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ERASMUS UNIVERSITY OF ROTTERDAM Reprint Prohibited
ERASMUS SCHOOL OF ECONOMICS
MASTER THESIS
VENTURE CAPITAL
A DRIVING FORCE FOR THE DEVELOPMENT
OF THE CLEANTECH INDUSTRY
IN THE U.S.A
NAME: SAVVAS IOSIFIDIS
STUDENT NUMBER: 332984
SUPERVISOR’S NAME: JOERN BLOCK
Rotterdam, September 2010
*Contact Information. E-mail address: [email protected]; phone: +31 (0) 62 634 7769
Abstract
Venture capitalists’ trends have been changing over time reflecting the fast reaction of
the industry to emerging investment opportunities. The so called cleantech industry is
the new target market for the venture capital (VC), especially in the U.S.A. Climate
change and environmental concerns, increasing oil prices and governmental policies
have driven the tendency towards sustainable energy.
While ICT and biotech have attracted the majority of the research literature little
attention has been paid in the renewable energy sector. After a detailed presentation
of the cleantech and the VC industries in the present paper, an empirical analysis
conducted, aiming to prove the contribution of the VC financing to the development of
the renewable energy technologies in the U.S.A. Comparing a number of cleantech
firms with equal number of consumer web businesses it was found that cleantech
industry appears to grow in terms of innovativeness and establishing networks. Human
capital was also found to be a significant factor in the development of the renewable
energy sector in the U.S.A.
Keywords: Cleantech, Venture Capital, Development
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Table of Contents
Abstract...................................................................................................................2
1. Introduction..................................................................................................4
2. The Cleantech Industry in the U.S.A..............................................................6
2.1 Definition of “Cleantech”...........................................................................72.1.1 Solar Power and Photovoltaic Systems.............................................82.1.2 Wind Power and Conversion Systems...............................................92.1.3 Hydroelectric power........................................................................102.1.4 Geothermal Power..........................................................................102.1.5 Biofuels-Biomass Energy.................................................................11
2.2 Public Policies Enforcing the Cleantech Development in the U.S.A.........12
3. The Venture Capital Industry......................................................................14
3.1 Definition and Characteristics of the Venture Capital..............................143.1.1 Human Capital and Venture Capital Investments...........................163.1.2 How Venture Capital Investments Influence Firm Growth..............18
3.2 The History of the Venture Capital Industry and the Transition from the “dot com” to the Cleantech Industry.......................................................................19
4. Hypotheses.................................................................................................21
4.1 Individual Characteristics of Founders Influencing Venture Capitalists’ Investment...............................................................................................................21
4.2 Firm-specific Characteristics-Indicators of Development.........................23
5. Data and Operationalization.......................................................................27
5.1 Descriptive Statistics................................................................................275.2 Measures.................................................................................................28
5.2.1 Dependent Variable........................................................................285.2.2 Independent Variables....................................................................285.2.3 Control Variables.............................................................................30
5.3 Methodology...........................................................................................30
6. Results and Discussion................................................................................31
6.1 Individual Covariates................................................................................326.2 Firm Covariates........................................................................................34
7. Conclusion and Further Research................................................................37
Appendices............................................................................................................40
References.............................................................................................................53
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1. Introduction
Varied factors are emerging for change towards cleaner and more energy
efficient technologies and services: climate change and other environmental concerns,
increasing oil prices, and rising living standards around the world that are putting an
ever-increasing strain on the environment. Russo (2003) contends that there are
strong social and institutional factors pushing towards greening. In recent times, these
factors have driven the creation of a clean technology (“cleantech”) venture capital
market where both independent venture capitalists (VCs) and corporate venture
capitalists (CVCs) have invested in the cleantech industry. According to Parker (2005),
the most prominent area of investment has been the energy sector, as approximately
40% of all cleantech VC investments have gone to clean energy.
