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The resilience of the entrepreneur. Influence on the success of
the business. A longitudinal analysis
Juan-Carlos Ayala
a,
⇑
, Guadalupe Manzano
b
a
Department of Business Administration, La Rioja University, C/La Cigüeña, 60, 26004 Logroño, Spain
b
Department of Education Sciences, La Rioja University, C/San José de Calasanz s/n, 26004 Logroño, Spain
article info
Article history:
Received 22 November 2013
Received in revised form 2 February 2014
Accepted 7 February 2014
Available online 14 February 2014
JEL classification:
M190
PsycINFO classification:
3120
Keywords:
Longitudinal
Entrepreneur
Gender
Resilience
Small business
Success
abstract
The literature regarding entrepreneurship suggests that the resilience of entrepreneur may
help to explain entrepreneurial success. In this article, we test whether a connection exists
between resilience dimensions and the success of established entrepreneurs in the Spanish
tourism sector, and whether any gender-specific differences exist. Resilience of subjects
was measured 5 years before the follow-up data was collected. The results show that the
three dimensions of resilience (hardiness, resourcefulness and optimism) help to predict
entrepreneurial success. The key factor in predicting the success of the entrepreneur is
resourcefulness. This could be said about both men and women. However, the ability to
predict entrepreneurial success of those who have hardiness and optimism is different
for men and women. The influence of optimism on the success of their businesses is greater
for women than for men.
Ó2014 Elsevier B.V. All rights reserved.
1. Introduction
Successful entrepreneurs establish their business goals and take timely decisions to achieve those goals in increasingly
competitive and uncertain environments. The information available to entrepreneurs is often ambiguous, incomplete or is
constantly changing. In these circumstances, resilient entrepreneurs, who show a high degree of tolerance for ambiguity
and adapt quickly to change, may be better prepared to succeed. Entrepreneurs who have resilience are willing to work hard
to achieve their goals, to adapt to changes in order to take advantage of the new situation and are able to learn from their
mistakes (Cooper, Estes & Allen, 2004; London, 1993).
As suggested in previous studies (Ayala & Manzano, 2010; Markman & Baron, 2003; Markman, Baron & Balkin, 2005;
Stoltz, 2000), resilience could be a key factor in the explanation of entrepreneurial success. However, previous empirical
research has not been conclusive. Perhaps one of the main reasons for this has been the complexity of defining the construct
http://dx.doi.org/10.1016/j.joep.2014.02.004
0167-4870/Ó2014 Elsevier B.V. All rights reserved.
⇑
Corresponding author. Address: Departamento de Economía y Empresa, Universidad de La Rioja, C/La Cigüeña, 60, 26004 Logroño, Spain. Tel.: +34 941
299374; fax: +34 941 299393.
E-mail addresses: juan-carlos.ayala@unirioja.es (J.-C. Ayala), guadalupe.manzano@unirioja.es (G. Manzano).
Journal of Economic Psychology 42 (2014) 126–135
Contents lists available at ScienceDirect
Journal of Economic Psychology
journal homepage: www.elsevier.com/locate/joep
of resilience (Luthar, Cicchetti & Becker, 2000) which has created considerable challenges when developing an operational
definition of resilience.
Although several instruments have been used to measure resilience, there are only a few instruments intended to assess
resilience in adults (Connor & Davidson, 2003; Karairmak, 2010; Windle, Bennert & Noyes, 2011). In this study, we use the
Spanish adaptation of the Connor–Davidson Resilience Scale (CD-RISC) (Connor & Davidson, 2003). This instrument was
developed using a representative sample of entrepreneurs and presents very good psychometric properties (Manzano &
Ayala, 2013).
Resilience is a dynamic adaptation process that allows entrepreneurs to continue to look towards the future despite harsh
market conditions, and despite the destabilizing events they must continually face. Resilience is the capacity an entrepre-
neur has in order to overcome particularly difficult circumstances. This capacity for adaptation and ‘‘bouncing back’’ in
the face of adversity depends on the individual’s resources and their interaction with the environment (Windle et al.,
2011). Resilience changes over time and can be developed and encouraged (Brewer & Hewstone, 2004). It is therefore rea-
sonable to assume that the resilience of the entrepreneur changes as a result of their business requiring them to adjust their
strategies and to develop skills for coping with different kinds of situations with optimism and courage. The predictive valid-
ity of resilience could then be called into question: does resilience have any predictive validity? The only way to find out if
resilience has any predictive validity is through longitudinal studies in which the dependent and independent variables are
kept apart (Hansemark, 2003; Ward, 1993).
