University entrepreneurship education experiences ... Pap… · 2 University entrepreneurship...
Transcript of University entrepreneurship education experiences ... Pap… · 2 University entrepreneurship...
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Faculty of Business and Law
University entrepreneurship education experiences:
enhancing the entrepreneurial ecosystems in a UK
city-region
Fumi Kitagawa1, Don J. Webber
2,
Anthony Plumridge2 and Susan Robertson
3
1University of Edinburgh
2University of the West of England, Bristol
3University of Bristol
Economics Working Paper Series
1505
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University entrepreneurship education experiences:
enhancing the entrepreneurial ecosystems in a UK
city-region
Fumi Kitagawa1, Don J. Webber
2,
Anthony Plumridge2 and Susan Robertson
3
1University of Edinburgh;
2University of the West of England, Bristol;
3University of Bristol
The recognition of a strong association between education and economic prosperity
has enthused higher education institutions (HEIs) to amplify their initiatives to
stimulate entrepreneurship within their local economies and beyond. However, the
actual processes and impacts made through entrepreneurship education, and the
extent to which and the conditions with which different types of programmes are
effective, are not understood well. This article fills part of this gap by adopting the
concept of university-based entrepreneurship ecosystems and contributes to the
understanding of different impacts of entrepreneurship education and their
implications for city-region development. Student-level data are gathered across two
HEIs within one city-region in England, which include demographic backgrounds,
university experiences and motivations and propensities to start-up businesses. Our
analysis reveals that students who believe their university education has helped them
develop competencies to address challenges of becoming an entrepreneur were 78
percent more likely to have experienced an increase in their stated preference to start-
up a business. This suggests that HEIs should be more actively engaged in
stimulating student entrepreneurial behaviour and developing university-based
entrepreneurial ecosystems that may lead to greater city-region economic
development.
Acknowledgement: The authors thank the ESRC for funding data collection and conference
delegates for helpful comments at the SW England and Wales branches joint Regional Studies
Association conference.
Keywords: Business start-up; Entrepreneurial propensity; Student motivations
JEL classifications: L26; I26; R58
Address for correspondence: Don J. Webber, Bristol Business School, University of the West
of England, Bristol, BS16 1QY, UK. Email: [email protected]
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Introduction
Entrepreneurship is established as a major stimulant of economic growth and social
transformation, and the roles that higher education institutions (HEIs) play in developing
regional and national entrepreneurship ecosystems have been attracting both policy and scholarly
attention in many countries (Fetters et al., 2010). The recent increase in the number of HEIs
using their initiatives to stimulate enterprise and entrepreneurship within their local economies
and beyond is driven, at least in part, by the growing recognition of an association between
students’ entrepreneurship experiences at HEIs and the performance of the wider economy
(European Commission, 2015; GEM, 2012; Linan et al., 2011). As a consequence, educators of
enterprise and entrepreneurship are likely to experience challenges to meet increasing and wider
demands from policy communities, as well as pleas for entrepreneurial guidance from students at
different life and career stages, who are from broadening disciplinary backgrounds, and who
have varied, diverse and unevenly developed career aims and objectives.
In this light, this article locates universities’ entrepreneurship education in broader
institutional and local contexts of “university-based entrepreneurship ecosystems” (Greene et al.,
2011). Entrepreneurship education is implemented through different types of inputs at varying
scales including individuals, organisations, society and the economy (European Commission,
2015) but the actual processes and impacts of such mechanisms, and the extent to which and the
conditions with which different types of programmes are effective, are not understood well. The
operational definitions of enterprise and entrepreneurship across universities varies and there are
different aspects covered under these concepts that can include employability skills, social
enterprise, self-employment, venture creation, employment in small businesses, small business
management and the management of high-growth ventures (Pittaway and Cope, 2007, p.480).
Moreover, the changing intellectual, economic, social and cultural movements for
entrepreneurship education and learning will have been influenced by the recent recession, the
growing interest in social, ethical and responsible entrepreneurship and the growing emphasis on
the individual’s active entrepreneurial learning rather than merely on supply side HEI initiatives.
Starting a business is just one of many alternatives for students who pass through the
education system and transit into their working lives. In this article, we conceptualise
entrepreneurship education broadly. Following Fayolle and Gailly (2009), entrepreneurship
education is defined as “the activities aiming to foster entrepreneurial mind-sets, attitudes and
skills” and covers a range of aspects such as “idea generation, start-up, growth and innovation.”
According to Stanboulis and Balaras (2014), entrepreneurship education is not only important for
the development of entrepreneurship and self-employment but also for the enrichment of
students’ attitudes and characteristics necessary to manage the uncertain environment of self-
employment.
The Developing Entrepreneurial Graduates: Putting entrepreneurship at the centre of
higher education (CIHE/NCGE/NESTA, 2008) report called for a joined up approach across
industry, government and higher education sectors to respond to societal and economic
challenges to develop entrepreneurial environments within HEIs and beyond. These challenges
require graduates to have innovative and entrepreneurial mind-sets, skills and behaviour in order
to enable them to be effective entrepreneurs. Government policy assumes that entrepreneurship
education curriculum taught in UK HEIs can positively influence graduates’ attitudes towards an
alternative career path and simultaneously equip them with skills to enable them to become an
entrepreneur with the necessary knowledge and skills to start up, manage and develop an
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economically viable business (Matley and Carey, 2007). However, data show that the percentage
of undergraduate students leaving universities in the UK to become self-employed is low.
Greater comprehension of university-based entrepreneurship ecosystems, with specific foci on
entrepreneurship training, would provide strategic understanding of the changing roles of
universities. We will set this agenda in a particular geographical context: entrepreneurship
education may lead to economic and social development in a city-region.
This article makes inroads into these issues by presenting empirical findings from
research that was specifically designed to investigate students’ attitudes towards
entrepreneurship in relation to their entrepreneurship education experiences at their universities.
This study has three aims: to investigate the motivations of students who embark on an education
strongly related to entrepreneurship; to examine changes in students’ attitudes towards setting
up a business while attending an HEI and; to elucidate if differences in HEIs environments affect
motivations, perceived barriers and actual student entrepreneurial behaviours. To carry out these
investigations we draw on an original data set collated from a survey of students attending two
universities with different organisational characteristics located in one of the UK city-region.