This thesis is motivated by the scant attention by researchers to venturing in
the area of clean energy (Teppo, 2006), especially in the U.S.A The present study
focuses on the role of investors and particular VC firms play in the development of the
clean energy market in the U.S.A. Additionally, general human capital is also
considered to be a valuable factor for the development of the renewable sector and
therefore it is included in the research part. The contribution of this paper to the
existing literature results from the strong evidence of the empirical analysis.
The empirical evidence is based on data from the CrunchBase (January 2010),
“the free database of technology companies, people, and investors that anyone can
edit”, introduced by TechCrunch, one of the most prominent blogs that promotes
technological innovations related to the Internet. CrunchBase is a detailed overview of
companies, individuals and investors focused on US high-tech sectors. In this study, a
total of 472 companies were included; 236 US VC backed internet present firms from
the cleantech industry and equal number of consumer web businesses.
The econometric results indicate that cleantech firms are more innovative than
web ventures after receiving VC financing. Theoretical and descriptive literature of firm
growth emphasizes that innovation is a crucial factor for firms wishing to expand (Coad
and Rao, 2008). Furthermore, human capital of founders has been investigated for the
4
purposes of this research and was found that management experience and skills and
high education expertise play a significant role in the development of the cleantech
industry. A strand of literature relates educational and management experience to
received financial resources. Based on traditional human-capital studies (e.g., Becker,
1964), Bates (1990) and Robinson and Sexton (1994) find that high educational
attainment is correlated with the munificence of received financial resources. Such
education and work experience has also been positively related with venture growth
(Colombo and Grilli, 2005). In addition, cleantech firms were found to have established
networks with suppliers, customers etc after the VC investments. According to
(Niederkofler, 1991) valuable strategic networks help firms develop technological and
human capabilities which are admittedly a growth pattern.
The paper provides detailed information of the cleantech and the VC industries
in Section 2 and 3 respectively. Section 4 introduces and discusses the hypothesis while
Section 5 includes the data and methodology used to investigate the influence of the
VC in the development of the cleantech industry in the U.S.A. The following Section
presents the results and the discussion of the empirical analysis. Conclusion and
further interesting research extensions follows in Section 7.
5
2. The Cleantech Industry in the U.S.A
“The science tells us that GHG emissions are an externality; in other words, our
emissions affect the lives of others. When people do not pay for the consequences of
their actions we have market failure. This is the greatest market failure the world has
seen. It is an externality that goes beyond those of ordinary congestion or pollution,
although many of the same economic principles apply for its analysis.”
-Nicholas Stern-
Climate change has been identified by governments and policy makers globally
as one of the greatest market failures the world has ever seen (Stern 2007). The source
of this failure is the emission of carbon dioxide equivalent which scientists have
identified as the basis for global warming. A key aspect of this global issue is financing
and commercializing the technologies which will facilitate economic transition to a low
carbon economy (Stern, 2007).
A review of the world's renewable and nonrenewable energy resources
indicates that the depletion of non-renewable resources is a matter of time, while the
renewable resources provide us with a hope for a better future (Quareshi, 1984). Wei
et al. (2010) underline in their research paper that greater use of renewable resources
and renewable energy systems and energy efficiency provides economic benefits while
at the same time protecting the economy from political and economic risks.
Furthermore, it has been realized that renewable energy sources and systems can
have a valuable impact on crucial technical, environmental, economic, and political
issues of the world (Dincer, 1999).
The current energy system landscape is changing as concerns over climate
change, energy price volatility, and energy security have motivated government,
entrepreneurs, and civil society to explore for energy system alternatives (Stephens
and Jiusto, 2010). The term “Cleantech” has been mainly used to describe these
energy system alternatives such as renewable energy technologies, energy
conservation, and energy storage technologies.
