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This paper reports the results of a two-phase study that explores new venture creation within the context of an entrepreneurial system. First, a genealogy of high-technology companies is presented depicting a high spin-off rate resulting from the presence of seven incubator organizations. Second, semantic structure analysis (Spradley 1980) based on semi-structured interviews with founders is used to develop a taxonomy. This taxonomy depicts the relationship among components in one entrepreneurial system, Boulder County, Colorado, that encourages, supports, and enhances regional entrepreneurial activity. Findings indicate that incubator organizations, spin-offs, informal and formal networks, the physical infrastructure, and the culture of the region are related uniquely and interact to form a system conducive for dense high-technology entrepreneurial activity. Additionally, greater rates of new venture formation were found following critical moments in the life of incubator organizations.
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190 JOURNAL OF SMALL BUSINESS MANAGEMENT
Journal of Small Business Management 2004 42(2), pp. 190 –208
An Entrepreneurial System View of
New Venture Creation*
by Heidi M. Neck, G. Dale Meyer, Boyd Cohen,
and Andrew C. Corbett
This paper reports the results of a two-phase study that explores new venture
creation within the context of an entrepreneurial system. First, a genealogy of high-
technology companies is presented depicting a high spin-off rate resulting from the
presence of seven incubator organizations. Second, semantic structure analysis
(Spradley 1980) based on semi-structured interviews with founders is used to develop
a taxonomy. This taxonomy depicts the relationship among components in one
entrepreneurial system, Boulder County, Colorado, that encourages, supports, and
enhances regional entrepreneurial activity. Findings indicate that incubator organ-
izations, spin-offs, informal and formal networks, the physical infrastructure, and
the culture of the region are related uniquely and interact to form a system conducive
for dense high-technology entrepreneurial activity. Additionally, greater rates of new
venture formation were found following critical moments in the life of incubator
organizations.
*A previous version of this paper was presented at the 1999 Babson-Kauffman Entrepreneur-
ship Research Conference, Columbia, South Carolina. Funding for this study was provided by
University of Colorado’s Center for Entrepreneurship and the Price Institute for Entrepre-
neurial Studies.
Dr. Neck is assistant professor of entrepreneurship and Paul T. Babson Term Chair Holder
at Babson College. Her research interests include the new venture creation, the growth of
entrepreneurial firms, and corporate entrepreneurship.
Dr. Meyer is Ted G. Anderson Professor of Entrepreneurial Development at the University
of Colorado–Boulder. His research interests include new venture creation, the nature of
entrepreneurial work, and the impact of bureaucracy and socioeconomic factors on small
and medium-sized enterprises (SMEs) and economic development.
Dr. Cohen is assistant professor of strategy and entrepreneurship at the University of
Victoria. His research interests include the internationalization of high-growth ventures, initial
public offerings, sustainable “green” entrepreneurship, and stakeholder theory.
Dr. Corbett is assistant professor of entrepreneurship and strategic management at Rens-
selaer Polytechnic Institute. His research interests include opportunity recognition, decision-
making, and the management of innovation and technology.
Introduction
This paper explores new venture cre-
ation within the context of an entrepre-
neurial system. Silicon Valley, arguably
the most famous and successful entre-
preneurial system, has been the envy of
regional economic developers and the
living laboratory for many academic
researchers trying to ascertain how such
communities have come to exist and to
thrive. Furthermore, the goal of these
Silicon Valley observers has been not
only description but also replication. The
wealth and job creation found in areas
such as Silicon Valley, Boston’s Route
128, and North Carolina’s Research Tri-
angle can be a region’s answer to floun-
dering local economies. Unfortunately,
many of the models presented in the lit-
erature (Leslie and Kargon 1996; Miller
and Cote 1987; Hall and Markusen 1985;
Rogers and Larsen 1984) fail to prove
successful when replication is attempted.
Previous research has shown the
importance that different, single ele-
ments of an entrepreneurial system may
have on the overall macroeconomic
development of a region. Spilling (1996)
focused on the effect of a mega-event;
Stough, Haynes, and Campbell (1998)
examined the effect of clusters of high-
technology firms; Shepherd (1987) exam-
ined government interaction; and Florida
and Kenney (1988) measured the impact
of venture capitalists. Here, this study
broadens the focus to investigate the
interaction of many different elements
of an entrepreneurial system, while also
examining what impact this interaction
can have on the macroeconomic devel-
opment of a region. Before modeling
with a goal toward replication can
begin, first a deeper understanding
underlying the phenomenon of extreme
regional entrepreneurial activity must be
acquired.
This paper reports the findings of a
study that analyzes a system of dense
high-technology entrepreneurial activity
in Boulder County, Colorado. First, a
genealogy of high-technology companies
is presented, depicting a high spin-off
ratio resulting from the presence of a
small number of incubator organizations
(Phase I). Second, semantic structure
analysis (Spradley 1980) of semi-
structured interviews is used to develop a
taxonomy (Phase II) that depicts the
incubator–spin-off relationship and that
describes the other core components of a
high-technology entrepreneurial system.
The discussion of new venture creation
is framed within the context of entrepre-
neurial systems,which Spilling (1996)
defines as the interaction of actors, roles,
and the environment that determine the
entrepreneurial performance of a region.
Through this study’s examination, it
can be seen that Boulder County com-
prises the elements of an entrepreneurial
system, while being part of a larger, open
system of economic exchange. This foun-
dation of an entrepreneurial system is
used for two reasons. First, the genealogy
of high-technology firms in Boulder
County is contained within this entrepre-
neurial system; the system contains and
supports entrepreneurial activity. Second,
the entrepreneurial activity results from
an evolution of components over time
that interact to form a dynamic system
that fuels new venture creation (Van de
Ven 1993).
Entrepreneurial Systems
and New Venture
Creation
Regions of high entrepreneurial activ-
ity are important for research, but the
many forces and actors fueling the activ-
ity cannot be studied independently.
