Founding thefuture

OrganizationScience
Vol. 19, No. 1, January–February 2008, pp. 3–24
issn 1047-7039 eissn 1526-5455 08 1901 0003
informs®
doi 10.1287/orsc.1070.0311
© 2008 INFORMS
Founding the Future: Path Dependence in the Evolution of
Top Management Teams from Founding to IPO
Christine M. Beckman
Paul Merage School of Business, University of California, Irvine, Irvine, California 92697, cbeckman@uci.edu
M. Diane Burton
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, burton@mit.edu
We contrast life-cycle and path-dependent views of entrepreneurial firms by examining the evolution of top management
teams. We show how initial conditions constrain subsequent outcomes by demonstrating that the founding team’s
prior functional experiences and initial organizational functional structures predict subsequent top manager backgrounds
and later functional structures. We find that narrowly experienced teams have trouble adding functional expertise not already
embodied in the team. We also find that firms beginning with a limited range of functional positions are less likely to
develop complete functional structures. Importantly, we do not find functional structure and functional experience to be
interchangeable. We find that firms beginning with more complete functional structures are likely to go public faster, and
firms beginning with broadly experienced team members obtain venture capital more quickly regardless of the experience
and structural composition of the top management team in place at the time of these outcomes. Further, broadly experienced
founding teams that build an early team with a full complement of functional positions achieve important milestones
faster than firms that start with neither experience nor structure. This suggests that creating positions as “placeholders” in
new ventures, where positions are created and filled with the intent of bringing individuals with more relevant experience
onboard later, is not obviously a path by which to succeed. By examining the origins of top management team experience
and functional structures, we illustrate the lasting imprint of founders on top management team composition and firm
outcomes.
Key words: entrepreneurship; organization and management theory; organizational evolution and change; organizational
demography
Introduction
The popular press often portrays successful high-tech-
nology firms being launched by specialized techno-
logical geniuses: Brilliant scientists found a company
(frequently in a garage), then attract more broadly expe-
rienced executives and venture capital to bring the firm
to the next level (Audia and Rider 2005). A similar view
is taken by entrepreneurship scholars who take a life-
cycle perspective (e.g., Greiner 1972): Executives are
replaced as the firm outgrows their capabilities in a pro-
cess of “professionalization” (Hellman and Puri 2002,
Boeker and Karachalil 2002). Our research examines the
extent to which these images reflect reality. There is
broad consensus that successful firms are led by sea-
soned professional managers who bring a full range
of skills to the venture (Roberts 1991, Cooper et al.
1994, Burton et al. 2002) and create an organization
of functional structure with clear roles and accountabil-
ity (Ancona and Caldwell 1992, Keck 1997, Roure and
Keeley 1990, Jensen and Zajac 2004, Sine et al. 2006).
Yet we know relatively little about how teams and firms
evolve over time.
Although many pundits explicitly recommend that
entrepreneurial firms replace founders with professional
managers (Charan et al. 1980, Flamholtz and Randle
2000, Wasserman 2003), it is less clear how a new
firm founded by narrowly experienced technologists
in an undifferentiated functional structure is able to
attract broadly experienced team members and develop
a broad portfolio of functional positions. In fact, much
of the extant organizational literature that emphasizes
homophily (McPherson et al. 2001, Ruef et al. 2003),
imprinting (Boeker 1988, Burton and Beckman 2007),
and inertia (Hannan et al. 1996, Phillips 2005) suggests
that this kind of professionalization and organizational
evolution would be both difficult and unlikely.
In this paper we explore how the breadth of founder
prior experiences and early decisions about functional
structures influence the types of executives who are
attracted and retained and the types of structures that are
subsequently put into place. We contrast the life-cycle
perspective with a path-dependent view of firm develop-
ment. We argue that, contrary to the images of the pop-
ular press and life-cycle theories of entrepreneurial firm
development, homophily and imprinting operate such
that subsequent executives and structures bear a strong
resemblance to founding executives and structures. Our
research extends the idea that founders bring important
experiences and make critical choices early in a firm’s
history that leave a lasting organizational imprint.
Building on established traditions in top management
team demography and upper echelon literatures, we
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Beckman and Burton: Path Dependence in the Evolution of Top Management Teams
4 Organization Science 19(1), pp. 3–24, © 2008 INFORMS
examine two facets of the team: the breadth and depth
of the position assignments in the new venture and the
prior experiences that team members bring to the firm
(Bunderson and Sutcliffe 2002). We conceptualize prior
functional experience as a measure of the team’s human
capital (whether someone has prior sales or engineering
experience, for example) and functional assignments as
a measure of functional structure distinct from the skills
and qualifications of any specific incumbent (whether a
firm has a vice president of sales or engineering, for
example).
Interestingly, although the extant literature recognizes
both structural and human capital differences among
nascent ventures, they are rarely considered simultane-
ously. Instead, scholars interested in functional struc-
ture tend to ignore the characteristics of the individuals
who occupy structural positions (e.g., Roure and Keeley
1990, Sine et al. 2006), and scholars interested in teams
and individuals tend to ignore structure (e.g., Cooper
et al. 1994). Indeed, in much of the top management
team (TMT) demography research, functional structure,
and experiences are considered interchangeable (e.g.,
Ancona and Caldwell 1992, Keck 1997).
Treating structure and experience as conceptual and
empirical equivalents may be reasonable in established
organizations, where we expect to see team members
with relevant experience in a position (e.g., a person with
a sales background in a sales job). In entrepreneurial
ventures, however, there may or may not be a match
between prior functional experience and current func-
tional assignment. Consider the technologist with no
management experience who takes on the role of pres-
ident, the sales person who is responsible for human
resource management or customer service, and the recent
business school graduate with prior engineering expe-
rience who fulfills the business development or mar-
keting function. This potential for a mismatch between
prior experience and structural assignment offers a
compelling arena in which to compare life-cycle and
path-dependent perspectives. Whereas life-cycle mod-
els advocate that firms create positions as “placehold-
ers” until executives with the relevant experience can
be hired and the firm can be professionalized (Hell-
mann and Puri 2002, Boeker and Wiltbank 2005), path-
dependent models would be more cautionary, given the
potential dangers of functional structures filled by in-
dividuals with atypical experience (Burton and Beckman
2007). In sum, we argue that functional experience and
functional structure are distinct, and we explore their
interrelationships and their effects on firm outcomes.
Theory and Hypotheses
Prior experience of the top manager and the functional
structure of a firm have long been of interest in the TMT
demography (Pfeffer 1983) and upper echelons litera-
tures (Hambrick and Mason 1984). A relatively large
body of empirical research confirms the intriguing and
sensible possibility that the demographic composition of
TMTs has consequences for organizational strategy and
performance (see Finkelstein and Hambrick 1996 and
Williams and O’Reilly 1998 for reviews).
A large number of studies have focused on functional
diversity and demonstrated a relationship among top
manager functional diversity and a variety of outcomes
including firm performance, reorientation, and exter-
nal communication (e.g., Eisenhardt and Schoonhoven
1990, Ancona and Caldwell 1992, Lant et al. 1992).
When theorists posit a positive main effect of functional
diversity, they generally argue that diversity enhances
organizational performance because broad functional
representation ensures that the TMT has the full range
of capabilities needed to manage the organization (e.g.,
Keck 1997, Randel and Jaussi 2003). Although the main-
stream demography literature has advanced to identify a
variety of process variables that account for the relation-
ship between diversity and outcomes (e.g., Smith et al.
1994), as well as a host of factors that moderate the
relationship between diversity and outcomes (e.g., Jehn
et al. 1999), an important conceptual distinction between
functional experience and functional structure has been
largely ignored. The literature has generally used the
same logic to account for diverse functional structures
and diverse functional experiences, treating these dimen-
sions as interchangeable and considering the choice of
measuring structure or experience a methodological detail
(but see Bunderson and Sutcliffe 2002 for an exception).
Functional structure refers to the existence of func-
tional roles or positions irrespective of any person who
might occupy the role, but functional experience refers
to the human capital characteristics of the individual
incumbents. This distinction is theoretically interesting,
as it allows us to consider team evolution from both
a structural perspective and a human capital/social psy-
chological perspective. If structure and experience are
distinct and separable constructs, each should have a
unique effect on firm outcomes. Structure and experi-
ence may also evolve through different paths, or one
may be antecedent to the other. Our research considers
these possibilities and extends the existing empirical and
theoretical literatures by distinguishing functional expe-
rience from functional structure. Our work contributes
to the small but growing number of studies that are lon-
gitudinal by design (Boone et al. 2004, Sørensen 2004),
and so can also respond to calls to explore the sources
of demographic distributions in organizations (Mittman
1992, Lawrence 1997, Carroll and Harrison 1998) and
address why TMTs “look the way they do” (Hambrick
2007, p. 338).
We address Hambrick’s call by examining the role of
the founding team in creating the experiences and struc-
ture of the subsequent TMT. If path dependence occurs,
then initial functional structures will predict a deepening