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2.1 Definition of “Cleantech”
The term “clean technology” or “green technology” (or “cleantech”) is relatively
new and has taken on a variety of meanings. According to Knight (2010), cleantech is
defined as the collection of technologies aimed at transforming the carbon base of the
energy sector. These technologies are primarily on the supply side and refer to biofuels
technologies (liquid fuels derived from biomass), renewable energy generation
technologies (such as solar, wind, etc), and technologies which complement coal-fired
electricity generation to reduce its carbon-intensity (such as carbon, capture and
storage). On the demand side, clean technologies refer to technologies which improve
the efficiency of energy demand (such as smart meters) (Knight, 2010).
The Cleantech Group directs attention to the difference between the term
"cleantech," with those of environmental technology or "green tech", popularized in
the 1970s and 80s. Cleantech is new technology and relevant business models offering
remarkable returns for investors and customers while providing solutions to global
problems (Cleantech Group LLC, 2008). Cleantech addresses the issue of ecological
problems with new science, emphasizing natural approaches such as biomimicry and
biology.
The most representative and descriptive definition of the cleantech is given by
Pernick and Wilder (2007). In their book “The Clean Tech Revolution”, cleantech refers
to every product, service, procedure that delivers value exploiting limited or zero
nonrenewable resources and/or creates radically less waste than conventional
offerings. According to their written, cleantech includes a range of products and
services, such as solar systems and hybrid electric vehicles (HEVs) that utilize
renewable materials and energy sources or reduce the use of natural resources by
using them in a more efficient and productive way, cut or eliminate pollution and toxic
wastes, provide investors, customers and companies with the promise of exceptional
returns, reduced costs and lower prices (Pernick and Wilder, 2007).
The following sessions provide detailed information for the five major clean
technologies that optimize the harness of natural resources, offering a cleaner and/or
7
less wasteful alternative to traditional products and services concerning energy
generation and storage, transportation, materials and recycling.
2.1.1 Solar Power and Photovoltaic Systems
The amount of energy supplied by the sun to the earth is more than five times
larger than the world electric power consumption to keep modern civilization going.
The direct conversion of solar energy to electricity by photovoltaic (PV) systems has a
number of considerable advantages as an electricity generator. Roofing tile PV
generation, for example, saves excess thermal heat and conserves the local heat
balance which causes a considerable reduction of thermal pollution in densely
populated city areas (Hamakawa, 2002).
It was in 1890 that the PV effect was observed by Henri Becquerel and this
became a subject of scientific investigation through the early 20th century. In 1954,
Bell Labs in the U.S. introduced the first solar PV device while 4 years later solar cells
were being used in small-scale scientific and commercial applications (Shirland, 1966).
From 1984 through 1990, the first solar electric generation station (SEGS) plants were
built in California's Mohave Desert and still operate today after being upgraded (SEIA,
2010).
Research and production progress continue every day resulting to cost-effective
PVs in a rapidly growing number of areas. Global PV market growth has averaged more
than 25 percent annually over the last decade, with worldwide growth rates for the
last 5 years well over 35 percent (SEIA, 2010).
The U.S. solar energy market grew more than 48 percent in 2007 as a result of
state and federal policies, incentives and cost-reducing programs while factors like a
cost for emitting carbon may help the solar energy reach cost-parity faster than
expected. Despite the fact that consumption of solar energy has exploded since 2005,
concerns about rising costs, energy security and supplies, new state and federal
incentives, solar energy represents less than 1 percent of the U.S. energy mix.
The U.S. ranked fourth in the world for new solar electric installations in 2009.
Germany was first, Italy was second, and Japan was third. In 2009, the U.S. solar
industry supported 17,000 new jobs. Total employment in the U.S. solar industry at the
8
end of 2009 was 46,000 with expected estimations of 60,000 by the end of 2010 (SEIA,
2010).
−Insert Figure 1 about here−
2.1.2 Wind Power and Conversion Systems
Until the early twentieth century wind power was used to provide mechanical
power to pump water or to grind grain (Ackermann and Soder, 2002) while windmills
were used across the Great Plains to pump water and generate electricity (DOE).