According to Malecki (1997), “entrepre-
neurship is a process as well as a phe-
nomena” (p. 58); therefore, it seems
plausible to view a region of high
entrepreneurial activity as a system in
addition to the previous research that
examined the actions of individual
NECK et al. 191
actors, events, or organizations alone.
The process of entrepreneurship—as one
of identifying an opportunity, creating a
team, marshalling resources, and starting
the venture (Morris 1998; Timmons
1999)—and the system in which it occurs
feed off each other. Van de Ven (1993)
best explains the importance of an entre-
preneurial system and the codependence
of the individual, the process, and the
system. “This infrastructure does not
emerge through a few discrete events or
by the actions of one or even a few key
entrepreneurs...Entrepreneurship con-
sists of an accretion of numerous insti-
tutional, resource, and proprietary events
involving many actors who transcend
boundaries of many public and private
sector organizations” (p. 218).
Van de Ven (1993), citing supporting
studies (Usher 1954; Jewkes, Sawers,
and Stillerman 1958; Constant 1980;
Rosenberg 1983), argues that researchers
focusing on individual entrepreneurs
have ignored the historical evolution and
actions of multiple actors that create the
infrastructure for entrepreneurship. As
the infrastructure develops and as the
entrepreneurial system grows, the
system will thrive only if the environ-
ment is conducive for entrepreneurial
activity and new venture creation (Pen-
nings 1980). Spilling’s (1996) research
points to the importance of the interact-
ing elements in the entrepreneurial
system: “Economic development is a
result of complex entrepreneurial pro-
cesses. Many things are linked together;
many ventures develop in close inter-
action with each other and with envi-
ronmental factors. Furthermore, the
development of communities requires
more than just the development of a
number of businesses; it is also about
infrastructure, public institutions, and
about firms that can match together in
advanced production systems” (p. 91).
Overall, the literature implies a com-
plex relationship of many interacting
elements that need to be in place to
support high levels of regional entrepre-
neurial activity, yet the extant research
fails to depict these relationships truly.
This study’s research supports previous
findings of the environmental factors
conducive to entrepreneurship yet con-
tributes additional knowledge regarding
the relationships inherent in a geo-
graphic area of dense entrepreneurial
activity.
The following section (Phase I)
discusses the relationship between
incubator organizations and related spin-
offs and maps the genealogy of high-
technology firms in Boulder County. A
later section (Phase II) depicts relation-
ships of core components by means of a
taxonomy developed from interviews
conducted with a sample of founders
from firms on the genealogical tree.
Boulder County
Genealogy Study Phase I:
The Genealogical Tree
According to Malecki (1997), “Regions
with high levels of entrepreneurship will
tend to spawn further entrepreneurs” (p.
63). Furthermore, the sociological theory
of isomorphism, specifically mimetic iso-
morphism, claims that organizations tend
to mimic one another (DiMaggio and
Powell 1983). As a result, the authors
believe the “spawning” effect produces
a community of similar or related new
ventures. In other words, a genealogy of
firms created from organizations spawn-
ing new organizations is a natural occur-
rence within an entrepreneurial system.
It also is apparent that time and context
may play crucial roles in this spawning.
Certain critical moments—and when
they happen during the evolution—can
have dramatic effects on the incidences
of spawning. Mapping the relationship
between incubator and spin-off organi-
zations, and when viewed together with
certain critical moments, can shed light
on the evolutionary process occurring
within the entrepreneurial system.
192 JOURNAL OF SMALL BUSINESS MANAGEMENT
In this discussion (and within the
trees in the figures), only the “families”
within Boulder County are reported on.
The limitations of not discussing other
family members within this open system
that may reside outside of Boulder
County are recognized; however, the
initial research design set parameters
and boundaries that required a focus on
the parents within the local system.
Because of this, and before presenting
the genealogical tree and describing its
development, it is necessary to establish
a definitional foundation from which this
research builds.
Incubator Organizations
and Spin-Offs
For the purpose of this research, an
incubator is defined as the organization
where the entrepreneur was employed
before starting his or her new venture
(Cooper 1985). The literature is relatively
sparse with respect to incubators in this
context, and there has been even less
research aimed at understanding the
various roles an incubator organization
may play in new venture creation.
A spin-off organization is defined as
a new firm formed by an individual or
group of individuals leaving an existing
firm and starting a new firm in the same
industry (Garvin 1983, p. 3). The authors
believe this definition is restrictive, par-
ticularly given Cooper’s (1985) definition
of an incubator; he does not imply that
the incubator and the spin-off are in the
same industry. As a result, the authors
adopted Garvin’s (1983) definition with
one important deviation: “In the same
industry” was changed to “in a related
industry.” Industry similarity in today’s
high-technology environment often is
blurred, and boundaries are not detected
easily.
Relatedness is researched most often
under the domain of diversification strat-
egy or parent–subsidiary relationships
within large corporations. But it seems
reasonable to view incubator and spin-
off relationships using similar terminol-
ogy. Woo, Willard, and Daellenbach
(1992, p. 438) stated that a parent and
subsidiary were related if they met one
of the following criteria: (1) Both sold to
the same or very similar types of cus-
tomers; (2) Both engaged in the sale of
similar lines of products or services; or
(3) Both produced their products or serv-
ices through the use of similar produc-
tion technologies.
Sample, Data Collection, and
Genealogical Mapping
The 1998 Boulder County R&D/Manu-
facturers Directory was used in this study
to develop the sample. A brief survey was
mailed to each chief executive officer
(CEO)/founder of the 999 technology
firms in the directory. The survey con-
tained four simple questions regarding
firm foundings and spin-offs that would
allow assessment if the founder met the
established criteria for inclusion on the
tree. A total of 184 useable surveys were
returned, and 42 were returned due to
wrong address or no forwarding address,
giving a 19-percent response rate. In
addition to the mail survey, informal
interviews were conducted with five well-
regarded venture capitalists in Boulder
County and with six key business leaders
considered to be historians of the busi-
ness community. These informal inter-
views, combined with the mail survey,
allowed for creation of the beginnings of
the high-technology genealogy.