The remainder of this article proceeds as follows. In the next section we present a review
of the existing entrepreneurship ecosystems literature with emphasise on knowledge gaps. The
subsequent section provides details of the method, data and institutional contexts including UK
policy developments. The empirical analysis that follows highlights the relative importance of
individual and contextual factors in shaping students’ entrepreneurial propensities. The final
sections discuss the findings and conclude with future research and policy implications.
Conceptual frameworks
University-based entrepreneurial ecosystems, incentives and entrepreneurship education
Studies over recent decades demonstrate that the development of university-based
entrepreneurship ecosystems (Greene et al., 2010) is conditioned by a number of factors
including the knowledge infrastructure, industry environments, knowledge and technology
transfer systems, policies at national and local levels and strategies adopted by individual
universities and their leadership. According to Moore (1993, p.76), the ecosystem concept is
understood as “an economic community supported by a foundation of interacting organizations
and individuals.” Business ecosystems are often described in states: birth, expansion, leadership
and self-renewal where a “business ecosystem, like its biological counterpart, gradually moves
from a random collection of elements to a more structured community” (Moore, 1993, p.76).
Meanwhile, Aulet’s (2008) conception of the ecosystem includes different actors and facets
including individuals, organizations and resources, and specifically includes government,
demand, invention, funding, infrastructure, entrepreneurs and culture. This framework enables
the schematic understanding of different types and sources of inputs of entrepreneurship
education and makes, through ecosystems, multi-dimensional outcomes.
Other conceptions of entrepreneurial ecosystems and incentives exist. Entrepreneurial
event theory considers firm creation to be the result of interaction among contextual factors,
which act on an individual’s perceptions of the desirability and feasibility of becoming an
entrepreneur (Linan et al., 2010). The subjectivist theory of entrepreneurship focuses on
individuals, their knowledge, resources and skills, and the processes of discovery and creativity
through interactions. As knowledge is invariably mentioned as a necessary requirement for
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entrepreneurial activity, it is opportune for universities to service their local and regional
economies by providing entrepreneurship education and stimulating entrepreneurial activities.
Outcomes of entrepreneurial education are varied and can include changes in individual actions,
greater propensities to find a job (‘employability’), greater propensities to start a business, new
entrepreneurs, new ‘intrapreneurs,’ societal change and social mobility and inclusion, and
economic growth (European Commission, 2015).
From this perspective the provision of enterprise and entrepreneurial knowledge could
enhance the propensity of a student to embark on the path towards starting up a business, and this
could affect the development of a local economy. For instance, Rupasingha and Goetz (2013)
indicate that higher self-employment rates are associated with income and employment growth in
the US. Recent literature on skills and workforce development argues for ‘pro-innovation’
organisational practices (OECD, 2010). In this light, educating and training graduates with
entrepreneurial behaviour and skills seem to be critical not only for business start-ups but also
for workforce development and the inducement of workplace innovation.
Factors and processes that affect entrepreneurship attitudes, behaviour and career
There is a lack of consensus on the factors that contribute to an individual’s decision to start a
business (Krueger and Brazeal, 1994). Entrepreneurial careers are recognised as more complex
than organisational careers and require the simultaneous appreciation of multiple factors
(Greenhouse et al., 2000; Rae, 2007). Career choices are influenced by a number of issues
including family background, social and economic background, educational experience, formal
and informal exposures to entrepreneurial activities and enterprise training/education provisions
at HEIs and throughout a student’s life course. Understanding of “entrepreneurial intension”
(Autio et al., 2001) therefore requires an understanding of students’ demographic characteristics
and social backgrounds, which can be idiosyncratic and heterogeneous, as well as an
understanding of career patterns in order to design more effective entrepreneurial education
initiatives (Jack and Anderson, 1999; Cooper et al., 2004).
There is still a considerable gap in the understanding of the influence of entrepreneurship
education in the making of an entrepreneur (Nabi et al., 2010). An individual’s belief with
respect to their abilities in a range of activities central to entrepreneurship may influence the
likelihood of pursuing entrepreneurial behaviour. However, changing beliefs and attitudes are
not always sufficient to bring about behaviour change. Individual’s intentions matter here as
intentions are conceived as reflecting a “person’s willingness to pursue a certain behaviour,
taking into account constraints and limits which might be imposed by the external environment
or the background/abilities of the individual” (Cooper and Lucas, 2006, p.670). High levels of
confidence are seen as an essential component shaping the propensity to start-up a business, with
self-confidence in one’s own skills being linked to “innovation, opportunity recognition and
intention to start a new venture” (Cooper and Lucas, 2006, p.669).
Individual differences in business start-up propensities are known to stem from various
characteristics including a number of demographic factors such as age, education, work status
and household income (Blanchflower, 2004) and past economic inactivity or unemployment
(Rosti and Chelli, 2005). There is contested evidence about the factors that affect the propensity
to start-up a business. Previous studies show that women are significantly less likely to own a
business than men (Blanchflower, 2004; Minniti and Nardone, 2007) even though business
failure rates are not related to the gender of the proprietor (Perry, 2002; Kepler and Shane, 2007).
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The neoclassical economics literature assumes that students make a rational choice to embark on
self-employment and that this choice is affected by a range of de/incentivising issues. There is
evidence to suggest that starting a business may be related to the fixed costs of work and hence
are related to convenience, such as for a parent with childcare responsibilities (Edwards and
Field-Hendrey, 2002). There is also evidence to suggest that decisions concerning employment,
marriage, household production and child-rearing are interdependent (Cowling and Taylor, 2001)
and that men are more likely to opt for self-employment to improve their long-term career
options while women are more likely to start their own business from a position of economic
inactivity or unemployment (Rosti and Chelli, 2005).
The empirical analysis that follows highlights the relative importance of individual and
contextual factors in shaping entrepreneurial propensities. Within the university-based
entrepreneurial ecosystems framework, entrepreneurship education is seen as an incentivising
factor for individuals to become an entrepreneur as it provides knowledge of the entrepreneurial
institutional framework (Lian et al., 2011) and of entrepreneurial competencies (Sanchez, 2013)
that give extra credence to an individual’s tenacity to become an entrepreneur (Lian et al., 2011).
