Entrepreneurship In Urban And Rural Switzerland Similar Or Worlds Apart

Description
Brief outline regarding entrepreneurship in urban and rural switzerland similar or worlds apart.

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287
14. Entrepreneurship in urban and
rural Switzerland: similar or worlds
apart?
Heiko Bergmann and Daniel Baumgartner
RESEARCH BACKGROUND AND AIM OF THE
ANALYSIS
Entrepreneurship research, either explicitly or implicitly, mainly deals with
entrepreneurship in agglomerations or urban areas. There are a number
of reasons why cities may be particularly conducive to entrepreneurship
(Bosma et al. 2008). People on average have higher levels of education, and
regional demand is higher and more diversifed. Most new frms produce for
a regional market, which explains why the development, structure and level
of regional demand have a strong infuence on the level of entrepreneurial
activities (Reynolds et al. 1994). In most countries, there is a close rela-
tionship between the regional level of income and the population density,
contributing to higher start- up rates in urban areas. Moreover, cultural and
economic diversity is higher (Florida 2002) and ‘innovation appears to be a
large city phenomenon’ (Feldman and Audretsch 1999, p. 415).
However, few studies investigate the characteristics and factors infuenc-
ing start- ups in rural areas beside the agricultural sector (McElwee et al.
2005). Kalantaridis (2004) fnds that entrepreneurial activities in selected
European rural areas are clustered in diferent behaviour patterns strongly
depending on the characteristics of entrepreneurs and a supportive local
context within the region. Empirical studies further focus on the character-
istics of entrepreneurs in rural areas (for example, Vaillant and Lafuente
2007), where special attention has been given to the entrepreneurial poten-
tial of immigrants into rural areas (Guelsuemser et al. 2008; Kalantaridis
and Bika 2006). Other studies explore the role of the socio- institutional
‘milieu’ that rural entrepreneurs interact with (for example, Meccheri
and Pelloni 2006; Stathopoulou et al. 2004; Vaillant and Lafuente 2007).
Agglomeration areas, however, generally seem to ofer a more favourable
entrepreneurial milieu.
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While it may be true that agglomerations are the focal point of entre-
preneurship, there is also a growing awareness that entrepreneurship is
a vital ingredient for rural development. In most developed countries,
agriculture is no longer the backbone of rural economies. The OECD
(2006) has included entrepreneurship and endogenous economic growth
as a main focus in its New Rural Paradigm. The Swiss Secretariat for
Economic Afairs (SECO) even goes a step further. In its report on the new
law on regional policy in Switzerland, the stimulation of entrepreneurship
is at the top of a number of policy measures that should lead to stronger
endogenous economic development in the non- urban areas of the country.
The defnition of entrepreneurial behaviour in these areas as ‘the willing-
ness and the ability to undertake something’ (Expertenkommission 2003,
p. 100), however, remains somehow unsatisfactory.
The general aim of this contribution is to broaden our understanding
of entrepreneurship in rural areas in Switzerland. So far, determinants
and characteristics of entrepreneurship have mostly been studied either in
general or in agglomeration areas only. Our key interest is whether these
determinants and characteristics also prevail in rural areas or if there
are diferences between urban and rural entrepreneurship in the case of
Switzerland. In order to do so, we look at diferent phases of the entrepre-
neurial process and address the following three research questions. First,
we aim to check for diferent attitudes towards entrepreneurial activities
of individuals in urban and rural areas in Switzerland. Second, we aim to
identify diferences in the determinants to start a new business in urban
and rural areas in Switzerland. Finally, we aim to compare the outcomes
of the entrepreneurial process in terms of new frm characteristics in urban
and rural areas in Switzerland.
The chapter is divided into six sections. After this introduction, the
second section gives an overview of the literature and presents the concep-
tual framework underlying the analysis. The next section discusses data
and methods used. The fourth section presents the results of our analysis,
which are then discussed in the following section. The fnal section con-
cludes and gives an outlook on further research on the topic.
FINDINGS FROM PREVIOUS STUDIES AND
CONCEPTUAL FRAMEWORK
Spatial Patterns of Entrepreneurial Activity in Rural and Urban Areas
Most investigations of regional entrepreneurial activities fnd a positive
relationship between population density and entrepreneurial activity.
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Agglomerations usually have higher levels of entrepreneurial activity than
rural areas (see Bergmann and Sternberg 2007; Fritsch and Falck 2007;
Reynolds et al. 1994). However, the distinction between urban and rural
areas in multivariate analyses, which are prevailing today, is somewhat
unsatisfactory: If taken into account at all, the urban–rural diference is
only treated as one variable. Papers on regional entrepreneurship varia-
tions usually investigate urban and rural areas in the same model while
only taking account population density or a dummy variable for agglom-
erations in contrast to rural areas (Bergmann and Sternberg 2007; Naudé
et al. 2008). Such an approach assumes that the basic processes and infu-
encing factors are the same in both types of regions.