The researchers have demonstrated that differences in personal characteristics between men and woman could influence
the success of their businesses (Boden & Nucci, 1999; Danes et al., 2009; Danes, Stafford & Loy, 2007). On the other hand, the
investigations into the relation between resilience and gender differences are not conclusive. Campbell-Sills, Forde & Stein
(2009) encountered significant differences between the degree of resilience shown by men and women. However, Burns and
Anstey (2010) or Karairmak (2010) have shown that there are no differences in the degree of resilience based on gender.
Therefore, another research question arises: if the resilience has a predictive validity on the success of the entrepreneurs,
is gender a discriminating factor in the predictive validity of resilience? To answer this question we again need to conduct
longitudinal studies in which the measurement values of individual resilience are collected before measuring the success of
the business.
2. Resilience of the entrepreneur and business success
Resilience refers to the human ability to adapt in the face of tragedy, trauma and other adversity (Bonanno, 2004; Connor
& Davidson, 2003; Newman, 2005). Resilience is used to characterise individuals who are able to easily and quickly overcome
setbacks related to their life and career aspirations (Zautra, Hall & Murray, 2010). Resilience is an important quality for entre-
preneurs (Sutcliffe & Vogus, 2003). Resilience is the result of the interaction between entrepreneurs and their environment.
It is a dynamic and evolving process through which entrepreneurs acquire the knowledge, abilities and skills to help them
face the uncertain future with a positive attitude, with creativity and optimism, and by relying on their own resources. Entre-
preneurs are resilient when faced with adverse circumstances and are able to develop and mobilize resources they often did
not suspect they possessed. That is to say, resilience represents a real growth strategy for entrepreneurs.
Resilience is a multidimensional construct that comprises a network of favourable attitudes and behaviours. Resilience
can be thought of as the amalgamation of a range of personal and behavioural qualities rather than a specific characteristic
(Cooper, Estes & Allen, 2004; Lamond et al., 2008). As such, the construct of resilience has always been difficult to define
(Luthar, Cicchetti & Becker, 2000), as difficult as it has been to develop an operational measure of resilience. Although a num-
ber of scales have been developed for measuring resilience, they are not widely validated (Windle et al., 2011). One exception
is the Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003) which has been validated in numerous studies
(Burns & Anstey, 2010; Karairmak, 2010; Lamond et al., 2008). The majority of researchers have demonstrated that the CD-
RISC has a multifactorial structure (Burns & Anstey, 2010; Jorgensen & Seedat, 2008; Karairmak, 2010). Manzano and Ayala
(2013) has shown that resourcefulness, hardiness and optimism are distinct factors in the entrepreneurs’ resilience. Hardi-
ness refers to control of oneself, not to the control of the actions or support of others. It means that the entrepreneurs are not
easily frustrated when facing adverse situations, they are audacious and they fight to achieve their goals (Kobasa, 1979).
Resourcefulness refers to the resources, capabilities and skills the entrepreneur possesses in order to control the various ad-
verse situations they have to face. Resourcefulness implies that the entrepreneurs believe in their own ability to control
events and influence the outcome of situations in which they find themselves in (Powell & Baker, 2011). Another component
of resilience is optimism. It refers to the capacity of the entrepreneur to maintain a positive attitude in difficult circum-
stances, situations where there is great uncertainty regarding the outcomes. It is the capacity of the entrepreneurs to learn
from mistakes and see them as an opportunity rather than a failure (Fredrickson, 2001; Schneider, 2001).
Resilient entrepreneurs have a greater ability to renew themselves over time through innovation and adjust to diverse
and turbulent changes in the environment (Reinmoeller & Baardwijk, 2005). Resilient entrepreneurs have a high degree
of self-esteem, feel they are in control and are not afraid to fail. If this happens, despite adversity, they ‘‘rise again’’ stronger
than before because they have learnt from the situation, because they have experienced and made mistakes, and because
they have been able to change so as to adapt to the new circumstances of their environment (Cannon & Edmondson, 2005).
