entrepreneurship The countries with most support, the three countries with least support, and Denmark , weighted toward 2010 Ireland 4.2 Taiwan 3.8 Singapore 3.7 Denmark percentile rank Japan 2.6 Czech Republic 2.5 Bosnia 2.2 Training and Network Organization in Entrepreneurship in Denmark

133 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies In short, support for growth-entrepreneurship has been increasing considerably in Denmark, and Denmark is among the developed countries with most support for growthentrepreneurship. Opportunities for entrepreneurship Opportunities refer to the opportunities that people in the society have for exploiting business ideas by starting, running and expanding businesses (Schøtt, 2006a:74, 2007b:38, 2008:27, 2009, 2010). Opportunities are thus a broad framework condition that encompasses the more specific institutional framework conditions considered above. Opportunities in Denmark are assessed annually by asking a panel of experts to ascertain truthfulness of each of the following statements, In Denmark, there are plenty of good opportunities for the creation of new firms. In Denmark, there are more good opportunities for the creation of new firms than there are people able to take advantage of them. In Denmark, good opportunities for new firms have considerably increased in the past five years. In Denmark, individuals can easily pursue entrepreneurial opportunities. In Denmark, there are plenty of good opportunities to create truly high growth firms. Each expert ascertains truthfulness of each statement in terms of Completely false, Somewhat false, Neither true nor false, Somewhat true and Completely true. The assessment is quantified on a scale from 1 to 5. The assessments are then averaged across the experts and averaged across the five statements for a measure for the year. With measurement taken in recent years we can track changes in opportunities for entrepreneurship. Opportunities have been changing, Table Opportunities in Denmark were expanding up to , but opportunities have been contracting since 2007, i.e. during the crisis. Table Opportunities in Denmark Annually from 2002 to Where does this expansion of opportunities bring Denmark now, in comparison to other countries? Opportunities are assessed in the other countries participating in GEM, Table Opportunities are greater in several countries, notably USA, Australia and New Zealand. Among the developed countries, Denmark is considerably above the middle, with 71% of the others below. 132 Training and Network Organization in Entrepreneurship in Denmark 2010

134 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Opportunities for starting The three countries with greatest opportunities, the three countries with least, and Denmark , weighted toward 2010 USA 3.8 Australia 3.7 New Zealand 3.6 Denmark percentile rank Hungary 2.8 Greece 2.7 Italy 2.6 In short, opportunities in Denmark have been declining in the most recent years, but Denmark remains considerably above the middle among the developed countries. Institutional framework In the above, we examined ten specific institutional conditions, Financial resources for entrepreneurship, Government policies for entrepreneurship, Public programs for entrepreneurship, Technology transfer to entrepreneurship, Commercial and legal infrastructure, Internal market openness to new firms, Physical infrastructure for new firms, Intellectual property rights, Support for growth-entrepreneurship, and Opportunities for business. These specific conditions tend to go hand in hand. Therefore it is sensible to consider how they vary overall. Overall, have the institutional conditions been improving or declining, or are they stable, specifically during the economic recession in recent years? For this, we compute the mean of the above measures of specific institutional conditions, Table The institutional framework improved up to , but has apparently been declining slightly since 2007, during the economic recession. This recent decline in institutional framework contrasts with the substantial, steady and continual improvement in the cultural framework examined earlier (and summarized in Table 16.9). Table Institutional framework, as mean of specific institutional conditions, in Denmark Annually from 2002 to Where does this institutional framework bring Denmark in comparison to other coun- Training and Network Organization in Entrepreneurship in Denmark

135 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies tries? The institutional framework is assessed similarly in the other countries participating in GEM, here as the mean of the specific conditions. The institutional framework is more supportive in several other developed societies, notably in Singapore and Switzerland, Table Among the developed countries, Denmark is much above the middle, 26% of the others are above and 74% of the others are below. Table Institutional framework The countries with most supportive institutional framework, the countries with least, and Denmark , weighted toward 2010 Singapore 3.6 Switzerland 3.5 Taiwan 3.4 Austria 3.3 Finland 3.3 Denmark percentile rank Hungary 2.5 Italy 2.5 Russia 2.5 Poland 2.4 Bosnia 2.3 Denmark is thus placed well above the middle among the developed countries in both its institutional framework and cultural framework. Next we shall examine the overall framework, combining both institutional and cultural conditions. The framework overall The framework for entrepreneurship has now been examined in terms of four cultural conditions and ten institutional conditions. Several of these conditions have changed over the years, and Denmark is more or less like other developed societies. Overall, how has the framework changed in Denmark? How does the framework in Denmark, overall, compare to the framework elsewhere? To examine the trend in the overall framework, we can average the assessments of the 14 conditions examined above. The framework in Denmark, overall, has changed over the years, Table The framework improved up to about 2006 and seems to have been stable since then. 134 Training and Network Organization in Entrepreneurship in Denmark 2010

136 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies Table Mean of national framework conditions in Denmark Annually from 2002 to The framework is each other society can be ascertained by the average across the 14 conditions, Table The framework, overall, is best in Taiwan, secondly in Singapore, Hong Kong, United States and Switzerland. Denmark has a framework that, overall, is considerably better than the typical framework in the developed countries, with 68% of the developed countries having a framework less good than the framework in Denmark. Table Mean of national framework conditions Societies with best framework, societies with weakest framework, and Denmark , weighted toward 2010 Taiwan 3.4 Singapore 3.4 Hong Kong 3.4 USA 3.3 Switzerland 3.3 Denmark percentile rank Italy 2.6 Hungary 2.6 Poland 2.5 Japan 2.5 Bosnia 2.4 Several conclusions can be drawn from the above analyses of framework conditions, their changes in Denmark, and their favorableness in Denmark in comparison to other developed countries. Over the years several of the Danish framework conditions have become more favorable and are more favorable today than some years ago, notably the cultural framework conditions. Several Danish framework conditions, however, have also been declining in the most recent years, during the economic recession, notably several institutional framework conditions. Where does this improvement bring Denmark compared to other countries? Most of the Danish framework conditions are rather close to the typical situation for developed Training and Network Organization in Entrepreneurship in Denmark

137 National conditions for entrepreneurship: trends in Denmark and comparisons to other societies countries, and rank around the middle among the developed countries. Several conditions are much more favorable in Denmark than typical among the developed countries. Conversely, a few conditions are less favorable in Denmark than typical among the developed countries. So, overall, the framework in Denmark is notably better than is typical for the developed countries. How the framework conditions affect entrepreneurship will be examined next. 136 Training and Network Organization in Entrepreneurship in Denmark 2010

138 Chapter 17. Effects of framework conditions upon level of entrepreneurship What are the national dynamics of entrepreneurship? More specifically, this chapter addresses the questions, How are the cultural conditions affecting one another? How are the institutional conditions interrelated? How are the cultural and institutional conditions affecting entrepreneurship? The cultural and institutional conditions are a framework for entrepreneurship in society. A favorable framework enhances entrepreneurship whereas an unfavorable framework hampers performance in the society. The framework is favorable in some societies and less favorable in other societies, and this shapes the level of entrepreneurial activity, so the level differs from one society to another. Is entrepreneurial activity in the various countries tightly coupled with its framework conditions? Whether entrepreneurial activity goes hand-in-hand with a framework condition, in the various countries, is ascertained by the correlation between the activity and the condition, computed across the countries. Entrepreneurial activity in a country is measured by the TEA-rate (Chapter 15), and each of 14 framework conditions was measured (Chapter 16). The 14 correlations between entrepreneurship and the 14 framework-conditions are all between.0 and.5 (each variable is averaged across years up through 2010, and then the correlation between variables is computed across the 39 developed countries). For the developing countries, however, entrepreneurship is far less coupled with its framework conditions (Schøtt and Jensen 2009). The framework conditions are related to each other. We shall examine how the institutional conditions are interrelated and how the cultural conditions are interrelated. Then we shall examine how the institutional conditions and the cultural conditions jointly affect entrepreneurship. Institutional conditions creating opportunities Opportunities for exploiting business ideas is a condition for entrepreneurship, but it is not a institutional condition like the nine others examined earlier financial resources, government policies, public programs, technology transfer, commercial and legal infrastructure, internal market openness, physical infrastructure, intellectual property rights, and support for growth-entrepreneurship. Opportunities should rather be considered as the condition emerging as a combination of the nine more basic institutional conditions. The institutional conditions are related in the way that opportunities can be con- Training and Network Organization in Entrepreneurship in Denmark

139 Effects of framework conditions upon level of entrepreneurship sidered a consequence emerging as a combination of the institutional conditions, not as a straightforward sum of these conditions, but in the way that each condition has a positive effect on opportunities. Indeed, opportunities is positively correlated with each of these nine basic institutional conditions, Table 17.1 (based on 39 developed countries; each correlation is statistically highly significant). A positive correlation of opportunities with an institutional condition means that, typically, a country with a favorable institutional condition provides ample opportunity (and, typically, a country with an unfavorable condition offers few opportunities). Thus, specifically, a country with abundant financial resources provides great opportunities, typically (and a country with poor financial resources offers few opportunities, typically). A country with supportive policies typically has great opportunities (and a country with unsupportive policies typically offers few opportunities). The multiple correlation is the correlation of opportunities with an optimal combination of institutional conditions. Countries with a combination of several favorable institutional conditions tend to have especially great opportunities, and this tendency is quite strong (and those with a combination of several unfavorable institutional conditions tend to have especially few opportunities). Table Correlation of opportunities with each institutional condition Developed societies Financial resources.6 Government policies.6 Public programs.5 Technology transfer.5 Commercial and legal infrastructure.6 Internal market openness.4 Physical infrastructure.6 Intellectual property rights.7 Growth-entrepreneurship.6 Multiple correlation with all nine.8 Opportunities, as a condition, is seen in Table 17.1 to be positively correlated with each of the nine basic institutional conditions, and is highly correlated with a combination of basic institutional conditions (the multiple correlation is much higher than any of the nine correlations). How opportunities are the consequence of a combination of the basic institutional conditions can be ascertained by a regression of opportunities on the conditions. In this regression we keep only those conditions that seem substantively significant. By this modeling, five of the eight conditions seem to matter. Commercial and legal infrastruc- 138 Training and Network Organization in Entrepreneurship in Denmark 2010

140 Effects of framework conditions upon level of entrepreneurship ture has a large effect, a country with extensive commercial and legal infrastructure facilitates opportunities, typically. Internal market openness also matters much, a country with wide openness provides many opportunities, typically. Intellectual property rights seemingly also expand opportunities. Government policies also create opportunities. Physical infrastructure also appears to enhance opportunities. But these various framework conditions go hand in hand with one another, so much that it is hard to disentangle their effects and to estimate the separate effect of each framework condition on opportunities. These estimated effects are shown in Figure 17.1 (statistical details are in the Appendix in Table A17.1). The other institutional conditions have no separately discernible effects, meaning that the data on only 39 developed countries are insufficient to discern their effects, separate from the five discerned effects. The magnitude of an effect is indicated by the thickness of the arrow. Figure Estimated effects upon opportunities from institutional conditions Government policies Commercial and legal infrastructure Internal market openness Opportunities Physical infrastructure Intellectual property rights Having examined how the institutional conditions are interrelated, we shall now examine effects among the cultural conditions. Training and Network Organization in Entrepreneurship in Denmark