However, there is some evidence that the entrepreneurial process difers
in urban and rural areas at some points, for example:
Individual motivations for entrepreneurial activities: in rural areas ?
independence is an important motivation for starting a business
(Westhead and Wright 1999). It can be assumed that these busi-
nesses are less growth oriented than purely opportunity driven
ventures, which are more prevalent in metropolitan areas (Bosma
et al. 2008).
Sectoral distribution of entrepreneurial activities: while agriculture- ?
related businesses are more prevalent in rural settings, high-
technology start- ups are rare (North and Smallbone 2000).
Drawing on evidence from New Zealand, new frms in peripheral
regions are relatively more often founded in manufacturing indus-
try and less often in the business services sector (Tamásy and Le
Heron 2008).
Institutional and physical environment for entrepreneurial activities: ?
potential entrepreneurs in rural areas may face higher transaction
cost, for example, for venture capital due to physical distances and
a lower quality of infrastructure, which limits their growth potential
(Keeble 1993). Furthermore, the institutional framework that aims
at supporting entrepreneurial activities in rural areas may not ft the
needs of potential entrepreneurs (Meccheri and Pelloni 2006).
Thus, the general perception seems to be that start- ups – as a measure
of entrepreneurial activity – are fewer in number in rural areas and have
a lower growth potential, although there is also some contrasting evi-
dence. Stam (2005), for example, does not fnd a general spatial pattern
of fast- growing young frms (‘gazelles’) in the Netherlands. Regions with
relatively high numbers of gazelles can be found in the highly urbanized
areas as well as in accessible rural areas. However, gazelles are slightly
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under- represented in remote rural areas. This result demonstrates that
rural areas are not homogeneous.
Conceptual Framework
In order to assess entrepreneurial activities in rural and urban Switzerland
we use the research framework for rural entrepreneurship proposed by
Stathopoulou et al. (2004) as a starting point for our analysis. Entrepreneur-
ship is conceptualized as a process consisting of three main stages:
First ? , the conception- stage: this phase includes the perception or the
creation of an economic opportunity. Potential entrepreneurs have
to discover new or evaluate existing business opportunities to start
up a business venture (Shane 2003).
Second ? , the realization- stage: in this second stage, potential entre-
preneurs engage in entrepreneurial activities and start to exploit the
opportunities that have been discovered and evaluated in the frst
stage. In this stage, the often described entrepreneurial capacities
– for example, risk- awareness (Knight 1921) or allocation and coor-
dination of scare resources (Casson 2003) – have to unfold in order
to successfully set up a new business venture.
Third ? , the operation stage: the operation of the newly founded busi-
ness venture is the last stage of the start- up process in the model.
This stage refects the results of a successful entrepreneurial process
in the foregoing stages.
This separation into three diferent stages is similar to the separation
used within the Global Entrepreneurship Monitor (GEM). The main dif-
ference is that in the GEM project the operation stage is further separated
into a young business stage and an established business stage (Reynolds
et al. 2005, p. 209f). Stathopoulou et al. (2004) state that the three stages
are embedded in an ‘entrepreneurial milieu’. Such a milieu is characterized
by assets of the physical (for example, natural resources, landscape), the
socio- institutional (for example, social capital, local and regional govern-
ance) and the economic (for example, business networks, infrastructure)
environment in which entrepreneurs are embedded. This milieu separates
rural from urban entrepreneurship and consequently leads to observable
diferences in the entrepreneurial process in rural and urban areas. Hence
rural entrepreneurs are persons ‘living in a rural location and the difer-
ence between them and an urban entrepreneur may be found in the efects
of rurality on the entrepreneurial process’, as Stathopoulou et al. (2004,
p. 412) write.
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Starting from an understanding of entrepreneurship as a spatially
embedded three- stage process, we add three further elements to our
research framework. First, we assume that the understanding of the
entrepreneurial milieu as presented by Stathopoulou et al. (2004) is also
suitable for entrepreneurship in urban areas, even if the two environments
may have diferent characteristics and may difer in their importance for
successful entrepreneurial processes. Support for this assumption can
by found in the ‘innovative milieux’ literature (Camagni 1995; Maillat
1998), which adapts the concept of the regional milieu for rural and urban
regions similarly. Second, we consider the fact that the entrepreneurial
process is not only shaped by the entrepreneurial milieu. It is also the
individual decision to enter the entrepreneurial process that may difer
between urban and rural entrepreneurial milieux. We generally distinguish
between person- related determinants and regional determinants that
afect the decision to enter the entrepreneurial process. Third, we defne
two main levels of analysis (see Figure 14.1). While in the frst and the
second part of the entrepreneurial process the entrepreneur is the suitable
level of analysis, the level of the enterprise is our level of analysis for the
third stage.
In all three stages, person- related and regional determinants infuence
Entrepreneurial milieu (urban or rural)
Person related
determinants
1st stage
‘conception’
3rd stage
‘operation’
Regional
determinants
Entrepreneur level Enterprise level
2nd stage
‘realization’
Source: Adapted from Stathopoulou et al. (2004).
Figure 14.1 Entrepreneurship as a three- stage process
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the entrepreneurial process. We briefy discuss these two groups of deter-
minants in the following paragraphs.
