WHO DO I HIRE FIRST?
THE EFFECT OF FIRST YEAR EMPLOYEES’ SOCIAL CAPITAL
ON FIRM SURVIVAL
BRAM TIMMERMANS
Aalborg University
Department of Business Studies
Fibigerstræde 4,
DK-9220 Aalborg Ø, Denmark
Email: [email protected]
2nd of January 2008
(First draft please do not quote)
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1.
INTRODUCTION
This paper takes the point of departure within labor mobility and how the previous
location an individual was situated influences the performance of the current firm. This
concept, which is the phenomenon where an employee leaves an employer and starts
working in another form of employment (Mincer and Jovanovic 1981 and Elias 1994),
related to performance is evident when focusing on newly established firms. Especially
since most of the founders of these new ventures were employed before they started
their own business (Sørensen and Philips 2004). There exists already a line of literature
that links the characteristics of the previous workplace with the performance of the new
established firms, e.g. better performing firms will produce better performing ventures
(Klepper 2002, Dahl and Reichstein 2006) and smaller firms produce better
entrepreneurs (Sørensen and Philips 2004), which make the importance of labor mobility
more evident. One of the reasons why the previous workplace is important is related to
its function as an organizational blueprint for the new established firm (Baron et al.
1999). Besides the blueprint factor, as a result of experience, the contacts obtained in this
firm are regarded as another factor determining the new firm performance (Burton et al.
2002) and it is these contacts that are the main interest of this paper.
Whenever these contacts contribute to a better performance this organization is able to
extract benefits from the relations with these contacts. In other words one is intended to
speak of this phenomenon as social capital (Portes 1998). However, the contacts the new
firm has are not only established at the previous workplace. Typical contacts that are
important for newly established venture, but have been established in a more private
setting, are the relations with family and friends. Greve and Sallaf (2003) thereby stress
that these ties are important, for the founder, in all the phases of the entrepreneurial
process. All in all these ties enable access to for a new firm important sources e.g.
financial capital, human capital and knowledge capital (Sorenson 2005).
It is thus very logic that organizational researchers are interested in the social capital of
founders (Davidsson and Honig 2003, Audretsch and Keilbach 2004, Fornahl 2005, Dahl
and Sorenson 2007) but the picture is not yet complete. What should be taken into
consideration is that one of the first tasks a founder will undertake is recruit others to
join the firm (Dahl and Klepper 2007). Since a large share of these new employees are,
just like most of the founders, already experienced and the fact that in the first years the
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number or new employees will be small the background of these first year employees
would influence the performance of the firm using their organizational blueprints and
contacts. This will thus not be an attribute only possessed by founders and co-founders.
This paper will thus look at the social capital of these first year employees and the effect
on the performance, in terms of survival, of the new established firm.
For the empirical angle of this paper I will use the Danish annual census dataset. With
this dataset I will identify the potential size of the employees’ social capital and how this
subsequently affects the survival of the firm where these employees are employed. The
longitudinal character of the data is very suitable for identifying social capital since one
of the important requirements for building social capita.
In the next section I will shortly explain the concept of social capital. Thereby choosing
the dichotomy that I will use throughout the paper and setting up the hypothesis. In
Section 3 I will continue with describing the Danish census dataset, sample selection and
the construction of the variables. Section 4 will present the descriptive statistics followed
by the results of the logistic regression and I will conclude this paper with a short
discussion and concluding remarks in Section 5.
2.
THEORY AND HYPOTHESES
Social capital has received increasingly more attention ever since Coleman (1988)
presented his work on the link between social capital and human capital. The concept
itself refers to, as I already mentioned in the introduction, the ability to obtain benefits
from the actors to whom another actor is connected (Portes 1998) and although it can be
treated both on the individual and organizational level it is primarily an attribute
ascribed to individuals (Davidsson and Honig 2003). The social connections of an
organization are after all determined by the social connections the members of this
organization have. However, the organizational component becomes important later on
in this section when I discuss how to treat social capital in this paper.
One of the attributes that can be obtained from one’s social contacts are, first of all, other
forms of capital like financial capital, human capital, and knowledge capital (Burt 1992,
Sorenson 2005). What has to be taken into account however is that these forms of capital
are mostly temporary and borrowed (Lin 1999) but available for use.