141 Effects of framework conditions upon level of entrepreneurship Cultural foundation for education and skills The four cultural conditions education, skills, individualism and esteem which were examined in Chapter 16, are likely to be related as causes and effects. The cultural value a society attaches to individualism is likely to enhance the esteem of the entrepreneurial vocation in the society. Education for the entrepreneurial vocation in the society is likely to be affected by the esteem of the vocation in the society and also by the individualism in society. The education, in turn, expectedly affects the skillfulness of the people in the society. This sequence of effects among cultural conditions will then promote entrepreneurship. The effects among cultural conditions can be estimated, like the effects among the institutional conditions were estimated, by regression analysis. The effect upon esteem from individualism is estimated to be huge (statistical details are in the Appendix in Table A17.2). A society that values individualism also attaches high esteem to the entrepreneurial vocation, typically. The effect upon education for entrepreneurship from individualism is also estimated to be big. A society that values individualism also offers much education in entrepreneurship, typically. Esteem of the entrepreneurial vocation in society, however, has no discernible separate effect upon the education in entrepreneurship provided by the society. That an effect is not discerned is surprising, as a positive effect was expected, but this is probably because esteem is so intertwined with individualism that a separate effect cannot be discerned (it is also difficult to discern effects because the sample of countries is so small, just 39 developed countries, the statistical details are in the Appendix in Table A17.3). Skills are promoted mainly by individualism. A society that values individualism also has a population with extensive entrepreneurial skills, typically. Education also promotes skills, also when controlling for individualism, but this effect is weaker than the effect of individualism. Esteem of the entrepreneurial vocation has no discernible separate effect upon skills of the population (statistical details are in the Appendix in Table A17.4). These effects among the cultural conditions are shown in Figure 17.2, where the thickness of an arrow represents the magnitude of the effect. Figure Estimated effects among cultural conditions Esteem Education Individualism Skills 140 Training and Network Organization in Entrepreneurship in Denmark 2010

142 Effects of framework conditions upon level of entrepreneurship How these cultural conditions, jointly with opportunities, shape entrepreneurship will be examined next. Effects upon entrepreneurship from cultural and institutional conditions The cultural conditions and the opportunities in a society are a framework for commercial entrepreneurship in the society, and their effects upon entrepreneurial activity can be estimated. The level of commercial entrepreneurial activity in a society is here measured by the TEA-index, the rate of early-phase entrepreneurs in the population, as was examined in Chapter 15. First, the association of each condition with entrepreneurial activity is indicated by their correlation, Table Each condition has a correlation with entrepreneurial activity that is positive. Entrepreneurship is even higher correlated with a combination of the five conditions (the multiple correlation is higher than any of the five). Table Correlation of national entrepreneurial activity (TEA) with opportunities and each cultural condition (N = 39 developed societies) Opportunities.5 Individualism.4 Esteem.2 Education.3 Skills.4 Multiple correlation with all five.6 The effect upon entrepreneurship from each condition, while holding the other conditions constant, is estimated by a regression (statistical details are in the Appendix in Table A17.5). Opportunities have a huge effect upon entrepreneurial activity. A society that provides abundant opportunities will also have a high level of entrepreneurial activity, typically, whereas a society with few opportunities will have little entrepreneurial activity. Individualism also has a large effect on entrepreneurial activity. A society that values individualism will also have many entrepreneurs, typically, whereas a society that devalues individualism will have fewer entrepreneurs. Skills also appear to promote entrepreneurship, but the separate effect is much smaller than the effect of opportunities and the effect of individualism. Education also appears to promote entrepreneurship, but the separate effect is also small. Esteem has no discernible separate effect on entrepreneurial activity. These effects are shown in Figure Cultural conditions promote entrepreneurship through several sequences of positive effects. The cultural value attached to individualism directly promotes entrepreneurship and also promotes all the other three cultural conditions: esteem of the entrepre- Training and Network Organization in Entrepreneurship in Denmark

143 Effects of framework conditions upon level of entrepreneurship neurial vocation, the education in entrepreneurship and the entrepreneurial skillfulness of the population. Education promotes skills, so there is an indirect effect of education upon entrepreneurship in the manner that education promotes skills which in turn promote entrepreneurship. Individualism not only directly affects entrepreneurship but also has indirect effects through education and skills. Figure Estimated effects upon developed nations entrepreneurship from their cultural and institutional conditions Esteem Education Individualism Skills Entrepreneurship Opportunities The effect of the framework upon entrepreneurship can be graphed by plotting the countries according to their entrepreneurship and to the optimal combination of framework conditions, Figure 17.4, in which an asterix marks a country. The association between the framework conditions and the level of entrepreneurship is obvious, a country with an extensive framework will also have a high level of entrepreneurship, typically, whereas a society with a meager framework will have little entrepreneurial activity. The USA, marked U on Figure 17.4, illustrates the effect. The framework conditions in the USA are extremely extensive, and the overall framework in the USA has been better than in any other country (on average across the years). This framework places the USA at the better end of the horizontal axis in Figure The level of entrepre- 142 Training and Network Organization in Entrepreneurship in Denmark 2010

144 Effects of framework conditions upon level of entrepreneurship neurship in the USA is among the highest among the developed countries, this entrepreneurship places the USA very high up on the vertical axis. Denmark, marked D in Figure 17.4, is around in the middle in its framework and is also around the middle in its entrepreneurial activity. Figure Plot of developed societies according to their combined framework conditions (horizontal axis) and their entrepreneurship (TEA, vertical axis) 16 * * * * * 10 U * * * * ** * * * * * * * * * * * * * * * * * * D * * * * * * * Training and Network Organization in Entrepreneurship in Denmark

145 Effects of framework conditions upon level of entrepreneurship In conclusion, in developed societies, both the cultural and the institutional framework conditions greatly promote entrepreneurial activity in discernable ways, cultural conditions enhance the entrepreneurial skills of the population and basic institutional conditions create opportunities for the population to bring their skills into entrepreneurship. This tight coupling between framework and entrepreneurship in developed societies is illustrated by the USA. The American framework has apparently been better than in the other countries (on the whole during the last decade), and consequently the level of entrepreneurship in the USA has also been among the highest among the developed countries. Denmark also displays this tight coupling between framework and level of entrepreneurship. Denmark has a level of entrepreneurship that has been about typical for the developed countries (Chapter 15; on the whole during the last decade), and Denmark has a framework that is about typical (Chapter 16). This is easily understood. When the country has a framework that is about typical, then we also predict the resulting level of activity to be about typical. 144 Training and Network Organization in Entrepreneurship in Denmark 2010

146 Chapter 18. Conclusion: Training and network organization bring comparative advantages Training creates human capital in the heads and minds of people, who then as entrepreneurs utilize their human capital to pursue, select and nurture networks and take advantage of resources embedded in their networks, which thus are a form of capital, social capital. The human capital thereby goes into the entrepreneurs creation of social capital, from which they may gain a comparative advantage. The study has been about training shaping human capital that goes into the creation of social capital which brings comparative advantages. I have investigated people s learning through their education in entrepreneurship, their training in starting a business, and their networking through which they may learn, and investigated how people s learning expands their involvement in entrepreneurship and how entrepreneurs learning and networking expands their innovation, exports and expectations for growth. Students moving into entrepreneurship Students, as one segment of the population in Denmark, were in focus when I examined the students training and involvement in entrepreneurship (Chapter 3). Training to start a firm denotes instruction and other acquisition of knowledge and skills about starting a business. Training of therefore comprises instruction through formal education, receipt of knowledge alongside education (i.e. outside, but during education). Training also refers to learning upon finishing formal education (but that was not considered in the chapter about students, but was considered in the subsequent chapters). Training thus occurs in several contexts, partly because entrepreneurial training is growing and expanding in society and partly because entrepreneurial competencies are so diverse and complex. Education is like a column of building blocks, where learning in each block builds upon earlier blocks of learning. Training for entrepreneurship can also be considered as modules where the early modules may mainly instill motivation for innovation and for starting a firm, later modules may mainly develop creativity, opportunity-awareness and risk-willingness, and even later modules may mainly teach skills. The questions in Chapter 3 were, Are students frequently trained to start a business? Are students mostly trained within their education or mostly alongside their education? Is training often socially inherited, dependent on their parents education and occupation? Is training in education mainly theoretical or mainly practical? Does training often enhance motivation and competency to innovate and start a firm? Training and Network Organization in Entrepreneurship in Denmark

147 Conclusions: Training and network organization bring comparative advantages Do trained students more often than untrained students have entrepreneurial competencies? Do trained students more often than untrained students have attitudes of an entrepreneurial culture? Are trained students more often than untrained students intending to become entrepreneurs and working independently as student-entrepreneurs? Are student-entrepreneurs supported by family, friends and schools? Roughly half of the students (age 15 and older) have been trained to start a firm. The trained students have typically been trained within their education, and less often alongside their education. Training tends to be socially inherited, that is, training depends on the parents education and occupation, namely in the ways that students whose fathers had neither vocational nor higher education are more likely to get training that students whose fathers have a vocational education or a higher education, and students with self-employed parents are more likely to get training than students whose parents are employees. The training provided within education is typically mostly theoretical, rather than practical. Still, the training tends to enhance both motivation and ability to innovate and to start a business. Trained students, more often than untrained students, have entrepreneurial competencies. Trained students also especially often have attitudes of an entrepreneurial culture. Trained students, more often than untrained students, intend to become entrepreneurs. Trained students also more often start to work independently, and thereby they become student-entrepreneurs. The student-entrepreneurs are usually supported by both family and friends, but less often by their schools. The population and its training Having focused on the students as a segment of the population in Denmark, I broadened the perspective to examine the population and its training in entrepreneurship. People in the adult population may be trained like students and may also be trained upon finishing their schooling; in particular, they may get on-the-job-training during more or less formalized apprenticeship. The questions in Chapter 4 were, Are people frequently trained? Is people s training typically coupled with education? The analyses of people s training show that less than half of the population (age years) is trained. Training has been acquired mostly within education, and a substantial portion of people has been trained in more than one context. Training is unlikely to be uniform throughout the population. Likelihood of training may depend on personal background such as gender, age and extent of education. The questions in Chapter 5 were, Are people trained equally frequently in the genders and ages, or does likelihood of training depend on gender and age? Is people s training coupled with education in the same way for the genders and ages, or does coupling depend on gender and age? Is people s extent of training tightly coupled to education, in the way that the more education people have the more training they tend to have. 146 Training and Network Organization in Entrepreneurship in Denmark 2010