Person- related Determinants of Entrepreneurial Activity
There has long been a debate in entrepreneurship research as to why some
people start a business whereas others prefer to stay in paid employment.
Labour economic approaches assume that the employment decision is
mainly rational: People who intend to pursue gainful employment are
faced with the choice of independent and dependent employment (Knight
1921, p. 271). The decision as to which of these two types of gainful
employment is chosen is infuenced by their relative attractiveness. This
depends on the level of proft or expected pay, the current employment
situation, other person- related characteristics and regional and national
framework conditions.
The employment behaviour of women difers from that of men, and
there are clear gender- specifc diferences in entrepreneurial activities. In
most industrialized nations, including Switzerland, women’s entrepreneur-
ial propensity is lower than men’s (Minitti et al. 2005). Women’s working
lives include more interruptions and part- time work, which is why women
have less opportunity than men do to build up the professional expertise
and experience necessary for launching a start- up. Traditional role models
and the selection of vocational qualifcations and academic studies also
infuence the entrepreneurial propensity of women (Carter 1997).
The relationship between the level of education and entrepreneurial
propensity demonstrates contrasting tendencies. On the one hand, people
with a high level of education tend to have better prospects on the labour
market and higher earnings potential than less highly qualifed people.
According to this logic, entrepreneurial propensity should decline as the
level of education rises. On the other hand, many self- employed activities
require a high level of knowledge and skills. Empirical investigations show
that the second relationship predominates and that a positive correla-
tion between the level of education and entrepreneurial propensity can
therefore be assumed (Davidsson and Honig 2003; Robinson and Sexton
1994).
Similar to the level of education, there are diferent tendencies in rela-
tion to age and entrepreneurial propensity. One the one hand, expertise,
professional experience, self- confdence and the amount of capital avail-
able usually increase with age, which makes entrepreneurial activity
more probable (Bates 1995). On the other hand, the level of professional
and family embeddedness increases with age. Accordingly, the planning
horizon for the remainder of the working life decreases, which would tend
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to weigh against entrepreneurial activity. The impact of these two infu-
ences on the decision to launch a start- up can be analysed using life- cycle
models (Schulz 1995, p. 114f). Overall, the two contrasting infuences
demonstrate a reversed U- shaped relationship between age and entrepre-
neurial propensity, which is confrmed by most empirical studies. Initially,
entrepreneurial propensity increases with age, reaches its peak between
the ages of 35 and 40 approximately and then drops of towards the end of
the working life (Bates 1995; Welter and Rosenbladt, 1998). Former entre-
preneurs or business angels can be expected to have the knowledge and
the capability to launch a new start- up and it can therefore be assumed
that they have a higher entrepreneurial propensity than people without
such experience. Empirical studies support this conjecture (Davidsson and
Honig 2003; Wagner 2003).
There are contradictory infuences of unemployment on the level of
entrepreneurial activity. The pressure to go into self- employment is
greater for the unemployed than for those in employment. On the other
hand, jobless people often do not have the necessary skills, experience and
knowledge to do so. However, overall the positive infuence of personal
unemployment on the likelihood to become an entrepreneur seems to
prevail (Ritsilä and Tervo 2002).
Regional Determinants of Entrepreneurial Activity
The general economic framework conditions in a region have a consider-
able infuence on the level of regional entrepreneurial activities. Most new
frms produce for a regional market, at least in the start- up phase, which
explains why the development, structure and level of regional demand
has a strong infuence on the level of entrepreneurial activities. Therefore,
empirical investigations often include such factors as the purchasing
power or the density of a region’s population.
Microeconomic decision models show that people become self- employed
when they expect their self- employed activity to generate an adequate level
of proft (Knight 1921). As regional demand increases, therefore, more
frms are typically launched, as the high level of demand makes self-
employed activities lucrative. In a comparison of studies in six European
countries (Germany, France, Ireland, Italy, Sweden, the UK) and the
USA, Reynolds et al. (1994, p. 449) conclude that an increase in demand
makes the largest contribution to explaining regional diferences in entre-
preneurial activities: ‘No process is more fundamental than reactions to
increased demand for goods and services’ (Reynolds et al. 1994, p. 446).
Studies that are more recent, also demonstrate the infuence of demand
factors on the level of entrepreneurial activity (Armington and Acs 2002;
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Bergmann and Sternberg 2007; Fritsch and Falck 2007). Besides the
increase in regional demand, the absolute level of regional demand can
exert an infuence on entrepreneurial activities. Certain types of start- up,
such as in the feld of high- value person- related services, may only be
viable in regions where many wealthy customers live.
To sum up, there are a number of personal and regional determinants
that infuence the propensity of individuals to enter the entrepreneurial
process. Most of the evidence, however, is based on empirical studies that
do not assume diferent efects in urban and rural areas. It is therefore dif-
fcult to make explicit assumptions about entrepreneurship in rural areas
and to develop a specifc ‘rural entrepreneurship’ model for Switzerland.
Hence, our study is of an exploratory nature and tries to uncover difer-
ences in the entrepreneurial process between urban and rural areas.