Research method and institutional contexts of the study
Context of the study: The UK policy background
In the UK, the government agenda has focused on encouraging more graduates to pursue an
entrepreneurial career path (i.e. to start-up their own business) with an aspiration for the UK to
be “the best place in the world to start and grow a business” (DBIS, 2008). During the last
decade, a number of initiatives have been created to stimulate enterprise and entrepreneurship at
HEIs in the UK (CIHE/NCGE/NESTA, 2008). McKeown et al. (2006) found that the provision
of entrepreneurship education is varied, with both entrepreneurship and innovation courses on
offer. Entrepreneurship education is most often offered at postgraduate level and on a part time
basis, including courses on technology transfer. Matlay and Carey (2007) provided a longitudinal
study of UK HEIs and recognise that there are a number of actual and perceived barriers for
educators that need to be overcome or mitigated against in order to facilitate a better
understanding of stakeholder needs. They also emphasised that the measurement of the outcomes
of entrepreneurship education in the UK is still proving elusive. The challenges for educators of
entrepreneurship remain in the scaling-up of provision and in generating sustainable demand.
It is also known that institutional differences between old universities (pre-1992) and new
universities (post-1992) in the UK will condition the delivery of entrepreneurship education
(McKeown et al., 2006) and hence potentially shape entrepreneurial aspirations differently. Post-
1992 universities have always been more tightly integrated into their locality and have always
encompassed a broader range of activities, including interacting with local schools, firms, local
authorities and communities, and providing consultancy and Continuing Professional
Development (CPD) training opportunities to local industry. Other universities, often the more
traditional and prestigious institutions, tend to emphasise their national and international
orientations of research, teaching and other scholarly activities, rather than local and regional
connections. Nevertheless, recent years have witnessed that even those less locally-oriented
institutions are increasingly looking to their regions and localities for support and claim credit for
adding to the area’s economic and social strength (Charles et al., 2014).
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Recent policy changes in the UK have affected the institutional conditions for start-ups
and the potential roles of HEIs. In England, the recent change in home undergraduate students’
tuition fees seems to have further raised students’ interest in the employability agenda, which
includes start-ups opportunities as part of their career options. Under the 2010-2015 coalition
government, changes in the governance of local economic development increased the importance
of city-regions (Kitagawa and Robertson, 2011) and this ‘scalar shift’ happened against the
backdrop of the financial and economic crisis (Hutton and Lee, 2012) which has been used as a
justification for the policies of central government. These changes have had knock-on effects on
universities including a shortage of private sector investment, changes in student behaviour and
changes in demands and expectations from local stakeholders (Charles et al., 2014).
Research methods
Against such policy backgrounds, this study investigates the changing entrepreneurial attitudes
of students by comparing student cohorts from two universities in one city-region in England. In
order to carry out this comparative study, an online questionnaire survey was developed in order
to collect data that would contribute to improving the understanding of university students’
experiences, perceptions and attitudes towards entrepreneurship, their entrepreneurial activities
and education experiences, and their perceptions of skills and knowledge gained through their
university’s programmes. For convenience the survey was distributed between March 2011 and
May 2011 at both undergraduate and postgraduate levels across two universities located in a
single core city of the UK: The University of Bristol (UoB) and the University of the West of
England, Bristol (UWE). UWE is classified as a new (post-1992) university while UoB is an old
university. The two universities have different strengths and strategies regarding enterprise
education and academic entrepreneurship which reflects the two institutions’ historical
developments and differences in teaching and research activities.
In order to highlight some of the characteristics of the two universities, Tables 1 to 3
present data from the HEBCI survey (2009/10) of the two HEIs. While this institutional level
data only presents a snap-shot of entrepreneurial activities of the two institutions, the different
natures of university-based entrepreneurial ecosystems may emerge through such data. In terms
of the estimated current turnover of all active firms, UWE graduate1 start-up firms exceeds all
other English HEIs and the nature of entrepreneurial ecosystems at the two HEIs seems to be
very different. While UoB has strength in “Spin-offs with some HEI ownership,” UWE has a
higher number of graduate and staff start-ups. For universities, there tends to be a tension
between resourcing university-owned spin-outs and student-owned start-ups, which are
1 Other initiatives employed by UWE include Enterprise Fairs, where approximately 200 final year undergraduate
students from a range of degree programmes conduct a 30-second elevator pitch in front of a team of 18 tutors
and conduct poster presentations in front of anyone and everyone from within and beyond the university. This
forms the final element of an Enterprise Project, which is a final year dissertation module organised around the
creation and development of a business plan. These business plans correspond to a wide range of business
ventures covering everything from cutting edge software applications to artisan food businesses and also include
a considerable number of business plans focussed around sustainability (reflecting Bristol’s status as European
Green Capital). There are a range of prizes associated with the module all generously sponsored by Peter Fane of
Nurture Landscapes (http://www.nurturelandscapes.co.uk/) who is an alumnus of UWE, and prizes are for the
Best Enterprise Project, Best ‘sustainable’ Enterprise Project, and ‘The Project with the Most Potential’. Staff,
students and members of the public can participate in the day and to make nominations for what they believe to
be ‘The Project with the Most Potential.’
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subsidised by public funding. In the case of the latter, the motivation is more about education
process and individual development than about traditional tech transfer.
{Insert Table 1 about here}
{Insert Table 2 about here}
{Insert Table 3 about here}
The following sections present the findings from the student survey conducted at the two
universities in 2011about the students’ attitudes and orientations about starting up businesses.
Data description
The response rate of the questionnaire turned out to be 4 percent and the profile of our
respondents at the two HEIs is set out in Tables 4 to 10. After accounting for omitted
observations of variables that are necessary for this study, the final sample sizes were 1,210
UWE students and 1,144 UoB students. Table 4 shows the greater representation of postgraduate
students at the UoB, which reflects the composition of the student body across these two
universities. It is difficult to compare the Faculty composition of the two universities in our
sample as the Faculty structures differ.
Both full-time and part-time students are included in the sample, and the differences in
part-time/full-time student ratio at under- and post-graduate levels are broadly in line with the
two universities’ cohorts. Table 5 reveals the gender bias in the sample and Table 6 shows the
age distribution of respondents, which reflects the higher proportion of mature students in the
student population at UWE, all of which reflect differences between the cohorts.