148 Conclusions: Training and network organization bring comparative advantages We would expect that training depends on gender in the way that more of the men than of the women have been trained because entrepreneurship is traditionally a male vocation. We would expect that training depends on age in the way that more of the young than of the older have been trained because training in schools has been expanding during recent decades. We would expect training to be coupled to education as a positive correlation, in the way that the more education people have the more training they tend to have. The analyses show that training to some degree is shaped by personal background characteristics, namely gender, age and extent of education. Gender affects training in the way that men get more training than women, also when controlling for age and education, but this gender effect is rather small. Age affects training in the way that young are more trained than older, also when holding gender and education constant, and this age effect is stronger than the gender effect. Education affects training, in the way that the more education people get the more training they tend to get. This effect of education is stronger than the effects of age and gender. Training to start a business may involve becoming motivated to start, assimilating entrepreneurial cultural orientations, honing awareness of opportunities, becoming able to evaluate ideas, and learning to commit, organize, plan and execute. Training does not in one shot train all these competencies. First people may be trained in some things, and then later return for further training in other things. It is therefore important to know whether training is typically a once-in-a-lifetime experience, or whether people trained in one context are especially likely to return for further training. The question of whether people trained in one context have high odds of returning for further training in another context is therefore a series of questions, addressed in Chapter 6, Do people trained in one part of their schooling have high odds of becoming trained later in their schooling? Do people trained within education have high odds of becoming trained alongside education? Do people trained within education have high odds of becoming trained upon completion of education? Do people trained alongside education have high odds of becoming trained upon completion of education? We would expect that training begets training in every way, and that the odds for returning for further training are high. The analyses show that people who are trained in one context are especially likely to return for further training in another context. Training is neither a one-shot experience and then avoided nor something that occurs at random, but is something like a spiral of returning, training begetting training, with a recurrence of training at a higher level. The learning from the training is considered, what the trained youngsters have acquired and learnt during their training, and also the benefits of training. The questions in Chapter 7 were, Is training within education mostly theoretical or mostly practical? Does training typically enhance motivation and ability to innovate and start a business? Does training benefit people in their jobs and in some occupations more than in others? Training and Network Organization in Entrepreneurship in Denmark

149 Conclusions: Training and network organization bring comparative advantages The analyses of the content of the training, what people acquire and learn during training, and also its usefulness, show that training within education is typically theoretical and not practical (practical learning is probably more frequently acquired in training upon completion of education), that training typically enhances motivation and ability to innovate and start a business, and that training frequently benefits people in their jobs, especially in entrepreneurial occupation but often also in employment and other occupations. From the focus on trained youngsters I again broadened the perspective to the population to examine people s competencies for entrepreneurship, and differences in competencies of trained persons and untrained persons. The questions in Chapter 8 were, Are competencies distinguishing entrepreneurs from non-entrepreneurs? Have competencies in the population been changing during the last decade? Are competencies dependent on personal background such as gender, age and education? Are trained persons more competent than untrained persons? We would expect certain competencies to be common among entrepreneurs and far less prevalent among non-entrepreneurs, perhaps even rare, so that the competencies distinguish entrepreneurs from non-entrepreneurs. We would also expect that competencies in the population have been increasing because of the increasing training in entrepreneurship. Competencies expectedly depend on gender in the way that males have more entrepreneurial competencies than women do, partly because males get more training than women do. Competencies expectedly depend on education in the way that highly educated persons have more entrepreneurial competencies than less educated persons. These expected associations are of course merely formulations of hypotheses, which are more or less plausible and subject to testing. The analyses of entrepreneurial competency in the population show that entrepreneurial competency is multidimensional, encompassing at least four aspects - upstartcompetency, opportunity-awareness, risk-willingness and role-modeling which are distinct. Peoples entrepreneurial competency is greatly strengthened by training, and also promoted by education, apart from training. Competency is also affected by age, in the way that older tend to be more competent than younger people. Competency is also related to gender, in the way that men more than women report competency. Training is not just training competencies but is also shaping an entrepreneurial culture in the minds of the trained people. Culture refers to the things that are valued in society, the things that people attach value to. To the extent entrepreneurship is valued in society, the culture is entrepreneurial and society has an entrepreneurial culture. The concept of culture thus applies to society. The culture in a society may change over time, it may become increasingly entrepreneurial. Policies in Denmark and around the world aim at changing the culture, and to make it increasingly and pervasively entrepreneurial. The concept of culture can also be applied more narrowly when things are highly valued in part of society and less valued in another part of society, and we then call this a subculture. Thus, we may possibly find that a society does not have an entrepreneurial culture but has an entrepreneurial subculture. Policies aiming at changing the culture may succeed in creating an entrepreneurial subculture within one part of society, spe- 148 Training and Network Organization in Entrepreneurship in Denmark 2010

150 Conclusions: Training and network organization bring comparative advantages cifically the young generation, but not in other parts of society. The questions in Chapter 9 were, Is the culture in Denmark changing in the direction of an entrepreneurial culture? Is an entrepreneurial subculture prevailing within a gender, specifically among men? Is an entrepreneurial subculture prevailing within an age-group, specifically the young? Is an entrepreneurial subculture prevailing within an educational group, specifically those with vocational secondary education? Is an entrepreneurial subculture prevailing among the trained people? We would expect that the culture in Denmark has become more entrepreneurial in recent years. But we also expect that culture is not uniform, but that there may well be an entrepreneurial subculture among men, in the young generation, among those with vocational secondary education, and among those who have been trained to start a business. The analyses of entrepreneurial competency in the population show that entrepreneurial culture is multidimensional, encompassing at least four values the value of a career as entrepreneur, the value of status based on success, the value of inequality and the value of stories in the media and these four values are quite distinct. Peoples assimilation of entrepreneurial culture is on the whole not systematically related to gender and neither to education. The value attached to entrepreneurial culture is promoted by training, and also increases with age, but the effects of training and age are small. Entrepreneurial culture is thus surprisingly homogenously spread out across various segments of the population, i.e. across both genders, across educational levels, and fairly much across ages and also fairly much across trained and untrained people. Training affects careers. There may be a tight coupling between and education and an occupation. For example, learning to work with electrical installations is a vocational education in the form of apprenticeship with schooling, the learner is an electrician-apprentice who then graduates as a skilled craftsman and becomes an electrician who can be self-employed and work independently in the occupation of electricians who are certified by their education. This education and occupation are coupled tightly in so far as the education is a necessary and sufficient condition for the occupation. Another example is the coupling between Ph.D. education and research as an occupation; this education and occupation have a coupling that is tight to the extent most youngsters with this education become researchers and most researchers have this education. Such tight coupling often defines a profession. Entrepreneurship is not a profession in so far as entrepreneurs are not educated or trained in entrepreneurship. Policies, however, are aiming to professionalize entrepreneurship, to tighten the coupling between the entrepreneurial occupation and the entrepreneurial training. The questions in Chapter 10 were, Do trained people much more frequently than untrained people become entrepreneurs? Do entrepreneurs much more frequently than non-entrepreneurs have training? Trained people more often than untrained people become entrepreneurs, as was naturally expected, and entrepreneurs more often than non-entrepreneurs have received training, so there is a coupling between training and entrepreneurship. However, the coupling is not tight; rather, the coupling is loose. The chance or odds that trained per- Training and Network Organization in Entrepreneurship in Denmark

151 Conclusions: Training and network organization bring comparative advantages sons are entrepreneurs are nearly twice the odds that untrained persons are entrepreneurs. In other words, the chance or odds that entrepreneurs are trained are nearly twice the odds that non-entrepreneurs are trained. These odds are not much greater than 1, so the coupling is rather loose. Training affects careers and, in turn, may have consequences for their income. Training to start a firm often makes the trained persons more motivated and competent to innovate and start a firm, and is often beneficial in work, not only in self-employment but also in employment. So we would also expect that training often increases income. I hypothesized a tendency that the more training people have received, the higher is their income. So the question in Chapter 11 was, Does people s training increase their income? Analysis shows that training has an effect on income which is positive. People who are trained tend to get considerably higher income than people who are not trained. The more people have been trained the more income they tend to get, and the increase is considerable. This additional income is distinct for training, and cannot be due to the other characteristics gender, age, education and occupation which are held constant or controlled for. Entrepreneurs and their network organization Having considered the population and its training, I then focused on the entrepreneurs, specifically on the kind of organization they create, a network organization. Entrepreneurs intending to start a business, or starting a business, or running an established business depend on and utilize many kinds of resources. An important resource is knowledge, both in the form of past learning from their education and experience and ongoing in the form of advice from their environment. Entrepreneurs get advice from advisors, a narrow or wide circle of advisors drawn from various spheres in the life of the entrepreneur. The entrepreneur s relations with these advising persons are called the entrepreneur s network of advisors or advice network. The network is an organization around the entrepreneur. It is the assembly-line where the entrepreneur assembles information and other resources that go into the entrepreneurial work, but it is less orderly and planned than an ordinary assembly-line. The assembly is more like bricolage. The organization of this network, the network organization, and the way it is organized around the entrepreneur, are expectedly important and consequential for the entrepreneurial work. The network organization is conceptualized as the organization of the work and flow of resources and information around the entrepreneur. This network organization has organizational properties such as size and a department-like configuration in the form of spheres for acquisition of resources. The network is where the resource of information is embedded and acquired in the form of advice, as a social capital. This conceptualization of the network organization draws on the traditions of research on organizations focusing on resource dependency and on information processing, where performance is contingent on acquisition of information and other resources and capacity for processing them. The network organization around an entrepreneur has several properties that may be 150 Training and Network Organization in Entrepreneurship in Denmark 2010

152 Conclusions: Training and network organization bring comparative advantages important and consequential. These organizational properties of the network around a person are conceptualized. The property, that has attracted most attention, is size, size of the network around the person. Size is theorized to be important because it connotes the volume of resources or information that the person may obtain. Such information or resources can bring benefit and is therefore a kind of capital, denoted social capital, and is social because the resources are embedded in the network and thus the benefit or comparative advantage is reaped in the social environment. The person invests in creating and maintaining the network and can mobilize it to bring advantage and reap a profit when the benefit exceeds the investment. The size of an entrepreneur s network has been found to bring benefit, I found earlier, specifically for survival, profit and growth, and also for innovation, exporting and growth-expectation. The organization of the network, in its qualities apart from size, may also bring advantage. Certain kinds and configurations of relations tend to bring advantage. Social capital may reside in networks that reach across a wide spectrum of kinds of contacts, networks that have weak ties to contacts, networks that have dense relations among the contacts, networks that confer autonomy on the actor, and networks that have disconnects or holes among the contacts, rather than being dense. The organization of the network, and not only its size, were also examined here. The organization of the network around an entrepreneur was conceptualized in terms of the salience of spheres of the environment from where the advisors are drawn. The questions in Chapter 12 were, How is the network organized? What are the spheres in the environment around an entrepreneur which gives advice on the business? How is salience of a sphere shaped by the national culture? Entrepreneurs have networks of different sizes. Some report that they did not get advice from anybody, and some reported to use more than a dozen advisors. On average, the entrepreneurs used about a handful of advisors. But the entrepreneurs actually differ very much from one another in the sizes of their networks. The environment around an entrepreneur is not homogenous, but is more or less divided into somewhat distinct and separate spheres or departments. An often distinguished sphere is the family sphere comprising ancestors and descendent, relatives in between ancestors and descendent, and some joined by marriage. The sphere itself is not homogenous and we speak about close family and more distant relatives, indicating that it has no definite boundary. Such spheres are sources of resources for the entrepreneur. The resources in one sphere may be unique to that sphere. Analyses revealed five spheres in the network organization around an entrepreneur, the private sphere of family and friends the job sphere of boss and coworkers the professional sphere of accountant, lawyer, banker, the market sphere of collaborators, competitors, suppliers and customers the entrepreneurship sphere of mentors, public service advisors, investors, contacts abroad, people who have come from abroad, researchers and inventors. These spheres are likely to give different kinds of advice. The private sphere is likely to give support or discouragement. The job sphere may serve as sounding board. The professional sphere offers codified knowledge. The market sphere may provide information Training and Network Organization in Entrepreneurship in Denmark