DATA AND METHODS
Diferences in entrepreneurship between urban and rural milieux may
appear at two levels of analysis. In the frst and the second stage of the
entrepreneurial process, such diferences may be related to the entrepre-
neur as the driving force of new venture creation. In the third stage of
the entrepreneurial process, diferences may occur in the characteristics
of newly founded business ventures, that is, at the enterprise level. The
following analysis is therefore based on two diferent data sources: data
from the adult population survey of the Global Entrepreneurship Monitor
(GEM) and the Swiss statistics of company demographics UDEMO.
The main source of data to investigate urban–rural diferences in the
conception and the realization stage of the entrepreneurial process is the
adult population survey (APS) of the GEM for Switzerland from the years
2005 and 2007. The GEM is an international research project that aims to
measure, compare and explain entrepreneurial activity in diferent coun-
tries of the world. Previous publications have demonstrated that GEM
data, originally intended for international comparisons, can also be used
for interregional analyses within a country, as we do in this contribution
(Bergmann and Sternberg 2007; Rocha and Sternberg 2005). The general
methodology of the GEM APS is described in Reynolds et al. (2005). The
basic unit of analysis in the GEM project is the entrepreneur. The GEM
APS surveys for Switzerland consist of random samples of 5456 (2005)
and 2148 (2007) persons who were interviewed by telephone. The high
numbers of interviewed persons allow a regional analysis of the GEM
data for Switzerland. The availability of micro- level data is a major advan-
tage of the GEM project since it makes it possible to combine individual
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characteristics of the founder and the business with characteristics of the
region where the person lives in a single analysis.
We use the Swiss statistics of company demographics UDEMO to
investigate diferences between urban and rural areas in third stage
of the entrepreneurial process. Unfortunately, this database only con-
tains company- related characteristics and no information about the
founder itself. The UDEMO database is based on the ‘Betriebs- und
Unternehmensregister’ (plant and company register), which is adminis-
tered by the Swiss Federal Statistical Ofce. It captures the names, busi-
ness activities (that is, industry sector of the venture, classifed according
to NOGA
1
- categories), legal structure, number of employees and spatial
location of all plants and companies in Switzerland from 1999 to 2006
(Grossi 2005). All new entries which are commercially active and which
work for at least 20 hours per week can be identifed and are included in
the UDEMO database as ‘foundations ex nihilo’.
The data sources contain information about the place of residence of
the entrepreneur (GEM) or the location of the newly founded enterprise
(UDEMO). Both data samples hence can be split into an urban and a rural
sample. We use the classifcation of Swiss statistics to distinguish between
urban and rural areas in Switzerland (Schuler et al. 2004). Following this
classifcation, rural areas are the ‘residual’ municipalities outside the core
cities of agglomerations and the agglomeration municipalities according to
the defnition applied by the Swiss Federal Statistical Ofce (BfS) in 2000.
This defnition is mainly based on commuter statistics, population density
and sectoral structure of the local economy (for more details see BfS 2005).
Table 14.1 shows the distribution of municipalities and population
between urban and rural areas in Switzerland. Urban areas account for
73 per cent of the population but only 21 per cent of the total area of
Switzerland. Rural areas, on the other hand, show an administratively
fragmented picture since more than two- thirds of all Swiss municipalities
are classifed as rural. We use a combination of descriptive and analytical
methods to address the research questions of this contribution. We use
descriptive statistics based on GEM data to provide answers to the frst
research question about entrepreneurial attitudes in urban and rural
Switzerland.
The second research question on the determinants of entrepreneurial
activities in urban and rural areas is also investigated on the basis of the
GEM dataset. The individual data from the telephone survey are com-
bined with regional data from ofcial statistics in order to assess personal
related and regional determinants of entrepreneurial activity. Early- stage
entrepreneurial activity, which was formerly known as the TEA- rate in
the GEM- project, acts as dependent variable in the multivariate analyses.
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Early- stage entrepreneurial activity acts as a proxy for the entrepreneurial
activities in the second stage of the entrepreneurial process. This measure
encompasses nascent entrepreneurs but also active frms that have been
set up within the past three and a half years (Reynolds et al. 2005).
2
In
order to identify potential diferences between urban and rural areas we
conduct separate logistic regression models for both types of areas and
compare the results. On the basis of the discussion in the previous chapter
we include the following person- related variables as dependent variables:
gender; ?
age (in years) and in squared form. The squared value of age (in ?
years) is included as a separate variable in order to be able to iden-
tify non- linear relationships between age and start- up activity;
educational attainment (in which three levels are distinguished: ?
vocational training, grammar school, tertiary education) in contrast
to people without such education;
employment status, in terms of two binary variables (unemployed, ?
homemaker) in contrast to people who are working;
indicators of previous entrepreneurial activity, namely, former busi- ?
ness ownership and business angel activity.
The following regional variables are included as dependent variables:
self- employment rate: self- employed persons as percentage of all ?
gainfully employed persons in the canton in 2000 (source: Swiss
Federal statistical ofce);
purchasing power in 1000 CHF per capita in the canton in 2005 ?