{Insert Table 4 about here}
{Insert Table 5 about here}
{Insert Table 6 about here}
A complex web of factors characterise the relationships between the educational
achievement of children and the educational level of their parents. As there have been many
studies showing a significant positive relationship, it is not surprising that the higher grades
required to obtain a place at the UoB are reflected in our sample with a greater proportion of
parents attaining tertiary education, as shown in Table 7. Table 8 shows a higher proportion of
UK students amongst UWE respondents than those attending UoB, which reflects the
composition of the student body at the UoB that traditionally attracts a greater proportion of
international students. Table 9 shows that a greater proportion of UWE respondents studying
applied disciplines than at UoB, and this too reflects the very different origins and evolution of
the two HEIs.
{Insert Table 7 about here}
{Insert Table 8 about here}
{Insert Table 9 about here}
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Entrepreneurial attitudes
A key question in our survey focused on students stated intentions of starting up a business.
Given the importance of the business cycle and confidence for the realisation of entrepreneurial
orientations, we generate a new variable called “Start-up soon” which is equal to 1 (one) if the
student responded to the questions “Are you interesting in starting-up a business sometime in the
future” with either “Yes, within five years”, “Yes, within ten years” or “Yes, in the future, not
decided when”; this variable is equal to 0 (zero) if the responded instead stated “No.”2 This is our
proxy for entrepreneurial orientation and is the dependent variable in the regression estimations
below. Table 10 presents the full breakdown of this variable split by university. Although about
the same proportion of students in both universities stated that they would not start up their own
business (33% for UoB, 29% for UWE), there is an important disparity between universities with
students at UWE being almost 50 percent more likely to want to start up their own business
within the next five years (13 percent at UoB, 20 percent at UWE).
{Insert Table 10 about here}
Also included at the bottom of Table 10 is the distribution of attitude changes to
entrepreneurial orientation since the student enrolled in the university degree. Although the
majority of students’ entrepreneurial orientation had not changed, there was a positive movement
towards greater entrepreneurial orientation with 16.6% of respondents indicating that they were
more positive towards entrepreneurial activities after their studies than before they started their
degree.
Entrepreneurial intensions
It is possible to achieve a greater understanding of student-level entrepreneurial orientations by
using this data set to investigate the likelihood of respondents to express an intention of starting
up a business.3 This is achieved by undertaking a series of regressions as set out below in Table
11 where we adopt a specific-to-general model building approach. The dependent variable in
each regression is binary corresponding to whether the student suggested that they will “Start-up
soon” their own business.
{Insert Table 11 about here}
Column 1 indicates that males are 2.1 times more likely to want to start up a business
soon than are females and UWE students are 1.7 times more likely to want to start up a business
soon than are UoB students. This might be associated with the greater emphasis placed on
vocational and applied programs in newer HEIs. Both of these results are statistically significant
across all five columns. There is also only weak tentative evidence that full-time students are
more entrepreneurial than part-time students and postgraduate are more entrepreneurial than
2 We exclude from our analysis those respondents who indicated that they were “Unsure” or had already started
their own business. 3 Although this research does not circumnavigate the terminal issue of intentions not necessarily matching
realisation, it is nevertheless a step towards better understanding of entrepreneurial aspirations.
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undergraduate students, suggesting that university entrepreneurial guidance should be available
to all students across all levels and modes of study.
Columns 2 and 3 introduce family factors into the regression. If the father has primary
education as their highest level of education then the student is most likely to want to start up a
business: if the father has secondary education then the student is about (1 / 0.550 =) 82 percent
more likely not to want to start up a business and if the father has a tertiary education then there
is no statistically significant additional effect but if anything the effect would seem to be to
reduce entrepreneurial aspirations even further. Note that neither mothers’ educational
attainment nor fathers’ occupational status appear to have any effect on a students’
entrepreneurial aspirations. Relative to the mother being unemployed, if a student’s mother is in
a lower supervisory and technical occupation then the student is likely to have greater
entrepreneurial aspirations. These findings are in line with the suggestion that students of
relatively poorly educated parents and/or a mother in a relatively poor employment position are
more likely to have the perception that they need to rely on their own employment initiatives
(including entrepreneurial expertise) rather than on the value of educational credentials as a
ticket to a good job.
Prior experiences
The survey asked about prior vocationally-relevant experience, and this information is included
in column 4. Prior vocationally-relevant experience was categorised as full-time work
experience, part-time work experience, informally arranged internships (e.g. organized on
student’s own initiative), formal internships (e.g. placement year provided as part of degree
programme) and experience in running their own business. Of these, students who had arranged
an internship informally were 1.9 times more likely to intend to start their own business. Column
5 also provides evidence that those students who had already had experience of running their
own business were 2.2 times more likely to intend to start their own business. Both of these
results are sensitive to the inclusion of perceived benefits of going to university, as included in
column 5. Students who suggested that going to university to gain skills in order to start up their
own businesses were 3.2 times more likely to want to start up a business than those who did not
go to university for this reason. The lack of statistical significance of a range of entrepreneurial-
related activities that may be associated with the decision to go to university could reflect a broad
interpretation of entrepreneurship and a lack of a perceived relevance of education for starting up
a business. Finally, students who have a family member who owns a business are 1.7 times more
likely to want to start up their own business.
The analysis above suggests that entrepreneurial orientation is developed prior to
attending an HEI and is associated with only certain family backgrounds. Prior activity
associated with starting a business is most strongly associated with an intention to start a
business after leaving university. There is also the indication that those students who show
initiative in arranging work experience and internships are more likely to start a business; this
effect is likely to be associated with prior entrepreneurial orientation, peer groups, university
guidance and/or something else. Having established this indicative baseline, it is opportune to
progress and identify factors that change students’ entrepreneurial orientations.
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Changing attitudes to setting up a business
This section examines the change in students’ entrepreneurial orientation since starting their
degree, as tabulated in Table 10. The questionnaire administered to UWE students included
supplementary questions designed to explore this issue, thus the remaining analysis refers to
respondents from UWE only. As the change in students’ entrepreneurial orientation has an
ordered Likert response, an option for the analysis of this data is to implement ordered logistic
regression; these are presented in Table 12.
{Insert Table 12 about here}
Column 1 assesses whether gender, degree stage, student type and the 2011 business
cycle economic situation were associated with changes in entrepreneurial orientation while at
university. Although attitudes did not change more for males than females or more for full-time
students relative to part-time students, attitudes did change more for undergraduates relative to
postgraduates with undergraduates being 1.5 times more likely to state an improvement in their
entrepreneurial attitude while attending the HEI. Perhaps PG programmes are generally viewed
as less relevant to entrepreneurship or perhaps the students’ entrepreneurial tendencies were
already affected in their undergraduate studies. Further investment by a student in a PG
programme may be viewed as more valuable for mainstream employment than starting a
business.
