csss: entrepreneur and small business support in csi insights from trialogue’s 2012/13

UWC Colloquium

Monday 15th September

GEM in 1997

GEM in 2014

GEM Study

• Most authoritative and informative study in the world

• Used by policy makers in planning small business policies

• GEM studies individuals, their profile and characteristics such as

perceptions, attitudes, aspirations and intentions

• Fledgling businesses that have not yet started

• New business start-ups

• Established business owners

What makes GEM Unique?

GEM Measures

•TEA…early-stage entrepreneurial activity

- nascent

- new businesses

•GEM distinguishes between

- opportunity

- necessity

- age

- gender

GEM Objectives

• To measure differences in the levels of entrepreneurial activity

between countries

• To uncover factors leading to the enhancement and hindrance of

entrepreneurship

• To suggest policies that may enhance the national level of

entrepreneurship

Total entrepreneurial activity rates in GEM countries, 2013

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Alg

eria

India

Lib

ya

Iran

Vie

tnam

Phili

ppin

es

Bots

wan

a

Ang

ola

Ug

an

da

Gh

an

a

Mala

wi

Nig

eria

Zam

bia

Suri

na

me

Ru

ssia

Mala

ysia

Mace

do

nia

Cro

atia

Pola

nd

Slo

vakia

Hu

ng

ary

Ro

ma

nia

Bosnia

Sou

th A

fric

a

Gu

ate

mala

Lithu

ania

Esto

nia

La

tvia

Ja

ma

ica

Ch

ina

Uru

gu

ay

Mexic

o

Arg

en

tina

Bra

zil

Tha

iland

Pan

am

a

Peru

Co

lom

bia

Ch

ile

Indo

ne

sia

Ecu

ado

r

Ita

ly

Ja

pa

n

Fra

nce

Belg

ium

Ge

rman

y

Spa

in

Fin

lan

d

Gre

ece

No

rwa

y

Slo

venia

Kore

a

Un

ited

Kin

gdo

m

Cze

ch R

ep

ub

lic

Taiw

an

Sw

itze

rla

nd

Port

ug

al

Sw

eden

Pue

rto

Ric

o

Lu

xe

mb

ou

rg

Irela

nd

Ne

the

rla

nds

Isra

el

Sin

gap

ore

Ca

na

da

US

A

Trinid

ad

& T

ob

ag

o

Factor-driven economies Efficiency-driven economies Innovation-driven economies

Relative rankings, 2002 - 2013

Year

SA’s TEA ranking SA’s TEA rate Median Number of positions

above/ below median

2002 20th out of 37

countries

6.3 19 1 below

2003 22nd out of 31

countries

4.3 16 6 below

2004 20th out of 34

countries

5.4 17 3 below

2005 25th out of 34

countries

5.2 17 8 below

2006 30th out of 42

countries

5.3 21 9 below

2008 23rd out of 43

countries

7.8 22 1 below

2009 35th out of 54

countries

5.9 27 8 below

2010 27th out of 59

countries

8.9 30 3 above

2011 29th out of 54

countries

9.1 27 2 below

2012 22nd out of 69

countries

7.3 9.6 12 below

2013

35th out of 67

countries

10.6 10.3 1 above

Perceptions of good opportunities &

capabilities in the adult population, 2001 -

2013

Potential entrepreneurs 2001 2005 2009 2013 Ave SSA

Perceive good opportunities 19.7 27.3 35.4 37.8 74.5

Perceive capabilities 30.4 35.2 35.5 42.7 78.9

2003 2005 2009 2013 Ave SSA

Entrepreneurial intentions 12.2 10.7 13.3 15.4 58.3

Good career choice 48.0* 55.2 63.7 74.0 77.8

High status to successful entrepreneurs 48.0 56.0 64.0 74.7 80.2

Media attention for entrepreneurship 47.5 54.4 63.9 78.4 77.5

Entrepreneurial attitudes in SA towards

entrepreneurial intentions, 2003-2013

Opportunity – and necessity-driven entrepreneurship in

SA, 2001 - 2013

2001 2005 2009 2013 Ave SSA

Necessity-driven (% of TEA) 18.3 39.5 32.7 30.3 38.6 Opportunity-driven (% of TEA) 64.7 57.1 63.7 68.6 57.9 Ration of Necessity vs. opportunity 3.53 1.44 1.94 2.26 1.56

Entrepreneurial activity in South

Africa by gender, 2002 - 2013

2002 2005 2009 2013 Ave SSA

Male - opportunity 3.9 3.4 4.6 8.8 21.7

- necessity 2.2 1.9 2.3 3.3 10.2

- total 7.3 5.9 7.2 12.3 32.4

Female - opportuntiy 2.7 2.1 3.0 5.8 17.3

- necessity 2.6 1.8 1.6 3.1 12.0

- total 5.8 4.5 4.7 9.0 29.9

Motivation for early-stage entrepreneurship by race,

2005 -2013

2005 2009 2013

Black African - opportunity driven 22.9% 49.1% 58.3%

- necessity driven 29.3% 30.1% 27.4%

Coloured - opportuntiy driven 9.3% 3.0% 1.5%

- necessity driven 2.1% 0.6% 1.2%

Indian - opportunity driven 6.4% 1.8% 1.8%

- neccesity driven 3.6% 0.6% 0.9%

Whites - opportunity driven 19.3% 9.7% 7.3%

- necessity driven 3.6% 1.2% 0.9%

2001 2005 2009 2013 Ave SSA

None 0.0 0.0 13.2 5.1 30.1

Some secondary 45.5 42.5 29.9 33.4 30.6 Secondary degree 43.2 44.6 42.5 48.2 23.9

Post secondary 11.3 12.9 14.4 13.3 15.5

Distribution of educational levels for TEA in South Africa,

2001 -2013

Youth findings

“Where I live working

for the government

is the best way to

earn a good living”.

67%

of the youth

agree with

this statement

“Young adults

that start

their own

business

have to work

too hard for

little money”.

61%

of the

youth

agree with

these

statements

“Young adults

start their

own

business

because

they cannot

find a job”.

TEA

Male 13.1%

Female 8.9%

40%

Believe a

young

woman’s

primary

responsibility

is to start and

maintain a

family

34% Believe men

should earn more than

women and that young

women are disadvantaged

in starting a business due

to religious and or cultural

beliefs

Policy

Necessity

-Driven

businesse

s

High-growth

businesses

Opportunity-

driven

businesses

Policy

Necessity-

Driven

businesses

High-growth

businesses

Opportunity

-driven

businesses

Policy

Necessity-

Driven

businesses

High-

growth

businesses

Opportunity-

driven

businesses

• Poor quality with respect to primary and secondary education

• High drop out rate with respect to education

• Extremely low levels of students taking maths & sciences

• Poor quality of maths and science education

• Low levels of potential and intentional entrepreneurs

• Low levels of conversion from early-stage business to

established businesses

• High business failure rates

• High levels of corruption & nepotism

• High levels of crime

• Credibility in eyes of overseas investors

• Unemployment & underemployment

Challenges facing South Africa, 2014