Organization Science 19(1), pp. 3–24, © 2008 INFORMS 5
of these structures over time. If homophily occurs, then
initial functional experiences will predict a deepening of
these experiences over time. If functional structure and
functional experience are interchangeable, then having
either will enable a firm to broaden as it evolves. Further-
more, we examine whether these initial characteristics of
the team and firm have lasting consequences. If, as life-
cycle theories predict, initial functional structures and
experiences are irrelevant to subsequent changes, then
there should be little relationship between the founding
team experiences and structures and subsequent experi-
ences and structures, particularly as founders are replaced
and firms mature. Thus, in stark contrast to a path-
dependent perspective, where origins are a source of sub-
sequent constraint, the life-cycle perspective emphasizes
opportunity and adaptation.
In summary, we consider five interrelated questions:
(1) whether the functional experience of the founders
shapes initial decisions about functional structure,
(2) whether the initial functional structure constrains
future functional structure, (3) whether the initial func-
tional structure shapes the functional experience of exec-
utives hired by the firm, (4) whether the functional
experience of the founders influences the experiences of
executives who join subsequently; and (5) whether the
initial functional structure and experiences shape firm
outcomes.
To examine these questions, it is important to first dis-
tinguish between the founding team and TMT. Founding
teams are made up of people who create the firm, irre-
spective of whether they hold executive titles. For exam-
ple, a founder may hold a position of “director of engi-
neering” rather than vice president. TMTs are made up
of people who hold executive titles, regardless of when
they join the firm. Although there is overlap between
these teams at founding if all founders hold executive
titles, the teams are conceptually and empirically dis-
tinct. Founders are not added as the firm grows, and,
as TMT members join the firm and founders leave, the
teams continue to diverge.
Our first question about the relationship between prior
functional background experience and initial functional
structural decisions draws on two ideas—that func-
tional background experiences shape a person’s world
view and that people carry their prior experiences with
them across organizational settings. We rely on early
statements and recent empirical evidence suggesting
that functional training conditions individual cognitions
(Dearborn and Simon 1958, Sutcliffe 1994, Tripsas and
Gavetti 2000) and an established empirical tradition
demonstrating that when employees leave an organiza-
tion, they carry that organization’s routines and ideas
with them (Baty et al. 1971, Boeker 1997, Sørensen
1999, Phillips 2002). For example, the functional expe-
rience and strategy of the founder’s prior firm influ-
ences the strategy of the new firm (Boeker 1988), and
founders’ experiences in a prior firm shape the routines
and practices they put in place in a new firm (Phillips
2005, Beckman 2006). In addition, there is growing evi-
dence that the functional background experiences of a
TMT influence how it defines and enacts organizational
positions (Fligstein 1990, Phillips 2005). Extending this
idea to initial decisions about the allocation of positions
and responsibilities, we hypothesize that founders will
put functional structures in place that mirror their own
experiences (Schein 1992, Burton and Beckman 2007).
For example, a founding team with a member from a
sales and business planning background may decide to
combine the sales and business planning functions under
a single executive and build an organization where these
functions are closely interrelated and externally (cus-
tomer) oriented. The background of the initial marketing
executive—business development, classical marketing,
or sales—leads to different choices about what the mar-
keting function does and with which other functions it
is aligned. Thus we hypothesize:
Hypothesis 1 (H1). Founding team functional expe-
rience will shape initial functional structure.
Once the initial functional structures are put into
place in an organization, they are likely to be main-
tained and strengthened over time. Support for this argu-
ment comes from several theoretical traditions. Social
theorists have long argued that institutions are self-
reinforcing (Michels 1915, Downs 1967). In addition,
theories of organizational imprinting suggest that initial
decisions about the allocation of responsibility among
team members have lasting consequences (Stinchcombe
1965, Baron et al. 1996, Hannan et al. 1996, Burton
et al. 2002). For example, Baron et al. (1999) find
that founding organizational blueprints, around which
employment relations are managed, predict subsequently
adopted decisions and structures (including adding new
functional positions; creating formal documentation and
organizational charts). Finally, arguments of structural
inertia suggest that initial structures will be maintained
over time (Hannan and Freeman 1984). Thus, a range
of work suggests that initial functional structures predict
later functional structures. We therefore hypothesize:
Hypothesis 2 (H2). Founding functional structure
will shape the breadth and depth of subsequent func-
tional structure.
Founding functional structure will also likely shape
subsequent management functional experience. Exten-
sive literature on job analysis—which in modern human
resource management is the foundation of job descrip-
tions, job design and redesign, performance appraisal,
selection, and training—defines jobs as combinations of
tasks that require particular knowledge, skills, and abili-
ties that can be generically specified (cf. Fine and Cron-
shaw 1999). Indeed, the extensive literature on organi-
zational design, formalization, and even internal labor

markets has a vision of clearly defined and hierarchi-
cally ordered positions or roles (see Osterman and Bur-
ton 2004 for a recent review). Jobs exist in organiza-
tions as “placeholders” against which individuals in the
labor market can be matched (e.g., Wanous 1992; see
Miner 1987 for a review of this literature and an alter-
native view). Similarly, these characterizations of roles,
jobs, and positions imply that the organizational func-
tional structure shapes the characteristics of subsequent
incumbents.
Consider again the firm in which sales and business
planning positions are closely aligned. When a new
executive is recruited to take over the combined position,
the structure of the position will influence the choice
of executive for the position. A different founding team
might decide to create stand-alone sales and business
planning functions, which would lead to different future
candidates. Thus, the structural choices made by the
founding team have implications for the characteristics
of the subsequent executives who would be capable of
filling the defined positions, attracted to the opportu-
nity, and attractive to the incumbent team members. Our
arguments imply that structural decisions made by firm
founders constrain the pool of people who might be will-
ing or able to join the firm. Thus we hypothesize:
Hypothesis 3 (H3). Founding functional structure
will shape the breadth and depth of subsequent func-
tional experience.
Finally, there are reasons to expect an associa-
tion between the prior functional experiences of the
founding team and subsequent TMT experience. Sev-
eral mechanisms (which may operate simultaneously)
could generate this path dependence. For instance, the
attraction-selection-attrition (ASA) cycle described by
Schneider (1987) would predict that founding and future
TMTs will share similar characteristics. Managers seek
organizations where existing personnel have similar char-
acteristics, founders select managers like themselves, and
managers who do not fit will leave. For example, Boone
et al. (2004) find that even when environmental conditions
shifted dramatically, Dutch newspaper executives tended
to hire new executives who were demographically similar
to those already in place. Thus, founders and managers
alike should be attracted to one another when they share
common experiences and knowledge.
A large literature on homophily (Rogers and Bhowmik
1971, Ruef et al. 2003) also suggests this relationship.
Although research on homophily has generally focused
on categories such as race and gender, there is grow-
ing evidence that the same processes apply to occupa-
tions (McPherson et al. 2001). Founders may privilege
and recruit executives with functional experiences
similar to their own rather than executives with func-
tional experience that may be more relevant for the posi-
tion being filled. For example, engineers might prefer
a CEO with a technical background over one with a
finance background. It is important to note that these ten-
dencies toward functional homophily within a position
may result in team-level functional heterogeneity. Teams
will be functionally diverse if, for instance, individ-
ual preferences for homophily exist on founding teams
where members come from a variety of functional back-
grounds. Alternately, founders with diverse functional
backgrounds (functional generalists) may value that vari-
ety and seek TMT members who themselves have diverse
experiences. Thus, at the team level, homophily and
similarity-attraction arguments imply similarity between
the experiences of the founding team and the experiences
of the TMT. We therefore hypothesize:
Hypothesis 4 (H4). Founding team functional expe-
rience will shape the breadth and depth of subsequent
TMT functional experience.
Following a path-dependent logic, our hypotheses sug-
gest a tight linkage between initial team experiences/
structures and subsequent TMT experiences/structures.
Importantly, this implies there will be relatively little
change in functional structure or human capital experi-
ence from the founding team to later teams. Thus, in
sharp contrast to the dominant image of narrowly experi-
enced engineers in an unstructured nascent venture who
are replaced by professionals who evolve the firm into a
professional bureaucracy, our hypotheses imply that ini-
tial founding team characteristics and structural choices
should be a powerful predictor of later experiences and
structures—even controlling for compositional changes.
Contrary to a life-cycle perspective that would be agnos-
tic about initial conditions, our theoretical arguments
imply that initial conditions restrict subsequent firm and
team options.
To further understand the lasting consequences of
these initial conditions, we also directly link found-
ing experiences and structures to firm outcomes. Both
the entrepreneurship and TMT literatures offer ample
evidence linking human capital characteristics such as
the type and amount of prior experience to firm suc-
cess (Aldrich and Zimmer 1986, Roberts 1991, Cooper
et al. 1994). Other work finds that a range of prior
experiences as well as shared experiences benefit the
firm (Eisenhardt and Schoonhoven 1990, Beckman et al.
2007). Still other work links the functional structure of
the firm to firm outcomes (Ancona and Caldwell 1992,
Keck 1997, Roure and Keeley 1990). More recently,
Sine et al. (2006) demonstrate that formalized functional
positions and functional specialization is positively asso-
ciated with firm success in a sample of Internet start-ups.
Together these studies document that a broad set of both
team functional experiences and functional structures are
predictive of firm outcomes. Thus, we hypothesize:
Hypothesis 5 (H5). The breadth of founding team
functional experiences and functional structures are pos-
itively associated with firm success.