(source: GfK- Group, Nuremberg);
Table 14.1 Urban and rural areas in Switzerland in 2000
Number
of munici-
palities
Percent-
age of
munici-
palities
Share of
popu-
lation
(in 1’000)
Share of
popu-
lation
(percent)
Share
of area
(absolute,
km
2
)
Share
of area
(percent-
age)
Urban
Areas
979 34 5 345 73 9 006 21
Rural
Areas
1 917 66 1 943 27 30 982 79
Total 2 896 100 7 288 100 39 988 100
Source: Achermann (2005).
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The third research question is examined using a combination of the two
databases. As a frst step, we compare the outcomes of the entrepreneurial
process in rural and urban Switzerland. In this regard, we analyse difer-
ences in start- up rates in urban and rural areas on the basis of the UDEMO
and the GEM dataset. As a second step, we focus on the outcomes of the
entrepreneurial process, by specifcally looking at business sectors that can
be assumed to have a high impact on regional development:
Entrepreneurial activities ? in sectors that apply new technologies:
entrepreneurship in business sectors that apply new technolo-
gies and procedures such as ICT services and in particular the
high- technology sector positively infuences regional development
(Audretsch and Keilbach 2005). In order to identify sectors that
apply new technologies within the UDEMO database we use the
industry classifcation by Duemmler et al. (2004). The authors use
the industry classifcation of the OECD (2001) in order to identify
high- technology industries on the base of the NOGA classifcation.
They further add some NOGA activities within fnancial services to
the part of business activities that apply new technologies.
Entrepreneurial activities in sectors with ? high export orientation:
economic activities in sectors with high export orientation have been
identifed as an important driver for endogenous economic develop-
ment especially in rural regions in Switzerland (Buser et al. 2005).
Balmer et al. (2007) have identifed industry sectors with high export
orientation. The authors use a set of 24 indicators provided by of-
cial statistics combined with data internally generated by the Credit
Suisse banking institute to identify the extent of export- orientation
of 28 industry sectors.
As a last step, we compare results from the GEM project regarding
the characteristics of new businesses in urban and rural business with the
distribution of new business in sectors, which apply new technologies and
have a high export orientation on the basis of the UDEMO dataset.
RESULTS
Conception Stage: Attitudes towards Entrepreneurship in Urban and Rural
Areas
In order to analyse possible diferences in the conception stage of the
entrepreneurial process we analyse the attitudes of the general population
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towards entrepreneurial activities in rural and urban areas. In this regard,
we focus on the perception of opportunities, the acquaintance with other
entrepreneurs and the perception of the social approval of entrepreneurial
behaviour.
As the comparison in Table 14.2 shows, there are diferences in the atti-
tudes of the general population towards entrepreneurship between urban
and rural areas. People in urban areas signifcantly more often see good
opportunities for starting a business than people in rural areas. People in
urban areas also more often know somebody personally who started a
business in the past two years. However, this diference is not statistically
signifcant. There is hardly any diference concerning the perception of the
societal recognition of successful entrepreneurs. Overall, there are some
attitude diferences between urban and rural areas although these are
smaller than one might have expected.
Realization Stage: Factors Infuencing Entrepreneurship in Urban and
Rural Areas
In this section, we look at the determinants of entrepreneurial activities in
rural and urban areas. Table 14.2 summarizes the results for two logistic
regression models calculated separately for urban and rural areas. The
results for urban areas are generally in line with the fndings from other
studies, as discussed in the second section of this chapter. Considering
Table 14.2 Attitudes of the general population towards entrepreneurial
activities in urban and rural areas in Switzerland
Urban areas
(n = 5338)
Rural areas
(n = 2216)
Signifcance of
diference
(95% sign.)
In the next six months, there
will be good opportunities
for starting a business in the
area where you live (% yes)
42.7% 35.8% Yes
You know someone
personally who started a
business in the past 2 years
(% yes)
44.2% 40.1% No
In Switzerland, those
successful at starting a new
business have a high level of
status and respect (% yes)
73.1% 72.6% No
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Entrepreneurship in urban and rural Switzerland 299
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person- related variables, men have a higher start- up propensity than
women. There is an inverse U- shaped relationship between age and entre-
preneurial activity, education has a positive efect and being a homemaker
has a negative efect. Former business owners and business angels are
more likely to start a new business than others. Looking at the regional
variables, there is a positive infuence of the regional self- employment
rate and of the regional purchasing power on individual entrepreneurial
propensity.
Model 2 shows the results for rural areas, in which it is evident that
some but not all relationships that can be found for urban areas are also
prevalent in rural areas. We do not fnd an infuence of being a home-
maker, a former business owner or a business angel on entrepreneurial
activity. Furthermore, none of the regional variables are signifcant.
Thus, the infuencing factors on start- ups in rural areas are more difcult
to determine and the results for rural areas are often not in line with the
theoretical predictions. However, it has to be acknowledged that in urban
as well as in rural areas the explanatory power of the models is rather low,
suggesting that in both cases a number of other factors such as chance and
‘triggering events’ are at work.