A set of criteria was developed to
ensure that the appropriate companies
were depicted on the tree. First, the
authors were interested in individual
founders and founding teams; however, a
passive investor was not considered part
of a founding team. For example, if
company B spins off from company A, but
if a member of the founding team comes
from company C, then it is assumed that
company B is a product of company A and
C. Second, the authors were interested
only in related, high-technology spin-offs.
NECK et al. 193
Once the tree was in workable form,
it was shown in various mediums (formal
interviews, presentations to companies,
newspapers, Internet) to solicit feedback
and to make additions and corrections.
Developing the genealogical tree was an
iterative process that required multiple
data sources and informants. New tech-
nology firms are born daily in Boulder
County. Many of these firms die, merge,
or are acquired; therefore, the genealog-
ical tree is a snapshot at one point in time
of the entrepreneurial system’s evolution.
What Does the Genealogical
Tree Tell Us?
The genealogy of high-technology
firms in Boulder County is seen in Figures
1a and 1b. A total of 176 companies are
depicted on the tree, of which seven are
considered incubator organizations (tree
trunks) that have led to the spawning
effect in Boulder County.Boxes on Figures
1a and 1b denote these companies.
The seven main incubator organiza-
tions illustrated on the tree represent a
diverse mix of organizations. Figure 1a
points to the importance and impact of
a few large corporations. IBM was one of
the first large technology companies to
arrive in Boulder County in 1965. Four
years later (1969) a team of IBM techni-
cal employees left the company and
founded StorageTek,1today a leading
global data storage company. Figure 1b
depicts the role of a large research uni-
versity and two scientific government
organizations, the National Center for
Atmospheric Research (NCAR) and the
National Institute of Standards and Tech-
nology (NIST), as also contributing to the
spawning effect. Ball Aerospace (Figure
1b) is considered a corporate incubator
(as is IBM, for example), yet the univer-
sity played a role in its beginning. In
summary, four large corporations, the
university, and two scientific government
organizations were the impetus for the
spawning effect that created a multitude
of related spin-offs that are contained
within the Boulder County entrepre-
neurial system.
Viewing the genealogical tree from a
“trunk-only” perspective contributes
additional insights into factors leading to
increased rates of new venture creation.
Figure 2 charts the rate of new venture
creation by what is considered to be the
critical corporate incubators of Boulder
County (StorageTek, Ball Aerospace,
NBI). There is at least one critical
moment in the evolution of these cor-
porations that motivated employees to
leave the incubator (by choice or by
force) and to create a related new
venture. It is during and after these crit-
ical moments that the rate of spawning
is the greatest.
Boulder County
Genealogy Study Phase
II: The Entrepreneurial
System
Two questions drove this research
process as Phase II was entered. First,
given the relatively sparse research on
incubators and their related spin-offs, are
there various roles the incubators play in
the entrepreneur spinning off and start-
ing a related new venture? Second, if an
entrepreneur is truly just an actor among
many (Barth 1972), what are the other
driving forces in an entrepreneurial
system, and how are these components
related?
Sample and Data Collection
Semi-structured interviews lasting
one to one and one-half hours in length
were conducted with 15 founders of
spin-off firms found on the family tree.
194 JOURNAL OF SMALL BUSINESS MANAGEMENT
1Prior to 1987 StorageTek was called Storage Technology Corporation. After emerging from
Chapter 11 bankruptcy protection, the company renamed itself StorageTek.
Figure 1a
Genealogical Tree (Corporate Incubators)
NECK et al. 195
IBM
1965
StorageTek
1969
Iomega
1965
Promotif
Media
1993
Object
Learning
Environment
1994
Lexmark
1991
Peripherals
Unlimited
1993
Avalon
Imaging
1987
Johnson
Engineering
1973
Advanced
Micro Devices
1977
Intellidex
(na) Radian
International
1990
Mountain Optech
1985
Pinetree Peripherals
1992
Reference Technology
1982
Kapre
1992
Quantum
1999
Cherokee
(na)
Data Expert Systems
(na)
Breece Hill
Technologies
1993
SCC
Communications
1979
Dyad I
1995
Signal Soft
1995
IBS Systems
1990
Intelligent
Storage
1983
Exabyte
1985
Datasonix
1992
Ecrix
1996
Marlowe
Engineering
(na)
Aweida
Systems
(na)
Aspen
Peripherals
1984
Copex
1996
Prolink
1965
Raycom Systems
1981
Niwot
Networks
1965
BVT
Associates
1984
Compatible
Systems
1985
Reputable
Systems
1996
Miniscribe
1965
Data Storage
Marketing
1986
Prarie Tek
1965
Conner Peripherals
1986
Animal Tag
(na)
Integral Peripherals
1990
Mariner Systems
1973
NBI
1965
Anatel
Communications
1983
Purecycle
1972
AIS
1976
Synergetics
1973
Cadis
1986
Requisite
Technology
1994
Infonow
1990
RIBA
1965
Unicad
1965
Simagine
1997
Cadzooks
1982
Cadis
1986
Spatial
Technology
1986
Autotrol
Technology
1965
Sku Logic
(na)
Graphtex
1980
Power
Takeoff
1995
Cadnetix
1981
Neocad
1984
Colorcom
1987
Coral
Systems
1991
Sigma
Solutions
1990
Daisex
1990
Spectralink
1991
Intergraph
Electronics
1990
Veribest
1996
The Master's
Fund
1983
Hill Carmen
Ventures
1982
Sequel
Ventures
1996
Somantogen
1985
Allos
Therapeutics
1994
Capital Health
Management
1986
Fisher
Imaging
1987
Hill
Partnership
1981
Hill, Kirby,
Washing
1983
McData
1982
Electronic
Manufacturing
Systems
1994
Figure 1b
Genealogical Tree (University and Government Incubators)
196 JOURNAL OF SMALL BUSINESS MANAGEMENT
University of
Colorado
1876
Precision Visuals
1996
Amgen
1981
Regina Products
1968
Somantogen
1985
Display Tech
1984
Macro-Vision
Communications
1996
Sievers Instruments
1983
DFM Engineering
1979
Research Systems
1978
SpectraLogic
1979
Erbtec
1970
Radiometrics
1987
Optimal Decision
Engineering
1993
Analytical Spectral
Devices
1990
Opto Electronic
Computing Systems
1987
ODS
1998
Boulder Nonlinear
Systems
1988
Opto Electronic Data
1992
CDM Optics
1996
Macrovision
1997
Colorado
Micro Display
1996
Colorlink
1995
Astrolux
(na)
Bosonics
1996
Bosonics
Software
1997
Micro Decision Ware
1980
Polarsoft
1994
Intermezzo
1997
P3
1998
Viasoft
1994
Boulder Technology
1991
Web Farming
1997
Synergen
1981
Genomica
1996
Nexstar
1991
Commsult
1965
Bio-Feedback
Systems
1971
NCAR
1960
A.I.R.