153 Conclusions: Training and network organization bring comparative advantages about business opportunities. The entrepreneurial sphere may convey tacit knowledge about entrepreneurship. Some entrepreneurs get advice mainly from the private sphere, other entrepreneurs seek more in the job sphere, other entrepreneurs search more in the professional sphere, other entrepreneurs rely more on the market sphere, while yet other entrepreneurs more pursue the entrepreneurial sphere. For an entrepreneur, some spheres are highly salient, while other spheres are less salient. For an entrepreneur, the salience of each sphere depends on national context. The more secular-rationalistic (and less traditional) the culture is, the less salient the private sphere, but the more salient the job sphere, the professional sphere, the market sphere and the entrepreneurship sphere. The spheres and other properties of the network around an individual depend not only on characteristics of the national context but also on characteristics of the individual. The question of how the network organization is shaped by characteristics of the individual entrepreneur can be elaborated as a series of specific questions, addressed in Chapter 13, Is size of the network around an entrepreneur dependent on the entrepreneur s training, gender, age, education and phase in the entrepreneurial process? Is salience of each sphere in the network around the entrepreneur affected by the entrepreneur s training, gender, age, education and phase? The analyses show how the network organization is shaped by attributes of the entrepreneurs. Size of the network is greatly enhanced by training. Size of the network is also affected by the phase, in the way that the network is smaller in the intending phase than in the starting phase. Training enhances salience of the professional sphere and salience of the market sphere. The private sphere is especially salient for entrepreneurs who are females, young and in the intending phase. The network organization and its organizational properties are thus the consequence of certain conditions, both cultural and individual. In turn, the network organization has consequences for entrepreneurial work, specifically performance. The aspects of performance are here innovation, exporting and growth-expectation of entrepreneurs. Then the issues are how these performance aspects are affected by the organizational properties of the network. Specifically, the questions in Chapter 14 were, Is innovation affected by size of the network and salience of the spheres in the network? Is exporting affected by size of the network and salience of the spheres in the network? Is growth-expectation affected by size of the network and salience of the spheres in the network? We might expect that network size enhances each dimension of performance; at least this is the traditional idea about the effect of networking. But, going beyond orthodoxy, we may expect that networking in certain spheres will enhance performance. Specifically, I hypothesized that salience of the entrepreneurial sphere and salience of the market sphere will enhance performance. Analyses show that the network organization affects performance, specifically innovation, exporting and growth-expectation. Size of the network enhances exporting and growth-expectation, and salience of the market sphere and salience of the entrepreneurship sphere promote innovation. 152 Training and Network Organization in Entrepreneurship in Denmark 2010

154 Conclusions: Training and network organization bring comparative advantages Society and its framework conditions affecting its entrepreneurship The changing level of entrepreneurship in Denmark and other societies is considered. Chapter 15 addressed the issues, Is the trend in the level of entrepreneurship upward, stable or downward? How does the level in Denmark compare to the levels in other societies? By all our several measures, the level of commercial entrepreneurial activity in Denmark declined during the economic crisis , and the level in 2010 is less than the level was just a few years before. However, the leading indicator of interest in pursuing entrepreneurial activity, the rate of prospective starters with an intention of starting within a few years, has increased substantially in 2010, and predicts, albeit with much uncertainty, an increase in rates of starting new businesses in the next few years. Has entrepreneurial activity in other countries also declined? Very large declines in entrepreneurial activity have occurred in Hong Kong, Portugal, Australia, Serbia, Spain and Denmark, followed by Croatia, Italy and USA. Conversely, there have actually been considerable increases in entrepreneurial activity in many other countries, despite the economic recession. Evidently, the economic recession hit especially hard in Denmark. This decline in activity in Denmark has also been felt by those who started or operated business around 2009 when we asked them about their perceptions. Danish entrepreneurs reported that the global economic crisis made it harder to start, worsened business opportunities and reduced their growth-expectations. The Danish entrepreneurs experienced such hardships more often than entrepreneurs in other countries. Where does this bring Denmark in comparison to other developed countries in the level of entrepreneurial activity? Denmark is currently below the middle among the developed countries in the level of entrepreneurial activity, by all our measures. Denmark was hovering somewhere around the middle among the developed countries for several years before the economic crisis hit in 2008, but since 2008 Denmark has dropped well below the middle. To understand why entrepreneurial activity in a country is at a certain level, we can consider the national framework conditions for entrepreneurship. The national conditions for entrepreneurship are examined; we track trends in Denmark and make comparisons to other societies in the national framework of conditions for entrepreneurship. Specifically, Chapter 16 answered the questions, Are cultural and institutional conditions in Denmark improving or deteriorating? How does the framework in Denmark compare to the framework in other societies? Over the years several of the Danish framework conditions have become more favorable and are more favorable today than some years ago, notably the cultural framework conditions. Some of the Danish framework conditions, however, have also been declining in recent years, during the economic recession, notably several institutional framework conditions. Where does this improvement bring Denmark compared to other countries? Most of the Danish framework conditions are rather close to the typical situation for developed countries, and rank around the middle among the developed countries. Several conditions are much more favorable in Denmark than typical among the developed countries. Conversely, a few conditions are less favorable in Denmark than typical among the de- Training and Network Organization in Entrepreneurship in Denmark

155 Conclusions: Training and network organization bring comparative advantages veloped countries. So, overall, the framework in Denmark is a little better than is typical for the developed countries. These framework conditions affect entrepreneurship in the various countries. Specifically, Chapter 17 addressed the questions, How, within a nation, are the cultural conditions affecting one another? How, within a nation, are the institutional conditions interrelated? How are the cultural and institutional conditions affecting entrepreneurship? In developed societies, both the cultural and the institutional framework conditions greatly promote entrepreneurial activity in discernable ways, cultural conditions enhance the entrepreneurial skills of the population and basic institutional conditions create opportunities for the population to bring their skills into entrepreneurship. This tight coupling between framework and entrepreneurship in developed societies is illustrated by the USA. The American framework has apparently been better than in the other countries (on the whole during the last decade), and consequently the level of entrepreneurship in the USA has also been among the highest among the developed countries. Denmark also displays this tight coupling between framework and level of entrepreneurship. Denmark has had a level of entrepreneurship that has been about typical for the developed countries (on the whole during the last decade), and Denmark has had a framework that has been about typical (on the whole during the last decade). This is easily understood. When the country has a framework that is about typical, then we also predict the resulting level of activity to be about typical. Human capital from training is invested in networks embedding social capital In conclusion, the coupling between training and networking is an investment of human capital in social capital which brings returns, comparative advantages. Training creates human capital, especially entrepreneurial competences in the minds of the trained persons. This training-based human capital brings a comparative advantage in the way that trained persons get higher income than untrained persons. Furthermore, entrepreneurs invest their training-based human capital in the creation of social capital in the way that trained entrepreneurs create networks that are especially large and resourceful in that the market sphere and the professional sphere in their networks are especially salient. This training-based social capital brings comparative advantages in the way that salience of the market sphere enhances innovation and in the way that large networks enhance exporting as well as growth-expectation. 154 Training and Network Organization in Entrepreneurship in Denmark 2010

156 Appendix with technical specifications Chapter 5 on People s training shaped by personal background: gender, age and education brings Figure 5.3 showing effects on training from gender, age and education. The figure summarizes a multiple linear regression of training, measured by number of contexts, on the three independent variables, Table A5.1. The standardized coefficients are used for the thickness of the arrows in the figure. The standardized coefficient for education shows a positive effect of education on training, which is the strongest effect. The standardized coefficient for age shows a negative effect of age upon training, which is less strong that the effect of education. The standardized coefficient shows an effect of gender, namely that males get more training than females, but this gender effect is weaker than the effects of age and education. Table A5.1. Training (number of contexts) affected by gender, age and education Linear regression. N = R 2 =.05 Independent variable Measurement Regression coefficient Standardized regression coefficient P-value Gender Female 0; Male Age Logarithm of years Education Scale 0 to Constant 1.22 If training is measured not as a numerical variable, but as a binary variable, trained versus untrained, effects can be estimated by a logistic regression, and they turn out to be similar to those estimated in the above linear regression: a gender effect by which being male rather than female increases the probability of being trained, age decreases the probability of being trained, and education increases the probability of being trained. Chapter 8 on People s competencies enhanced by training brings Figure 8.1 showing how entrepreneurial competency is affected by four characteristics training, education, gender and age. The figure summarizes the regression analysis in Table A8.1. The thickness of the arrows accords with the standardized regression coefficients. Training and Network Organization in Entrepreneurship in Denmark

157 Appendix with technical specifications Table A8.1. Competency affected by training, gender, age and education Linear regression. N = R 2 =.10 Independent variables Measurement Regression coefficients Standardized regression coefficients P-value Training Number of contexts Education Scale 0 to Gender Female 0; Male Age Log of years Constant.14 Chapter 9 on People s culture shaped by training brings Figure 9.1 showing how entrepreneurial culture is affected by training and age and not affected by education and gender. The figure summarizes the regression analysis in Table A9.1. The thickness of the arrows accords with the standardized regression coefficients. Table A9.1. Culture affected by training, gender, age and education Linear regression. N = R 2 =.01 Independent variables Measurement Regression Standardized P-value coefficients regression coefficients Training Number of contexts Education Scale 0 to Gender Female 0; Male Age Log of years Constant.35 Chapter 13 on Network organization shaped by the entrepreneur s training and background brings Figure 13.1 showing how size of network is affected by the entrepreneurs training and phase but unaffected by education, age or gender. The figure summarizes the regression in Table A Training and Network Organization in Entrepreneurship in Denmark 2010

158 Appendix with technical specifications Table A13.1. Size of entrepreneurs networks, affected by gender, age, education, training and phase The phase of starting is the frame of reference that each other phase is compared to. Linear regression. R 2 =.10. N = 288 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Gender Women 0; men Age Logarithm of years Education Scale Training Number of contexts of training Phase of intending 1 intending; * 0 otherwise Phase of own-man. 1 owning-man.; otherwise Constant.39 Chapter 13 also brings Figure 13.2 showing how salience of spheres in the network around an entrepreneur is affected by the entrepreneur s attributes, namely training, gender, age, education and phase. The figure summarizes Tables A13.2, A13.3, A13.4 and A13.5. Table A13.2 shows that salience of the private sphere is affected by gender in that way that the private sphere is less salient for male entrepreneurs than for female entrepreneurs, also when holding constant the other characteristics (the gender effect is significant as indicated by the small p-value in the table). Salience of the private sphere is negatively affected by age; the family sphere is less salient for older than for younger entrepreneurs, probably because young entrepreneurs often get advice from their parents (the age effect is significant, as indicated by the small p-value in the table). Salience of the private sphere is not affected by education, and not affected by training (when holding the other characteristics constant). Phase affects salience of the private sphere in the way that the private sphere seems more salient in the phase of intending than in the phase of starting (the effect is marginally significant). Training and Network Organization in Entrepreneurship in Denmark