Interestingly, the existing literature is silent as to
whether structure might be more important to firm suc-
cess than experience or vice versa. If the structure and
experience are distinct conceptual constructs, then they
should have independent effects. If, as the extant demog-
raphy literature has implied, structure and experience are
interchangeable representations of the same underlying
construct, then having either broad functional experience
represented among the founding team members or a dif-
ferentiated functional structure should be sufficient to
fuel the development of a firm with a broadly experienced
TMT and a differentiated functional structure. However,
if structure and experience are not interchangeable, then
an increase on one dimension cannot compensate for a
weakness on another dimension. Our analyses explore
these alternatives.
If, as we posit, the founding conditions set teams and
firms on a particular path, then cross-sectional studies
of TMTs overattribute outcomes to the current team and
overestimate the extent to which teams can be reformed.
We pursue a research strategy that begins with the found-
ing team and then tracks changes in personnel—both
through entrances and exits—and in functional compo-
sition to explore exactly how the founding team and
initial structures shape the subsequent TMT and later
structures.
Data and Methods
This paper begins with a sample of entrepreneurial high-
technology firms in California’s Silicon Valley that were
studied as part of the Stanford Project on Emerging
Companies (SPEC) (see Baron et al. 1999 for a detailed
description) but includes additional data on individual
executives. The focus on firms in a single region allows
us to hold constant key labor market and environmental
conditions. Within the region, the SPEC study focuses
on the high-technology industries of computer hardware
and/or software, telecommunications, medical devices
and biotechnology, semiconductors, manufacturing, and
research. The sampling frame explicitly oversamples
young and small firms. The firms in the sample have
at least 10 employees and are no more than 10 years old
at the time data collection begins in 1994–1996. About
half of the firms are founded before 1989, and thus the
median age of the firms in 1994 is five years. Our sample
is not representative of all start-up firms in that we have
fewer solo founders and more teams of three or more
founders, but this is typical of high-technology start-ups
(Eisenhardt and Schoonhoven 1990, Ruef et al. 2003).
Our sampling frame has the disadvantage of biasing the
sample toward firms that have survived several years and
thus are more likely to be (or become) successful. That
said, we sample firms that both do and do not receive
venture funding and go public. We see no a priori rea-
son to expect that our hypothesized effects, where TMTs
are constrained and shaped by founding teams, will be
different for a broader sample of start-up firms.
The key independent and dependent variables for this
study are constructed from career histories. We construct
a monthly database of every founder and every execu-
tive that ever worked for one of the sampled firms from
founding through December 2000 or the time of initial
public offering (IPO), acquisition, or failure (see below).
The founding team was identified in an interview with
the founder (the mean founding team has 2.82 mem-
bers), and all subsequent TMT members are identified as
those individuals ranked as vice president or higher (e.g.,
senior vice president, CTO, CIO, COO). It is impor-
tant to note that founders do not always hold TMT
titles (as evidenced by an average TMT smaller than the
founding team at time zero). Our data sources include
interviews (conducted in 1994–1995 and 1996–1997),
internal company documents (business plans and pro-
motional documents), Lexis/Nexis news searches, Dow
Jones Interactive, Edgar Archives (useful for firms about
to go public and for top managers who have been
involved with public companies), The San Jose Mercury
News (the local paper has a regular column on promo-
tions, movements, and resignations in the Silicon Val-
ley), and extensive Web searches. Over a six-year period
we completed at least four complete searches for each
person and spent thousands of person-hours collecting
career data on team members. We confirmed, via inter-
view or telephone, nearly 50% of the career histories col-
lected through 1996–1997 with the person designated by
the CEO or the human resources person. This increases
the reliability of the earliest team data, the most difficult
period to gather consistent data through archival sources.
Despite extensive research, we do not obtain complete
career histories on all team members. Often the chronol-
ogy of careers is correct but the dates unclear. This data
problem precludes us from constructing duration vari-
ables such as years of experience in a particular function,
a method commonly pursued by demography scholars.
Because some of our team data may be incomplete, we
make a point to control for variables that may impact the
completeness of the data (i.e., firm size) as well as the
average amount of person data collected by firm.
Our final database contains information on 1,485
executives in 167 firms holding 1,940 positions in our
sampled firms. We collect a median of two past posi-
tions for each person, including employer identity and
job title, with a maximum of 19 positions for a sin-
gle person, although we limit our analysis to the prior
three employers. This includes data for executives (often
founders) who we confirm had no prior work experience
(at least 38 founders join one of our firms directly from
school). For Hypotheses 1–4 and our analysis of team
evolution we rely on our full sample (167 firms). For
our analysis of outcomes, firms that are not independent
(e.g., wholly owned subsidiaries) or at risk of going pub-
lic (e.g., nonprofit research centers) are excluded (result-
ing in a sample of 158 firms for our outcome analysis).

Dependent Variables
In this research we examine three types of dependent
variables: (1) functional organizational structure, (2) team
member functional experience, and (3) firm out-
comes. The difference between functional structure
and team functional experience mirrors the difference
between functional assignment diversity and func-
tional background diversity in the demography literature
(Bunderson and Sutcliffe 2002).
Functional organizational structure is measured as
whether the firm has defined executive-level posi-
tions in each of the following six functional areas:
sales and marketing, general administration (includ-
ing human resources), science/R&D/engineering, oper-
ations, business development/strategic planning, and
finance/accounting. For each firm, we calculate whether
a firm has a given functional position, when it is first
established, and how many executive-level positions in
a given function simultaneously exist in a team for each
month of the firm’s life. For example, a technology-
intensive firm may be founded with a CTO and a vice
president of engineering. The vice president of engineer-
ing job is later transformed into the position of senior
vice president of engineering, and a vice president of
hardware and a vice president of software are hired. This
firm clearly has a science/R&D/engineering function. It
is established at age 0 and there are ultimately four
executive-level positions in this function on the TMT.
We also create a count measure ranging from 0 to 6
that represents the number of functional categories cov-
ered each month to predict the breadth of functional
structure. Firms with no executive positions are coded 0
for structure; firms with executive positions for all six
functions are coded six.
Prior functional experience of TMT members is gath-
ered from career histories. We code up to three prior
positions for every individual into one of the six func-
tional areas (see above). From team-level career histories
we calculate a variable, updated monthly, indicating how
many team members have prior experience in a function
to capture the depth of functional experience on a team.
We also create a count measure ranging from 0 to 6
that represents the range of prior functional experience
brought by the team in each month and that thus cap-
tures the breadth of functional experience. A six indi-
cates that all possible functions are represented in the
prior experiences of the team.
We have two firm outcome measures: time to receive
venture capital (VC) and time to IPO, and we con-
duct event-history analyses to examine these outcomes.
These firm outcomes represent the most significant mile-
stones in the life of a young start-up (Shane and Stuart
2002), particularly during the time period and in the
region that we study. We focus on time to first VC fund-
ing rather than cumulative rounds or total funds raised,
because future rounds are based on more direct knowl-
edge about the firm than the first VC financing, and
amount is a firm and industry-specific choice (Gompers
and Lerner 1999). By modeling time to first VC fund-
ing, we examine characteristics of the team that allowed
the firm to obtain funding more quickly than other firms,
as well as whether they receive VC backing. By choos-
ing IPO as our second dependent variable, we can com-
pare the performance of entrepreneurial firms across
multiple industries—a task that is quite difficult using
accounting-based measures of profitability. Recent stud-
ies have examined IPO as an outcome variable indicating
firm success (Stuart et al. 1999, Certo et al. 2001, Gulati
and Higgins 2003, Shane and Stuart 2002, Hannan et al.
2006). This IPO measure also allows us to examine a
firm outcome that occurs over a longer time horizon
than initial VC funding. VC financing and IPO data are
collected via public and proprietary databases (such as
Venture One and Venture Economics), government fil-
ings, annual reports, internal company documents, and a
survey instrument sent to the most senior finance exec-
utive in the firm (see Hellmann and Puri 2002).
Of our 158 firms at risk of IPO or VC, 26 exit the
risk set through IPO, acquisition, merger, or failure with-
out securing VC, and another 14 do not receive VC
by the end of 2000. Thus, 118 firms (71%) obtain VC
funding and 87 (51%) go public during our sampling
period. At first glance these numbers seem unusually
high; however, the end of our time period (late 1990s)
witnessed an explosion of VC investments and IPOs in
entrepreneurial firms in the United States.
Independent and Control Variables
Our key independent variables are the founding team’s
functional experiences and initial functional structures.
These measures are created like the dependent vari-
ables but focus on the team and functional struc-
tures at founding. That is, we code the breadth and
depth of initial functional structure and founding team
functional experience in each of the following six func-
tional areas: sales and marketing, general administration
(including human resources), science/R&D/engineering,
operations, business development/strategic planning, and
finance/accounting. At founding the mean number of
unique functional positions, our measure of structure,
is 1.8, which typically represents a firm with a general
administrative position such as president or CEO and a
vice president of science or engineering. The mean num-
ber of prior functional experiences at founding is 1.5.
Firm-Level Controls. Firm size is the number of em-
ployees at the start of a calendar year, lagged by one
year. Because of the skewed distribution of this mea-
sure, we use a logged measure in our analyses. We
control for whether the firm had an innovation strat-
egy, because strategy has been linked to VC financing
in prior research (Burton et al. 2002). We also control