1975
Kinetek
Information
Systems
1988
Digilog
1988
Sportswaves
Unlimited
1989
Continental
Control Systems
1995
Meadowlark
Optics
1979
High Plains
Optics
1975
Boulder
Vision
1992
Ball
Aerospace
1956
Ascent Technology
1991
NetTrack
1996
Iracom
(na)
Micro Motion
1977
Topaz Group
1996
Xertex
Technologies
1994
Earthwatch
1993
Timing
Solutions
1990
Syntex Chemicals
1946
Trimax
1993
Colorado
Venture
Management
1979 J'Leen
1981
OneCom
1997
Engineering
Management
Services
1989
Boundless
1995
US West
1984
Freshwater
Produce
1984
Labyrinth
Computer
Services
1988
Applied
Technologies
1978
Bold Tech
1996
Peakview
1998
The Moutain Area
Exchange
1997
Colorado
Internet
1993
Cyberspace
Development
1994
XOR
1991 CV/CS
(na)
Colorado
Engineered
Products
(na)
Vacuum Formed
Products
1973
Advanced
Pumping
Systems
(na)
Shaula
Navigation
1996
Boulder Electronic
Optics
1984
Environmental
Optical Sensors
1991
NIST
1951
Materials
Research
1985
Composite
Technology
Development
1988 Boulder Metrics
1994
Picosecond
Pulse Labs
1981
Scientech
1968
Engineering
Measurement
1967
Colormetrics
1996
Bell Labs
1965 STC
Communications
1977
Radish
Communications
1981
Karat
Communications
1993
Technology &
Management
Solutions
1985
Roache Chemicals
1973
Spring Step
1996
Allos Therapeutics
1994
At least one company founder was inter-
viewed from five of the seven trunks. Of
the 15 firms interviewed, the mean
number of employees is 222 (s.d. =632)
and mean annual sales (1997) is $6.2M
(s.d. =9.6). There were four concentra-
tion areas that bounded the interview:
(1) role of the incubator organization; (2)
role of Boulder County; (3) description
of the spin-off and how it emerged; and
(4) the entrepreneurial team. All inter-
views were recorded and later were
transcribed.
Semantic Structure Analysis
via NUD·IST2
Two forms of qualitative analysis,
domain and taxonomic analyses, were
NECK et al. 197
1960 1965 1970 1975 1980 1985 1990 1995 2000
1960 1965 1970 1975 1980 1985 1990 1995 2000
xx
xx
xx xxxxx xxx
x
xxxxx
x
xx
x
xxxxxx x
StorageTek
Ball Aerospace
1960 1965 1970 1975 1980 1985 1990 1995 2000
xxxxx
xxxxx xx xx xx
x
x
NBI
xx x x xxx xx xx x xxx xx
x
xx x x x x x
x
x
1984-1987 Chapter 11 bankruptcy
protection
5000 employees laid off from October,
1984 to September, 1985
1980: NBI's
Initial Public
Offering
1991: Chapter
11 bankruptcy
filing
Late 80s: Company
growth brings
bureaucratic structures
1998: Internal incubator
is established to retain
entrepreneurial engineers
Figure 2
Critical Incubator Moments Spawning Greater Rates of
New Venture Creation
2Interested readers may wish to have more detail on the methods involved in this study’s
semantic structure analysis. Please contact the authors for more detail regarding the qualita-
tive methodology.
used to make sense of the interview data.
Both of these analyses are based on
semantic relationships and thus can be
classified as semantic structure analysis
(Spradley 1980). First, the domain analy-
sis was used to uncover patterns in the
data. Next, taxonomic analysis was used
to uncover relationships among the iden-
tified patterns. “The domain analysis and
taxonomic analysis are often combined
into a single process because the taxo-
nomic analysis is often an extension
of the domain analysis” (Spradley 1980,
p. 116). The entire qualitative analy-
sis (domain and taxonomic) was con-
ducted using a computer aided text
analysis (CATA) software program called
NUD·IST. The use of computer software
to analyze qualitative data allows for a
more systematic approach to the analy-
sis that contributes to reduced coding
error, increased objectivity, validity, and
rigor (Wolfe, Gephart, and Johnson
1993).
A domain is defined as a category
of meaning that includes other smaller
categories (Spradley 1980). Using the
interview questions, an initial domain
list was developed, and as the inter-
views were coded, other domains were
added. Upon completion, the domain
analysis is simply a hierarchical coding
schema designed to bring order to
unstructured data. Then, the taxonomic
analysis allows the researcher to dis-
cover the story of the patterns and the
relationships among specific domains
(Spradley 1980). The patterns are based
on semantic relationships (for example,
X is a part of Y; X describes Y; X is a
kind of Y).