The main reason given for engaging in entrepreneurial activities difers
only slightly between urban and rural areas. While in urban areas 60.4
per cent of all entrepreneurs start a business because they want to take
advantage of a business opportunity, the respective share is only 56.3 per
cent in rural areas. On the other hand, the percentage of so called ‘neces-
sity entrepreneurs’ is higher in rural areas, although the diferences are not
statistically signifcant.
Operation Stage: Results of the Entrepreneurial Process in Urban and
Rural Areas
In order to examine diferences in the third stage of the entrepreneurial
process, the operation of a new business, we frstly compare the start- up
rates in urban and rural areas on the basis of the UDEMO and the GEM
database. On average 11 442 new frms have been founded per year in
Switzerland between 1999 and 2006 with the highest rate in the year 2000
(total 13 304). If the number of new frms is divided by the population in
the respective area, considerable diferences between frm foundation rates
in rural and urban areas result (see Figure 14.2). We conduct a Kruskal-
Wallis- Test on the means of the rural and urban foundation rates for each
year and fnd the diferences to be signifcant in all years. Firm founda-
tion rates in urban were therefore signifcantly higher than in rural areas
between 1999 and 2006.
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Table 14.3 Determinants of being an early- stage entrepreneur 2005/2007
(summarized results of logistic regressions)
Coef. B Model 1: urban area Model 2: rural area
Wald stat. Sign. Coef. B Wald stat. Sign.
Person- related variables
Gender (1 = male) 0.2954 5.36 * 0.6078 5.44 *
Age (in years) 0.1775 24.10 ** 0.2113 10.04 **
Age squared ?0.0023 26.57 ** ?0.0027 10.94 **
Combined
signifc. of two
age variables
a
** **
Vocational
training (1= yes)
0.8978 8.67 ** 0.5826 1.54
Grammar school
(1= yes)
0.9839 7.89 ** 1.6122 9.28 **
Tertiary education
(1= yes)
1.2715 17.41 ** 0.9923 4.25 *
Unemployed (1=
yes)
0.4962 5.81 * 0.9867 5.51 *
Homemaker (1=
yes)
?0.3682 5.33 * 0.2154 0.55
Former business
owner (1= yes)
1.3358 27.88 ** 0.6160 1.14
Business angel
(1= yes)
0.6720 12.28 ** 0.3569 2.16
Regional variables
Self- employment
rate 2000 (in %)
0.2044 7.71 ** ?0.0414 0.14
Purchasing Power
2005 (in 1000
CHF)
0.0306 4.31 * 0.0269 0.46
Year 2007 (1=
yes)
0.0968 0.52 ?0.1191 0.23
Constant ?10.5616 50.38 ** ?8.4623 9.74 **
N 5338 2216
Nagelkerke
R- Square
0.076 0.063
Notes:
** Signifcant on 99%- level.
* Signifcant on 95%- level.
a
The variable age was introduced into the models in single form and as age- squared
in order to control for non- linear relationships. In all the described models, the age
variable has a positive impact on the probability of starting a new business whereas the
age- squared variable has a negative infuence. Therefore the combined infuence of age
on self- employment takes an inverse U- shaped form. The combined signifcance of the
two age variables is tested by using an adjusted Wald- test.
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301
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In contrast to the UDEMO data, GEM does not measure the number
of companies in a given region but the number of people who are involved
in entrepreneurial activities. The share of people currently trying to start
a new business or who are owners and managers of a new business (TEA
rate) is 6.0 per cent in urban areas compared to 5.0 per cent in rural areas,
although the diference is not statistically diferent. Secondly, we focus
our analysis of new frm foundation rates on business activities that are
presumed to be of high value for regional economic development, namely,
businesses that apply new technologies and procedures and business
activities that show a high export orientation.
Figure 14.2 illustrates diferences between rural and urban start- ups
regarding the share of new frms in sectors with a high or low export orien-
tation. We only consider the start- ups in sectors that have been classifed
by Balmer et al. (2007) as being either export oriented or oriented to the
domestic market. To control for macroeconomic environment variances,
we use the mean value of start- up rates from 2000 to 2005 and, again, nor-
malize the start- up rates with population data in rural and urban areas.
While only 0.12 business ventures per 1000 inhabitants have been founded
in export- oriented sectors in rural areas, the share of export- oriented start-
ups in urban areas is twice as high. The diference between the two rates is
statistically signifcant (Kruskal- Wallis- Test).
3
Figure 14.3 also shows the share of new frm formations in sectors that
apply new technologies. Similar to the classifcation of export- oriented
start- ups we use the classifcation of Duemmler et al. (2004). ‘Innovative
sectors’ are those industry sectors that are most likely to apply new
technologies. We normalize the sample by population distribution and
use again the mean 2000–05 to control for macroeconomic and cyclical
efects.
As Figure 14.3 demonstrates, the rate of new frm formation in sectors
that are likely to apply new technologies in rural areas is less than half the
rate in urban areas. The diference between the two rates is statistically
signifcant (Kruskal- Wallis- Test). It should be noted, however, that so
far we measure diferences between urban and rural areas in terms of the
number of new frms in certain sectors per 1000 inhabitants. Considering
the fact that the new frm formation rate is considerably higher in urban
areas compared to rural areas (Figure 14.2) the above discussed difer-
ences are somewhat mitigated. The higher share of start- ups in exporting
and technology- intensive sectors can to a large extent be explained by the
higher overall start- up rate in urban areas compared with rural areas.