The economic situation of 2011 affected students’ attitudes towards entrepreneurial
activities with students who stated that the economy encouraged (discouraging) them to start up a
business being 1.8 ([1/0.669=] 1.49) times more likely to state that their attitude improved
(deteriorated). This may reflect perceptions of the probability of achieving projected returns, or
return-related threshold issues as emphasised by McCann and Folta (2012), but may be less
relevant for students if they do not have a baseline estimate of projected returns.
Students’ perceptions of the skills needed for entrepreneurial success were included in
column 2, as greater knowledge, reflection and/or recognition of the need for these skills may
have been accrued while attending university. Out of a wide variety of potentially important
skills and competencies included in the regression (see notes on the bottom of Table 12) the only
statistically significant one that the students suggested was important in changing their
entrepreneurial orientation was communication skills. Students who think that communication
skills are needed to become an entrepreneur are about 1.4 times more likely to have experienced
an improvement in their attitude towards setting up a business, perhaps because they believe they
are good at this skill.
Challenges associated with becoming an entrepreneur
The questionnaire also asked students to provide information about their perceptions of the
challenges associated with becoming an entrepreneur. The list of potential challenges included:
obtaining finance, evolving a business idea, competition in the market, building a team,
acquiring the necessary management skills and identifying markets. Respondents were asked
whether UWE had helped them develop the skills necessary to overcome these challenges. Only
one issue was reported by students as being a potential challenge: if the student suggested that
their biggest challenge to becoming an entrepreneur is identifying markets then they were 1.2
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times more likely to have experienced an improvement in their attitude to setting up their own
business, perhaps because they have improved their knowledge of markets at UWE. Similarly,
students who believe that their UWE education has helped them develop competencies to
address challenges of being an entrepreneur were about 1.8 times more likely to have
experienced an improvement in their attitude towards setting up their own business.
Extracurricular and extra-university activities
Questions were also asked about enterprise and entrepreneurship extracurricular activities and
whether these were perceived to be useful for their future career development. The response rates
to these extra questions varied and would have severely restricted the regression sample and
hence these issues are addressed separately.
Table 13 highlights students’ perceptions of the usefulness of a range of extracurricular
activities. Roughly 75 percent of students indicated that they did not find these activities useful.
There is only one activity which more than 30 percent of students suggested was useful:
short/intensive programmes on entrepreneurship and enterprise skills. One-to-one drop in
sessions on enterprise advice was also perceived to be relatively useful. This suggests that
universities promotion of entrepreneurial and enterprise extracurricular skills should focus on the
provision of either intensive courses or a drop in session.
{Insert Table 13 about here}
In contrast, Table 14 highlights the students’ perceptions of the usefulness of a range of
extra-university activities. The vast majority of these extra-university activities were perceived to
be much more useful than extracurricular activities. The two most useful activities were
volunteering in enterprise activities and enterprise activities in the private sector; the perception
of the usefulness of the latter was found to be equally helpful irrespective of whether the activity
was locally or internationally focused, whereas the former seems to have been more useful if it
had a domestic focus. The perceived usefulness of learning from friends or through buying or
selling on the Internet were both low, with less than a third of respondents suggesting that these
were useful. Nevertheless, less than half the students suggest that extra-university activities were
useful, suggesting the need for greater effort to identify a better match between private enterprise
activities and students’ entrepreneurial needs.
{Insert Table 14 about here}
The analysis of the survey data shows that the entrepreneurial propensity of the students
are influenced by a variety of demographic attributes, educational levels, parental education,
parental occupational backgrounds, family influences, previous work experiences (including
having already started up a business), and being affiliated with different HEI. Additional
analyses related the impact of university experiences to the entrepreneurial propensities of the
student. Student background characteristics, self-selection into courses providing start up
business skills and already having experience in running a business do explain part of the
differences between the universities. However, findings in this article also reveal that students
who think that the task of identifying markets is a big challenge to becoming an entrepreneur are
more likely to have experienced an improvement in their attitudes to setting up their own
13
business, perhaps due to the provision of such useful knowledge at their HEIs. In particular,
students who believe that their university education has helped them develop competencies to
address challenges of becoming an entrepreneur are about 78 percent more likely to have
experienced an improvement in their attitude to setting up their own business.
Concluding remarks: towards a broader conception and communication of the university-
based entrepreneurial ecosystems
The findings from this study provide unique insights to the literature in terms of students’
learning experiences and how different entrepreneurship factors such as demographic attributes
and prior experiences interplay in their changes in attitudes, competences development and
career making processes. The data set provides a unique comparative study of two universities
and their students’ perceptions set in one city-region. Analysis of the data reveals clear
asymmetries. One asymmetry is found in terms of gender while another asymmetry is found in
the nature of university-based entrepreneurial ecosystems across the two HEIs. These condition
both the likelihood of a student being aspirational and any behavioural changes experienced at
university towards starting their own business.
The findings are useful from two main different perspectives. First, although the study is
of specific value to the universities at both institutional level and School/Departmental levels in
terms of gaining profiles of student populations that capture their entrepreneurship experiences
and their perceptions of university programmes, it is also a strong indication that student bodies
are heterogeneous in their propensities to start up businesses and the possibilities of being
encouraged to start up businesses. Such knowledge helps university academics and educators in
designing future entrepreneurship provisions to meet growing diverse students’ demands and
experiences within and across universities.