J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135 127
Stoltz (2000), who studied personal resilience through what he terms the Adversity Quotient (AQ), has demonstrated that
resilience is a major factor underlying success in entrepreneurial settings. Successful entrepreneurs had a significantly higher
AQ score than those who were less successful. In fact, resilience has been argued to be an appropriate measure of entrepre-
neurial success in the early stages of a venture when hard financial indicators are not available or appropriate (Markman
et al., 2005).
Baron and Markman (2003) or Envick (2005) provided additional evidence that resilience is a major factor underlying
success in entrepreneurial settings. Others authors have suggested that entrepreneurial success and performance are a func-
tion of resilience (Hayward, Foster, Sarasvathy & Fredrickson, 2010; Markman & Baron, 2003), achievement motivation, risk-
taking propensity (Stewart, Watson, Carland & Carland, 1999) and the capacity to adapt to and tolerate ambiguity (Bhidé,
2000).
If resilience is believed to be a critical factor in understanding an entrepreneurs’ capacity to sustain the business venture,
it seems logical to assume that entrepreneurs who have more resilience will also be those whose ventures are more success-
ful (Hayward et al., 2010; Stoltz, 2000): it seems logical to assume that resilience positively influences entrepreneurial suc-
cess. For Envick (2005) and Cannon and Edmondson (2005) the said relationship can be sustained by the expected learning
process which supposedly takes place when living through adverse conditions. For Fisher (2011), resilience predicts entre-
preneurial success. Resilience contributes to the explanation of an entrepreneur’s capacity for sustained entrepreneurial ac-
tion and/or in achieving entrepreneurial success.
We know of no previous study that has examined the importance of the resilience of the entrepreneur according to gen-
der differences and its relation to the success of the business. Some studies suggest that gender differences do not help to
explain the degree of resilience of the subjects (Burns & Anstey, 2010; Karairmak, 2010), while others conclude that such
a relationship exists (Liebenberg, Ungar &Van de Vijver, 2012; Merrell, Cohn & Tom, 2011; Reed, Fazel, Jones, Panter-Brick
& Stein, 2012; Tol, Song & Jordans, 2013). On the other hand, regarding the effect of gender on company growth, previous
studies, which have been conducted without taking into consideration the degree of resilience of the subjects, have reported
contradictory results (Cliff, 1998; Du Rietz & Henrekson, 2000; Fairlie & Robb, 2009; Johnsen & McMahon, 2005; Marco,
2012).
Based on the previous literature, we expect resilience factors to predict entrepreneurial success (H1). In addition, we ex-
pect to find that the factors of resilience help to predict the success of businesses run by men as much as they do the success
of businesses run by women (H2).
3. Method
3.1. Sample and data collection
Participants were entrepreneurs operating in the tourist industry in 2008, selected randomly from the SABI (Sistema de
Análisis de Balances Ibéricos -Iberian Balance Sheet Analysis System-,) database, managed by Bureau Van Dyck and Grupo In-
forma S.A. This database contains economic and financial information on 1,250,000 Spanish companies founded since 1996.
The tourist industry was selected for various reasons. First, tourism is the largest service industry worldwide and Spain
occupies a leading position in international tourism. In the last decade, Spain has remained second in the world in terms of
the number of foreign tourists received per year. Spain welcomed more than 57.7 million visitors in 2012, which represented
an income of 43,521 million euros (Ministry of Industry, Energy and Tourism, 2013). Second, the tourism industry is a pillar
of the Spanish economy. In 2012, the tourism industry represented 10.8% of its gross domestic product (GDP) and employed
over two million people (12.2% of the total workforce) (Ministry of Industry, Energy and Tourism, 2013). Third, in relation to
other sectors, the Spanish tourist industry has the highest proportion of female entrepreneurs (Alonso-Almeida, 2013;
England, 2010).
Entrepreneurs were required to meet the two following requirements: (a) be the founder/owner and manager of a con-
solidated company which has been operating for over 42 months (established business owners in the terminology of the Glo-
bal Entrepreneurship Monitor –GEM-); (b) the company has more than 10 employees and less than 50. According to the
criteria of GEM a business that has a number of workers under 50 and over 10 is a small business.