for whether the firm sought to differentiate itself through
its sales, marketing, or service, as this strategy implies
a greater need for the sales and marketing function than
other strategies. Initial strategy is coded from interviews
with the founder and has been empirically validated (see
Hellmann and Puri 2000). For example, firms with inno-
vation strategies are those that described themselves as
“first movers.” In addition, we control for the date the
firm shipped its first product, because product shipment
may affect the skills and structures required as well as
firm outcomes. We also include the cumulative num-
ber of rounds of VC funding that the firm had obtained
because such firms are more likely to go public (Gom-
pers and Lerner 1999), but we obtain similar results
when we use a simple dummy variable (e.g., equal to
1 when the firm obtains VC). Finally, we control for
the amount of firm-level team data collected by includ-
ing the average number of prior positions collected for
each person in the firm. This allows us to control for
the possibility that we have more data on individuals in
successful firms.
Team-Level Controls. We include founding team size
and then include measures for the cumulative entrances
and exits to the TMT as controls. These variables cap-
ture both change and growth in the teams (Tushman
and Rosenkopf 1996, Beckman et al. 2007). A life-cycle
perspective suggests that growth is the critical determi-
nant of success, and these entrances and exits would
be expected to wipe out any effects of origin. Further,
these controls ensure that our effects for experience and
structure are net effects of turnover. The proportion of
TMT positions held by founders is included to control
for the extent to which founders with executive titles are
counted as part of both teams. All team variables are
updated monthly.
Industry-Level Controls. Medical devices and the bio-
technology industry (combined as medically related) is
the only significantly different industry for our out-
comes; thus, we include a dummy variable for this indus-
try in all models. The number of IPOs in each industry
by year controls for industry-specific variation in rates
of IPO, and the number of VC deals by year controls
for available financial resources.
Results
Descriptive statistics and a correlation matrix for the
full sample are presented in the appendix. To exam-
ine the influence of the founding team’s prior func-
tional experience on the initial functional structure (H1),
we conduct an event history analysis predicting time
to the first executive-level position in a functional
area using Cox proportional hazards models with the
Huber/White/sandwich estimator of error and clustered
by firm to correct for heteroskedasticity and serial corre-
lations. We regress the time to the first position for five
different functions on the prior functional experience of
the founding team. The key independent variable is how
many members of the founding team had prior experi-
ence in the function. (We exclude general administration
because almost all firms start with a president or CEO.)
We report these results in Table 1. For each func-
tional area we generate a baseline model that includes
control variables only and then a test model that adds
a variable indicating the amount of relevant prior func-
tional experience on the founding team. The number of
exits indicates the number of firms that ever create an
executive-level position in the function reported. During
our observation period, 75% of the firms create a posi-
tion in the science/engineering function (125 of 167);
only half ever create an executive position responsible
for manufacturing/operations (82 of 167), and fewer than
one-fourth create an executive position in business devel-
opment or strategic planning (42 of 167). Firms that
have a function at founding—in other words, a member
of the founding team creates the position—are censored
immediately. Our models therefore capture the rate of
functional position creation for those firms that do and
that do not have the relevant prior functional experience.
Table 1 reports hazard ratios and reveals that larger
firms with larger founding teams, and those that obtain
VC financing, create functional positions at a higher rate.
For two of our five functional areas, science/engineering
and sales/marketing, we find that having functional expe-
rience represented on the founding team significantly
increases the rate at which the structural position is
added to the TMT. Founding teams with sales experi-
ence are 69% more likely to add a sales position. Found-
ing teams with science experience are 44% more likely
to add a science position. The coefficients are in the
predicted direction for both finance and strategic plan-
ning/business development, although they do not achieve
statistical significance. Based on these results, we find
modest support for H1.
To examine the relationships between initial func-
tional experience and initial functional structure on sub-
sequent team functional experience and later functional
structures (H2, H3, and H4), we perform yearly panel-
poisson regression analyses predicting counts of expe-
rience and structure for each function. We specify an
AR1 error structure to account for serial autocorrelation
and again report robust standard errors. These results are
presented in Table 2.
Table 2 is organized into two panels with yearly team-
level observations. The first panel presents our results for
TMT functional structure. The second panel presents our
results for TMT prior experience. The first six models
in each panel represent each of the functional areas of
interest and are counts of the depth or number of func-
tional positions or experience in each area. The final
model in each panel is a cumulative count variable that

Table 1 Event History Analysis Predicting Time to First Functional Position
(1) (2) (3) (4) (5)
Science/ Sales/ Mfg./ Finance/ Strategy/
Engineering Marketing Operations Acct. Bus. Dev.
Log firm size 1 20∗∗
1 29∗∗
1 25∗
1 08 1 49∗∗∗
0 09 0 13 0 14 0 11 0 23
Medical-related industry 0 98 0 28∗∗∗
0 9 1 21 2 05∗
0 21 0 11 0 32 0 30 0 85
Innovation strategy 1 26 1 14 1 23 0 97 1 46
0 22 0 27 0 38 0 22 0 70
Marketing strategy 0 8 0 84 1 81∗
0 9 1 59
0 23 0 24 0 62 0 24 0 76
Cumulative rounds of VC 1 49∗∗∗
1 29∗∗∗
1 26∗∗∗
1 21∗∗∗
1 19∗
0 14 0 10 0 08 0 08 0 12
Prop. founders on TMT 0 92 0 88 0 82 0 59∗∗
0 95
0 07 0 12 0 19 0 13 0 28
Product developed 1 01 0 77 0 50∗∗
1 18 0 55∗
0 23 0 17 0 15 0 27 0 20
Average number of prior person positions 1 06 0 91 0 97 0 88 1 2
0 08 0 09 0 09 0 09 0 16
Founding team (FT) size 1 17∗∗∗
1 16∗∗
0 99 1 18∗
1 1
0 06 0 09 0 09 0 10 0 15
Cumulative entrances to the TMT 1 12 1 25∗∗
1 1 1 02 1 05
0 13 0 14 0 11 0 09 0 17
Cumulative exits from the TMT 0 82 0 87 0 9 0 79 0 85
0 23 0 20 0 19 0 23 0 17
FT prior science/engineering exp. 1 44∗∗∗
0 11
FT prior sales/marketing exp. 1 69∗∗∗
0 24
FT prior mfg/operations exp. 0 76
0 31
FT prior finance/accounting exp. 1 4
0 38
FT prior strategy/business dev. exp. 1 63
0 97
Observations 6,054 7,343 9,762 8,756 12,562
Exits 125 121 82 114 42
Firms 167 167 167 167 167
Log-pseudolikelihood −558 62 −515 27 −367 73 −498 34 −187 38
Note. Robust standard errors.
∗
Significant at 10%; ∗∗
significant at 5%; ∗∗∗
significant at 1%.
ranges from 0 to 6 to capture the breadth of functional
positions or experiences.
We test our second hypothesis, that founding func-
tional structure will be associated with subsequent
functional structure, in the first panel. Across all speci-
fications, there is a strong positive relationship between
the founding structure and the subsequent structure, even
controlling for whether the founding team has experi-
ence in a given functional area. Model 7 in Panel 1
presents the count variable predicting the number of
functional positions eventually covered by the firm.
Consistent with the results for each function, firms that
begin with more initial structure are likely to cover more
functional areas over time. Thus, while the founding
team prior experiences shape initial structures (in mod-
est support of H1 in Table 1), it is these initial structures
that shape subsequent structures (in strong support of H2
in Panel 1 of Table 2).
We test the impact of initial structure and founding
team prior experience on later TMT prior experience
in Panel 2 of Table 2 (H3 and H4). Contrary to H3,
initial functional structures do not serve as placehold-
ers to facilitate bringing in later executives with rele-
vant functional experience. Indeed, the only statistically
significant finding (for sales/marketing positions) is the
opposite of this prediction.
However, the pattern of results revealed in Panel 2 of
Table 2 shows support for H4. There is a strong rela-
tionship between the functional background experience
of the founding team and that of the later TMT prior
experience, even controlling for changes in team compo-
sition. The relationship is consistently revealed for each
of the functional areas (Models 1–6) and in the cumu-

Table2PanelPoissonwithRobustStandardErrors,withAR1ErrorStructure,PredictingTMTExperienceandStructure
Panel1:TMTfunctionalstructurePanel2:TMTpriorexperience
(1)(2)(3)(4)(5)(6)(7)(1)(2)(3)(4)(5)(6)(7)
Science/Sales/Mfg./Finance/Admin/Strategy/Num.ofScience/Sales/Mfg./Finance/Admin/Strategy/Num.of
Engin.Mktg.Ops.Acct.HRBus.dev.functionsEngin.Mktg.Ops.Acct.HRBus.dev.Priorexp.
FTpriorscienceexp.007043∗∗∗
006006
FTscienceposition033∗∗∗
−004
006006
FTpriorsalesexp.029∗∗∗
054∗∗∗
010009
FTsales/mkt.position015∗
−017∗∗
007008
FTpriormfg./ops.exp.−005149∗∗∗
023021
FTmfg./ops.position096∗∗∗
017
015020
FTpriorfin./acct.exp.−003089∗∗∗
021024
FTfin./acct.position087∗∗∗
018
015021
FTprioradmin./HRexp.005047∗∗∗
006013
FTadmin./HRposition022∗∗∗
−006
003008
FTpriorbusinessdev.exp.−011124∗∗∗
051031
FTbusinessdev.position071∗∗
005
028057
FTpriorexperience−000014∗∗∗
count002003
FTstructure011∗∗∗
001
count002003
Log-firmsize007∗∗∗
007∗∗∗
011∗∗
005∗
003∗∗
015∗
003∗∗∗
001−001−001009∗
0003001
002003004003001009001002003005005002007001
Medical-related053∗∗∗
−037035045∗∗∗
022∗∗
117∗∗∗
014∗∗
019−046∗
042027−003056∗
011∗
industry014034025015010039007014027026024024033007
Innovationstrategy01−024∗
007−025∗
008026−00301−01042∗
0019022006
013013019014007041005011013024018017037006
Marketingstrategy01−017031−003020∗∗
044−002017009039019013012008
016017020016009045005013015031022020048007

Table2(cont’d.)
Panel1:TMTfunctionalstructurePanel2:TMTpriorexperience
(1)(2)(3)(4)(5)(6)(7)(1)(2)(3)(4)(5)(6)(7)
Science/Sales/Mfg./Finance/Admin/Strategy/Num.ofScience/Sales/Mfg./Finance/Admin/Strategy/Num.of
Engin.Mktg.Ops.Acct.HRBus.dev.functionsEngin.Mktg.Ops.Acct.HRBus.dev.Priorexp.
CumulativeVC001004∗∗
003006∗∗
001004002∗∗
002007∗∗∗
008∗∗
008∗∗∗
004001004∗∗∗
rounds002002002002001005001001002004003003005001
Prop.founders017−072∗∗∗
−064∗∗
−131∗∗∗
031∗∗∗
−088−037∗∗∗
−013−039−091∗∗∗
−149∗∗∗
−066∗∗∗
−049−044∗∗∗
onTMT023020027030009061008018025033036025049011
Avgnum.prior002−025∗∗∗
−01−001−002−002−003017∗∗∗
020∗∗∗
028∗∗∗
018∗∗
008031∗∗
014∗∗∗
pers.positions007006009007003016002004006009008006012003
Foundingteamsize008∗∗
006−009006001004002∗
−003008∗
0080101002003
004005006005002009001004004009007006016002
CumulativeTMT016∗∗∗
019∗∗∗
017∗∗∗
013∗∗∗
009∗∗∗
020∗∗∗
009∗∗∗
015∗∗∗
024∗∗∗
021∗∗∗
016∗∗∗
015∗∗∗
025∗∗∗
013∗∗∗
entrances003003003003001006001002003003004003005002
CumulativeTMT−022∗∗∗
−022∗∗∗
−026∗∗∗
−020∗∗∗
−009∗∗∗
−035∗∗∗
−015∗∗∗
−016∗∗∗
−022∗∗∗
−017∗∗∗
−027∗∗∗
−013∗∗∗
−029∗∗∗
−015∗∗∗
exits003003005004002010002003005004005005008002
Productdeveloped−029∗
−026−035∗∗
−019008−046−010∗
−033∗∗
−011017−053∗∗
017004−003
016017017015007048006014014027025016035006
Constant−165∗∗∗
−037−142∗∗∗
−101∗∗∗
−050∗∗∗
−315∗∗∗
086∗∗∗
−126∗∗∗
−197∗∗∗
−336∗∗∗
−212∗∗∗
−151∗∗∗
−362∗∗∗
000
033026036033014070010023029051038031076015
Observations1,2561,2561,2561,2561,2561,2561,2561,2561,2561,2561,2561,2561,2561,256
Numberoffirms167167167167167167167167167167167167167167
Waldchi-square359.44437.37290.98170.94380.4193.19502.59288.2352.42220.31157.88152129.33507.41
Differenceinchi-square120.2212.4106.78−18789.5974.3323.99123.775.42103.995.61−3876.97111.08
frombaseline
Note.Robuststandarderrorsinbrackets.
∗
Significantat10%;∗∗
significantat5%;∗∗∗
significantat1%.