159 Appendix with technical specifications Table A13.2. Salience of private sphere in the networks around entrepreneurs, affected by their gender, age, education, training and phase The phase of starting is the frame of reference that each other phase is compared to. Linear regression. R 2 =.05. N = 288 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Gender 0 for women; * 1 for men Age Logarithm of years Education Scale Training Number of contexts Phase of intending 1 intending; * 0 otherwise Phase of operating 1 operating; otherwise Constant 4.25 Table A13.3. Salience of professional sphere in the networks around entrepreneurs, affected by their gender, age, education, training and phase The phase of starting is the frame of reference that each other phase is compared to. Linear regression. R 2 =.04. N = 288 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Gender 0 for women; for men Age Logarithm of years Education Scale Training Contexts of training * Phase of intending 1 intending; otherwise Phase of operating 1 operating; otherwise Constant Training and Network Organization in Entrepreneurship in Denmark 2010

160 Appendix with technical specifications Table A13.4. Salience of market sphere in the networks around entrepreneurs, affected by their gender, age, education, training and phase The phase of starting is the frame of reference that each other phase is compared to. Linear regression. R 2 =.04. N = 288 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Gender 0 for women; for men Age Logarithm of years Education Scale Training Number of contexts * of training Phase of intending 1 intending; otherwise Phase of own-man. 1 owning-man.; otherwise Constant.42 Table A13.5. Salience of entrepreneurship sphere in the networks around entrepreneurs, affected by their gender, age, education, training and phase The phase of starting is the frame of reference that each other phase is compared to. Linear regression. R 2 =.03. N = 288 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Gender 0 for women; for men Age Logarithm of years Education Scale Training Number of contexts * of training Phase of intending 1 intending; otherwise Phase of own-man. 1 owning-man.; otherwise Constant.38 Training and Network Organization in Entrepreneurship in Denmark

161 Appendix with technical specifications Salience of the job sphere is not affected by any of the characteristics in a statistically significant way, so no table is reported for the job sphere, and no arrows point toward the job sphere in Figure 13.2 in Chapter 13. Chapter 14 on Network organization enhancing innovation, exporting and growthexpectation brings Figure 14.1 showing how size of the network and salience of each sphere affect innovation, exporting and growth-expectation. The figure summarizes Tables A14.1, A14.2 and A14.3. The thickness of the arrows in the figure are given by the standardized regression coefficients. Table A14.1. Innovation, affected by the network, controlling for characteristics of the entrepreneur and the enterprise Linear regression. R 2 =.19. N = 486 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Network size Scale 0 to * Private sphere Scale salience Job sphere salience Scale Professional sphere Scale salience Market sphere Scale * salience Entrepreneurship Scale * sphere s. Gender 0 women; 1 men Age Logarithm of years Education Scale Opportunity 0 need motivated; motivation 1 op.mot. Phase of starting 0 operating; 1 starting Sole proprietorship 0 not sole; 1 sole Owners Log of number of owners Firm age Logarithm of years Firm size Log of number of persons Constant Training and Network Organization in Entrepreneurship in Denmark 2010

162 Appendix with technical specifications Table A14.2. Exporting, affected by the network, controlling for characteristics of the entrepreneur and the enterprise Linear regression. R 2 =.11. N = 469 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Network size Scale 0 to * Private sphere Scale salience Job sphere salience Scale Professional sphere Scale sal. Market sphere Scale salience Entrepreneurship Scale sp.sal Gender 0 for women; 1 for men Age Logarithm of years Education Scale Opportunity 0 need motivated; motivation 1 op.mot. Phase of starting 0 operating; 1 starting Sole proprietorship 0 not sole; 1 sole Owners Log of number of owners Firm age Logarithm of years Firm size Log of number of persons Innovation Scale Constant.70 Training and Network Organization in Entrepreneurship in Denmark

163 Appendix with technical specifications Table A14.3. Growth-expectation, affected by the network, controlling for characteristics of the entrepreneur and the enterprise Linear reg ression. R 2 =.51. N = 444 entrepreneurs Measurement Regression coefficient Standardized regression coefficient P-value *onesided Network size Scale 0 to * Private sphere Scale salience Job sphere salience Scale Professional sphere Scale sal. Market sphere Scale salience Entrepreneurship Scale sp.sal Gender 0 for women; 1 for men Age Logarithm of years Education Scale Opportunity 0 need motivated; motivation 1 op.mot. Phase of starting 0 operating; 1 starting Sole proprietorship 0 not sole; 1 sole Owners Log of number of owners Firm age Logarithm of years Firm size Log of number of persons Innovation Scale Constant.65 Chapters 15 to 17 examine the national level of entrepreneurship, its national framework conditions, and effects of framework conditions on the level of entrepreneurship. The unit of analysis is a developed society. The analyses are on the developed societies, 39 developed societies, including Denmark. The 39 developed societies are actually a fairly large sample of developed societies, the sample is nearly a census of all the developed societies in the world (the developed societies that have not yet participated in GEM are mainly new states in Eastern Europe such as Slovakia, Estonia, Lithuania, 162 Training and Network Organization in Entrepreneurship in Denmark 2010

164 Appendix with technical specifications Ukraine and Belarus). The 39 developed societies are those that have participated in GEM during some or all of the years (listed in Chapter 2). Figure 17.1 in Chapter 17 is based on the regression shown here in Table A17.1. The thickness of the arrows are given by the standardized regression coefficients. Table A17.1. Opportunities shaped by five institutional conditions (the other institutional conditions had no separate discernible effects) Linear regression. R 2 =.62. N = 39 developed societies Standardized regression coefficients P-value (one-sided) Government policies Commercial and legal infrastructure Internal market openness Physical infrastructure Intellectual property rights Figure 17.2 in Chapter 17 is based on the regressions shown here in Tables A17.2, A17.3 and A17.4. The unit of analysis is a developed society. Data are available on all 39 developed societies participating in GEM during some or all of the years (listed in Chapter 2). Table A17.2. Esteem, as affected by individualism Linear regression. R 2 =.73. N = 39 developed societies Standardized Probability-value regression coefficient Individualism one-tailed Table A17.3. Education, as affected by individualism (esteem had no separate discernible effect) Linear regression. R 2 =.31. N = 39 developed societies Standardized Probability-value regression coefficient Individualism.56 0,0001one-tailed Training and Network Organization in Entrepreneurship in Denmark

165 Appendix with technical specifications Table A17.4. Skills, as affected by education and individualism (esteem had no separate discernible effect) Linear regression. R 2 =.73. N = 39 developed societies Standardized regression coefficient Probability-value (one-sided) Education Individualism Figure 17.3 in Chapter 17 is based on the regression shown here in Table A17.5. Entrepreneurial activity is measured by TEA (Chapter 15), with each country s mean across the years Opportunities (and also individualism, skills and education) is measured as the country s mean across the years Table A17.5. Entrepreneurship level, as affected by opportunities, individualism and skills (education and esteem had no separate and discernible effect) Linear regression. R 2 =.28. N = 39 developed societies Regression coefficient Standardized regression coefficient Probability-value (one-tailed) Opportunities Individualism Skills Constant Figure 17.4 in Chapter 17 plots the developed nations according to the predicted TEA in Table A17.5 and the TEA. More precisely, the vertical axis refers to entrepreneurial activity, as measured by TEA (each country s mean across the years ). The horizontal axis refers to the level of TEA predicted by the regression, with the coefficients in Table A17.5, using the expression, Predicted TEA = ,33 * Opportunities +.74 * Individualism +.79 * Skills 164 Training and Network Organization in Entrepreneurship in Denmark 2010

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167 Bibliography Coduras, A., J. Levie, D. Kelley, R.J. Sæmundsson and T. Schøtt, (2010). A Global Perspective on Entrepreneurship Education and Training: A Special Report of the Global Entrepreneurship Monitor. Coleman, J. S., (1988). Social Capital in the creation of human capital. American Journal of Sociology, 94(supplement): S95-S120. Coleman, J. S., (1990). Foundations of Social Theory. Cambridge: Harvard University Press). Coser, R. L., (1975). The complexity of roles as a seedbed of individual autonomy, in L.A.Coser (ed.), The Idea of Social Structure (New York: Harcourt, Brace, Jovanovich): Cubion, (2008). Evaluering af entreprenørskabssøjlen. Danish Enterprise and Construction Authority, (2008) Entrepreneurship Index Entrepreneurship Conditions in Denmark (Copenhagen: Danish Enterprise and Construction Authority). Danish Enterprise and Construction Authority, (2009) Entrepreneurship Index Entrepreneurship Conditions in Denmark (Copenhagen: Danish Enterprise and Construction Authority). Danmarks Statistik, (2005). Generel Erhvervsstatistik. In Statistisk Årbog 2005, Copenhagen, Danmarks Statistik: Drucker, P., (1985). Innovation and Entrepreneurship: Practices and Principles. London: Heinemann. Eckhardt, J. T. and S.A. Shane, (2003). Opportunities and entrepreneurship. Journal of Management, 29(3): Erhvervs- og Boligstyrelsen, (2002). De nye virksomheder 4. statistiske portræt af iværksættere. Copenhagen, Erhvervs- og Boligstyrelsen. Erhvervs- og Byggestyrelsen, (2007). Iværksætterindeks 2007 Vilkår for iværksættere i Danmark. Copenhagen, Erhvervs- og Byggestyrelsen. Erhvervs- og Byggestyrelsen, (2008). Iværksætterindeks 2008 Vilkår for iværksættere i Danmark. Copenhagen, Erhvervs- og Byggestyrelsen. Erhvervs- og Byggestyrelsen, (2009). Iværksætterindeks 2009 Vilkår for iværksættere i Danmark. Copenhagen: Danish Enterprise and Construction Agency Training and Network Organization in Entrepreneurship in Denmark 2010

168 Bibliography Erhvervs- og Byggestyrelsen, (2010). Iværksætterindeks 2010 Vilkår for iværksættere i Danmark. Copenhagen: Danish Enterprise and Construction Agency. Eurostat, (2005). Business demography in Europe results from 1997 to Statistics in Focus, vol. 36. Forbes, D. P., (2005). Are Some Entrepreneurs More Overconfident Than Others, Journal of Business Venturing, 20(5), pp Freeman, L. C. and D. Ruan, (1997). An international comparative study of interpersonal behavior and role relationships. L Année Sociologique, 47: GERA (Global Entrepreneurship Research Association), (2011). Global Entrepreneurship Monitor s (GEM) homepage. Gilbert, B. A., P.P. McDougall & D.B. Audretsch, (2006). New Venture Growth: A Review and Extension, Journal of Management, 32(6), pp Granovetter, M., (1973). The strength of weak ties, American Journal of Sociology, 78: Granovetter, M., (1983). The strength of weak ties: A network theory revisited, In R. Collins (ed.), Sociological Theory, 1983 (San Francisco: Jossey-Bass): Hancock, M., K. Klyver and T. Bager, (2001). Global Entrepreneurship Monitor, Danish National Executive Report Copenhagen, Erhvervsfremmestyrelsen. Hancock, M. and T. Bager, (2002). Global Entrepreneurship Monitor, Danish National Executive Report Odense, Odense University Press. Hancock, M. and T. Bager, (2003). Global Entrepreneurship Monitor, Danish National Report Copenhagen, Børsens Forlag. Hancock, M. and T. Bager (eds.), (2004). Global Entrepreneurship Monitor, Denmark Copenhagen, Børsens Forlag. Hart, D.M., (2003). Entrepreneurship policy What it is and where it came from. In D. M. Hart (ed.) The emergence of entrepreneurship policy Governance, start-ups, and growth in the U.S. knowledge economy, New York, Cambridge University Press: Hoffmann, A., L.B. Larsen, P. Nellemann and N.V. Michelsen, (2005). Quality Assessment of Entrepreneurship Indicators, FORA Report vol. 14. Copenhagen, Ministry of Economics and Business Affairs Division for Economic and Business Research. Training and Network Organization in Entrepreneurship in Denmark