Secondly, the study would be of value to Bristol city-region where the two universities
provide a large number of graduates with a variety of high-level skills as part of the university-
based entrepreneurial ecosystems. As the HEBCI data indicates, graduate start-ups impact the
local economy in terms of external investment, number of firms and turnover. Although
universities in Bristol attract young and mature students with a variety of experiences both from
the UK and beyond, a significant number of graduates remain in the city-region after their
studies, including those who start-up their own businesses. Greater understanding the
entrepreneurship and enterprise education profiles of university graduates and their destinations
can shape strategies of city-region development. Different universities have different
organisational structures and different student needs and demands. Further study is needed in
order to understand the institutional characteristics of entrepreneurship education and activities at
the two HEIs as well as the relationships and embeddedness of this education to the city-region
entrepreneurial ecosystems.4
While the literature highlights concepts such as the entrepreneurial university (Clark,
1998; Etzkowitz, 2003) and university entrepreneurship (Rothaermel et al., 2007) as important
university-based entrepreneurial orientations, earlier studies on universities’ entrepreneurship
activities tended to focus on a rather narrow set of activities related to the commercialisation of
research, such as patenting and spin-off firm formation. Recent studies argue that undue policy
and research interest has been placed on the commercialisation of research results and the
protection of intellectual properties emanating from universities while neglecting other types of
4 One example is the universities’ links to incubators and entrepreneurial networks in the city-regions
14
entrepreneurial and engagement activities that can be less visible but equally or even more
important (Leydesdorff and Meyer, 2010; Walsh et al., 2008; D'Este and Patel, 2007). It has been
pointed out that leading research universities seem to benefit from the commercialisation of
publicly funded research (Hughes et al., 2013) and also that economic returns from patent
application and university spin-off companies is small and skewed (Harrison and Leitch, 2010).
For most universities, effective knowledge transfer is made through graduates and local
processes and practices that are contingent upon the nature of industrial development in the
regional economy (Dill, 2014). The conceptualisation of university-based entrepreneurial
ecosystems needs to balance the diverse characteristics associated with different types of HEIs
and the synergies between research, teaching and other types of entrepreneurial activities.
Furthermore, through our investigation, several issues have emerged that need further
consideration in order to ensure greater integration of students’ experiences in to the
conceptualisation of the university-based entrepreneurial ecosystems.
First, the number of students engaged in entrepreneurship education is not large in
relation to the whole student population. The impact of entrepreneurship education needs to be
put in perspective as it seems to be directly and positively influencing a small portion of the
students. Secondly, entrepreneurship education consist of a diverse range of activities, such as
combining curricular and non-curricular activities, awareness raising, supporting those with
experiences and encouraging those who had no prior experiences. In particular, there is a lack of
data and insufficient understanding of students’ experiences including the relative importance of
extra-curricular activities and informal enterprise experiences. Thirdly, there is a lack of
consistent data on entrepreneurship education and related activities available at the city-region
level encompassing universities’ organisational boundaries.
Given the growing role of city-regions in local economic governance in England, and the
increasing attention focused towards entrepreneurial-based local development, the student-level
data and the results presented in this study contribute to an improved future strategic
development policy. Furthermore, greater access to and use of cross-HEI data on graduates’
destinations and the roles played by local intermediaries (including local incubators) could
improve understanding of the impact of co-organised training courses at the city-region level on
strategic development.
The findings of the study highlight the need to develop a broader and more integrated
conceptualisation of university-based entrepreneurial ecosystems. University-based
entrepreneurial ecosystems need to be seen as a wide spectrum consisting of education and extra
curriculum activities as well as the more usual conceptualisation based on the commercialisation
of research and spin-off firm formation. Entrepreneurial activities encompass not only
technology-based start-ups but also other areas such as social enterprise and start-ups in creative
industry. Different types of knowledge creation, skills and competences are needed in order to
shape entrepreneurial developments and stimulate entrepreneurial propensities, and should be
identified as an integral part of university-based entrepreneurial ecosystems. For example, an
important issue appears to be the need for universities to use outreach policies and activities to
engage students with private sector enterprises, including alumni networks.
Through learning-by-doing activities students can improve their entrepreneurial and
enterprise skills. We further argue that HEIs should be aware of the important roles that
university-based entrepreneurial ecosystems can have in addressing the development problems
experienced by their city-regions. HEIs should be more aware of the important roles that they
have in influencing student entrepreneurial behaviour, and should communicate their
15
contributions more effectively. The impacts that entrepreneurship education has on business
start-ups and entrepreneurial activities in general need to be integrated in a broad
conceptualisation of the university-based entrepreneurial ecosystems. Future research should
investigate and improve understanding of students’ perceived barriers and challenges to
becoming an entrepreneur. The trajectories and impact of graduate start-ups of local
development are also areas that need further examination as part of the long term evolution of
university-based entrepreneurial ecosystems. Greater understanding of the processes of
entrepreneurial training and of the wider impacts on skills and the economy will can be used to
enhance the functioning and sustainability of entrepreneurship ecosystems at the city-region
level.
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17