lative count measure (Model 7). It is important to note
that only the parallel structure or experience is predic-
tive. In supplementary analyses we confirmed there were
no effects for the noncorresponding functions. In other
words, sales experience does not predict the establish-
ment of a science position; it is only science experience
that is significantly associated with science functional
structures and subsequent science experience. We present
the more parsimonious models in the paper for purposes
of clarity.
Across most specifications we see that large firms,
and firms where teams are growing, have more broadly
experienced TMTs and more functional positions. This
suggests that firms are growing and becoming more
experienced over time, which is consistent with a life-
cycle perspective. Further, firms with VC funding often
gain TMT experience and functional structures. How-
ever, our findings imply that structures and experiences
accrue more to those firms that are already advantaged.
Overall, our findings for structural precedent (we find
support for H2 but not for H3) are weaker than our find-
ings for cognitive framing (H1) and homophily (H4). Yet
we see that initial functional structures matter (H2).
Finally, to test H5 regarding firm outcomes, in Table 3
we conduct event history analyses on monthly observa-
tions and report Cox proportional hazards models using
maximum likelihood estimation and robust estimates of
standard error (Lin and Wei 1989). The founding year
is represented as age = 0 with all the initial conditions
represented as covariates that are updated where appro-
priate. Firms remain in the sample until they achieve the
outcome of interest; until they cease to exist as indepen-
dent entities through failure, merger, or acquisition; or
until the end of the sample period, at which time they
are censored.
We present our results in two panels in Table 3 to
demonstrate the influence of founding team on the tim-
ing of two different outcomes: obtaining VC and com-
pleting an IPO. Model 1 is the baseline model that
includes controls only. Note that team compositional
changes are accounted for by the inclusion of measures
of both entrances to and exits from the TMT. Model 2
examines founding team variables and includes count
measures for both the amount of initial functional struc-
ture in the firm and the amount of prior functional expe-
rience possessed by the founders. In Model 3 we also
include the interaction of these terms. The main effects
are centered prior to calculating the interaction (as sug-
gested by Cronbach 1987) to reduce collinearity between
the main effects and the interaction term. Model 4 adds
the same count variables and their interaction for the
TMT team to assess whether the effects of the founding
team are eliminated when the subsequent team is con-
sidered. It is in this model that we most strongly assess
path dependence against life cycles in determining the
relationship between team and firm characteristics and
outcomes. As in Table 1, we report hazard ratios, so
numbers larger than 1 indicate an increase in the rate,
and numbers smaller than 1 indicate a decrease in rate
of achieving the firm outcomes.
In the first panel, the VC analysis, we see that firm
size and the average amount of data collected for team
members are both positively associated with attaining
VC financing. In addition, TMT departures are posi-
tively related to obtaining financing. This may indicate
that firms replace executives to build a team attractive
to venture capitalists. In Model 2 we find that each
additional functional area represented in the prefound-
ing career history increases the likelihood of attracting
VC financing by 14%. The effect of functional struc-
ture is also positive but not statistically significant. Inter-
estingly, in Model 3, the interaction of structure and
experience is negative and statistically significant. The
interaction effect should be interpreted as the effect of
experience on the outcome when structure is 0. The
influence of founding functional experience on the time
to VC financing is weaker for firms that begin with no
functional structure; they have a 13% lower likelihood
of receiving VC. Not surprisingly, the founding team
effects are attenuated when we include characteristics of
the subsequent team in Model 4 (although the interaction
remains significant) because, as we know from Table 2,
founding team experience also predicts TMT experience.
The strong correlation between the founding and TMT
composition in the early years makes Model 4 difficult
to interpret; however, the pattern of results suggest that
the range of prior experience held by the founding team
is an important correlate of VC financing, and firms that
start with both experience and structure reach this mile-
stone faster than other firms.
In Panel 2 of Table 3 we present a similar set of anal-
yses for time to IPO. The control variables have larger
effects on the rates of IPO. Firms in medical-related
industries go public at least five times more quickly than
firms in other industries, and firms in industries with a
high number of IPOs go public more quickly than firms
in other industries. In addition, we see that the effect
of turnover has two countervailing effects on rates of
IPO: firms benefit from entrances and are hindered by
exits. These effects, while consistent with the life-cycle
perspective, do not wipe out the founder effects, as seen
in Model 2. Thus, origins do matter for outcomes. In
contrast to our VC findings, Model 2 in Panel 2 reveals
that functional structure is associated with an increased
likelihood of IPO, and prior experience is not. In Model
3 we see that the interaction of structure and experience
is negative and statistically significant, suggesting that
structure cannot substitute for a lack of experience. The
influence of founding functional structure on the time to
IPO is weaker for firms that begin with no prior func-
tional experience; they have a 23% lower likelihood of

Table 3 Event History Analysis: Effect of Founding Team on Firm Outcomes
Panel 1: VC Panel 2: IPO
(1) (2) (3) (4) (1) (2) (3) (4)
Firm size 1 65∗∗∗
1 65∗∗∗
1 70∗∗∗
1 61∗∗∗
1 29 1 16 1 19 1 18
0 16 0 16 0 17 0 17 0 22 0 21 0 21 0 23
Medical-related industry 1 14 1 3 1 37 1 38 5 46∗∗∗
6 97∗∗∗
8 63∗∗∗
7 10∗∗∗
0 27 0 31 0 33 0 36 1 86 2 52 2 92 2 65
Innovation strategy 1 29 1 33 1 36 1 38 0 74 0 7 0 68 0 77
0 30 0 31 0 32 0 34 0 20 0 19 0 19 0 23
Marketing strategy 0 8 0 82 0 78 0 79 1 11 1 03 0 93 0 9
0 23 0 24 0 23 0 24 0 39 0 35 0 31 0 30
VC deals/IPOs in industry 1 1 1 1 1 18∗∗∗
1 19∗∗∗
1 18∗∗∗
1 18∗∗∗
0 00 0 00 0 00 0 00 0 03 0 03 0 03 0 03
Cumulative VC 1 12∗∗
1 14∗∗∗
1 14∗∗∗
1 08
0 06 0 06 0 05 0 06
Avg. person positions 1 19∗∗
1 19∗∗
1 18∗∗
1 19∗∗
2 21∗∗∗
2 30∗∗∗
2 46∗∗∗
2 58∗∗∗
0 09 0 09 0 09 0 09 0 31 0 33 0 35 0 40
Founding team (FT) size 1 02 0 99 1 1 01 1 13 1 02 1 09 1 03
0 05 0 05 0 05 0 05 0 09 0 09 0 10 0 10
Product developed 0 91 0 94 0 89 0 89 0 66 0 69 0 71 0 60∗
0 20 0 21 0 20 0 21 0 18 0 19 0 20 0 18
Prop. founders on TMT 0 95 0 97 0 94 0 97 0 54 0 59 0 53 0 77
0 10 0 11 0 12 0 12 0 22 0 25 0 24 0 33
Cumulative TMT entrances 0 86 0 81 0 83 0 66∗∗
1 63∗∗∗
1 66∗∗∗
1 68∗∗∗
1 43∗∗
0 13 0 13 0 13 0 12 0 16 0 17 0 18 0 21
Cumulative TMT exits 1 71∗
1 63∗
1 80∗∗
2 75∗∗∗
0 66∗∗∗
0 65∗∗∗
0 63∗∗∗
0 75∗
0 48 0 46 0 50 1 00 0 06 0 07 0 07 0 11
FT structure count 1 07 1 11 0 87 1 41∗∗∗
1 50∗∗∗
1 45∗∗∗
0 13 0 13 0 18 0 21 0 21 0 20
FT experience count 1 14∗
1 19∗
0 95 0 94 1 05 1
0 11 0 11 0 13 0 12 0 15 0 15
FT structure ∗ experience 0 87∗
0 79∗∗
0 77∗∗∗
0 78∗∗∗
0 07 0 09 0 07 0 07
TMT structure count 1 4 1 78∗∗∗
0 29 0 33
TMT experience count 1 53∗∗∗
1 33
0 24 0 24
TMT structure ∗ experience 1 05 0 89
0 12 0 08
Observations 6,107 6,107 6,107 6,107 13,085 13,085 13,085 13,085
Log-pseudolikelihood −516 91 −515 43 −513 86 −506 96 −290 02 −287 6 −284 12 −276 69
Exits 118 118 118 118 86 86 86 86
Firms 158 158 158 158 158 158 158 158
∗
significant at 1%.
going public. The effects of the founding structure per-
sist through the inclusion of contemporary structure (see
Model 4). Structure may be an important signal to public
investors.
In general, our findings suggest that venture capitalists
are more concerned with the prior experience of execu-
tives in firms that they fund, whereas the public markets
evaluate functional structure. Both milestones are more
easily achieved by the firms that start with both structure
and experience. A key conclusion from the analyses in
Table 3 is that although the impact of the TMT tends to
be stronger than the founding team on these outcomes,
founding team effects persist, controlling for changes to
the team.
Supplementary Analyses
The above findings begin to establish organizational
functional structure and incumbent prior functional
experience as distinct constructs and demonstrate sup-
port for our main theoretical argument that initial con-