169 Bibliography Inglehart, R. and C. Welzel, (2005). Modernization, Cultural Change and Democracy. New York: Cambridge University Press. Inglehart, R. World Values Survey. < > Kelley, D., N. Bosma and J.E. Amoros, (2011). Global Entrepreneurship Monitor Global Report. Kirzner, I. M., (1976). The Economic Point of View: An Essay in the History of Economic Thought. Kansas City, Sheed and Ward. Knoke, D. and R.S. Burt, (1983). Prominence. Applied Network Analysis: A Methodological Introduction, edited by Ronald S. Burt and Michael J. Minor. (Beverly Hills: Sage Publications), Lee, S. M. and S.J. Peterson, (2000). Culture, entrepreneurial orientation, and global competitiveness. Journal of World Business, 35(4): Lepoutre, J., W. van den Berghe, O. Tilleuil and H. Crijns, (2010). A new approach to testing the effects of entrepreneurship education among secondary school pupils. (Ghent: Vlerick Leuven Ghent Management School). Working Paper Series 2010/01. Lin, N. and B. Erickson, (2008). Social Capital: An International Research Program. (Oxford: Oxford University Press). Lundstrom, A. and L. Stevenson, (2005). Entrepreneurship policy: theory and practice. New York, Springer. Ministeriet for Videnskab, Udvikling og Teknologi; Kulturministeriet; Undervisningsministeriet; og Økonomi- og Erhvervsministeriet, (2009). Strategi for uddannelse i entreprenørskab. Morrison, A., (2000). Entrepreneurship: What triggers it? International Journal of Entrepreneurial Behavior & Research, 6(2): Mueller, S. L. and A.S. Thomas, (2000). Culture and entrepreneurial potential: a nine country study of locus and control and innovativeness. Journal of Business Venturing, 16(1): Nakata, C. and K. Sivakumar, (1996). National culture and new product development: an integrative review. Journal of Marketing, 60(1): Nordic Council of Ministers, (2010). Nordic Entrepreneurship Monitor. (Copenhagen: Nordic Council of Ministers). 168 Training and Network Organization in Entrepreneurship in Denmark 2010

170 Bibliography OECD, (2008). Entrepreneurship Review of Denmark. Paris, OECD, Directorate for Science, Technology and Industry. Peterson, R.A., (1980). Entrepreneurship and organization. In Nystrom, P.C. and W. H. Starbuck (eds.) Handbook of organizational design, vol. 1, Oxford, Oxford University Press. Pfeffer, J. and G. Salancik, (1978). The External Control of Organizations. New York: Harper & Row. Porter, M. E., (1991). Towards a dynamic theory of strategy. Strategic Management Journal. 12: Reynolds, P., N. Bosma, E. Autio, S. Hunt, N. de Bono, I. Servais, P. Lopez-Garcia and N. Chin, (2005). Global Entrepreneurship Monitor: Data collection design and implementation Small Business Economics, 24: Sarasvathy, D., H. Simon and L. Lave, (1998). Perceiving and Managing Business Risks: Differences Between Entrepreneurs and Bankers, Journal of Economic Behavior and Organization, 33(2), pp Schumpeter, J. A., (1934). The Theory of Economic Development. Schøtt, T., (2005a). Entrepreneurial activity in a country: index constructions. Schøtt, T., (2005b). Iværksætterkulturen i Danmark og andre lande analyse via Global Entrepreneurship Monitor. In Søgaard, V., S.G. Svendsen, S.B. Bruun og C. Høyer (eds.) Årsrapport 2004/2005 Center for Småvirksomhedsforskning, Kolding, University of Southern Denmark, Centre for Small Business Studies: Schøtt, T., (2005c). Undervisning i iværksætteri i Danmark og i andre lande analyse via Global Entrepreneurship Monitor. In Søgaard, V., S.G. Svendsen, S.B. Bruun og C. Høyer (eds.) Årsrapport 2004/2005 Center for Småvirksomhedsforskning, Kolding, University of Southern Denmark, Centre for Small Business Studies: Schøtt, T., (2006). Entrepreneurship in Denmark 2005 studied via Global Entrepreneurship Monitor. Kolding, University of Southern Denmark, Centre for Small Business Studies. Schøtt, T., (2007). Entrepreneurship in the Regions in Denmark 2006 studied via Global Entrepreneurship Monitor. Kolding, University of Southern Denmark, Centre for Small Business Studies. Training and Network Organization in Entrepreneurship in Denmark

171 Bibliography Schøtt, T., (2008). Growth-Entrepreneurship in Denmark 2007 studied via Global Entrepreneurship Monitor. Kolding, University of Southern Denmark, Center for Entrepreneurship and Small Business Studies. Schøtt, T., (2009). Education, Training and Networking for Entrepreneurship in Denmark 2008 studied via Global Entrepreneurship Monitor. Kolding: University of Southern Denmark, Centre for Entrepreneurship and Small Business Studies. Schøtt, T., (2010). Social and Commercial Entrepreneurship in Denmark 2010 studied via Global Entrepreneurship Monitor. Kolding: University of Southern Denmark. Schøtt, T., (2010). Socialt og kommercielt iværksætteri i Region Syddanmark. CESFO Rapport. Kolding: University of Southern Denmark, Centre for Entrepreneurship and Small Business Studies. Schøtt, T., (2010). Modtagelighed for innovation i befolkningens hverdagsliv og arbejdsliv. In P.V.Freytag, K.W.Jensen, K.Klyver and K.B.Munksgaard (eds.) Årsrapport 2010 Center for Entreprenørskab og Småvirksomhedsforskning. Kolding: University of Southern Denmark, Centre for Small Business Studies: Schøtt, T. and J. Christensen, (2005). Iværksætteres kompetenceudvikling kurser i Vejle Amt. In V. Søgaard, S.G. Svendsen, S.B. Bruun and C. Høyer (eds.) Årsrapport 2004/2005 Center for Småvirksomhedsforskning, Kolding, University of Southern Denmark, Centre for Small Business Studies: Schøtt, T. and K.W. Jensen, (2007). Knopskydning i og omkring danske virksomheder Follow-up på Global Entrepreneurship Monitor. In T. Bager, M.R. Evald and C. Vintergaard (eds.) Iværksætterne og de etablerede virksomheder, Copenhagen, Børsens Forlag: Schøtt, T. and K.W. Jensen, (2009). The Coupling between Entrepreneurship and Public Policy: Tight in Developed Countries but Loose in Developing Countries. Estudios de Economia, 35(2): Schøtt, T. and K. Klyver, (2006). Markedet for råd efterspørgslen fra iværksættere og udbuddet fra rådgivere. In Bager, T., P.R. Christensen, H. Neergaard and S.G. Svendsen (eds.) Iværksætterrådgivning i Danmark, Copenhagen, Børsens Forlag: Schøtt, T. and H. Ottósson, (2009). Entreprenørers træning i entreprenørskab: effekten på foretagsomhed In Bager, T., and S.L. Nielsen (eds.) Entreprenørskab og kompetencer. Copenhagen: Børsens Forlag: Selvstændighedsfonden, (2008). Entreprenørskab i undervisningen Training and Network Organization in Entrepreneurship in Denmark 2010

172 Bibliography Shane, S., (1992). Why do some societies invent more than others? Journal of Business Venturing, 7(1): Shane, S., (1993). Cultural influences on national rates of innovation. Journal of Business Venturing, 8(1): Shane, S., (2003). A General Theory of Entrepreneurship: The Individual-opportunity Nexus. Cheltenham, Edward Elgar. Smallbone, D. and F. Welter, (2001). The role of government in SME development in transition economies. International Small Business Journal, 19(4): Storey, D. J., (1994). Understanding the Small Business Sector, Routledge. Strangler, D., (2009). The Economic Future just Happen, Kauffman Foundation. Sundbo, J., (1998). The Theory of Innovation: Entrepreneurs, Technology and Strategy, Mass, Edward Elgar. Swedberg, R. (ed.), (2000). Entrepreneurship: The Social Science View. Oxford, Oxford University Press. Thomas, A. S., and S.L. Mueller, (2000). A case for comparative entrepreneurship: Assessing the relevance of culture. Journal of International Business Studies, 31(2): Tiessen, J. H., (1997). Individualism, collectivism and entrepreneurship: a framework for international comparative research. Journal of Business Venturing, 12(5): Warhuus, J. P., (2000). Global Entrepreneurship Monitor National vurdering af iværksætteraktivitet Copenhagen, Erhvervsfremmestyrelsen. Weber, M., (1930). The Protestant Ethic and the Spirit of Capitalism. London, Allen and Unwin. Wennekers, S., A. Van Stel, R. Thurik, and P. Reynolds, (2005). Nascent entrepreneurship and the level of economic development, Small Business Economics, 24(3), pp Wickham, P., (2006). Strategic Entrepreneurship, Pearson Education Limited. Training and Network Organization in Entrepreneurship in Denmark

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174 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Angola Universidade Católica de Angola (UCAN) Manuel Alves da Rocha Salim Abdul Valimamade Banco de Fomento Angola (BFA) SINFIC Sistemas de Informação Industriais, S.A. Sociedade Portuguesa de Inovação (SPI) Argentina Center for Entrepreneurship, IAE Business School Universidad Austral Augusto Medina Douglas Thompson Sara Medina João Rodrigues Nuno Gonçalves Silvia Torres Carbonell Aranzazu Echezarreta Juan Martin Rodriguez Center for Entrepreneurship, IAE Business School, Universidad Austral MORI Argentina Banco Santander Rio Australia Australian Centre for Entrepreneurship Research, Queensland University of Technology Belgium Vlerick Leuven Gent Management School Bosnia and Herzegovina Entrepreneurship Development Centre Tuzla (in partnership with University of Tuzla) Per Davidsson Michael Stuetzer Paul Steffens Marcello Tonelli Jan Lepoutre Hans Crijns Miguel Meuleman Bahrija Umihanic Rasim Tulumovic Sladjana Simic Mirela Arifovic Boris Curkovic Esmir Spahic Admir Nukovic Subsecretaría de Desarrollo Económico, Ministerio de Desarrollo Económico Gobierno de la Ciudad de Buenos Aires Queensland University of Technology Policy Research Centre Entrepreneurship and International Entrepreneurship, Flemish Government Federal Ministry of Development, Entrepreneurship and Crafts Municipality of Tuzla Ministry of Education, Science, Culture and Sports of Tuzla Canton Q&A Market Research Dedicated Research PULS d.o.o. Sarajevo Training and Network Organization in Entrepreneurship in Denmark