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Another attribute of social capital is that the relation, or a tie between individuals, is
built on trust (Putnam 1995). Building of trust, however, requires two main elements i.e.
time and interaction. Thus, for building social capital it is required to know the contact
for a certain period of time and during this period have frequent interaction, often
accompanied by geographical proximity (Fornahl 2005, Dahl and Sorenson 2007).
There are different ways in which these ties can be categorized. One of the most familiar
categorizations is between strong and weak ties as identified in the classic work by
Granovetter (1973) where strong ties are those ties with friends and family and weak ties
the relation with acquaintances. Strong ties would provide a relatively stable access to
resources. Weak ties, however, will provide access that would normally be more
difficult to obtain. Because of the loose connection it is information that none of your
strong ties would have since your strong ties in a network are often very connected
among as well since they meet in similar settings. This is what Burt (1992) identifies as
the lack of structural holes (Burt 1992). Another classification, and the one that will be
adopted in this paper, is the one mentioned by Adler and Kwon (2002) between bridging
and bonding ties. Here the organizational dimension, to what I hinted in the first
paragraph of this section, comes forward. The organizational setting in which actors are
located determines whether a tie is bridging or bonding.
Whenever an actor has a tie with an individual that is located outside the organization
then one is intended to speak of a bridging or external tie. Bridging ties provide access to
unique knowledge and contacts (Beckman et al. 2007). Thus, resources that otherwise
would not be available for the firm (McEvily and Zaheer 1999). Although this
description shows much resemblance to the strength of weak ties argument of
Granovetter (1973) a bridging tie does not necessarily have to be a weak tie. Bonding ties
are relations that exist inside the organization and build much on the degree of trust and
cohesion within the firm (Beckman et al. 2007). There is clearly a trade off between
bridging and bonding ties. Whenever a bonding tie exists between individuals in the
organization there is high likelihood they know the same bridging tie. For accessing
more bridging ties the share of bonding ties in an organization would have to decline.
However both ties are considered important for the performance of newly established
firm (Davidsson and Honig 2003).
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2.1.
Bridging Ties Hypotheses
Bridging ties are thus ties an individual possesses but one that exists outside the
organizational setting of which this individual is member of. I will start out formulating
the hypothesis by looking at the contacts obtained at the previous workplace, as I started
this paper by mentioning the importance of the previous firm.
Burton et al. (2002) explicitly mentioned that established relations in the previous firm
determine new firm performance. I will make a distinction between two types of
relations that could have been established while being in this previous firm, which are
(1) relations between colleagues and (2) the relation with actors external to the previous
firm. The likelihood of establishing a tie with a colleague is high, especially since the
interaction with this group occurs on a daily bases. Thereby is the strength of a tie with a
colleague positively correlated with the period a person works for the same firm.
Whenever a person leaves the firm the connection with his former colleagues will not
disappear over night. In previous studies one finds even support that former colleagues,
after current colleagues, are still an important source of information (Schrader 1991,
Dahl and Pedersen 2003). Since the value of the social capital decays the longer
individual have been apart from each other I assume that the ties are strongest with
former colleagues an employee had at the previous firm. During a period of
employment a person comes in contact also with individuals and organizations outside
the firm with whom they regularly interact e.g. customers, suppliers, supportive
industries, etc. These contacts might also be valuable for future professions. Work tenure
will, just like the strength of a tie with a former colleague, determine the strength of
these ties. The first hypothesis will thus be:
Hypothesis 1: A long tenure at the previous firm increases the likelihood of firm survival.
However, having been outside the labor market for a certain number of years between
the previous firm and the current firm means a higher chance of losing contacts. Being
outside the labor market can be considered as an element weakening the bridging ties an
individual possesses. Thus,
Hypothesis 2: The longer the employee’s period of “between jobs” before entering the newly
established firm lowers the likelihood of firm survival.
The interaction with colleagues occurs often because one is closely located to each other,
at least regarding the fact that they would work in the same building. Social capital is
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thus in most cases confined in a certain geographical space and having experience, and
thus likelihood of having social ties, in a certain region can be considered as important
for having many social connections (Dahl and Sorenson 2007). Dahl and Sorenson (2007)
have made a study looking at the location behavior of newly established venture. In
their researched they proved that those ventures established in the region where the
founder has previous experience have lower failure rates. In the starting up process of a
new firm there would be a high dependence on bridging ties. Not only for getting access
to attributes like human and financial capital but also from the viewpoint of social
support .