The authors’ interest was in identify-
ing the parts of the entrepreneurial
system in Boulder County as well as in
identifying the role the incubator played
in the spin-off. It soon became evident
that these questions were not exclusive
mutually. Rather, they were tied to each
other by one semantic relationship: X is
a part of Y. The taxonomy combines
domains into a larger, more inclusive
domain: the Boulder County entrepre-
neurial system. The taxonomy shown in
Figure 3 depicts the Boulder County
entrepreneurial system as the domain,
and all boxes to the right of this domain
illustrate the relationship each compo-
nent has to the other in the entrepre-
neurial system.
The taxonomy should be read right to
left in order to understand how each
component is related (Spradley 1980).
There are two domains, incubator organ-
izations and the county, that represent
the core of the entrepreneurial system.
More important, however, are the parts
of these domains and how these parts
connect with the whole. There are six
major components within Boulder
County that emerged from the taxonomic
analysis (see Figure 3). First, the rela-
tionship between incubators and their
related spin-offs plays an important role
in creating and growing the entrepre-
neurial system. Next, formal and infor-
mal networks are critical to supporting
and enhancing new venture creation.
Finally, the physical infrastructure and
culture also contribute to the spawning
effect within the boundaries of the
system. Together, these components
(incubators, spin-offs, informal networks,
formal networks, physical infrastructure,
and culture) are all related and are all
part of the Boulder County entrepre-
neurial system.
The percentages noted in Figure 3
indicate frequency of responses (for
example, 73 percent of the founders
interviewed discussed the university as
playing a role in the number of high-
technology startups in Boulder County;
67 percent of the founders participate in
some type of informal network). In the
following sections the taxonomy is used
to guide this discussion. The components
will be defined in greater detail, and
interview excerpts will be used to
support the components (parts) further
we uncovered in the system.
198 JOURNAL OF SMALL BUSINESS MANAGEMENT
Entrepreneurial System
Components
It is necessary for descriptive purpose
to discuss the components of the Boulder
County entrepreneurial system independ-
ently. However, this study’s notion of a
system points to the interaction of the
components and the relationships each
has with the other. Therefore, it seems
fitting to begin with a quote from a founder
that exemplifies looking at the whole
system comprised of individual parts.
NECK et al. 199
Figure 3
Taxonomy of the Boulder Country Entrepreneurial System
Components with Frequencies of Founders Reporting
Second and
Future
Generation
Spin-Offs
73%
60%
73%
53%
67%
47%
20%
100%
67%
County
Informal Network
Formal
Network
Physical Infrastructure
Culture
University
Professional/Support Services
Government
Capital Sources
Talent Pool
Large Corporations
13%
33%
Incubator
Organizations
Implicit
Spin-Offs
(New Ventures)
Explicit
Spin-Offs
(New Ventures)
Components of the Boulder County
Entrepreneurial System
67%
“Every one of the founders really
likes the Boulder County area. We
like the quality of life and there is
good access to high-tech jobs. We
all have a history in engineering-
type disciplines, and so that com-
bination of having the right skill
set and having the right environ-
ment attracted us all here. And the
community is very, in my opinion,
very proactive in terms of wanting
new companies to start up. And I
expect new technology to continue
to be developed here. I think right
now if you talk to most of the
major venture capital companies,
they do have some investment in
Boulder County one way or
another and it’s seen as a very
positive thing.” (Founder,
Company 12)
The Incubator Spin-Off
Relationship
It was found that the incubator can
play an implicit or explicit role in the
entrepreneur leaving her or his current
organization to start a new venture.
Those incubator organizations playing an
implicit role were not aware of the
employee planning to leave and to start
a related business. As a result, the role
the incubator played revolved mainly
around the founder acquiring technical
or product knowledge, market knowl-
edge, experience, and relationships with
customers who eventually would follow
the founder. From Figure 3, it can be
seen that 67 percent of the founders’
incubators played an implicit role. Those
incubators who played an explicit role
knew about the employee’s intention,
and the incubator provided support in
terms of such things as assistance in
setting up the business or use of facili-
ties and equipment. In 33 percent of the
companies interviewed, the incubator
played an explicit role. Arguably it can
be stated that all incubators provide
some type of implicit role in terms of
developing skills and abilities necessary
to the entrepreneur’s success; however, it
is necessary to show that some incuba-
tors do provide, or at least try to play, an
explicit role. The first excerpt is illustra-
tive of an incubator playing an implicit
role while the second excerpt pertains to
an explicit role.
“Because of the experience that I
had learned at [incubator], I knew
exactly how to mark-up these
products and how to bring them to
market and what customers really
needed. And so it turns out that
that experience I had at [incuba-
tor] was invaluable when it came
to marketing the lines of products
that we have now.” (Founder,
Company 7)
“So they wanted to get out of
the business, but they had signed
contracts with a variety of cus-
tomers with installed systems that
they would be around for five, ten
years to support these systems. So
for them to get out of the business,
they had to find somebody to do
that support, and since [ Joe] and I
were both involved in that depart-
ment, we said, ‘Gee, we’ll start
[Company 9], and we’ll take over
all that for you.’ They said, ‘Great.
Here’s all the equipment.’ They
basically set up our business.
(Founder, Company 9)
Founders were asked about their own
role as an incubator in spinning off new
ventures (second generation spin-offs).
The majority of the companies inter-
viewed (87 percent) indicated that their
company had not incubated entrepre-
neurs. A critical issue for the founders
was keeping the entrepreneurial talent
they had in-house and their preference
not to play an explicit role in incubating
their employees. The next excerpt is
indicative of these findings. However, the
200 JOURNAL OF SMALL BUSINESS MANAGEMENT
one following does point to the excep-
tion of those founders interviewed. The
founder of Company 4 (the only one in
this sample) spoke about the desire
to incubate but about the difficulties
involved (second excerpt).
“Really we try to keep people
here. The reality is we’ve tried to
structure an environment where
people, even if they have an entre-
preneurial kind of makeup and
desire, they have the opportunity
to do things here to fulfill that.