175 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT CIES Internacional Bolivia Universidad Católica Boliviana/ Maestrías para el Desarrollo Brazil IBQP Instituto Brasileiro da Qualidade e Produtividade Marco Antonio Fernández C. Gover Barja Gonzalo Chavez Simara Maria de S.S. Greco Romeu Herbert Friedlaender Jr. Joana Paula Machado Eliane Cordeiro de Vasconcellos Garcia Duarte FAUTAPO SOBOCE S.A. CAF Embajada de Dinamarca USAID/Proyecto Productividad y Competitividad Bolivia Universidad Católica Boliviana FUNDAPRO AVINA-RBE Serviço Brasileiro de Apoio às Micro e Pequenas Empresas SEBRAE Serviço Nacional de Aprendizagem Industrial - SENAI / PR Bonilha Comunicação e Marketing S/C Ltda. [email protected] Chile Universidad del Desarrollo José Ernesto Amorós Carlos Poblete Serviço Social da Indústria SESI / PR Universidade Federal do Paraná UFPR InnovaChile de CORFO Opina S.A. [email protected] Regional Teams: Arica y Parinacota Univ. de Tarapacá Vesna Karmelic Área Emprendimiento, Liderazgo y TIC s de la Universidad de Tarapacá Tarapacá Corporación Privada para el Desarrollo de la Univ. Arturo Prat Mauricio Vega Gobierno Regional de Tarapa Antofagasta Univ. Católica del Norte Gianni Romaní Universidad Católica del Norte, DGIP. Gobierno Regional, Agencia Regional Desarrollo Productivo. 174 Training and Network Organization in Entrepreneurship in Denmark 2010

176 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Atacama Agencia Regional de Desarrollo Productivo Atacama Omar Gonzalez CORFO, Agencia regional de Desarrollo Productivo. Coquimbo Univ. Católica del Norte Karla Soria Universidad Católica del Norte, Valparaíso Univ. Técnica Federico Santa María Cristóbal Fernández Robin Jorge Cea Valencia Juan Tapia Departamento de Industrias y Centro de Ingeniería de Mercados, CIMER, de la Univ. Técnica Federico Santa María El Mercurio de Valparaíso Metro politana Univ. Mayor Cristina Betancour Universidad Mayor Libertado Bernardo O Higgins Corporación de Desarrollo Pro O Higgins Braulio Guzmán, Aracelly Tapia Corporación de Desarrollo Pro O Higgins Maule Univ. Católica del Maule Andrés Valenzuela, Alejandro Sottolichio Universidad Católica del Maule Bío-Bío Univ. Católica de la Santísima Concepción Jorge Espinoza UCSC-Facultad de Ciencias Económicas y Adminitrativas Univ. del Desarrollo José Ernesto Amorós Carlos Poblete UDD-Facultad de Economía y Negocios. Araucanía Univ. de la Frontera INCUBATEC Gerardo Lagos China Tsinghua University SEM Gao Jian Qin Lan Jiang Yanfu Cheng Yuan Li Xibao Dirección de Innovación y Transferencia Tecnológica de la Universidad de La Frontera SEM Tsinghua University SINOTRUST International Information & Consulting (Beijing) Co., Ltd. [email protected] qinl2.04@ sem.tsinghua.edu.cn Training and Network Organization in Entrepreneurship in Denmark

177 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Colombia Universidad del Norte Pontificia Universidad Javeriana Cali Liyis Gómez Núñez Piedad Martinez Carazo César Figueroa Fernando Pereira Alberto Arias Universidad del Norte Pontificia Universidad Javeriana Cali Universidad de los Andes Universidad Icesi Centro Nacional de Consultoría Universidad de los Andes Raúl Fernando Quiroga Rafael Augusto Vesga Diana Carolina Vesga Universidad Icesi Costa Rica Asociación Incubadora Parque Tec (PARQUE TEC) Rodrigo Varela Villegas Luis Miguel Álvarez Juan David Soler Libreros Marcelo Lebendiker Fainstein Petra Petry Banco Interamericano de Desarrollo / FOMIN IPSOS Central America [email protected] [email protected] Universidad de Costa Rica (UCR) Rafael Herrera González GTZ / Programa Desarrollo Económico Sostenible en Centroamérica (DESCA) Cámara de Industrias de Costa Rica (CICR) Guillermo Velásquez López Banco Centroamericano de Integración Económica (BCIE) [email protected] Fundación CRUSA [email protected] Croatia J.J. Strossmayer University in Osijek Slavica Singer Natasa Sarlija Sanja Pfeifer Suncica Oberman Peterka Djula Borozan Asociación Incubadora Parque Tec Ministry of Economy, Labour and Entrepreneurship SME Policy Centre CEPOR, Zagreb J.J. Strossmayer University in Osijek Faculty of Economics, Osijek Puls, d.o.o., Zagreb [email protected] 176 Training and Network Organization in Entrepreneurship in Denmark 2010

178 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Catinet Denmark University of Southern Denmark Ecuador Escuela Superior Politécnica del Litoral (ESPOL) ESPAE Graduate School of Management Egypt The British University in Egypt (BUE) Egyptian Junior Business Association (EJB) Middle East Council for Small Businesses and Entrepreneurship, (MCSBE) Finland Turku School of Economics, University of Turku Thomas Schøtt Torben Bager Kim Klyver Hannes Ottossen Kent Wickstrom Jensen Majbrit Rostgaard Evald Suna Løwe Nielsen Mick Hancock Mette Søgaard Nielsen Virginia Lasio Ma. Elizabeth Arteaga Guido Caicedo Hala Hattab David Kirby Amr Gohar Mohamed Ismail Sherin El-Shorbagi Lois Stevenson Khaled Farouq Anne Kovalainen Pekka Stenholm Tommi Pukkinen Jarna Heinonen France EMLYON Business School Olivier Torres Danielle Rousson Germany Leibniz University of Hannover and Federal Employment Agency (BA) Institute for Employment Research (IAB) Ghana Institute of Statistical, Social and Economic Research, University of Ghana Rolf Sternberg Udo Brixy Christian Hundt Arne Vorderwülbecke Ernest Aryeetey George Owusu Paul W. K. Yankson Robert Osei Kate Gough Thilde Langevang Foundation for Entrepreneurship Escuela Superior Politécnica del Litoral (ESPOL) Survey Data Industrial Modernization Center, Ministry of Trade & Industry Ministry of Employment and the Economy Turku School of Economics, University of Turku Survey Data AC Nielsen Taloustutkimus Oy Caisse des Depots CSA Federal Employment Agency (BA) Institute for Employment Research (IAB) Zentrum fuer Evaluation und Methoden (ZEM), Bonn wigeo.uni-hannover.de Danish Research Council Training and Network Organization in Entrepreneurship in Denmark

179 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Datapower SA Greece Foundation for Economic and Industrial Research (IOBE) Guatemala Francisco Marroquín University Hungary University of Pécs, Faculty of Business and Economics George Mason University Indiana University Stavros Ioannides Aggelos Tsakanikas Stelina Chatzichristou Hugo Maúl Mónica de Zelaya David Casasola Georgina Tunarosa Lisardo Bolaños Irene Flores Fritz Thomas Jaime Diaz László Szerb Zoltán J. Ács Attila Varga József Ulbert Gábor Márkus Attila Petheö Dietrich Péter Siri Terjesen Foundation for Economic and Industrial Research (IOBE) Francisco Marroquín University OTKA Research Foundation theme number K George Mason University University of Pécs, Faculty of Business and Economics Pablo Pastor [email protected] Szocio-Gráf Piac-és Közvélemény-kutató Intézet [email protected] Iceland Reykjavik University Rögnvaldur J. Sæmundsson Hannes Ottóson Iran University of Tehran Abbas Bazargan Caro Lucas Nezameddin Faghieh A.A. Moosavi-Movahedi Leyla Sarfaraz A. Kordrnaeij Jahangir Yadollahi Farsi M.Ahamadpour Daryani S. Mostafa Razavi Mohammad Reza Zali Mohammad Reza Sepehri Ireland Dublin City University Paula Fitzsimons Colm O Gorman Budapest Corvinus University, Doctorol School of Business Széchenyi University, Doctoral School of Regional- and Economic Sciences Reykjavik University Capacent Gallup [email protected] Iran s Ministry of Labour and Social Affairs Iran s Labour and Social Security Institute (LSSI) Dr. Mohammad Reza Zali [email protected] Enterprise Ireland IFF paula@fitzsimons-consulting. com 178 Training and Network Organization in Entrepreneurship in Denmark 2010

180 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Israel The Ira Center for Business, Technology & Society, Ben Gurion University of the Negev Ehud Menipaz Yoash Avrahami Miri Lerner Yossi Hadad Miri Yemini Dov Barak Harel Yedidsion The Ira Center for Business, Technology & Society, Ben Gurion University of the Negev Sami Shamoon College of Engineering The Brandman Institute Italy EntER - Bocconi University Jamaica University of Technology, Jamaica James Hayton Giovanni Valentini Girjanauth Boodraj Vanetta Skeete Mauvalyn Bowen Joan Lawla Marcia McPherson- Edwards Horace Williams Advanced Technology Encouragement Centre (ATEC) in the Negev College of Business and Management, University of Technology, Jamaica Japan Keio University Takehiko Isobe Venture Enterprise Center Ministry of Economy, Trade and Industry Korea Jinju National University Sung-sik Bahn Sanggu Seo Kyung-Mo Song Dong- hwan Cho Jong-hae Park Min-Seok Cha Latvia The TeliaSonera Institute at the Stockholm School of Economics in Riga Olga Rastrigina Anders Paalzow Alf Vanags Vyacheslav Dombrovsky Small and Medium Business Administration (SMBA) Korea Aerospace Industries, Ltd. (KAI) Kumwoo Industrial Machinery, Co. Hanaro Tech Co., Ltd. Taewan Co., Ltd. Target Research giovanni.valentini@ unibocconi.it KOCI Market Research and Data Mining Services Social Survey Research Information Co.,Ltd (SSRI) [email protected] [email protected] Hankook Research Co. [email protected] TeliaSonera AB SKDS [email protected] Training and Network Organization in Entrepreneurship in Denmark

181 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Brima Gallup Macedonia University Ss. Cyril and Methodius Business Start-Up Centre Macedonian Enterprise Development Foundation (MEDF) Malaysia University Tun Abdul Razak Radmil Polenakovik Tetjana Lazarevska Lazar Nedanoski Gligor Mihailovski Marija Sazdevski Bojan Jovanovski Trajce Velkovski Aleksandar Kurciev Bojan Jovanoski Igor Nikoloski Ljupka Mitrinovska Roland Xavier Leilanie Mohd Nor Dewi Amat Sepuan Mohar Yusof Mexico Tecnológico de Monterrey Marcia Campos Arturo Torres Elvira Naranjo Montenegro University of Montenegro Dragan Lajovic Milorad Jovovic Tamara Backovic Stana Kalezic Olja Stankovic Radmila Damjanovic Milos Raznatovic Irena Peric Nada Radovanic Ivana Zecevic Ana Sebek Stevan Karadaglic Miljan Sestovic Macedonian Enterprise Development Foundation (MEDF) National Centre for Development of Innovation and Entrepreneurial Learning (NCDIEL) University Tun Abdul Razak Rehanstat Tecnologico de Monterrey Alduncin y Asociados [email protected] Economic Faculty of Montenegro Investment Development Fund of Montenegro Ministry of Economy Of Montenegro Employment Agency of Montenegro Directorate for Development of Small and Medium-Sized Enterprises Damar DOO Podgorica [email protected] Chamber of Economy Montenegro 180 Training and Network Organization in Entrepreneurship in Denmark 2010