Table 1: Active and surviving firms
Number of active firms
Spin-offs with some HEI
ownership
Formal spin-offs,
not HEI owned Staff start-ups Graduate start-ups
2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09
University of Bristol 20 21 7 6 2 1 2 3
University of the West
of England, Bristol 1 1 1 1 14 11 41 30
Number still active which have survived at least 3 years
Spin-offs with some HEI
ownership
Formal spin-offs,
not HEI owned Staff start-ups Graduate start-ups
2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09
University of Bristol 17 16 7 6 1 1 2 3
University of the West
of England, Bristol 1 1 1 1 9 5 15 13
Table 2: Employment and turnover of active firms
Estimated current employment of all active firms (FTE)
Spin-offs with some HEI
ownership
Formal spin-offs,
not HEI owned Staff start-ups Graduate start-ups
2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09
University of Bristol 120 92 49 72 28 28 10 12
University of the West
of England, Bristol 0 0 2 2 30 28 174 162
Number still active which have survived at least 3 years
Spin-offs with some HEI
ownership
Formal spin-offs,
not HEI owned Staff start-ups Graduate start-ups
2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09
University of Bristol 6400 3539 532 450 300 300 830 508
University of the West
of England, Bristol 0 0 100 100 2692 2395 44217 12555
18
Table 3: Estimated external investment received (£ thousands)
Spin-offs with some HEI
ownership
Formal spin-offs,
not HEI owned Staff start-ups Graduate start-ups
2009/10 2008/09 2009/10 2008/09 2009/10 2008/09 2009/10 2008/09
The University of
Bristol 7800 8790 8000 3000 0 0 0 0
University of the West
of England, Bristol 0 0 0 0 0 0 25 5045
Table 4: Enrolment status of sample population
UWE UoB
Number % of respondents Number % of respondents
UG Full-time 930 77 730 64
UG Part-time 46 4 11 1
PG Full-time 130 11 312 27
PG Part-time 88 7 70 6
UG Exchange student (< a year) 3 0 13 1
PG Exchange student 3 0 3 0
Other 10 1 5 0
Totals 1210 100 1144 100
Response rate 4.84 6.36
19
Table 5: Gender of sample population
Gender UoB (N=1144)
%
UWE (N=1210)
%
Total (N=2354)
%
Male (N=903) 39.4 37.4 38.4
Female (N=1451) 60.6 62.6 61.6
Table 6: Age range of sample population
Age
UoB
(N=1144)
%
UWE
(N=1210)
%
Total
(N=2354)
%
17-21 52.3 45.9 48.9
22-26 31.6 30.1 30.7
27-31 8.0 8.6 8.3
31-35 2.5 5.0 3.7
36-40 1.5 3.3 2.4
41-plus 4.1 7.2 5.6
Total 100 100 100
Table 7: Highest level of education of father and mother by institution
Highest level
UoB
%
UWE
%
Father
primary 4.5 7.4
secondary 29.3 47.1
tertiary 66.3 45.5
Mother
primary 4.4 6.9
secondary 33.2 51.6
tertiary 62.4 41.6
Total 100 100
Table 8: Region of origin of student sample population
UoB
%
UWE
%
Total
%
UK home 76.7 85.2 81.2
EU 8.6 7.2 7.8
International (non EU) 13.2 6.4 9.7
Other 1.6 1.2 1.3
20
Table 9: Frequency of respondents by Faculty and University
Respondents by Faculty/Division
(N=2354)
% Respondents
by Faculty/Division
UoB (48.6%)
Arts 9
Engineering 8
Medical and Vet 5
Medicine and Dentistry 3
Science 13
Social Science and Law 11
UWE (51.4%)
Business and Law 10
Creative Arts, Humanities and Education 14
Environment and Technology 11
Health and Life Sciences 14
Hartbury College 2
Other 1
21
Table 10: Entrepreneurial orientation
UoB
(N=1144)
UWE
(N=1210)
Number % of institution Number % of institution
Already started my own business
28
2
50
4
Yes, within five years
} =1 for
“Start-up
soon”
78 7 161 13
Yes, within ten years 74 6 81 7
Yes, in the future, not decided when 230 20 303 25
No }
=0 for
“Start-up
soon”
373 33 345 29
Unsure 361 32 270 22
Totals 1144 100 1210 100
Total intending at any time 410 36 595 49
My attitude towards setting up my own business has changed since I enrolled in my university degree
I was initially very positive but now I am negative 14 1.4 %
I was slightly positive but now I am negative 51 5.1 %
My attitude has not changed 770 76.9 %
I was slightly negative but now I am positive 138 13.8 %
I was very negative but now I am positive 28 2.8 %
22
Table 11: Ordinary logistic regression: desire to start-up a businessa
(1) (2)b (3)
c (4)
d (5)
e
N 1638 1638 1638 1638 1638
Male 2.135***
(0.227)
2.141***
(0.228)
2.144***
(0.231)
2.161***
(0.236)
2.291***
(0.324)
Female Control variable
UWE 1.656***
(0.174)
1.728***
(0.188)
1.753***
(0.199)
1.863***
(0.215)
1.349**
(0.204)
Bristol University Control variable
Under graduate 0.799
(0.101)
0.795
(0.101)
0.776**
(0.100)
0.793
(0.105)
0.603***
(0.102)
Post graduate Control variable
Full time 1.397
(0.248)
1.387
(0.247)
1.354
(0.247)
1.388
(0.256)
1.000
(0.236)
Part time Control variable
Dad: Tertiary education – 0.610
(0.165)
0.614
(0.169)
0.610
(0.170)
0.628
(0.224)
Dad: Secondary education – 0.550**
(0.145)
0.546**
(0.145)
0.550**
(0.148)
0.690
(0.240)
Dad: Primary education Control variable
Mum: Lower supervisory and technical
occupations – –
0.313***
(0.138)
0.296***
(0.132)
0.237***
(0.133)
Mum: Unemployed Control variable
Gained enterprise experience while
spending time as an intern – – –
1.857***
(0.336)
1.394
(0.315)
Gained enterprise experience: started up
own business before university – – –
1.654
(0.509)
2.156**
(0.839)
Start business skills – – – – 3.213***
(0.256)
Family member owns a business – – – – 1.683***
(0.248)
Constant 0.647
(0.114)
0.747
(0.210)
0.690
(0.282)
0.533
(0.226)
0.042***
(0.032)
Log pseudo-likelihood -1084.432 -1080.603 -1070.921 -1061.487 -712.426
Wald chi2 75.91*** 83.57*** 102.93*** 121.80*** 725.57***
Notes: a Dependent variable in all these regressions is “Start-up soon”. Odds-ratios are presented with robust standard errors
in parentheses. ***, ** and * signify statistical significance at the 1%, 5% and 10% levels respectively. b
Mother’s education was also included from this regression onwards, but remained consistently statistically
insignificant. c All dad job occupation variables were included from this point onwards with Dad: Unemployed as the control
variable. All variables were consistently statistically insignificant throughout. Also included from this regression
onwards were all the job descriptions of the mother; in this case all jobs descriptions were statistically insignificant
throughout except for Mum: Low sup job, with Mum: Unemployed as the control variable. d Also included from this regression onwards were Gained enterprise experience in full time work, Gained enterprise
experience in part time work while in education and Gained enterprise experience in a formerly organized program,
all of which remained statistically insignificant throughout. e Also included in this regression were issues related to the benefits of going to university, including Qualifications
are important, Personal Development is important, Advancement of career opportunities, Academic Knowledge,
Technical knowledge and Management skills, all of which were not found to be statistically significant.