The same would also be valid for these first year employees in new established ventures.
They might, just as the founder, have essential connections that help the firm survive.
However, there is most likely a difference in the relative value of some of the ties both
possess. In the case of the founder the social ties will already come on the scene before
the business is up and running (Greve and Sallaf 2003). Resources need to be gathered
and support by family and friends is a crucial element. There is thus a heavy reliance on
social ties regarding professional matters and on those ties with a high private character
e.g. with family and friends. Fornahl (2005) groups the motivation of the establishments
of these ties in two categories. The first one are ties that are established because the
members of a certain network have the same goal, i.e. the professional tie, and there are
ties that develop for other reasons, i.e. private ties.
I argue that for employees having experience in the same commuting region is
important. With this experience the employee might come more easily in contact with
the contacts as they were already identified when discussing Hypothesis 1 i.e. former
colleagues and contacts like suppliers, customers, and supportive industries. One might
question whether or not the reliance on ties with family and friends is crucial for the
survival of the new firm. I argue that this is most likely not the case. Thus although an
employee has lived in the current location and thus obtained many bridging ties from a
personal perspective these ties will not be as valuable as those bridging ties that have a
more professional character. In case of the employees the following two hypotheses will
be formulated:
Hypothesis 3: a high share of employees that worked in a different region while they worked
for the previous workplace brings a lower likelihood of survival.
And:
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Hypothesis 4: a high share of employees that since the previous job moved to a new region
is negative for firm survival
For Hypothesis 3 I am interested of the experience in the commuting region. A
commuting region consists of several municipalities and the professional contacts might
thus be spread of a larger region then the municipality where most likely most of your
personal social ties will be residing. Therefore the municipality is the observatory
location in Hypothesis 4.
2.2.
Bonding Ties Hypotheses
Bonding ties are thus the relations that exist inside the organization, which means, in
this case, ties that already existed between members of the organization before starting a
career in the new firm. There are different settings in which these previous ties were
created e.g. friendship, family, former classmates, former colleagues etc. In this paper I
decide to only focus on the ties that exist because the members of the organization
shared the same experiences in a previous workplace. In the case of this paper it means
that I will look again at the previous firm and see whether or not the employee shared
the same previous workplace with respectively the founder(s) and other employees.
Beckman (2006) described, based on already existing literature, some benefits of having
shared experiences in the same firm; i.e. shared language, common perspective, degree
of trust, common frame, shared vision and set of goals, and a conceptual filter. The tie
that exists is most likely freed from conflicts; otherwise they probably would not want to
join the same firm. These bonding ties will also not bring resources from outside the
organization (Beckman et al. 2007). However, in general the cohesiveness in the firm will
be strengthened the more bonding ties exist. Since I make a distinction between the
relation between employees and founder(s) and among employees the hypotheses will
be:
Hypothesis 5: high degree of previous firm work experience between employees and
founders increases the chance of firm survival.
And:
Hypothesis 6: high degree of previous firm work experience among employees increases the
chance of firm survival.
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3.
DATA AND METHOD
3.1.
The Dataset
For the analyses of the effect of first year employees on the survival of newly established
firm I will rely, as many did before me, on the Danish Integrated Database for Labor
Market Research which is maintained by Statistics Denmark. When referring to this
database I will do so by using its Danish acronym IDA. The information that is
contained within this dataset makes it very suitable for this study for the following
reasons.
Since the database is built up from government registers it contains information
regarding all individuals that (legally) reside in Denmark in a given years. This
information has been collected every year, since 1980, and is thus an annual census of
the population of Denmark.
For all these individuals IDA has information regarding their characteristics e.g. gender,
age, highest fulfilled education, annual income, nationality, etc. Information regarding
their labor market status is also provided, which makes it possible to track down in
which firms, industries and region this person has worked and what their position
within a firm has been. Because the longitudinal character it is possible to follow their
career track since 1980. Thereby linking employees and employers to firm and measure
characteristics such as tenure, work experience and connections with colleagues.
3.2.
The Sample
For constructing a sample I set a number of requirements. Currently I am only interested
in those firms that, besides the founder, have other employees and which were founded
in 2000. To assure that these firms are newly established I use both the plant and the
firm identification number. Each firm may consist of multiple plants and since I am able
to identify the year of establishment through the plant identification number I will omit
those firms, which have a plant that was established before 2000. However, that all the
plants in a firm might have been established in the same year does not automatically
mean that the firm did not exist previously. The next step is to remove those firms that
have a firm identification number that existed between 1980 and 1999. As mentioned
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previously a firm might consist of multiple plants. For the analysis in this paper I will
only focus on those firms that consisted of only one plant in the year of establishment.
