Presentation by Maria Wishart at ISBE 2019

1. Maria Wishart Maria.Wishart@wbs.ac.uk
Stephen Roper Stephen.Roper@wbs.ac.uk
Halima Jibril Halima.Jibril@wbs.ac.uk
Resilience in under-represented
entrepreneurs and their
businesses
14 November 2019

2. Background
Small businesses that are led by entrepreneurs from under-
represented groups experience lower turnover and higher
failure rates than their counterparts (ERC, 2018)
Ethnic-led small businesses in London are 15% more likely to
have experienced a crisis than non-ethnic-led (Wishart, Roper
and Hart, 2018)
Research questions:
What is the relationship between an SME leader’s resilience and that
of their firm?
How does this vary in firms led by under-represented groups (ethnic
and female)?

3. Theoretical framework
1. Resilience research in an SME context
• Link between leader resilience and firm performance (Ayala &
Manzano, 2014; Fisher et al, 2016)
• Firm resilience linked to social capital (Baron & Markman,
2000) strategic diversity (Conz et al, 2015) and
resourcefulness (Powell & Baker, 2011) of leader
• SME characteristics influence firm resilience, e.g., age of firm
(Herbane, 2015), size of firm (Hammock, 2015), ownership of
premises (Dahlhamer & Tierney, 1998), sector (Jaaron &
Backhouse, 2014) & location (Doern et al, 2016)
• No studies that overtly link individual and firm resilience: lack
of agreed measure for firm resilience

4. Theoretical framework
2. Manager characteristics & firm risk management practices
• Optimistic CEOs make different financial decisions (Graham et
al, 2013); overconfidence impacts negatively on investment
decisions, amplified in men (Barber & Odean, 2001)
• Married managers more risk averse (Roussanov & Savor,
2013)
• Religion influences risk appetite of leaders (Noussair et al,
2013)
• Age and educational attainment of leaders are correlated with
firms’ policies (Bertrand & Schoar, 2003)
• Cross-country differences in risk attitude observed (Ferreira,
2018)

5. Hypothesis development
H1: The individual resilience level of a small business leader will predict
the likelihood of their firm to plan for adversity.
H2: The effect of individual resilience on planning for adversity is higher
for females.
H3: The effect of individual resilience on planning for adversity is higher
for ethnic minority individuals.
H4: The effect of individual resilience on planning for adversity varies
with national context i.e. country.
H5: The effect of individual resilience on planning for adversity varies
with geographical location i.e. low income or medium income area.

6. Data and methods
• Data set of 901 small businesses with between 3 and 99 employees, 516
based in London, 385 based in Frankfurt.
• Information on firm level characteristics and strategies, and individual
characteristic of the business leaders, including resilience score
• Dependent variable: Presence of resilience planning - indicator variable
equal to one if the business has a formal strategy for dealing with
adversity, and zero otherwise.
• Main independent variable: Individual leader resilience - Connor-
Davidson Resilience Scale (CD10), a ten-item measure of individual
resilience, gives a score of 0 to 40.
• Control variables: individual and firm level factors that might influence the
probability that a business has formal plans for dealing with adversity

7. Descriptive Statistics- Main variables
London sample Frankfurt sample
Variable N Mean Std. Dev. Variable N Mean Std. Dev.
Resilience planning 516 0.64 0.48 Resilience planning 385 0.61 0.49
CD10 516 31.42 5.73 CD10 385 32.11 5.13
Female 516 0.48 0.50 Female 385 0.45 0.50
Ethnic minority 516 0.30 0.46 Ethnic minority 385 0.26 0.44
Deprived region 516 0.51 0.50 Deprived region 385 0.50 0.50
Firm size 516 2.41 1.15 Firm size 385 2.39 1.18
External advice 516 0.52 0.50 External advice 385 0.40 0.49
Family owned 516 0.45 0.50 Family owned 385 0.48 0.50
External network membership 516 0.26 0.44 External network membership 385 0.77 0.42
Experience 516 0.46 0.50 Experience 385 0.39 0.49
Leader age 516 3.71 1.25 Leader age 385 4.19 1.09
Degree 516 2.47 1.22 Degree 385 0.57 0.50

8. Empirical model
We estimate the following Probit model for business resilience
planning
𝑌𝑖 = 𝛽0 + 𝛽1 𝐶𝐷10𝑖 + 𝛽2 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠𝑖 + 𝜀𝑖 … … . . (1)
• where 𝑌𝑖 is a dummy variable equal to 1 if a business has formal
procedures for planning for adversity, and zero otherwise.
• 𝐶𝐷10 is the Connor-Davidson 10-point scale that captures the
resilience of individual business leaders,
• 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠 is a vector of leader-specific and business-specific control
variables
• We apply sampling weights to improve representativeness

9. Results - main model (selected variables)
LONDON FRANKFURT
CD10 0.013 CD10 0.004
(2.99)*** -0.82
Female -0.117 Female -0.071
(2.42)** -1.3
Ethnic minority 0.113 Ethnic minority -0.022
(2.26)** -0.34
Deprived region -0.048 Deprived region 0.09
-1.02 (1.73)*
Firm size 0.032 Firm size 0.042
-1.41 (1.77)*
Turnover 0.026 Turnover 0.001
(2.04)** -0.6
External advice 0.081 External advice 0.062
(1.72)* -1.16
Founder managed 0.014 Founder managed -0.102
-0.27 (1.75)*
Family owned -0.011 Family owned 0.007
-0.22 -0.13

10. Results - moderating effects
(main coefficients of interest)
LONDON FRANKFURT
Gender
Ethnic
minority
Deprived
region
Gender
Ethnic
minority
Deprived
region
CD10-female 0.021 CD10-female 0.005
(3.24)*** -0.68
CD10-male 0.008 CD10-male 0.004
-1.45 -0.53
CD10-ethnic 0.003 CD10-ethnic 0.013
-0.44 -1.3
CD10-nonethnic 0.019 CD10-non ethnic 0.001
(3.50)*** -0.16
CD10-deprived
region
0.017
CD10-deprived
region
0.005
(2.77)*** -0.66
CD10-not deprived
region
0.01
CD10-not deprived
region
0.004
(1.73)* -0.53

11. Summary of results
H1: The individual resilience level of a small business leader will predict the likelihood
of their firm to plan for adversity. LONDON FRANKFURT
H2: The effect of individual resilience on planning for adversity is higher for females.
LONDON FRANKFURT
H3: The effect of individual resilience on planning for adversity is higher for ethnic
minority individuals. LONDON FRANKFURT
H4: The effect of individual resilience on planning for adversity varies with national
context i.e. country. SUPPORTED
H5: The effect of individual resilience on planning for adversity varies with
geographical location i.e. low income or medium income area. LONDON FRANKFURT

12. Implications
Significant relationship between CD10 and resilience
planning in London but not Frankfurt.
Differences between 2 cities – further research required:
are regulatory or cultural factors at work here?
Gender makes a difference but ethnicity does not –
distinctiveness of these two under represented groups