Table 4 Descriptive Statistics for Founding Teams Initial Types
(1)
Simple structure (2)
(narrow range of Simple structure, (3)
functional positions), broadly Complete structure
narrowly experienced team (broad range of (4)
experienced team (broad range of functional Complete (4) (4) (3) (2)
Full (limited range of prior prior functional positions), narrowly structure, broadly vs. vs. vs. vs.
Row Variable sample functional experiences) experiences) experienced team experienced team (1) (3) (1) (1)
1 Number of firms 167 50 14 44 59
2 Mean founding 2 82 2 16 2 71 2 82 3 41 17 57∗∗∗
3 65∗∗
4 23∗∗
n.s.
team size
3 Cumulative entrances 5 50 4 30 5 64 5 61 6 39 10 32∗∗∗
n.s. 3 53∗
n.s.
4 Cumulative exits 1 68 1 48 1 93 1 73 1 76 n.s. n.s. n.s. n.s.
5 Proportion of founders 0 55 0 60 0 50 0 56 0 52 n.s. n.s. n.s. n.s.
on TMT
6 Mean TMT size 4 42 3 24 4 43 4 32 5 49 20 02∗∗∗
5 06∗∗
3 97∗∗
n.s.
7 TMT experience 2 78 2 12 3 36 2 61 3 32 14 56∗∗∗
4 71∗∗
n.s. 6 23∗∗∗
8 TMT functions 3 27 2 56 3 64 3 55 3 58 9 21∗∗∗
n.s. 7 49∗∗∗
4 22∗∗
9 Proportion VC backed 0 71 0 58 0 71 0 68 0 83 8 42∗∗∗
2 76∗
n.s. n.s.
10 Proportion that 0 51 0 42 0 43 0 52 0 61 3 93∗∗
n.s. n.s. n.s.
achieve IPO
11 Firm age at end of 7 00 9 00 7 50 7 00 6 00 16 58∗∗∗
n.s. 5 58∗∗∗
2 94∗
observation period
Notes. Two-tailed tests for F -statistic. We do not include comparisons between cells 2 and 3 and cells 2 and 4 because there are not
significant differences. ∗
p < 0 10; ∗∗
p < 0 05; ∗∗∗
p < 0 01.
ditions constrain subsequent evolution. However, our
hypothesis tests do not allow us to fully understand the
interrelationships between structure and experience over
time. The strong support for the effects of initial expe-
rience on subsequent experience and for the effects of
initial structure on subsequent structure contrasted with
the weaker or nonexistent support for the cross effects.
This suggests that structure and experience are not sub-
stitutable. Having one does not appear to compensate for
the other.
To explore the interrelationships of structure, expe-
rience, and outcomes, we first descriptively character-
ize the team and firm evolutionary patterns revealed in
our data (see Table 4). The first column (Full sample)
presents overall means for all firms. We then divide
our sample, using mean splits on counts of founding
team functional experience and counts of initial struc-
tural positions, into four subsamples representing each
of the archetype cells described in Figure 1. Cell 1 most
closely captures the mythical “engineers in a garage”
as it describes a firm with a narrow range of functional
positions and functional expertise. In contrast, Cell 4
most closely captures the professional team in a func-
tional organization. The off-diagonals, Cells 2 and 3,
represent situations where the founding team has either
structure or experience, but not both.
Several points are noteworthy. First, Figure 1 and
Table 4 demonstrate that experience and structure are
clearly distinct concepts, and structure and prior experi-
ence do not always go hand-in-hand. The least common
starting state is represented by Cell 2—simple struc-
ture, but broadly experienced executives—which char-
acterizes 14 of 167 firms; however, firms are relatively
dispersed across the other cells. Firms with neither struc-
ture nor experience at founding (50 of 167 firms repre-
sented in Cell 1) appear to be disadvantaged on many
fronts: They start with smaller teams, do not grow as
much, and are less likely to receive VC or to go public
than firms with the most broadly experienced teams with
complete structures. (See Table 4, Rows 2, 6, 9, and 10.)
Table 4 also lends additional support for H5, that the
combination of initial background experience and func-
tional structure is important for firm success. Firms in
Cell 4 seem to achieve critical milestones more quickly
Figure 1 Archetype Founding Team Types
Cell 2 Cell 4
Cell 1 Cell 3
Organizational functional
structure
Low
Low
High
High
Prior
functional
experience
Complete structure
and
broadly experienced
team
Simple structure
and
broadly experienced
team
Complete structure
and
narrowly experienced
team
Simple structure
and
narrowly experienced
team
General partners
Engineers in
a garage
Business plan
competition entrants
Functional
organization

than firms in Cell 1. In addition, there is suggestive evi-
dence that narrowly experienced teams are not able to
accrue needed additional functional expertise as easily as
unstructured teams acquire structure. That is, comparing
narrowly and broadly experienced teams at each level
of structure (Cells 1 and 2; Cells 3 and 4), it appears
that, regardless of the starting structure, narrowly experi-
enced founding teams have significantly less broad TMT
experience at the end of the sample period (see Table 4,
Row 7). In contrast, when firms have broadly experi-
enced teams, the firms that lack initial functional struc-
tures (Cell 2) have the same level of structure at the end
of the time period as those that started with more com-
plete functional structures (Cell 4) (see Table 4, Row 8).
Thus, those teams with early functional experience can
develop functional structure, but those teams with early
functional structure do not develop functional experi-
ence. Finally, it is worth noting that executives exit all
types of firms at the same rate (see “Cumulative exits,”
Row 4 in Table 4). There are no significant differences
across the four starting states, suggesting there is not a
clear signal about “winning” firms.
In Table 5 we present monthly panel regression mod-
els, again correcting for autocorrelation and with robust
standard errors, where we attempt to discern the relation-
ship between origin state and ultimate destination. Given
the evidence that successful firms have broadly expe-
rienced TMTs and complete functional structures, we
are particularly interested in understanding the path by
which firms end up in this state. Recall our count mea-
sures for breadth of experience and structure that range
from 0 to 6. If we consider these as interval representa-
tions along two continua, then the product of experience
and structure, an interaction variable with a theoretical
range of 0 to 36, is a linear representation of the com-
bined amount of structure and experience. The larger
the product of TMT structure and TMT experience, the
closer the firm is to having a complete structure and
all functions represented in the prior experiences of the
TMT (i.e., Cell 4). We treat this product as our depen-
dent variable in a series of regression models where
the key independent variables are initial structure, initial
experience, and the interaction of the two.
In Table 5, we report a baseline model, Model 1, with
controls only. Models 2 and 3 add founder functional
experience and initial functional structure, respectively,
to the model. Model 4 includes both key independent
variables. Model 5 includes the interaction of these two
counts to assess the relative importance of each. This
allows us to examine the extent to which experience
and structure can serve as substitutes and whether one
is more important than the other in influencing firm
and team evolution. Consistent with life-cycle predic-
tions of professionalization, firm size, VC, and entrances
to the TMT are positively associated with having a
broadly experienced team and complete structure, and
TMT entrances is one of the largest effects in the model.
Yet net of all of these effects, we see that founding
team experience and initial structure are important corre-
lates of the final destination state. Comparing Models 2
and 3, we see that founder functional experience alone
improves model fit more than initial functional structure
alone. Thus, it appears that initial experience is a more
substantial predictor than initial structure. But Model 4
demonstrates a significant joint effect, and Model 5
reveals a slight positive interaction. This is evidence of
the advantages associated with starting with both struc-
ture and experience (Cell 4) at founding; however, the
strength of the experience main effect and the weak sta-
tistical significance attached to the interaction imply that
Cell 2 is a better origin state than Cell 3.
We explored several alternative explanations of our
findings. One additional explanation is that a match
between initial and subsequent functional experience is
created through preferences for experienced executives.
Although all firms may seek to hire broadly experienced
executives, it is only firms with broadly experienced
founding team members that are able to attract the exec-
utive talent necessary for future success. Although sim-
ilar to homophily, it would be a result of only broadly
experienced founders being successful at recruitment.
Although it is difficult to empirically disentangle these
mechanisms, it is worth noting that all varieties of found-
ing team experiences influence TMT experience, regard-
less of whether the experience is particularly relevant
for the firm’s strategy. This gives more credence to the
homophily explanation.
Another alternative explanation is that “good” firms
attract both broadly experienced founding teams and
TMTs rather than founding teams predicting TMTs. This
concern of unobserved heterogeneity is a common issue
in empirical work, and we have done what we can
to explore this possibility—that people are attracted to
firms and not to other people. This would imply that
rather than initial experience and structure increasing the
ability of the firm to reach important milestones, expe-
rienced TMT members may be drawn to firms that look
like winners. Thus, the causality could go the other way:
Good firms attract good people rather than good people
creating good firms. Although we cannot rule out this
possibility, we do control for several measures of firm
quality. In addition to controlling for size and strategy,
we are also including whether the firm had a product as
a control. Also, recall that the exit rates and proportion
of founders on the TMT across our four cells in Table 4
are not significantly different. On average, 1.7 executives
leave the firm and founders account for more than 50%
of the TMT. This suggests that firm quality is difficult
to observe; otherwise, executives and founders would
leave low-quality firms at higher rates. Thus, it seems
likely that prospective TMT members have an easier
time assessing the quality of the existing team than the