Statistically, the sample size was calculated so that it would be representative of the population with a 5% standard error
and a 95% confidence level. The required sample size estimated by power analysis was 373 subjects.
A questionnaire survey research method was used to measure the resilience of entrepreneurs. Five interviewers, who
knew the objective of this study, telephoned potential responders at the entrepreneur’s workplace. Interviewers telephoned
a total of 650 entrepreneurs of which 534 produced usable questionnaires (overall response rate of 82%). All the interviews
were carried out in the first quarter of 2008.
A profile of the respondents is provided in Table 1. A comparison of this data with those from Spain’s Global Entrepre-
neurship Monitor (GEM Spain, 2007) shows that the characteristics of our sample are very similar to those shown by Spanish
established business owners.
Data for longitudinal study (objective growth and subjective growth) were collected 5 years after measuring the resil-
ience of the individuals. Of the total of businesses from the original sample, 26 had disappeared and 13 had changed own-
ership by 2012. This represents an average rate of abandonment of 7.30%, slightly higher than the rate of disappearance of
128 J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135
small businesses in the sector in the period under consideration (6.63%) (National Statistics Institute, 2013). The disap-
peared businesses may have gone bankrupt or been liquidated by their owners. Although it is fairly unlikely that the owners
would liquidate a successful business, we have adopted a conservative approach. Based on the idea that the closure the
businesses is a result worthy of consideration in the study, we included in the analysis the 26 businesses which have closed
down. We assumed that the average annual growth between 2008 and 2012 for the businesses which closed down was 0%
(Baum, Locke & Kirkpatrick, 1998). The 13 businesses that changed ownership during the period were eliminated from the
analysis.
3.2. Variables and measures
3.2.1. Resilience measurement
Resilience was measured using the Spanish version of the Connor–Davidson Resilience Scale (CD-RISC) which was devel-
oped using a sample of entrepreneurs (Manzano & Ayala, 2013). The instrument uses 9 items to measure hardiness (e.g. ‘‘I
am not easily discouraged by failure’’); 7 items to measure resourcefulness (e.g. ‘‘I am able to adapt to change’’) and 7 items
to measure optimism (e.g. ‘‘I see the humorous side of things’’). Respondents indicated their level of agreement using a 5
point Likert scale from strongly disagree (0) to strongly agree (4). Each of the three scales showed adequate parameters
for both internal reliability and convergent validity. The composite reliability of hardiness was 0.88 and its convergent valid-
ity was 0.57. For the resourcefulness and optimism scales the composite reliability and convergent validity were 0.87, 0.62
and 0.80, 0.54 respectively.
As can be seen in Table 2, both men and women show levels of hardiness, resourcefulness and optimism above the aver-
age values of the scale. The gender difference is not statistically significant in terms of resourcefulness, although it is in terms
of hardiness and optimism. In particular, women present higher values for hardiness and less for optimism than men.
3.2.2. Measuring entrepreneurial success
Although the explanation of success differentials between companies is a core issue in entrepreneurship research, there is
no consensus as to how the success construct should be assessed in empirical research. In accordance with the human capital
theory, entrepreneurs strive to receive financial returns from their venturing activities (Davidsson & Honig, 2003).
Most studies have used profitability, rate of growth, or stock market performance as measures of success (Combs, Crook &
Shook, 2005; Unger, Rauch, Frese & Rosenbusch, 2011; Marco, 2102). Nevertheless, we should bear in mind, that profitability
and growth measure different aspects of entrepreneurial success (Lee & Tsang, 2001) and sometimes these dimensions are
contradictory (Delmar, Davidson & Gartner, 2003). Moreover, none of the companies in the sample are listed on the stock
exchange and therefore it is difficult to establish its performance.
Table 1
Profile of respondents.
GEM
a
2007 Entire sample (N= 534) Men (n= 350) Women (n= 184)
Sex
Men 64.2% 65.5%
Women 35.8% 34.5%
Ages
Range 18–64 years 20–50 years 21–50 years 20–50 years
Average age 43.2 years 41.80 years 42.60 years 40.30 years
Educational level
Primary education 34.8% 33.9% 35.0% 31.7%
Secondary education 37.6% 36.6% 35.8% 38.2%
University degrees 27.6% 29.5% 29.2% 30.1%
Experience
% of entrepreneurs with experience 48.1% 49.0% 49% 49%
a
Global entrepreneurship monitor.