(Founder, Company 14)
“I think we would like to be more
of an incubator. In fact, we have
some money put aside if a good
idea comes along, whether it be
internal or external, we would be
open to looking into that. But,
that’s a very difficult field to get
involved in. It’s a tricky thing
because you need to look at a high
number of opportunities before
you find something that’s worth-
while. You don’t want to beat the
drum too loud and then people
will come up with ideas and you
keep giving them negative feed-
back.” (Founder, Company 4)
Informal and Formal Networks
This study’s perspective of networks
in the entrepreneurial system is that of a
social network defined as “as set of nodes
(for example, persons, organizations)
linked by a set of social relationships (for
example, friendship, transfer of funds,
overlapping membership) of a specific
type” (Laumann, Galskeiwicz, and
Mardsen 1978, p. 458). Therefore, the
various aspects of the network in the
entrepreneurial system are joined by
various relationships (Tichy, Tushman,
and Fombrun 1979). For this analysis, fol-
lowing Birley (1985), the social network
was separated into formal networks (uni-
versity, government,professional and
support services, capital sources, talent,
and large corporations) and informal
networks (friends, families, colleagues,
and informal relations with similar high-
technology companies).
The informal network appeared to be
an important element of the system. In
fact, 67 percent of those interviewed
identified at least one part of the infor-
mal network as being important to the
evolution of the entrepreneurial system
and their particular startup. One founder
expressed the role of the informal
network this way:
“What I think clicks and why
you get these threads of things is
really the social part, the commu-
nity building, where you get a
group of people that are in a work
situation and they see each other
under various kinds of stress over a
period of a year or so. The company
blows up or is acquired or becomes
non-profitable or something like
that and you get one or more people
leaving. You know, there’s a
natural tendency for those people
to kind of come together again.
Since there’s been this shared expe-
rience, and if they come together
again, it’s almost an indication
that there’s a trust relationship.
You ca n have fantastic ideas, but
any idea is going to break on you
and you just have to have that kind
of social inertia to make it work.”
(Founder, Company 2)
The formal network as can be seen
from the taxonomy (Figure 3) is com-
prised of the research university, regional
government agencies, professional and
support services (for example, lawyers,
accountants, consultants, suppliers),
capital sources (for example, venture
capitalists, business angels, and banks),
a high-technology talent pool, and large
corporations. Each of these components
of the formal network ranged in per-
NECK et al. 201
ceived importance from the sample of
founders from 73 percent for both the
importance of the university and for pro-
fessional and support services to only 47
percent for large corporations. When
taken together, the components of the
formal network clearly are critical for the
growth and evolution of an entrepre-
neurial system.
The University. The importance of a
research university for the development
of an entrepreneurial system has been
discussed since Frederick Terman from
Stanford helped launch Silicon Valley
by supporting Hewlett and Packard
(Bahrami and Evans 1995; Bruno and
Tyebjee 1982). The university can
support the system in many ways, such
as developing talented graduates, gener-
ating leading-edge technology, and pro-
viding faculty as consultants. Within the
formal network, the university was
among the most commonly cited reasons
(73 percent) for the development of the
entrepreneurial system:
“You know, IBM, I’m sure
wouldn’t have located here if it
hadn’t been for the university, and
I expect the Bureau of Standards
likely wouldn’t have been here.
So it’s sort of a symbiotic relation-
ship between these.” (Founder,
Company 4)
Government. The role the government
plays in the development of an entre-
preneurial system is an important area of
study. The government can play many
other roles, in either fostering or ham-
pering entrepreneurship in their regions
through tax rates and incentives, in pro-
viding other forms of financial support,
and in eliminating the bureaucratic “red
tape” often associated with applying for
permits and licenses. One founder noted
the importance of the government (or
lack thereof):
“You don’t get people, regulators
and others, walking in your door
wanting to check everything. I’m
not saying companies should not
be regulated. I think we should
have regulation and so on, but
you can stifle a company and
drive them into the ground by
policing them too much. You
don’t get that happening here.”
(Founder, Company 3)
Professional and Support Services. This
component includes entrepreneurial tax
and legal support, and consultants, as
well as the existence of organizations
that provide other inputs, some of which
go into the finished product. Professional
and support services were identified by
73 percent of the respondents as an
important component of the entrepre-
neurial system:
“The accounting firms are here
and some of them have specialists
in high-tech here. There are a
number of very competent corpo-
rate attorneys now that are expe-
rienced in start-ups and initial
public offerings, plus the fact
that you have the other services.
You’ ve go t machine shops and
glassblowers and electronic as-
semblers and all that.” (Founder,
Company 13)
Capital Sources. The growth of Boulder
County’s high-technology activity has
attracted venture and other forms of
capital. Although some of the founders
from this sample were not convinced that
Boulder has developed extensive capital
sources, 53 percent did feel that the pres-
ence of capital sources was a necessary
component fueling new venture creation.
Not only are venture capitalists from
Silicon Valley entering the region, but
also many new venture capital firms have
been founded in the county.
202 JOURNAL OF SMALL BUSINESS MANAGEMENT
“There are a lot of people [in
Boulder] who have made a great
amount of money in the high-tech
business and investments and
through various jobs and stuff.
So there’s money available to
you—venture capital money. And
there are angels that will come
along, private investors who’ll
come along and invest in you.