Table 5 Population-Averaged Panel Regression Analysis Predicting TMT Structure ∗ Experience, with Robust
Standard Errors and AR1 Error Structure
(1) (2) (3) (4) (5)
Log firm size 0 33∗∗∗
0 34∗∗∗
0 33∗∗∗
0 34∗∗∗
0 34∗∗∗
0 06 0 06 0 06 0 06 0 06
Medical-related industry −1 03 −0 35 0 14 0 18 −0 03
1 11 1 05 1 10 1 07 1 03
Innovation strategy 1 33 1 40 1 44 1 45 1 44
0 87 0 81 0 83 0 80 0 79
Marketing strategy 0 39 0 49 0 12 0 32 0 59
1 05 0 94 1 02 0 94 0 93
Cumulative rounds of venture capital 0 35∗∗∗
0 37∗∗∗
0 36∗∗∗
0 37∗∗∗
0 38∗∗∗
0 06 0 06 0 06 0 06 0 06
Prop. founders on TMT −0 09∗∗∗
−0 09∗∗
−0 09∗∗
−0 09∗∗∗
−0 09∗∗∗
0 03 0 03 0 03 0 03 0 03
Product developed 0 21 0 23 0 22 0 23 0 23
0 12 0 12 0 12 0 12 0 12
Average number of prior person positions 0 12 0 12 0 13 0 12 0 12
0 08 0 08 0 08 0 08 0 08
Founding team (FT) size 0 66∗∗
0 39∗
0 28 0 23 0 17
0 27 0 19 0 23 0 19 0 18
Cumulative entrances to the TMT 0 16∗∗∗
0 17∗∗∗
0 16∗∗∗
0 17∗∗∗
0 17∗∗∗
0 05 0 05 0 05 0 05 0 05
Cumulative exits from the TMT 0 08 0 07 0 08 0 07 0 06
0 12 0 12 0 12 0 13 0 13
FT prior experience count 1 90∗∗∗
1 52∗∗∗
1 29∗∗∗
0 37 0 42 0 43
FT structure count 1 80∗∗∗
1 02∗∗
0 86∗
0 45 0 48 0 46
FT exp. ∗ structure 0 70∗
0 38
Constant 2 16∗∗
2 61∗∗∗
3 02∗∗∗
3 00∗∗∗
2 82∗∗∗
0 85 0 71 0 81 0 71 0 69
Observations 14,269 14,269 14,269 14,269 14,269
Chi-square 131.58 183.36 160.08 192.54 192.27
∗
significant at 1%; two-tailed tests.
firm itself because the quality of the firm (independent
of people) is hard to assess. However, there may also be
an “escalation of commitment” (Staw 1976), whereby
subsequent team members remain with their firm despite
lower potential returns. Of course, the entrance rates are
significantly different across these cells. The founding
teams with both experience and structure grow more
rapidly than all other firms, but it appears these changes
in composition are driven by founding team composi-
tion. Still, understanding how people evaluate prospec-
tive employment opportunities in entrepreneurial firms
is an important area for future research.
Because we were able to observe firms for a rel-
atively short period of time, we are limited in our
ability to assess if and when founder imprints might
decay. In supplementary analyses we explore the extent
to which our results are driven by having relatively
young firms. We first replicated all our time-series anal-
yses, including yearly dummy variables to control for
the main effects of firm age and found results consis-
tent with those reported. We also replicated the analyses
in Table 2, Model 7, predicting both TMT functional
structure and TMT experience, including interactions
with initial experience and structure and firm age. We
find statistically significant age interactions; however,
the magnitude of the effects is trivial. We thus have
some confidence that our results hold for many years
post-founding.
We were concerned about several additional factors
that could have influenced our results. First, our effects
may be skewed by the bubble market of the late 1990s.
In supplementary analyses, we examine the possibility
that our results arise from period effects rather than our
theorized mechanisms. Our results are robust to restrict-
ing our VC financing events prior to 1993 (before the
market began to heat up) and our IPO events prior to
1996 (the first year that IPO rates jump significantly).

Firms may add positions to the TMT just prior to
receiving external financing or going public to signal
readiness to potential investors. We control for this
potential “window dressing” by reporting team entrances
and exits, and proportion founders on the TMT, lagged
12 months in all outcome analyses. Thus, changes made
within a year of the event were not considered. We found
substantially the same results with shorter and longer
lags, thus we feel comfortable using a conservative one-
year window. However, because we have announcement
dates and not dates when these discussions commenced,
we cannot completely rule out reverse causality.
Finally, we were concerned that the time-series data
may overemphasize the within-firm linkage between the
founding team and TMT. In addition to using robust
standard errors and correcting for autocorrelation in the
reported models, we also ran a series of panel regres-
sions. In these models we used founding team expe-
rience and structure to predict TMT experience and
structure (as in Table 2) at a given firm age (e.g., at year
4 and at year 8), and we found similar results.
Limitations
We have taken a first step in understanding TMT evo-
lution with rich longitudinal data. Of course, our study
has several limitations. First, as noted above, we observe
firms for a relatively short period of time and are thus
limited in our ability to assess the durability of founder
effects over long periods. A second weakness is that our
data for both executives and firms are somewhat incom-
plete. We do not have the kind of detailed performance
outcomes that are available for established public com-
panies. In addition, we may have been unable to find data
on TMT members who were not successful during their
career. However, ours is the first study to our knowledge
to attempt such a detailed look at the career histories of
executives in small firms over time, and such an examina-
tion almost by definition involves problems with missing
data. Furthermore, we have controlled for the potential
problem to the extent possible in all analysis.
A third limitation is that our sample has a success
bias because the firms survived on average five years
before we contacted them. We believe, however, that in
demonstrating an empirical phenomenon in an interest-
ing empirical setting and establishing a new model of
longitudinal research, the benefits of the sample far out-
weigh the concerns. Finally, there are questions of unob-
served heterogeneity that cannot be ruled out, although
we explore them to the extent possible in the above sup-
plementary analyses.
Discussion
Our research demonstrates that founding teams strongly
influence the TMT through path dependence. Consis-
tent with homophily expectations, founding teams that
begin with broadly experienced team members are more
likely to attract broadly experienced executives. Consis-
tent with ecological research, firms that begin with a
range of functional structures are more likely to develop
more complete functional structures. Thus, path depen-
dence, where the founding team shapes the subsequent
TMT, occurs through both homophily and imprinting.
We see cumulative advantage, as high-quality found-
ing teams become high-quality TMTs and less well-
endowed founding teams never catch up. In particular,
we see that 26% of our teams begin with broad
functional structures but narrowly experienced people
(Table 4), and they never catch up in terms of attracting a
broad range of functional experience. Firms founded by
narrowly experienced founders have difficulty attracting
broadly experienced executives. It does not seem to be
the case that narrowly experienced founders simply fail
to recognize the importance of other types of functional
expertise. Instead, even when the firm has created an
executive level position for a given function—a strong
statement that it needs and values that expertise—the
firm is limited in its ability to fill the position with the
relevant expertise if it does not already have an executive
in place with at least some experience in that function.
This suggests that structure is a poor substitute for expe-
rience. Thus, our results stand in sharp contrast to the
dominant image of engineers in an unstructured nascent
venture who are replaced by broadly experienced profes-
sionals who then formalize the structures and evolve the
firm into a professional bureaucracy. Our results imply
that the narrowly experienced “garage” entrepreneur is
not likely to succeed (Audia and Rider 2005).
Despite the significant findings, two of our hypothe-
ses receive modest or no support. We find only modest
support that initial functional experience predicts the
initial functional structure. Given the wealth of other
research documenting this transfer (Boeker 1988; Burton
and Beckman 2007; Phillips 2002, 2005), it is possible
that our measures of functional structure do not ade-
quately capture the nuance of how executives enact orga-
nizational positions. In addition, path dependence may
operate more strongly through homophily in the cases of
race or gender (see Phillips 2005). This would be a use-
ful area for future research, as initial functional structure
is an important decision that founders make.
Our lack of support for functional structures predict-
ing experience (H3) is quite relevant for human resource
management. At least in entrepreneurial firms, the struc-
ture of the position does not predict the experience
people bring to the firm, once controlling for initial
experience. Instead, it appears that the ASA frame-
work (Schneider 1987) and structural inertia (Hannan
and Freeman 1984) together account for the relation-
ship between early structure and experience and later
structure and experience. As noted above, establishing
positions and filling them with people who are “place-
holders” appears to be detrimental to the firm’s ability
to ultimately attract broadly experienced executives.