Table 2
Descriptive statistics.
Variable Total mean Stand. dev. Mean Chi-square p-value
Men Women
Hardiness 21.80 5.40 21.30 22.75 5.13 0.01
Resourcefulness 23.12 4.98 23.40 22.60 0.70 0.20
Optimism 15.73 3.86 17.21 12.92 3.12 0.04
Objective growth 6.03% 6.23% 5.52% 0.17 0.34
Subjective growth 5.21% 5.71% 4.25% 3.12 0.03
J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135 129
High growth tends to be considered a logical consequence of innovative, proactive and risk-taking behaviour on the part
of the firm, characteristics which are often associated with the entrepreneur (Brown, Davidson & Wiklund, 2001). Therefore,
we use growth as a proxy for entrepreneurial success. Business growth was assessed using an objective measure and a
subjective measure, according to the recommendation of Walker (2004) and Moreno and Casillas (2008). In order to obtain
the subjective measure of growth (Subjective Growth) the interviewees were requested to indicate the cumulative growth of
their business over the last five years (2008–2012) compared to other firms in the sector. The objective measure of growth
(Objective Growth) was obtained using information from the company’s annual accounts. Often, the growth of a business is
expressed using a multiple measure which included sales, assets and employment. In our case, the correlation between these
three variables was over 0.55 and significant (p< .001). For this reason, and in accordance with Moreno and Casillas (2008)
and Delmar et al. (2003), we use a single indicator: sales. The Growth objective has been measured first by calculating the
percentage of growth in sales for each company between 2008 and 2012 (SABI, 2012). We then calculated the difference be-
tween this growth rate and the average growth rate of the sector in the period under consideration. Table 2 shows that the
average value of objective growth is more than that of subjective growth. On the other hand, no gender-based differences are
observed in objective growth, while the average subjective growth value in firms managed by women is significantly less
than in those managed by men.
3.2.3. Control variables measurement
Individual-level demographic factors such as age, education and experience level were controlled because they may have
systematic relationships with resilience or growth. For example, human capital variables such as education and experience
have been shown to be positively related to venture growth (Ayala & Manzano, 2010; Lee & Tsang, 2001). Age has also been
found to contribute to the development of resilience, although the research findings are equivocal in this area (Burns &
Anstey, 2010; Campbell-Sills et al., 2009; Karaırmak, 2010). The responders were asked to indicate their age (measured as
a continuous variable), educational level (coded for each level as 1 = Primary education; 2 = Secondary education, and
3 = University degrees) and the number of years of work experience (including experience obtained prior to establishing
their firms). This was measured as a continuous variable.
Previous studies have shown that the performance rates of businesses can vary depending on the age of the company or
their size (Wiklund & Shepherd, 2005). Therefore, these variables were also controlled to reduce possible confounding effects
for significant results. The year in which the company was founded was obtained from the SABI database (SABI, 2008) and
was used to calculate the firm’s age. All the businesses in the sample were, in 2008, small companies according to the ter-
minology of the GEM (9 < employees < 50).
Industry effects were controlled by studying a single industry. The previous studies that have analysed the differences in
gender and other structural factors, which could explain the performance of the business (Marco, 2012; Rosa, Carter &
Hamilton, 1996), have concluded that control by industry is required in order to obtain undistorted results. The intercorre-
lations between the control variables and the rest of the variables in the regression model can be seen in Table 3. The sta-
tistically significant correlations (p< 0.01) between independent variables of the regression model are low (<0.26) which
indicates that a collinearity problem between these variables does not exist (Hair, Anderson, Tathan & Black, 1998).
3.3. Data analysis
In order to determine what role resilience factors play in understanding the entrepreneurial success, a hierarchical linear
regression analysis was used. In this analysis the dependent variables were the firm’s objective growth and the firm’s
subjective growth and the independent variables were the three factors of resilience.
Table 3
Intercorrelations.