This fnding is also supported by the GEM data. In contrast to the
UDEMO data, the GEM data allows the investigation of the export ori-
entation and use of new technology of the individual frm and not only
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303
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the sector the frm is operating in. The share of new businesses that are
exporting is almost the same in urban and rural areas (Table 14.4) and the
average share of exports is even slightly higher in rural areas. However, the
share of new businesses that use new technologies or procedures is higher
in urban areas compared to rural areas. These fndings are consistent with
the fndings of the UDEMO data where the diference regarding the use
of new technologies is considerably larger between urban and rural areas
than the diference in export activity.
To sum up, the analysis of new frm foundation rates in rural and
urban areas of Switzerland shows diferences in the third stage of the
entrepreneurial process, namely, the operation of a business. The level of
frm births and the level of frm births in industry sectors that apply new
technologies or procedures are both signifcantly lower in rural than in
urban areas.
DISCUSSION
Following the research framework of Stathopouluo et al. (2004), diferent
entrepreneurial milieux lead to diferences in entrepreneurial activities in
urban and rural areas. In the case of Switzerland, we found such difer-
ences in all three stages of the entrepreneurial process. In the conception
stage of the entrepreneurial process, our results suggest that the percep-
tion and creation of business opportunities is shaped by diferent attitudes
towards entrepreneurial activities in rural and urban areas. People in rural
Table 14.4 Characteristics of new businesses (TEA) in urban and rural
areas (GEM survey 2005/2007)
a
Entrepreneurs
(TEA) in urban
areas (n = 337)
Entrepreneurs
(TEA) in rural
areas (n = 98)
Exporting business (% yes) 39.4% 39.5%
Average share of exports 14.5% 15.8%
The technologies or
procedures required for the
product or service has been
available for less than a
year (% yes)
16.3% 9.2%
Note: It should be noted that due to the small sample size none of the observed diferences
are statistically signifcant.
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Entrepreneurship in urban and rural Switzerland 305
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areas are less optimistic about business opportunities than are their urban
counterparts. This result may refect the fact that fewer business opportu-
nities exist in rural areas but it might also be a sign of a generally lower
entrepreneurial self- confdence of potential entrepreneurs or the lack of
successful entrepreneurial role models in rural areas, as in the case of rural
Catalonia (Vaillant and Lafuente 2007). We fnd diferences for some but
not all attitudes investigated. Furthermore, diferences within Switzerland
seem to be smaller than international diferences in entrepreneurial atti-
tudes (Bosma et al. 2008).
Concerning the realization stage, we fnd diferences in the determinants
of entrepreneurial activity. For the most part, the results for urban areas
are in line with theoretical predictions and with the results of other studies
on regional entrepreneurship diferences. The factors infuencing start- ups
in rural areas, on the other hand, are far more difcult to determine. These
start- ups are launched independently of the entrepreneurs’ previous entre-
preneurial experience and regional infuences. This result corresponds to
fndings from other countries (Vaillant and Lafuente 2007). We do not
fnd an infuence of educational attainment and vocational training on the
decision to become an entrepreneur in rural areas. Determinants that have
not been tested in our study – such as the social and family embeddedness
of the start- up process (see also Meccheri and Pelloni 2006) – may be more
important in rural areas instead. Regional determinants of entrepreneurial
activity, such as purchasing power and the regional self- employment rate
which usually deliver signifcant results, fail to contribute to the explana-
tion of the extent to which individuals engage in entrepreneurial activities
in rural Switzerland.
Overall our results indicate that Swiss rural areas provide a milieu for
entrepreneurial activities that is not yet fully understood. In rural areas, the
explanatory power of our models is even lower than in urban areas, suggest-
ing that other factors including chance, ‘triggering events’ and lack of alter-
native employment opportunities are more important than in urban areas.
The explanatory power of our logistic regressions is rather low. However,
this is consistent with other studies that investigate entrepreneurial activ-
ity at the individual level (for example, Bergmann and Sternberg 2007;
Wagner 2003). Other studies that analyse regional start- up rates rather than
individual start- up activities are able to explain more than two thirds of the
variations in start- up rates (for example, Fritsch and Falck 2007). It is much
more difcult to identify individual entrepreneurs rather than to predict the
number of entrepreneurs in a region with known characteristics. There is
always an element of chance or, as Bygrave (1997, p. 3) puts it, a ‘triggering
event’ that makes somebody start a new business. Such triggering events are
very hard to capture in large- scale population surveys.
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We address the fnal stage of the entrepreneurial process – the operation
of a new business venture – mainly by analysing start- up rates and char-
acteristics of new businesses in urban and rural areas. The main fnding
from this analysis is that the share as well as the number of new businesses
that use new technologies is considerably higher in urban compared to
rural areas. It can be assumed that these frms have a greater impact on
regional development than other frms. This fnding is in line with Richard
Florida’s (2002) argument that urban areas are the nest of innovation and
creativity.