(Founder, Company 15)
Talent Pool. Without ample talent in the
area, entrepreneurs are likely to go else-
where to start their ventures. In the
Boulder area, the early layoffs of talented
IBM employees played a large role in
supplying individuals to start ventures or
to be hired by other startups. The mere
presence of high-technology entrepre-
neurial activity can attract talented
people to an area. Furthermore, in a
region of densely populated and related
ventures, an employee can leave one
startup and immediately can find
employment at a similar startup in close
proximity to the employee’s previous
employer. In other words, there is a
cross-pollination occurring. In this
survey, 67 percent of the founders cited
talent pool as an important element of
the entrepreneurial system and that it
contributed to their founding and
success:
“There’s a critical mass of not
only technology knowledge or tech-
nical people if you’re thinking of
high-tech, but there’s also a lot of
people now that have the business
school skills. They know how to
raise money. They know how to
manage. They know how to grow
things. The other big thing that
people fail to realize is that it’s
not until employees can quit one
job and walk across the street
and get another that it’s easy
to attract people.” (Founder,
Company 13)
Large Corporations. Large corpora-
tions play significant roles in the evolu-
tion of an entrepreneurial system. First
they support the talent pool as identified
above. They often employ talented
people who feel stifled by the bureau-
cracy and eventually spin off a new
venture with tangible technology taken
from the incubator organization or
intellectual capital developed while
employed at the incubator. Additionally,
some of the larger corporations such as
IBM and Storage Technology in Boulder
County downsized and left many techni-
cal people unemployed. These individu-
als then were motivated to start new
ventures. Large corporations also can
provide the foundation for a technology
base in an area. As was found through
the development of the genealogical tree,
four employees of IBM who had been
working in the data storage area founded
their own storage company, Storage
Technology. Data storage now has
become the most prolific technology
developed in the Boulder County area.
One founder, speaking of the role of
large corporations, stated the following:
“I actually think, in my opinion, it
actually got started when [name
deleted] left IBM and started up
Storage Technology. Because when
Storage Technology grew to be a
fairly good-sized company there
were literally thousands of engi-
neering jobs between IBM and
Storage Technology. Then, Hewlett
Packard also was along the front
range—so that was the third, what
I would call anchor company, that
provided an area where engineers
could go between companies if
they needed to. It wasn’t a one-
company kind of environment. In
many towns, in the South espe-
cially or even in the Midwest,
there’ll be one manufacturing
plant or one company per town.
So, if you live in that town you
NECK et al. 203
don’t have many options. Boulder
started off much better off than
that. They had access to three large
companies then lots of smaller
companies were starting up in the
area.” (Founder, Company 7)
Physical Infrastructure
To d ifferentiate from the intangible
infrastructure found in the network, the
physical infrastructure is defined as the
tangible components of the county’s
infrastructure such as roads, traffic, office
space, housing, and real estate. Of all the
components of the entrepreneurial
system, the founders interviewed viewed
the physical infrastructure most nega-
tively. Their perception was that Boulder
County, through its high cost of living
and its recent no-growth government ini-
tiative, ultimately would limit further
growth of the entrepreneurial system.
Only 20 percent of the founders found
the physical infrastructure of Boulder
to be supportive of the entrepreneurial
system. This seems to be an issue in
Silicon Valley as well, since it is becom-
ing increasingly cost-prohibitive to locate
there, particularly for employees who
cannot afford housing in the area. Specif-
ically, Boulder County has open-space
and growth-control policies in place that
contribute to above-average property
values because land availability is scarce
(Cote 1999). Therefore, high-margin
firms will remain in the area, but when
margins begin to diminish they may be
priced out of the system.
“It’s really the high-margin com-
panies that can afford to stay here.
As soon as you’re out in the big
competitive world where your
margins are getting slimmed
down you won’t be able to pay
the rent, so people will move to
Weld County or wherever they’re
going these days where things
are cheaper.” (Founder, Company
5)
Given the constraints of the physical
infrastructure, the migration of entre-
preneurs to more cost-effective areas is
imminent. The corridor connecting
Boulder to Denver makes travel to and
from Denver International Airport con-
venient (40 minutes); however, as the
corridor continues to develop, areas
closer to Denver and outside of Boulder
County most likely will offer entrepre-
neurs lower cost alternatives.
Culture
The last component of the county
found in this study’s taxonomy is the
culture of Boulder County. According to
Mintzberg, Ahlstrand, and Lampel (1998)
culture is what makes an organization,
industry, or nation unique. Responses
included the geography and climate of
the region, the intellectual capital, the
high-technology capabilities, and the
“spirit of the West.” The culture of
Boulder County initially attracted the
entrepreneurs to locate to Boulder
County, and few enticements from the
outside can encourage them to move.
A full 100 percent of the founders in
this study cited culture as an important
element of the entrepreneurial system:
“Any time you tell someone, or you
put on an application, that you’re
from Boulder, it carries a cachet
that is useful. There’s a lot of intel-
lectual stimulation. There’s not too
much dumbness that goes on in
Boulder. It’s just everywhere you
turn there are neat people....Its
beautiful; it’s healthy.” (Founder,
Company 11).
Culture may be the single most impor-
tant element for a system to develop and
also may be the most difficult element to
replicate and to manage.
Discussion and
Implications
The genealogical tree of high-
technology companies born in Boulder
204 JOURNAL OF SMALL BUSINESS MANAGEMENT
County, in conjunction with a taxonomy
of the components of the entrepreneur-
ial system that support new venture cre-
ation, tell an intriguing story. The
genealogical tree provides insights into
the presence of seven primary incubators
that were the impetus for the densely
populated region of high-technology
spin-offs. The tree gives a surface view
of the evolution of the entrepreneurial
system and the impact new venture cre-
ation can have on an environment and
existing businesses in the environment.
For example, today managers from
Storage Technology peruse the tree and
ask, “How did we lose all these entre-
preneurs?” They go on further to try to
quantify their opportunity losses from
the related new ventures that did not stay
in-house.
The genealogical tree supports much
of the current literature on entrepre-
neurial environments and systems, but it
also expands our existing body of knowl-
edge in the field. It is evident that the
university plays an important role (Leslie
and Kargon 1996) and that a few large
organizations contributed to even more
spawning (Smilor, Gibson, and Kozmet-
sky 1988), as did the scientific institu-
tions (Van de Ven 1993). The tree,
however, visually depicts the true impact
of such “incubators” on the growth and
evolution of the system. Additionally, the
impact of time and the critical moments
of an organization over this time con-
tribute to the rate of new venture cre-
ation (see Figure 2). The old adage
“Pictures are worth a thousand words”
is not an understatement here. The
problem, however, is that pictures are
only snapshots; therefore, the authors
attempted to delve into the complexities
of the system to make sense of why and
how the genealogical tree was planted
and was nurtured.