Little research has examined changes in teams over
time, much less from founding, and a major contribution
of this paper is the detailing of the relationship between
the founding team and TMT. We demonstrate that the
founding team exerts an influence on the firm not only
through directly influencing firm outcomes, but also by
shaping the very nature of the organization. An ahistorical
account of the TMT will overstate the ability of the TMT
to change; in fact, future teams may be best understood
by a detailed examination of the teams that have come
before. This finding limits the role of agency and suggests
sharp deviations from the initial path are unlikely (and
probably risky, see Hannan et al. 2006). Our research thus
further highlights the benefits of an evolutionary perspec-
tive on firms and teams (see Aldrich 1999).
We clearly see evidence of path dependence in our
analysis, and these effects are net of changes and growth
among the firms. The significant influence of team
entrances in many of our analyses, however, also offers
support for a life-cycle model of entrepreneurial firm
development. Growth does allow firms to add both func-
tional experience and structure, and these effects are sub-
stantive in our models. However, our intent here is to
demonstrate that the initial conditions do matter and not
all firms easily professionalize and grow. Particularly in
light of our lack of support for H3—initial structure does
not predict attracting that functional experience to the
firm—firms should be cautious in assumptions of adding
experience later. In contrast, our findings suggest deliber-
ate planning into the future is usefully done at founding.
Our results also add to the organizational demogra-
phy and upper echelon research, which has not to date
focused on developing dynamic models or explaining
the source of demographic distributions in organizations
(Lawrence 1997, Hambrick 2007). Our work begins to
address this weakness in the demographic approach by
exploring the path-dependent process that results in con-
tinued heterogeneity or homogeneity among teams. This
is not to say that organizational demography research has
not moved in important directions. To the contrary, criti-
cal work examines the team processes generated by diver-
sity (Knight et al. 1999, Pelled et al. 1999, Reagans and
Zuckerman 2001) and the difficulties of using indirect
measures of demographic composition rather than direct
measures of social networks to predict firm performance
(Reagans et al. 2004). Still, scholars rarely conduct longi-
tudinal studies (see Boone et al. 2004 and Sørensen 2004
for recent exceptions). More importantly, scholars have
devoted little attention to the sources of demographic
diversity. In addition, we point to a distinction between
functional experience and functional structure that has
received little attention in this literature; thus, our paper
fills several important gaps in the literature.
For the entrepreneurial literature, our research sug-
gests that the relevance of founding teams is more signif-
icant than has been acknowledged. Not only do founding
teams directly impact firm outcomes, but, through a pro-
cess of path dependence, the founding team shapes the
TMT. Entrepreneurship research often focuses on the
individual entrepreneur, but understanding the teams that
come together and develop over time is essential to
understanding the performance of entrepreneurial firms.
We advocate more studies with longitudinal data as well
as a focus on functional structure in addition to team
human capital. Also important, but largely unexplored
in this paper, is the impact of VC in shaping the TMT.
Our findings offer suggestive evidence that VC-backed
firms are better able to add structure and experience than
non-VC-backed firms; however, the precise mechanisms
are worthy of additional research.
Much more remains to be understood about entrepre-
neurial teams. How does a team attract founders with
varied experiences when we know diversity is atypical
(Ruef et al. 2003)? Given the long-term effects of these
initial choices, such an exploration would be very useful.
We know founding is not truly the beginning, because
entrepreneurs bring experience and networks with them
(Burton et al. 2002, Shane and Stuart 2002). A qualitative
assessment of how people, ideas, experiences, and struc-
tures come together to create a firm would be an impor-
tant contribution of future work. In addition, delving into
individual executive positions in the organization would
help us understand in more detail the mechanisms that
result in path dependence (Burton and Beckman 2007).
Despite the remaining questions, we are encouraged
by the consistency of our results, how they contribute to
and reflect current theories, and by the potential rewards
of examining teams over time in this rich research set-
ting of entrepreneurial firms. We demonstrate that found-
ing teams matter—both directly and indirectly—largely
through a process of path dependence. This sociologi-
cal and evolutionary approach demonstrates how initial
teams have a lasting impact on the firm.
Acknowledgments
Both authors contributed equally to this manuscript. The
authors thank Greg Northcraft for his insights and contribu-
tion to this manuscript. The authors also thank Roberto Fer-
nandez, Mauro Guillen, Nandini Rajagopalan, Jesper Sørensen,
Ezra Zuckerman, seminar participants at University of Califor-
nia, Berkeley, Harvard Business School, Massachusetts Insti-
tute of Technology, University of California, Los Angeles, Uni-
versity of California Irvine, Wharton, and attendees at the West
Coast Entrepreneurial Research Conference for constructive
comments on earlier drafts of this paper. An earlier version of
this paper was presented at the Academy of Management Meet-
ing in 2006. This research was supported by Stanford Project on
Emerging Companies (SPEC) at the Graduate School of Busi-
ness, the Harvard Business School Division of Research, UC
Irvine, and the MIT Entrepreneurship Center. The authors also
thank Jon Reuter, Candice Tulberg, and Stephanie Woerner for
helpful research assistance. All errors are the responsibility of
the authors.

Appendix
Table A Descriptive Statistics N = 167
Variable Mean Std. dev. Min. Max.
Firm size (logged) 4 07 0 99 0 69 7 47
Medical-related industry 0 14 0 35 0 1
Innovation strategy 0 48 0 50 0 1
Sales/marketing/service strategy 0 23 0 42 0 1
Cumulative rounds of VC 3 10 2 82 0 11
Proportion of founders on TMT 0 67 0 68 0 5
Product developed 0 77 0 42 0 1
Average number of prior 2 12 0 85 0 5
person positions (by ﬁrm)
Founding team (FT) size 2 82 1 61 1 10
Cumulative entrances to TMT 5 50 3 46 0 18
Cumulative exits from TMT 1 68 2 22 0 15
FT prior experience
Science/engineering 0 95 0 96 0 3
Sales/marketing 0 31 0 55 0 3
Manufacturing/operations 0 10 0 30 0 1
Finance/accounting 0 11 0 31 0 1
Administration/HR 0 38 0 58 0 3
Business development/ 0 07 0 25 0 1
strategic planning
Initial structure
strategic planning
TMT prior experience
strategic planning
TMT structure
strategic planning
FT experience count 1 47 1 03 0 4
TMT experience count 2 78 1 71 0 6
FT structure count 1 77 0 96 0 4
TMT structure count 3 38 1 63 1 6
IPOs in industry 4 51 4 49 0 18
VC deals in industry 1 502 22 1 000 60 567 3 367
Ever VC 0 71 0 46 0 1
Ever IPO 0 51 0 50 0 1

TableBCorrelationMatrix
123456789101112131415161718192021
1Firmsize(log)100
2Medicalindustry−015100
3Innovationstrategy−008026100
4Marketingstrategy008−010−052100
5Venturecapital020006020−019100
6Prop.foundersonTMT−018011−007007−018100
7Productdevelopment017−027001016013−006100
8Averagepriorpositions003004007−006007−017−003100
9Foundingteamsize013011008002003040001−017100
10Cum.TMTentrances037−016024−010031−037022−004024100
11Cum.TMTexits021−018012−004014−003019−021018063100
12FTexp.science/eng.006008020−018006−014−003001022020−004100
13FTexp.sales/mktg.001−017−014019−002−008007011017005−002015100
14FTexp.mfg./ops.−002−003−001001−003005004−008−005−001006004−008100
15FTexp.fin./acct.−002−003−002000−006−002−004−002023010011008023001100
16FTexp.admin./HR004−009−011−001−005−012−002000014017011−016009−008004100
17FTexp.bus.dev.−005010004009014−007009008−003001−006−004007015−001−005100
18FTstruc.science/eng.007−004017−013019−004005005031023008060020003018006−007100
19FTstruc.sales/mktg.023−017−008003−008−003010−003029021011011048004020023006022100
20FTstruc.mfg./ops.018−008−017019001−004005−017013004−006012016000−006023−009004026100
21FTstruc.fin./acct.007−012−005006−020−005−002−024000003000015005−003019−012−011011007016100
22FTstruc.admin./HR−001−001003−002−019026−005−014052012014000003−005022019−004−009015001−014
23FTstruc.bus.dev.−004017006004−006008−011004031006−004007006−006003018−004009008010−007
24TMTexp.science/eng.020018025−009022−028008017017044−011048000−004−006−008−003034010006−008
25TMTexp.sales/mktg.019−016002001030−030015018011052003013025−009−007007009015012012007
26TMTexp.mfg./ops.015004011002023−018021007006042009004−009025−013−009010008−006006−012
27TMTexp.fin./acct.012−005003006013−028005023010035−010024019−003026004008022016011003
28TMTexp.admin./HR022000014−007012−027001007012047014008007−011015030−007012018−004003
29TMTexp.bus.dev.005017018−006013−017−004011000024−004005000−006−003003027000004−013−011
30TMTstruc.science/eng.020026027−011023−016−003008035038−009048003−006009010−001046011010−001
31TMTstruc.sales/mktg.034−020003−005022−032021−002019059008015020−004005014005010039020010
32TMTstruc.mfg./ops.029001005007016−027014005−003030−009007012−004−015−002006−004011029−001
33TMTstruc.fin./acct.020002006000014−033011013005044−002011002−011008002002012010003017
34TMTstruc.admin./HR010013016004002019005−004055039010009−005−009012012−005006009−003−009
35TMTstruc.bus.dev.006023011000006−011−008004020020−006014006−008006013006009009−002−006
36FTexp.count000−010−003−001004−020004004022019005043058027046037028034036017010
37TMTexp.count026005019−006035−043014029012061−001024014−006006012012022014006−005
38FTstructurecount019−022−010010−009−006006−012033022008044038004021015−004056056052048
39TMTstructurecount030005013−007030−040013014012054−007020006−012003004009012017008006
40IPOsinind.007013008000008−005002005014017005−003006013000005003007004008−005
41VCdealsinind.−006−019−014007−017018−011−019−007−030013−011001003000003−007−004−002−002−005
42VC019015022−018071−015015022009028001012007000−003−006012017−001002−015
43IPO014019016−010027−029−004031012039−017022004−011−009005−003027006004−001

TableB(cont’d.)
222324252627282930313233343536373839404142
22FTstruc.admin./HR100
23FTstruc.bus.dev.020100
24TMTexp.science/eng.−006013100
25TMTexp.sales/mktg.−003−009036100
26TMTexp.mfg./ops.−002011044034100
27TMTexp.ﬁn./acct.002−001032040032100
28TMTexp.admin./HR003029027016005014100
29TMTexp.bus.dev.001012022027004013016100
30TMTstruc.sci./eng.010027069028018037035013100
31TMTstruc.sales/mktg.005001034068029044036028029100
32TMTstruc.mfg./ops.−018−001036038044035011009018038100
33TMTstruc.ﬁn./acct.000004031038034067025021030045036100
34TMTstruc.admin./HR040012033022024019024017030024012019100
35TMTstruc.bus.dev./st.pl.016034031021007019018033042018009015012100
36FTexp.count011014010019−005031018005023024002009002013100
37TMTexp.count−009012061065054063043044049058048061030033022100
38FTstructurecount008022015022002024015−007030031011018004006048013100
39TMTstructurecount−003006054055044061032030047062064071025042013080015100
40IPOsinind.009011012013017007015017021018−002008010018008015007013100
41VCdealsinind.010−010−039−032−037−044−032−015−038−038−031−050−020−017−005−057−006−054−026100
42VC−009005024035030026011016029026025030003007009042001039021−035100
43IPO−007005059046044053028014053039048056028021003066013067027−052045

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