Variables 1 2 3 4 5 67891011
1. Gender
2. Age 0.07
3. Education 0.12 0.04
4. Experience 0.24
**
0.08 0.13
5. Firm age 0.18 0.12 0.09 0.02
6. Hardiness 0.12
**
0.04 0.07 0.20
***
0.01
7. Resourcefulness 0.20 0.19
**
0.08 0.14
***
0.07 0.21
***
8. Optimism 0.22
**
0.03 0.01 0.09 0.05 0.23
***
0.25
***
9. Subjective growth 0.19
**
0.09
*
0.23
**
0.30
**
0.17
***
0.23
***
0.39
***
0.28
***
10. Objective growth of sales 0.17 0.11 0.22
***
0.31
**
0.14
***
0.27
***
0.42
***
0.25
**
0.83
***
11. Objective growth of assets 0.19 0.14 0.29
**
0.33
**
0.15
***
0.31
***
0.34
***
0.30
***
0.59
**
0.87
***
12. Objective growth of employments 0.22
*
0.17 0.33
**
0.28
***
0.12
**
0.29
**
0.44
***
0.28
**
0.63
***
0.90
***
0.56
***
***
p< .001.
**
p< .01.
*
p< .05.
130 J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135
We first added the control variables and then the independent variables. The validity of each model was evaluated
according to R
2
, Adjusted R
2
and Ftest of statistical significance.
4. Results and discussion
The Beta coefficients of the regression analysis, as well as its corresponding standard errors, are displayed in Tables 4 and
5. In all models, the Durbin-Watson statistic shows that the serial correlation of residuals takes values that are within the
acceptance range (1.5 and 2.5). This means that there is no auto-correlation problem in the data. The Condition Index in
all models is within the range of acceptance (15–20). In all cases, the variance inflation factor (VIF) values remained below
the recommended maximum value, which is around 5 (Kleinbaum, Kupper & Muñller, 1998). This means that there is no
multi-collinearity problem in the regression models used for this study.
For all individuals taken together, the results show that hardiness, resourcefulness and optimism have a statistically sig-
nificant positive relationship with objective and subjective growth; i.e. greater entrepreneurial objective and subjective
growth is associated with greater hardiness, resourcefulness and optimism. These findings provide support for hypothesis
1 and add to the empirical evidence that entrepreneurs’ resilience has a positive influence on the explanation of entrepre-
neurial growth and they back up the findings of previous studies such as those by Bhidé (2000), Envick (2005),orHayward
et al. (2010).
Of the three dimensions of resilience considered in the explanation of entrepreneurial growth, that which has shown the
greatest explanatory power is resourcefulness. This result, which remains when the individuals are divided into gender-spe-
cific groups, is not at all surprising. The companies included in the present sample were small companies (9 < employ-
ees < 50). Thus, they were still at a stage in their development where the founders are the key figures; they are immersed
in the day-to-day activities of the business and they are the ones who take most of the important decisions. This result sup-
ports the arguments made by Sasi and Sendil (2000) and by Nandamuri (2013) who argue that resourcefulness is the key to
becoming a successful entrepreneur.
When the individuals are divided into gender-specific groups, the results show that the three factors of resilience improve
the explanation both of the objective growth and the subjective growth. This result provides support for hypothesis 2. In
addition, the multivariate model has demonstrated that the importance of resourcefulness in the explanation both of objec-
tive growth and subjective growth is greater in the case of men than that of women. These findings support the argument
that the ability of resourcefulness to predict entrepreneurial success differs according to gender (Nandamuri, 2013).
Our results show that the subjective growth of the businesses run by women is less than that of businesses run by men.
This result is related to the different way in which men and women perceive the economic and social environment and the
influence that this perception has on decisions regarding the growth of the business. Women are more pessimistic than men
when the social environment and economic prospects are not good (such as was the case in the period analysed) and as a
result they grow their businesses less (Chang, Tsai & Lee, 2010; Jacobsen, Lee & Marquering, 2008). This could also be the
reason why the greatest predictive power of optimism occurs in the explanation of the growth of businesses run by women,
above all when the dependent variable is subjective growth. With regard to the hardiness variable, the relative importance of
this variable is different for the groups of men and women on the basis of which it is the dependent variable. More partic-
ularly, when the dependent variable is subjective growth, hardiness has a greater predictive power for men than for women.