However, it has to be acknowledged that, overall, diferences between
urban and rural areas are not as pronounced as one might have expected.
Switzerland is only a small country with a well- developed infrastructure.
In comparison to other countries, even peripheral regions are reasonably
well accessible. There is not one single urban area that dominates the whole
economy. It can be assumed that bigger countries with greater disparities
between urban and rural regions show greater diferences. Although cer-
tainly a special case, there are larger diferences in attitudes and start- up
rates between East and West Germany (Sternberg et al. 2006). Diferences
between urban and rural areas also seem to be larger in Germany than in
Switzerland. (Sternberg and Bergmann 2003).
CONCLUSIONS AND OUTLOOK FOR FUTURE
RESEARCH
The results presented from two Swiss datasets are generally in line with
recent empirical research which fnds entrepreneurial activities to difer
between urban and rural areas in Europe. Our results suggest that in rural
areas the entrepreneurial process and its results are to some degree difer-
ent from the urban area. In the case of Switzerland, these diferences exist
but are not as pronounced as they might be in larger countries with greater
economic disparities. Still, researchers should consider treating urban and
rural areas separately in future empirical studies on entrepreneurship.
Such a separation might not be necessary for all research questions but
should seriously be taken into account in studies of regional diferences
in entrepreneurial activities. Analysing urban and rural areas in the same
model while only taking account of population density or an urban–rural
dummy variable might not be sufcient because this approach assumes
that the basic processes and infuencing factors are the same in both types
of regions.
Our evidence from the Swiss case further supports the conclusion by
Toedtling and Trippl (2005) that there is no ‘one- fts- all’ regional policy
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approach to foster innovation and entrepreneurship. If the new regional
policy in Switzerland aims to support entrepreneurial activities in rural
areas successfully, the diferences identifed in entrepreneurial activities in
an urban milieu at all three stages of the entrepreneurial process should
be taken into account. The generally lower level of new businesses in rural
areas, particularly in innovative business sectors, for example, challenges
traditional policy approaches that aim to stimulate entrepreneurship in
high- technology and R&D oriented industries (see for example, Audretsch
and Feldman 2005). Policy instruments that focus on the sustainable
development of businesses in the manufacturing or tourism sectors may
better ft the rural entrepreneurial milieu. Rural areas, at least provide
‘resources that are highly valuable for a growing part of the society. [Such
resources] can constitute a good business opportunity’ (Dinis 2006, p. 14)
waiting to be exploited by rural entrepreneurs. In order to develop policy
measures that aid rural regions to develop a favourable entrepreneurial
milieu, further research has been set up.
4
The ongoing project aims to
identify determinants that more specifcally describe a favourable entre-
preneurial milieu in Swiss rural regions.
A limitation of our study is that we only use a binary distinction
between urban and rural regions and do not take into account of the fact
that there are diferent types of rural regions even within Switzerland. The
approach was made necessary by the sample size of the GEM survey with
respect to rural regions. Wagner et al. (2009) provide an example of a clas-
sifcation of Swiss regions, based on a cluster analysis that could act as a
starting point for further analyses. Furthermore, due to data limitations in
our multivariate models we only include regional variables at the canton
level. Since some cantons are rather large, this level might be too highly
aggregated to fnd statistically signifcant infuences on entrepreneurial
activities, especially in rural areas which are sparsely populated. Local
conditions might be more important than cantonal conditions for the indi-
vidual decision to start a new business. Further studies should therefore
conduct similar analyses on a lower level of spatial scale.
NOTES
1. NOGA stands for Nomenclature Générale des Activités économiques and is a classifca-
tion of the economic activities in Swiss enterprises in coherent groups provided by the
Swiss Federal Statistical Ofce. The classifcation is modelled after the latest version of
the statistical classifcation of economic activities in the European Community (NACE,
rev. 2). However, it takes into account the needs of various stakeholders in Switzerland,
too.
2. In order to compare the fndings form the GEM and the UDEMO data source, we
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excluded frms that have been founded in the primary sector (agriculture and forestry)
from the GEM data source. We do so mainly because the UDEMO statistics does not
cover frms in the primary sector (Grossi 2005). Furthermore, agriculture and forestry
just contribute 1.3 per cent to the Swiss gross national product and employ only 3.7 per
cent of the total Swiss labour force.
3. In the analysis of the UDEMO dataset export activity of rural frms may be slightly
underestimated since Balmer et al. (2007) do not classify economic activities in the
hotel and restaurant industry as export oriented. Many non- agglomeration areas in
Switzerland, though, depend strongly on foreign tourism and show high start- up rates in
this sector.
4. The research project entitled ‘Entrepreneurship in Swiss Rural Regions: A Spatial
Analysis’ is founded by the Swiss National Science Foundation (SNSF, Grant No.
100013- 118012) and looks at entrepreneurial activities as an important engine for rural
development. In this project, the characteristics of rural entrepreneurship and their
spatial distribution are studied within the rural regions of Switzerland.
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