182 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Stratus Netherlands EIM Business and Policy Research Norway Bodø Graduate School of Business Pakistan Institute of Business Administration (IBA), Karachi Palestine The Palestine Economic Policy Research Institute -MAS Jolanda Hessels Chantal Hartog Sander Wennekers André van Stel Roy Thurik Philipp Koellinger Peter van der Zwan Ingrid Verheul Niels Bosma Lars Kolvereid Erlend Bullvåg Bjørn-Willy Åmo Terje Mathisen Eirik Pedersen Sarfraz A. Mian Arif I. Rana Zafar A. Siddiqui Shahid Raza Mir Shahid Qureshi Samir Abdullah Yousef Daoud Tareq Sadeq Muhannad Hamed Alaa Tartir Peru Universidad ESAN Jaime Serida Oswaldo Morales Keiko Nakamatsu Liliana Uehara Ministry of Economic Affairs, Agriculture and Innovation Ministry of Trade and Industry Innovation Norway Kunnskapsparken Bodø AS, Center for Innovation and Entrepreneurship Kunnskapsfondet Nordland AS Bodø Graduate School of Business US Agency for International Development. Centre for Entrepreneurial Development, IBA, Karachi. LUMS, Lahore Babson College, USA Arab Fund for Economic & Social Development Palestinian National Authority (PNA) TNS Gallup Oasis International The Palestine Central Bureau of Statistics (PCBS) Universidad ESAN Imasen Training and Network Organization in Entrepreneurship in Denmark

183 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Portugal SPI Ventures Regional Team: Azores Universidade dos Açores (UAC) SPI Ventures Romania Babes-Bolyai University, Faculty of Economics and Business Administration Russia Saint Petersburg Team Graduate School of Management, Saint Petersburg Moscow Team State University - Higher School of Economics, Moscow Saudi Arabia The National Entrepreneurship Center Alfaisal University Augusto Medina Douglas Thompson Sara Medina João Rodrigues Nuno Gonçalves Gualter Manuel Medeiros do Couto João Crispim Borges da Ponte Nélia Cavaco Branco Matiş Dumitru Nagy Ágnes Györfy Lehel-Zoltán Pete Ştefan Benyovszki Annamária Petru Tünde Petra Szerb László Mircea Comşa Ilieş Liviu Szász Levente Matiş Eugenia Olga Verkhovskaya Maria Dorokhina Galina Shirokova Alexander Chepurenko Olga Obraztsova Tatiana Alimova Maria Gabelko Kate Murzacheva Munira A. Alghamdi Hazbo Skoko Norman Wright Ricardo Santa Wafa Al Debasi IAPMEI (Instituto de Apoio às Pequenas e Médias Empresas e à Inovação) FLAD (Fundação Luso- Americana para o Desenvolvimento) Governo Regional dos Açores (Secretaria Regional da Economia) PROCONVERGENCIA Babeş-Bolyai University, Faculty of Economics and Business Administration Graduate School of Management at Saint Petersburg State University State University Higher School of Economics Ministry of Economic Development of Russian Federation The Centennial Fund/ National Entrepreneurship Center GfKMetris (Metris Métodos de Recolha e Investigação Social, S.A.) Metro Media Transilvania Levada-Center [email protected] dumitru.matis@ econ.ubbcluj.ro [email protected] [email protected] [email protected] IPSOS [email protected] 182 Training and Network Organization in Entrepreneurship in Denmark 2010

184 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT RM PLUS Slovenia Institute for Entrepreneurship and Small Business Management, Faculty of Economics & Business, University of Maribor South Africa The UCT Centre for Innovation and Entrepreneurship, Graduate School of Business, University of Cape Town Spain Regional Teams: Instituto de Empresa Regional Universities: Miroslav Rebernik Polona Tominc Ksenja Pušnik Katja Crnogaj Mike Herrington Jacqui Kew Penny Kew Juan José Güemes Ignacio de la Vega Alicia Coduras Rafael Pampillón Cristina Cruz Rachida Justo Ricardo Hernández April Win Regional Team Directors: Ministry of the Economy Slovenian Research Agency Finance Slovenian Business Daily Swiss South African Cooperation Initiative (SSACI) Services SETA Small Enterprise Development Agency (SEDA) DGPYMES IE Business School Nielsen South Africa gsb.uct.ac.za Instituto Opinòmetre S.L. Andalucía Universidad de Cádiz José Ruiz Navarro Junta de Andalucía Asturias Univ. De Oviedo Enrique Loredo Gob. del Princ. de Asturias Aragón Univ. de Zaragoza Lucio Fuentelsaz Gob. de Aragón Dpto, Industria, Comercio y Turismo Instituto Aragones Fomento Consejo Aragones Cámaras de Comercio. Training and Network Organization in Entrepreneurship in Denmark

185 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Iñaki Peña Basque Country Orkestra Univ. De Deusto Univ. Basque Country Univ. Mondragón. Eusko Ikaskuntza SPRI, Gobierno Vasco Diputación Foral Álava Diputación Foral Bizkaia Diputación Foral Gipuzkoa Fundación Emilio Soldevilla Instituto Opinòmetre S.L. Canary I. Universidad de Las Palmas de Gran Canaria & Universidad de La Laguna Rosa M. Batista Canino La Caja de Canarias Gobierno de Canarias, Promoción Económica y Servicio Canario de Empleo. Fondo Social Europeo Cantabria Univ. De Cantabria Cátedra Pyme de la Universidad de Cantabria. Fco. Javier Martínez Santander Gob. Regional Cantabria. Consejería de Economía y Hacienda. Grupo Sordecan Fundación UCEIF Catalonia Universidad Autónoma de Barcelona Carlos Guallarte Yancy Vaillant Diputació de Barcelona: Àrea de Desenvolupament Econòmic. Generalitat de Catalunya: Departament de Treball. Ceuta Universidad de Granada Lázaro Rodríguez Mª del Mar Fuentes PROCESA C. Valenciana Univ. Miguel Hernández José Mª Gómez Gras Air Nostrum IMPIVA 184 Training and Network Organization in Entrepreneurship in Denmark 2010

186 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Extremadura Fundación Xavier de Salas Univ. De Extremadura Ricardo Hernández Juan Carlos Díaz Junta Extremadura, Univ. De Extremadura, Central Nuclear Almaraz, Sofiex, Arram Consultores, CCOO U.R Extremadura, Urvicasa Caja Rural de Extremadura, Palicrisa Fundación Academica Europea de Yuste. Fomento de Emprendedores, Grupo Alfwonso Gallardo, Infostock Europa Extremadura, Cámara Comercio Cáceres. UGT Extremadura, El Periódico Extremadura, Hoy Diario de Extremadura, Fomento Emprendedores, Infocenter, Ogesa, Hotel Huerta Honda Galicia Confederación de Empresarios de Galicia (CEG) CEEI Galicia, SA (BIC Galicia) Universidad de Santiago de Compostela Araceli de Lucas Confederación Empresarios Galicia (CEG) CEEI Galicia SA (BIC Galicia) Universidad de Santiago de Compostela Madrid City IEBS Iñaki Ortega Caja Madrid Ayuntamiento de Madrid Murcia Univ. de Murcia Antonio Aragón Alicia Rubio Fundación Caja Murcia Consejería de Economía, Empresa e Innovación Instituto Fomento región de Murcia. Centro Europeo de Empresas e innovación de Murcia Univ. Murcia Navarra Centro Europeo de Empresas e Innovación de Navarra Servicio Navarro de Empleo Cristina García Gobierno de Navarra, Servicio Navarro de Empleo Training and Network Organization in Entrepreneurship in Denmark

187 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Sweden Swedish Entrepreneurship Forum Switzerland School of Business Administration (HEG-FR) Fribourg Taiwan National Chengchi University Trinidad and Tobago China Youth Career Development Association Headquarters (CYCDA) Arthur Lok Jack Graduate School of Business, University of the West Indies Tunisia Institut des Hautes Etudes Commerciales - Sousse Pontus Braunerhjelm Ulrika Stuart Hamilton Mikael Samuelsson Kristina Nyström Per Thulin Rico J. Baldegger Andreas A. Brülhart Mathias J. Rossi Patrick E. Schüffel Thomas Straub Sabine Frischknecht Muriel Berger Verena Huber Chao-Tung Wen Chang-Yung Liu Su-Lee Tsai Yu-Ting Cheng Yi-Wen Chen Ru-Mei Hsieh Chung-Min Lo Li-hua Chen Shih-Feng Chou Karen Murdock Miguel Carillo Colin McDonald Faysal Mansouri Lotfi Belkacem Vinnova CECIS Confederation of Swedish Enterprise KTI /CTI (Conferderation s Innovation Promotion Agency) School of Business Administration (HEG-FR) Fribourg Small and Medium Enterprise Administration, Ministry of Economic Affairs Arthur Lok Jack Graduate School of Business, University of the West Indies GTZ Programme d Appui à l Entrepreneuriat et à l Innovation Turkey Yeditepe University Esra Karadeniz Union of Chambers and Commodity Exchanges of Turkey (TOBB) Uganda Makerere University Business School (MUBS) Rebecca Namatovu Warren Byabashaija Arthur Sserwanga Sarah Kyejjusa Wasswa Balunywa Peter Rosa Danish Research Council Makerere University Business School DEMOSKOP pontus.braunerhjelm@ entreprenorskapsforum.se gfs Bern [email protected] NCCU Survey Center [email protected] [email protected] Optima [email protected] Akademetre [email protected] Makerere University Business School [email protected] 186 Training and Network Organization in Entrepreneurship in Denmark 2010

188 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT IFF Research Ltd. United Kingdom Aston University Mark Hart Jonathan Levie Michael Anyadike-Danes Yasser Ahmad Bhatti Aloña Martiarena Arrizabalaga Mohammed Karim Liz Blackford Erkko Autio Alpheus Tlhomole United States Babson College Julio DeCastro I..Elaine Allen Abdul Ali Candida Brush William D. Bygrave Marcia Cole Lisa Di Carlo Julian Lange Moriah Meyskens John Whitman Edward Rogoff Monica Dean Thomas S. Lyons Joseph Onochie Ivory Phinisee Al Suhu Uruguay University of Montevideo Leonardo Veiga Adrián Edelman Pablo Regent Fernando Borraz Alvaro Cristiani Cecilia Gomeza Vanuatu UNITEC Robert Davis Malama Solomona Asoka Gunaratne Judith King Andrina Thomas-Lini Department for Business, Innovation and Skills (BIS) ONE North East Welsh Assembly Government Enterprise UK PRIME Birmingham City Council Aston Business School Hunter Centre for Entrepreneurship, University of Strathclyde Babson College Baruch College University of Montevideo Banco Santander Uruguay AusAID UNITEC New Zealand OpinionSearch Inc. Equipos Mori UNITEC New Zealand Training and Network Organization in Entrepreneurship in Denmark

189 National Teams in 2010 in Global Entrepreneurship Monitor Team Institution National Team Members Financial Sponsors APS Vendor CONTACT Zambia University of Zambia Francis Chigunta Valentine Mwanza Moonga Mumba Mulenga Nkula GEM Global Coordination Team Kristie Seawright Mick Hancock Yana Litovsky Chris Aylett Jackline Odoch Marcia Cole Jeff Seaman Niels Bosma Alicia Coduras Danish Research Council Department of Development Studies, University of Zambia 188 Training and Network Organization in Entrepreneurship in Denmark 2010