The contrary happens when the dependent variable is objective growth.
Table 4
Hierarchical linear regressión model on the relationship between resilience factors and Objective Growth.
Men + Women, n= 534 Men, n= 350 Women, n= 184
Control
variables
Resilience model,
control variables
Control
variables
Resilience model,
control variables
Control
variables
Resilience model,
control variables
b
ª
SE
ªª
bSE bSE bSE bSE bSE
Age 0.20 0.22 0.13 0.19 0.15 0.21 0.10 0.09 0.19
*
0.11 0.17 0.11
Education 0.21
***
0.06 0.17
**
0.07 0.18
***
0.09 0.14
**
0.05 0.22
***
0.06 0.20
**
0.08
Experience 0.23
***
0.05 0.15
***
0.03 0.23
***
0.07 0.15
***
0.04 0.23
**
0.08 0.17
***
0.05
Firm age 0.12
***
0.04 0.10
**
0.04 0.19
***
0.03 0.17
***
0.05 0.11
***
0.04 0.10
**
0.04
Hardiness 0.25
***
0.05 0.22
***
0.07 0.24
**
0.09
Resourcefulness 0.40
***
0.12 0.41
***
0.13 0.36
***
0.11
Optimism 0.23
***
0.07 0.19
***
0.05 0.21
***
0.06
R
2
0.15
***
0.41
***
0.16
***
0.41
***
0.15
***
0.39
**
Adjusted R
2
0.14
***
0.40
***
0.15
***
0.40
***
0.14
***
0.37
**
Fvalue 23.34
***
52.22
***
16.43
***
33.95
***
7.90
***
16.07
***
ª
Standardized regression coefficients.
ªª
Standard error.
***
p< .001.
**
p< .01.
*
p< .05.
J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135 131
The results of our study have several interesting implications for researchers, for institutions that encourage entrepre-
neurial behaviour in young people and for entrepreneurs themselves. As previous studies have suggested, resilience may
be developed and encouraged (Brewer & Hewstone, 2004). Entrepreneurs – through programmes to train them in the solu-
tion of complex problems in conditions of uncertainty, in the search for creative answers for adapting to change (Weick,
1993), in assertive communication, in relaxation techniques (Dodding, Nasel, Murphy & Howell, 2008), or in achieving a bet-
ter understanding of their strengths – can develop skills for coping with different kinds of situations with optimism and
courage, thus improving the success of their companies. This may be particularly important for students. Courses designed
to awaken the entrepreneurial spirit must be designed so as to enable students to cope with new situations where they have
to make decisions without having all the information. They should be taught to learn from mistakes, to build confidence in
themselves and to deal with unexpected situations with creativity and optimism (Fairlie & Holleran, 2012; Shepherd, 2004).
Furthermore, education and training programmes should include components that assist aspiring, or already established
entrepreneurs in assessing and developing their thinking-style versatility (Groves, Vance & Choi, 2011). It is the case that
men and women have differences in their style of management but, without giving up those differences, can achieve similar
levels of success (Watson, 2002).
This study, as all studies, has several limitations that are worth noting. First, we have researched the relationship between
resilience and entrepreneurial success in companies run by a single person who is also, at the same time, the founder and
owner of the business. This means that each firm benefits solely from the resilience of the founder. However, many
companies have more than one owner-founder and entrepreneurial success could depend on team resilience (Blatt,
Table 6
Hierarchical linear regressión model on the relationship between resilience factors and different measures of Objective Growth.
n= 534, Dependent variable: asset growth n= 534, Dependent variable: employment growth
Control variables Resilience model, control variables Control variables Resilience model, control variables
b
ª
SE
ªª
bSE bSE bSE
Age 0.10 0.19 0.09 0.17 0.12 0.15 0.10 0.12
Education 0.23
**
0.09 0.19
**
0.8 0.28
***
0.09 0.21
**
0.08
Experience 0.25
***
0.05 0.20
***
0.06 0.21
***
0.06 0.13
**
0.05
Firm age 0.10
***
0.03 0.09
**
0.03 0.09
**
0.03 0.07
***
0.02
Hardiness 0.20
***
0.06 0.21
***
0.06
Resourcefulness 0.28
***
0.09 0.36
***
0.11
Optimism 0.22
***
0.07 0.20
***
0.06
R
2
0.13
***
0.29
***
0.15
***
0.36
***
Adjusted R
2
0.13
***
0.28
***
0.15
***
0.35
***
Fvalue 19.76
***
30.69
***
23,34
***
42.27
***
⁄
p< .05.