From this starting point, Phase II of
the study was begun, which included
interviews of a sampling of high-
technology founders. The taxonomy of
the Boulder County entrepreneurial
system unfolds an accurate story of what
must be in place for a region to attract
high levels of entrepreneurial activity.
The components also are supported in
the literature (for example, Bruno and
Tyebjee 1982), yet the relationships
between and among the components
have been researched less. It should be
noted that perception could be just as
important (if not more) as reality. The
taxonomy was developed based on
the views of the founders living in
the system. More often than not, the
founders viewed the components as pos-
itive; however, any negative perceptions
of the system (physical infrastructure for
example) can have serious implications
on the future of the system. The region,
combined with the entrepreneurs in the
region, will encourage or will inhibit
future entrants; therefore, positive per-
ceptions become an important aspect of
maintaining the system. Capturing these
perceptions, as seen in the interview
excerpts, is one benefit of using qualita-
tive methods to study entrepreneurship.
Overall, these results represent only a
beginning in uncovering the phenome-
non of new venture creation. Studying
new ventures in the context of an entre-
preneurial system is a productive under-
taking; however, this study really only
has scratched the surface in terms of
understanding the dynamic relationships
involved within the system. From inter-
views with founders, the components of
the entrepreneurial system can be seen
to represent an evolving process; these
components came into existence over
time and continue to evolve and to
expand.
The question of replication is chal-
lenging. Before modeling of entrepre-
neurial systems for replication can begin
(if it can), first a “theory of evolution”
must be created to understand how entre-
preneurial systems are built over time. In
the case of Boulder County, the evolution
followed a well-defined path can be spec-
NECK et al. 205
ulated with some certainty—from the
founding of the university through the
establishment of a number of “anchor”
organizations to the development of a
highway, a new international airport, and
the influx of local venture capital (Cote
1999). These “moments” mark critical
time periods in the evolution of Boulder
County as an area of dense high-
technology entrepreneurial activity. The
intricate networks that have been devel-
oped throughout the system are highly
complex and involved, which make inten-
tional replication of these successful net-
works virtually impossible (Hannan and
Freeman 1977). According to Aldrich
(1999, 1990) the rate of new venture cre-
ation is highly dependent on the events
experienced by existing organizations in
the population; therefore, the evolution
of Boulder County as an entrepreneurial
system could not have been predicted.
For example, the ups and downs of
the older, established corporations have
motivated aspiring entrepreneurs to leave
and to start new ventures. It would not
be wishful thinking to have corporations
replicate the Chapter 11 bankruptcies of
StorageTek and NBI and the layoffs that
resulted. However, these moments were
critical in the evolution of the Boulder
County entrepreneurial system. It is
evident from Figures 1a and 1b that the
number of firms spawned from these two
companies had a strong economic
impact. A cofounder of StorageTek was
quoted recently as saying, “I have this pet
theory that entrepreneurship starts out of
the ashes of older companies. You need
success and failure in order to generate
more and more startups ...You look at
all the companies that have StorageTek as
an ancestor, and there are quite a few of
them. That has a lot to do with the ups
and downs of StorageTek” (Cote 1999,
p. 12).
Conclusion
At a time when the rate of total entre-
preneurial activity is decreasing in the
United States due to the recession and
the dot.com bust (Zacharakis et al. 2002),
the importance of entrepreneurship
to economic development cannot be
understated. This research exposed the
elements of a system that spawns
regional entrepreneurial activity.The out-
comes of strong entrepreneurial systems
were not addressed explicitly, but these
certainly can be implied. Job creation,
wealth creation, business growth, and
economic prosperity—these are all out-
comes of entrepreneurship when healthy
systems are in place (Morris 1998). But
as we continue to find our way in our
new networked and knowledge-based
economy, it is quite possible that entre-
preneurial systems, as this study has
depicted, ultimately will transcend phys-
ical boundaries.
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... Entrepreneurial ecosystems are defined as the interacting elements that foster new firm creation in a specific context (Neck et al., 2004) and research on entrepreneurial ecosystems contributes to our understanding of entrepreneurship (Neck et al., 2004), while literature focuses on gaining an understanding of components within these systems (Cohen, 2006). Likewise, the Global Startup Ecosystem Ranking provides a framework to understand entrepreneurship (Compass, 2017) and, the entrepreneurship ecosystem in Tel Aviv ranked sixth in the world in 2020. ...
... Entrepreneurial ecosystems are defined as the interacting elements that foster new firm creation in a specific context (Neck et al., 2004) and research on entrepreneurial ecosystems contributes to our understanding of entrepreneurship (Neck et al., 2004), while literature focuses on gaining an understanding of components within these systems (Cohen, 2006). Likewise, the Global Startup Ecosystem Ranking provides a framework to understand entrepreneurship (Compass, 2017) and, the entrepreneurship ecosystem in Tel Aviv ranked sixth in the world in 2020. ...
... Innovation focuses on combining resources in new ways that create value for users, while entrepreneurship involves developing and exploiting business opportunities based on innovation. The extant literature concerned with explaining entrepreneurial ecosystems (Audretsch et al., 2019;Neck et al., 2004) and the national systems of innovation in which they are embedded (Lundvall, 2010) emphasizes technology-based innovation as the foundation for entrepreneurial opportunities. ...
... A study conducted by Cohen [101] reported that 67 percent of surveyed entrepreneurs regarded the access to qualified human capital as of key importance for the success of their business ventures. For any region to become a hub of successful business startups, the potential to attract qualified skilled workers who seek excitement, challenge, and attractive compensation packages is the key [102]. Thus, in given assertions, the availability and access to qualify skilled human capital and effective talent management systems are critical factors. ...
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