The industry in which the new firm operates is the third requirement set. In this paper I
am only interested in firms that are active in the private sector, excluding the primary
sector. In order to make this selection I make use of the European NACE industry codes.
All those plants that are not within the 15 and 75 two-digit level NACE code are
excluded. Within these two digits there is one classification, between 40 and 45 (energy),
which is a mix of both public and private firm. The firms that are active within this digit
interval will also be omitted.
A total of 7976 firms within the Danish economy fulfill the above-mentioned
requirement. Within these firms there are in total 28731 employees out of which 18850
(65.61 percent) are registered as full-time workers. Among these firms 1933 firms consist
of only part-time employees.
3.3.
Variables
Now I will construct a number of variables that enables me to build a profile of each
firm based on the characteristics of the bridging ties of and bonding ties between the
employees inside this firm.
3.3.1.
Dependent Variable
Survival. As the dependent variable for the logistic regression I will use firm survival.
With survival I mean that the venture, which was founded in 2000, should still exist in
the year 2004. In some cases the venture might have disappeared between 2001 and
2003. Whenever this is the case this will not be considered as survival. Thus the survival
variable will receive the value one whenever the venture was able to exists throughout
all the years after establishment. Whenever a firm survives this firm will obtain the
value one.
3.3.2.
Independent Variables
Bridging ties. Bridging ties indicate the external ties new employees bring to the newly
established firms. For indicating these bridging ties I will construct four variables, two
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regional and two based on work experience, which will correspond with the formulated
hypotheses.
A variable indicating the likelihood of having contacts established in the previous
workplace will be the first variable I construct. The data provides me with information
regarding the workplaces where an employee was employed in the period 1980-1999.
Identifying the last previous workplace and then looking how many years this person
was active in that workplace enables me to calculate the tenure at this workplace. I will
not take the consecutive years of employment at this last firm because this might result
in leaving out those individuals that were on leave for one year. I decided to look at each
year, starting from 1980, and see whether the identification number was identical to the
identification number of the last employed work place. Consequently I will take the
natural log of the average number of years of work experience in the previous firm of all
employees as I construct the labor tenure variable. 1
The average number of years the employees were outside the labor market will be the
second bridging tie variable. For calculating this variable I will take the number of
empty observations between the last year an employee was registered at the previous
workplace and the year 2000. This would indicate the number of years an employee was
outside the Danish labor market e.g. unemployed, on leave, studying, abroad, etc.
Thereafter I will calculate the average number of years of all employees in the new firm
and take the natural log of this value. Of course I will add the value one to the average to
control for an average of zero years.
The regional variables indicate whether or not the employee in the current firm was
living or working in the same region when this person was active in the previous firm.
For each employee in the firm I will identify if the commuting region of the new firm is
similar to the commuting region of the previous firm. Whenever this is the case the
employee receives a value of zero and when the region changed it received the value of
one. Subsequently I will take calculate the share of employees that have moved into the
current commuting region as a result of the new position. The higher the share the lower
the likelihood of having strong professional ties in the direct vicinity of the firm. For the
1
The possibility occurs that none of the employees has labor tenure. Since it is not possible to
calculate the natural log of zero I will add one to this average to correct for this. The natural log
will in this case obtain the value zero. This is an exercise I will do for all natural log
measurements.
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residing variable I will use the same approach. However, instead of taking the
commuting region I will use the municipality for reasons already explained.
Bonding ties. Bonding ties were defined as the ties that existed between the members of
the new firm. A distinction has been made between the relation between employees and
founder(s) and among employees. Sharing the same previous firm would indicate a
higher likelihood of a stronger tie between members of the organization. For a founder
employee relationship I simply identify whether or not the employee and founder
shared the same previous workplace and consequently calculate the share of employees
within the firm that have a link with one of the founders.
The second measure, the shared experiences among employees, is a bit more
complicated since there is a possibility of multiple shared previous workplaces. Some
groups are larger and I would assume that these groups are more dominant then smaller
groups and definitely more dominant than employees that have no previously
established relation with other co-workers.