ª
Standardized regression coefficients.
ªª
Standard error.
***
p< .001.
**
p< .01.
Table 5
Hierarchical linear regressión model on the relationship between resilience factors and Subjective Growth.
Men + Women, n= 534 Men, n= 350 Women, n= 184
Control
variables
Resilience model,
control variables
Control
variables
Resilience model,
control variables
Control
variables
Resilience model,
control variables
b
ª
SE
ªª
bSE bSE bSE bSE bSE
Age 0.17
*
0.09 0.18 0.17 0.19
*
0.1 0.16
*
0.09 0.17
*
0.09 0.12
*
0.07
Education 0.25
**
0.10 0.20
**
0.08 0.22
***
0.07 0.19
***
0.06 0.26
***
0.06 0.20
**
0.07
Experience 0.22
***
0.05 0.16
***
0.05 0.21
***
0.06 0.15
***
0.04 0.21
***
0.06 0.14
***
0.04
Firm age 0.15
***
0.04 0.11
***
0.03 0.16
**
0.06 0.14
**
0.06 0.12
**
0.05 0.10
**
0.04
Hardiness 0.22
***
0.06 0.22
***
0.07 0.19
***
0.06
Resourcefulness 0.38
***
0.07 0.37
***
0.09 0.32
***
0.10
Optimism 0.26
***
0.04 0.17
***
0.06 0.23
***
0.06
R
2
0.17
***
0.38
***
0.18
***
0.39
***
0.20
***
0.40
**
Adjusted R
2
0.17
***
0.37
***
0.17
***
0.38
***
0.19
***
0.38
***
Fvalue 27.08
***
46.06
***
18.93
***
31.24
***
11.19
***
16.76
***
ª
Standardized regression coefficients.
ªª
Standard error.
***
p< .001.
**
p< .01.
*
p< .05.
132 J.-C. Ayala, G. Manzano / Journal of Economic Psychology 42 (2014) 126–135
2009). Furthermore, as the company becomes more complex, the founder or founders are often surrounded by other qual-
ified directors with whom they form a team. Future work could focus on finding out whether our results are maintained
when we analyse the relationship between resilience of the team and entrepreneurial success.
Second, our results are based on a sample of businesses which belong to different sub-sectors (hospitality, travel distri-
bution, accommodation, etc.) in the tourist industry. Future work could focus on finding out whether our results are main-
tained for different sub-sectors.
5. Robustness analysis
To assess the robustness and the credibility of our results we repeated the analysis using two alternative measures of
objective growth. In the first analysis we used assets to measure objective growth; in the second analysis we used the employ-
ment variable as a measure of objective growth. In both models, which were carried out on the entire sample (n= 534), the
independent variables were the three factors of resilience. Our results in Table 4 show the positive effect of the three factors of
resilience on objective growth measured by sales. This result is repeated in the models presented in Table 6. The results have
demonstrated that the relationship between resilience and objective success is stable and does not depend on how we mea-
sure the latter.
6. Conclusions
The findings of this study provide supporting evidence that within the framework of small companies, there is a positive
association between the resilience of entrepreneurs and the growth of their companies. On the other hand, the results pro-
vide supporting evidence that the factors of resilience affect, to varying degrees, the explanation of the growth of the com-
pany on the basis of gender.
This study seeks to take an important step towards an overall understanding of the influence of the resilience of the entre-
preneur/founder on the success of the business. Three aspects of this study distinguish it from most related studies to date.
First, it uses a measure of resilience which has been tested on a sample of entrepreneurs and has been shown to have good
psychometric properties. Secondly, it has a longitudinal design. The resilience was measured 5 years before measuring the
success of the business. Thirdly, it is the first study that has examined, based on a sample of entrepreneurs using longitudinal
design, if the differences of gender modify the predictive value of resilience.
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