23
Table 12: Ordered logistic regression: changing attitudes to setting up a business
(1) (2)a (3)
b
N 1001 1001 969
Male 1.189
(0.186)
1.192
(0.193)
1.086
(0.182)
Female Control variable
Undergraduate 1.453*
(0.313)
1.476*
(0.321)
1.622**
(0.367)
Post graduate Control variable
Full time 1.226
(0.320)
1.254
(0.330)
1.124
(0.307)
Part time Control variable
Perceives the current economic situation encourages
them to start up a business
1.868***
(0.450)
1.860**
(0.453)
1.747**
(0.441)
Perceives the current economic situation neither encourages
nor discourages them to start up a business Control variable
Perceives the current economic situation discourages
them to start up a business
0.669**
(0.111)
0.683**
(0.114)
0.726*
(0.125)
Think communication skills needed to become
an entrepreneur –
1.327*
(0.216)
1.433**
(0.246)
Biggest challenge to becoming an entrepreneur is
identifying markets – –
1.195**
((0.107)
Believes UWE education has helped them develop the
competences to address challenges of being an entrepreneur – –
1.777***
(0.170)
Cut 1 -3.925
(0.371)
-4.167
(0.642)
-2.868
(0.744)
Cut 2 -2.330
(0.286)
-2.571
(0.597)
-1.245
(0.702)
Cut 3 2.070
(0.281)
1.865
(0.593)
3.422
(0.716)
Cut 4 4.025
(0.331)
3.862
(0.617)
5.514
(0.742)
LR chi2 27.88*** 36.50*** 80.08***
Log likelihood -773.27 -768.96 -712.42 Notes: Odds-ratios are presented with robust standard errors in parentheses. ***, ** and * signify statistical
significance at the 1%, 5% and 10% levels respectively. a Also included in this regression onwards are Motivation, Team work, Negotiation skills, Management skills, Finance
skills, Market knowledge, Technical competency and Innovative capacity. None of these were found to be
statistically significant at the 5% level. b Also included in this regression are the importance of entrepreneurial challenges associated with finance, having a
business idea, being competitive in the market, working as a team and acquiring management skills and knowledge.
None of these were found to be statistically significant at the 10% statistical significance level.
24
Table 13: Percentages finding extracurricular activities useful
Short/intensive
programme on
entrepreneurship and
enterprise skills
1:1 drop in
session on
enterprise
advice
Ideas and
social
networking
challenge
Bizidea
competition
Business
incubator
Local
enterprise
network
Not useful (1) 32 32 30 36 37 43
(2) 12 18 20 15 17 12
Neither / nor (3) 20 21 24 24 21 19
(4) 19 18 16 15 14 12
Very useful (5) 17 11 10 12 11 14
(4) + (5) 36 29 26 27 25 26
Table 14: Percentages finding extra-university activities useful
Local
enterprise
activity in
private
sector
Volunteer
enterprise
activities
International
enterprise
activity in
private sector
International
volunteer
enterprise
activities
Learning
through
media
Learning
through
friends
Buying &
selling on
Internet
(e.g. Ebay)
Not useful (1) 12 11 13 16 15 12 22
(2) 13 14 19 17 27 25 23
Neither / nor (3) 33 30 25 30 30 33 28
(4) 22 24 17 16 17 18 15
Very useful (5) 20 20 26 23 11 12 11
% (4) + (5) 42 44 43 39 28 30 26
25
Recent UWE Economics Papers
See http://www1.uwe.ac.uk/bl/research/bristoleconomics/research for a full list
2015
1505 University entrepreneurship education experiences: enhancing the entrepreneurial ecosystems in a
UK city-region
Fumi Kitagawa, Don J. Webber, Anthony Plumridge and Susan Robertson
1504 Can indeterminacy and self-fulfilling expectations help explain international business cycles? Stephen McKnight and Laura Povoledo
1503 User-focused threat identification for anonymised microdata
Hans-Peter Hafner, Felix Ritchie and Rainer Lenz
1502 Reflections on the one-minute paper
Damian Whittard
1501 Principles- versus rules-based output statistical disclosure control in remote access environments
Felix Ritchie and Mark Elliot
2014
1413 Addressing the human factor in data access: incentive compatibility, legitimacy and cost-effectiveness
in public data resources
Felix Ritchie and Richard Welpton
1412 Resistance to change in government: risk, inertia and incentives
Felix Ritchie
1411 Emigration, remittances and corruption experience of those staying behind
Artjoms Ivlevs and Roswitha M. King
1410 Operationalising ‘safe statistics’: the case of linear regression
Felix Ritchie
1409 Is temporary employment a cause or consequence of poor mental health?
Chris Dawson, Michail Veliziotis, Gail Pacheco and Don J Webber
1408 Regional productivity in a multi-speed Europe
Don J. Webber, Min Hua Jen and Eoin O’Leary
1407 Assimilation of the migrant work ethic
Chris Dawson, Michail Veliziotis, Benjamin Hopkins
1406 Empirical evidence on the use of the FLQ formula for regionalizing national input-output tables: the case of the
Province of Córdoba, Argentina
Anthony T. Flegg, Leonardo J. Mastronardi and Carlos A. Romero
1405 Can the one minute paper breathe life back into the economics lecture?
Damian Whittard
1404 The role of social norms in incentivising energy reduction in organisations
Peter Bradley, Matthew Leach and Shane Fudge
26
1403 How do knowledge brokers work? The case of WERS
Hilary Drew, Felix Ritchie and Anna King
1402 Happy moves? Assessing the impact of subjective well-being on the emigration decision
Artjoms Ivlevs
1401 Communist party membership and bribe paying in transitional economies
Timothy Hinks and Artjoms Ivlevs
2013
1315 Global economic crisis and corruption experience: Evidence from transition economies
Artjoms Ivlevs and Timothy Hinks
1314 A two-state Markov-switching distinctive conditional variance application for tanker freight returns
Wessam Abouarghoub, Iris Biefang-Frisancho Mariscal and Peter Howells
1313 Measuring the level of risk exposure in tanker shipping freight markets
Wessam Abouarghoub and Iris Biefang-Frisancho Mariscal
1312 Modelling the sectoral allocation of labour in open economy models
Laura Povoledo
1311 The US Fed and the Bank of England: ownership, structure and ‘independence’
Peter Howells
1310 Cross-hauling and regional input-output tables: the case of the province of Hubei, China
Anthony T. Flegg, Yongming Huang and Timo Tohmo
1309 Temporary employment, job satisfaction and subjective well-being
Chris Dawson and Michail Veliziotis
1308 Risk taking and monetary policy before the crisis: the case of Germany
Iris Biefang-Frisancho Mariscal
1307 What determines students’ choices of elective modules?
Mary R Hedges, Gail A Pacheco and Don J Webber
1306 How should economics curricula be evaluated?
Andrew Mearman
1305 Temporary employment and wellbeing: Selection or causal?
Chris Dawson, Don J Webber and Ben Hopkins
1304 Trade unions and unpaid overtime in Britain
Michail Veliziotis
1303 Why do students study economics?
Andrew Mearman, Aspasia Papa and Don J. Webber
1302 Estimating regional input coefficients and multipliers: The use of the FLQ is not a gamble
Anthony T. Flegg and Timo Tohmo