As an inspiration for this measure I use the Hirschman Herfindahl Index (HHI), which is
also used by Beckman et al. (2007) to measure diversity in background affiliation. This
measures the concentration of one group within a certain system. Whenever the HHI
approaches the value one there is a high concentration of one group while no
concentration is present if the HHI approaches zero. The formula for the HHI is thus:
n
HHI   si2
i 1
HHI = Concentration of employees based on the previous workplace.
si = Share of employees who worker together in firm i out of the total employees in the
present firm.
n = Those shares were two or more current employees have worked together.
Using this index will, however, not fully grasp that what I am looking for, which is the
relation between individuals. It is more a measure indicating the variety in previous
firms since the shares of individuals that do not share a previous firm with anybody else
in the firm is included. Take as an example a firm that consist of two individuals both
coming from a different firm. Calculating the HHI of these two individuals based on the
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firm they are coming from would give me a value of 0.5 although there is no tie between
these individuals. Therefore the formula I propose is the following:
n
C i   si2
i 1
C i = Concentration of employees with a shared connection in the new firm.
si = Share of employees who worker together in firm i out of the total employees in the
present firm.
n = Those shares where two or more current employees share the same previous workplace.
With this formula I will still calculate the share of all the employees that share the same
previous workplace. When adding up the shares I will exclude those shares that only
consist of one employee. Using the shares still enables me to correct for the size of the
firm. To illustrate this imagine a firm with five employees where two employees share
the same previous workplace C i will have a value of 0.16. If this firm would consist out
of ten employees this C i would drop to 0.04 and when no employees share the same
previous firm this value would drop to zero. The smaller the share of employees with a
bonding tie the lower the impact of their trust will be on the performance of the firm. So,
this measure will illustrate better the effect of bonding ties within the firm.
However, regarding these two measures it should be noted that the individuals share
the same last workplace but did not necessarily work there at the same time. Having the
experience of working in the same firm would still result in similar languages and
behaviors. This cultural connection between individuals might strengthen the bond exist
between them.
3.3.3.
Control Variables
Firm characteristics. Regarding firm characteristics I will control for size, industry, and
location. The natural log of the size of the firm in the first year will be used as the first
control variable. A dummy variable for the industry will be the second variable created.
Some industries face tougher competition than others, which might explain why the
firm did not survive. The industries are split up in: manufacturing, construction,
wholesale and retail, hotel and restaurants, transport, financial services and business
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services. The third variable, also a dummy variable, is the location where the firm is
established. A firm might experience more competition whenever it is located in the
Copenhagen Metropolitan Area (CMA) compared to being located in another region in
Denmark. A dummy variable will indicated whether or not the firm is located in the
CMA. Such a variable has also been used in previous studies e.g. Brüderl and Schüssler
(1990), Eriksson and Kuhn (2006), Dahl and Reichstein (2006).
Employee characteristics. Other employee characteristics might also contribute to the
chances of survival for a new established firm. These are: age, education, years of total
work experience, full-time employee, and new to the labor market. For age I will
calculate the average age the employees in the firm. The age is easily identified in the
sample. Each year Statistic Denmark collects for all individuals in Denmark their highest
obtained education. This makes it easy for me to identify the two control variables for
education. These education variables will be the share of highly educated, meaning
those employees with a bachelor degree or higher, and the share of employees with a
degree between high school and bachelor. The control variable work experience will be
created by looking at the number of years the employee was registered as having a job in
the period 1980-1999. The natural log of the average work experience in the firm will be
the variable used. In constructing the sample of firms I already identified the number of
full- and part-time employees in a firm. Knowing how many full-time employees there
are compared to all employees I am able to calculate for each firm the share of full-time
employees. Being a full time employee would indicate commitment to the new
established firm. For the last control variable I will identify those employees that are
considered as being outside the labor market between 1980 and 1999. I consider this
group as new to the labor market.
4.
RESULTS
4.1
Descriptive statistics
Table 1 shows the survival rate of the newly established firms broken down by industry.
In total 3335 (42.81 percent) were still operational in 2004. Most firms are active within
business services (2431 or 30.48 percent) and wholesale and retail (2064 or 25.88 percent).
The highest survival rates are within manufacturing (47.87 percent) and transport (46.76
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percent) while the lowest are in hotels and restaurants (30.77 percent) and financial
services (32.43 percent).
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------------------------Insert Table 1 here
------------------------Table 2 shows the descriptive statistics of the other variables that will be used for the
regression analysis including the correlation matrix. The majority of the correlations are
highly significant. 2
------------------------Insert Table 2 here
-------------------------
4.2.
Regression Results
The results of the logistic regressions are summarized in Table 3, which consist out of
four models. The first model presents the effects of control variables on firm survival.
Model 2 adds the variables indicating the possibilities bridging ties and Model 3 does
the same but then for bonding ties. Finally, in Model 4, I add the variables that both
indicate the likelihood of bonding ties and bridging ties within the firm.
First I will, before discussing the outcome on the hypothesis, briefly explain the effects of
the control variables on the survival of the firm. The variables controlling for firm
characteristics show a positive effect on the size of the firm in the first year. As expected
the signs are in all three models positive and significant. When controlling for industry I
use manufacturing as the benchmark with whom the other industries will be compared.
In all three models Construction and Business Services do not significantly differ from
manufacturing. Wholesale and Retail, and Transport have a significant and positive sign
meaning that the likelihood of survival is higher in these two industries compared to
Manufacturing while being active in Financial Services, and Hotel and Restaurants has a
significant negative effect. Being located in the Copenhagen Metropolitan Area does not
show a significant effect.
2
I tested for multicollinearity using the variance inflation factor (VIF) method. I found the highest
VIF to be 4.68, which confirms that multicollinearity is not a concern
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Taking a closer look at the employee characteristics shows that a higher average age of a
newly established firm’s employees has a significant negative effect on survival. Having
a high share of employees with a highest fulfilled education between high school and
bachelor is significant and positive. The same is true for having a bachelor degree or
higher. However, this last education variable has a stronger effect in all three models.
Having a higher average of work experience within the new firm is, as expected,
positive. Within this variable some degree of bridging ties might apply since the more
work experience an individual has the higher the likelihood that the employee has
established ties. The control variable indicating the share of full-time employees is
significant and positive as well and stays this in all three models. The last control
variable presented in this model is the share of new to the labor market employees.
Although the likelihood of this group for having professional social ties is low a higher
share increases the likelihood on firm’s survival.
------------------------Insert Table 3 here
------------------------However, the most interesting variables will be those that will be used as proxies for the
bridging and bonding ties. Model 2 is where the bridging ties got added to the
regression. The first hypothesis finds support in the result of the regression analysis. A
higher tenure in the previous firm has a positive effect on the survival of the new firm.
To correct for the number of outside-the-labor-market years I added the variable and
this variable also shows the expected negative and significant sign. Not have worked for
a certain period between the previous and the current firm, number of years “in between
jobs”, might thus indicate a loss of social capital in the professional sphere. In the case of
Model 2 this hypothesis is supported although only at the 10 percent significance level
and with a very low parameter estimate.
Hypothesis 3 states that having a high share of employees that are new to the
commuting region of the new established firm has a negative effect on the survival of
this firm. The result of the regression analysis supports this hypothesis, as the effect is
highly significant and negative.
As it is argued in Hypothesis 4 argued that share of employees that live now in a
different municipality as they lived while working for the previous firm will negatively
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influence the likelihood of survival. Also this hypothesis is supported by the results.
However, I also argued that private ties, which are mostly represented within this
measure, are not as important as the professional ties in the case of employees. The
parameter estimate is contradicting this statement, since the effect is similar to changing
the work region.
Model 3 included the bonding ties between the individuals active in the firm both
founders and employees. Hypothesis 5 is, be according to the result of the regression,
supported at the 5 percent significance level. The last and sixth hypothesis states that the
higher the concentration of shared experiences in the previous firm the higher the
likelihood of survival. Also this hypothesis is supported. Note the high value of the
parameter estimate for this variable.
In the fourth model all variables are added. Within this model the outcome of
Hypotheses 1, 3 and 4 stay the same. Hypothesis 2 will now be rejected since the effect is
not significant anymore. Note here that the effect of this variable was already rather
weak in Model 2. Within the bonding ties the relation between founders and employees
turns out not significant and Hypothesis 6 remains strong and significant.
5.
Concluding Remarks
5.1.
Conclusion
When stating that social capital is an important attribute of a founder most people will
probably agree with me. However, since the recruiting of new personnel is one of the
first tasks this founder will undertake another carrier of social capital will enter the new
firm. The goal of this paper was thus to identify what the effect of employees’ social
capital is on the survival of the firm.
For identifying social capital I made a distinction between social capital based on
bridging ties and social capital consisting of bonding ties. These bridging ties are the ties
employees have with individuals outside the organization in which they are currently
working. These would be relations with: family, friends, former colleagues and business
contacts. Different settings foster the establishment and maintenance of the strength of
such a tie but predominantly have to do with the duration and frequency of the
interaction. Experience in a certain region and firm would thus be required. Therefore I
look at the experience in both the previous firm and the current region with regards to
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the likelihood of having social ties and the ability to use them. Labor tenure in the
previous firm shows positive effects on the survival of new established firms, while the
effect of haven been outside the labor market before starting the current job has no or
only very marginal negative effect. It can also be concluded from the results that having
experience in the region, both in residing and working, before starting a career at the
new established venture has a positive effect on the survival of the firm. This is what
was expected. However, what in my eyes is somewhat surprising is the stronger
negative effect on changing the living region compared to changing the working region.
Since I assumed that the professional contacts would be more important for the new
firm than contacts with friends.
Bonding or internal ties are the relations between of the members within the
organization. There are several ways in which these ties could have been established,
e.g. shared work experience, old friends, family business etc. The focus in this paper was
the relation based on a shared previous workplace. Existing relations between
founder(s) and employees has an ambiguous effect, although it is in any case not
negative. The most interesting result from the analysis conducted in this paper is the
strong positive effect on existing bonding ties between employees.
All in all the proxies for the likelihood that employees have strong ties in the new firm
they work seems to be supported. Besides being well connected as a founder it benefits
the firm to hire individuals that are rooted as well, both within the firm as well as
outside the new established venture.
5.2.
Further Work
Currently I have plans to develop this project in the following ways. First I would like to
extend the bonding ties analysis. In this paper I only focus on the bonding ties related to
the previous workplace. However, in Beckman et al. (2007) the authors look at the
previous three workplaces to see whether or not there is a link between the persons in
the founding team. A similar analysis can be conducted for the employees. There is an
increased likelihood that when looking at more previous firms that the persons never
met or worked each other in these workplaces. But the language and culture within the
organization might have influenced both in a way they can easier communicate. There
will be more similarities between those that have worked for the same firm in the past
and similarity creates a connection (McPherson et al. 2000), hence the expression birds of
-18-
a feather. What applies for the previous workplace might also apply for the share of
individuals that come from the same region, although this would be more difficult to
make operational.
6.
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-21-
Table 1: Survival and industry
Survive
no
Yes
Total
Industry
Total
Manufacturing
Construction
Wholesale &
retail
Hotel &
Restaurant
4641
250
662
1173
756
246
125
1384
58.19
3.69
8.3
14.71
9.48
3.08
1.57
17.35
Transport
Financial
services
Business
services
6.36
14.26
25.27
16.29
5.3
2.69
29.82
52.13
56.24
56.38
69.23
53.25
67.57
56.93
3335
270
515
891
336
216
60
1047
42.81
3.39
6.46
11.17
4.21
2.71
0.75
13.13
8.1
15.44
26.72
10.07
6.48
1.8
31.39
47.87
43.76
43.17
30.77
46.75
32.43
43.07
7976
565
1117
2064
1092
462
185
2431
100
7.08
14.76
25.88
13.69
5.79
3.32
30.48
Source: Based on data from Statistics Denmark
-22-
Table 2: Descriptive Statistics and Correlation
Variable
Means
S.D.
1
2
3
4
5
6
7
1
LOG (SIZE)
1.27
0.72
2
COPENHAGEN METROPOLITAN AREA
0.48
0.50
-0.01
3
LOG (AVERAGE AGE)
3.52
0.31
-0.09
0.06
4
SHARE BETWEEN HIGH SCHOOL AND BACHELOR DEGREE
0.43
0.42
-0.04
-0.07
0.29
5
SHARE BACHELOR DEGREE AND HIGHER
0.09
0.25
0.01
0.14
0.13
-0.27
6
LOG (AVERAGE YEARS OF WORK EXPERIENCE)
2.14
0.77
0.06
0.02
0.66
0.41
0.14
7
SHARE OF FULL-TIME EMPLOYEES
0.58
0.41
-0.13
0.05
0.30
0.27
0.11
0.39
8
SHARE OF NEW TO THE LABOR MARKET
0.08
0.22
-0.04
0.00
-0.34
-0.24
-0.08
-0.69
-0.23
9
8
9
10
11
12
SHARE OF EMPLOYEES WORKED IN ANOTHER COMMUTING REGION
0.27
0.39
0.00
-0.26
-0.18
-0.06
-0.07
-0.34
-0.12
10
SHARE OF EMPLOYEES THAT LIVED IN ANOTHER MUNICIPALITY
0.21
0.35
0.00
0.04
-0.30
-0.19
-0.06
-0.52
-0.20
0.59
0.41
11
LOG (AVERAGE YEAR OF TENURE IN THE PREVIOUS FIRM)
1.17
0.60
0.12
-0.03
0.42
0.25
0.06
0.60
0.22
-0.43
-0.27
-0.35
12
LOG (AVERAGE YEARS OUTSIDE THE LABOR MARKET)
0.43
0.62
-0.05
0.02
0.20
-0.04
-0.02
-0.05
-0.04
-0.13
-0.04
0.10
-0.01
13
SHARE OF EMPLOYEES SHARING THE PREVIOUS FIRM WITH FOUNDER
0.04
0.17
-0.04
-0.03
0.00
0.03
-0.04
0.03
0.00
-0.04
-0.08
-0.05
0.06
-0.07
0.07
0.21
0.24
0.01
0.13
0.08
0.05
0.19
0.14
-0.10
-0.11
-0.12
0.22
-0.15
14 CI
Note: Correlation estimates in bold indicate significance at 5% level
-23-
13
0.49
0.04
Table 3: Summary of the regression analyses
N=7976
Variables
Model 1
Standard
Coefficient
Error
Intercept
Model 2
Standard
Coefficient
Error
Model 3
Standard
Coefficient
Error
Model 4
Standard
Coefficient
Error
-1.357
0.336
***
-1.220
0.351
***
-1.157
0.339
***
-0.982
0.355
***
0.434
0.035
***
0.418
0.035
***
0.368
0.036
***
0.363
0.036
***
Business services
0.031
0.051
0.046
0.051
0.029
0.051
0.041
0.052
Financial services
-0.522
0.142
***
-0.518
0.142
***
-0.512
0.142
***
-0.509
0.143
***
0.281
0.089
***
0.309
0.089
***
0.295
0.089
***
0.321
0.090
***
Hotel and restaurant
-0.169
0.071
**
-0.166
0.071
**
-0.149
0.071
**
-0.149
0.071
**
Wholesale and retail
0.156
0.052
***
0.139
0.052
***
0.151
0.052
***
0.135
0.052
***
Construction
0.075
0.062
0.081
0.063
0.067
0.063
0.075
0.063
FIRM CHARACTERISTICS
Log (size)
Industries
Transport
Manufacturing
Copenhagen Metropolitan Area
Benchmark
-0.025
0.024
Benchmark
-0.037
0.026
Benchmark
-0.024
0.024
Benchmark
-0.033
0.026
EMPLOYEE CHARACTERISTICS
Log (average age)
-0.340
0.110
***
-0.325
0.120
***
-0.365
0.110
***
-0.389
0.120
***
Share between high school and bachelor degree
0.195
0.068
***
0.213
0.068
***
0.197
0.068
***
0.213
0.068
***
Share bachelor degree and higher
0.447
0.105
***
0.469
0.106
***
0.450
0.105
***
0.473
0.106
***
Log (average years of work experience)
0.583
0.064
***
0.360
0.071
***
0.550
0.064
***
0.374
0.071
***
Share of full-time employees
0.278
0.065
***
0.274
0.065
***
0.226
0.066
***
0.230
0.066
***
Share of new to the labor market
0.766
0.164
***
1.079
0.195
***
0.739
0.164
***
1.071
0.194
***
Share of employees worked in another commuting region
-0.226
0.076
***
-0.185
0.077
***
Share of employees that lived in another municipality
-0.281
0.094
***
-0.274
0.094
***
0.364
0.050
***
0.331
0.050
***
-0.081
0.045
*
-0.032
0.045
BRIDGING TIES
Log (average year of tenure in the previous firm)
Log (average years outside the labor market)
BONDING TIES
Share of employees sharing the previous firm with founder
0.293
0.135
**
0.214
0.136
Ci
0.916
0.121
***
0.784
0.123
*** Significant at the 1% level. ** Significant at the 5% level. *Significant at the 10% level.
-24-
***