The magnitude of wind energy usage has always fluctuated with the price of
fossil fuels. When fuel prices fell after World War II, interest in wind turbines
weakened but when the price of oil over-increased in the 1970s, so did worldwide
interest in wind turbine generators. However, this time, the main focus was on wind
power providing electrical energy instead of mechanical energy (Ackermann and
Soder, 2002). During the last decade of the twentieth century, world-wide wind
capacity has doubled approximately every three years and the costs of electricity from
wind power have declined to about one-sixth since the early 1980s (Ackermann and
Soder, 2002).
Development slowed down extensively in North America after the boom in
California during the mid-1980s. In 1998, a second boom started in the U.S.A and wind
energy has re-emerged as one of the most important sustainable energy resources.
The first megawatt (MW) turbines have been installed in 1999 and in 2001 many
projects have used MW turbines. Major projects were carried out in the states of
Minnesota, California, Wyoming and Texas due to financial incentives, e.g. offered by
the California Energy Commission (CEC), as well as green pricing programs (Ackermann
and Soder, 2002).
It is important to mention that more than 83% of the world-wide wind capacity
is installed in only five countries: Germany, USA, Denmark, India and Spain. Hence,
most of the wind energy knowledge is based in these countries. The U.S. wind industry
broke all previous records by installing nearly 10,000 MW of new generating capacity
in 2009. The total wind power capacity now operating in the U.S. is over 35,600 MW,
generating enough to power the equivalent of 9.7 million homes. America’s wind
9
power fleet will avoid an estimated 62 million tons of carbon dioxide annually,
equivalent to taking 10.5 million cars off the road, and will conserve approximately 20
billion gallons of water annually (AWEA, 2010).
−Insert Figure 2 about here−
2.1.3 Hydroelectric power
Hydroelectric power or hydropower passed in the energy matrix as a result of a
sequence of technological innovations in the late 19th century. Rapidly expanding
electricity demand turned hydropower in numerous countries into an ‘‘energy bridge’’.
Hydropower continues to serve as ‘‘energy bridge’’ in many parts of the world, but in
most countries it can only cover a small fraction of the total electricity needs
(Sternberg, 2008).
According to the US Energy Information Administration (2000), world total
energy consumption will grow by 59% between 1999 and 2020 while electricity
consumption is expected to rise by 73% over the same period (Klimpt et. al, 2002). This
growth will be driven mainly by developing countries where two billion people are still
without electricity. It is expected that fossil fuel power stations will provide the
majority of new electricity supply over the next 20 years, with greater impacts on air
quality and climate change.
Hydroelectricity represents a large-scale alternative to fossil fuel generation,
contributing only small amounts to greenhouse gas emissions and other atmospheric
pollutants (Klimpt et. al, 2002). Hydropower facilities in the United States can generate
enough power to supply 28 million households with electricity, the equivalent of nearly
500 million barrels of oil. The total U.S. hydropower capacity is about 95,000 MW.
Researchers are working on advanced turbine technologies that will help maximize the
use of hydropower and also minimize adverse environmental effects (DOE).
Nowadays, hydropower ranks first in renewable US primary energy net
generation. The following table shows the electricity net generation from renewable
energy by energy use sector and energy source from 2005 to 2009.
−Insert Table 1 about here−
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2.1.4 Geothermal Power
The geothermal energy was first used on a large scale for space heating,
industry, and electricity generation in the 20th century. It was Prince Piero Ginori Conti
that first introduced electric power generation with geothermal steam at Larderello,
Tuscany, in 1904 (Fridleifsson, 2001).
Direct use of geothermal energy can involve a broad variety of end uses, such
as space heating and cooling, industry, greenhouses, fish farming and health spas,
generally using existing technology and straight forward engineering. The technology,
reliability, economics, and environmental acceptability of direct use of geothermal
energy have been demonstrated throughout the world. The main types of direct use
are bathing/swimming/balneology (42%), space heating (35%, thereof 12% with
geothermal heat pumps), greenhouses (9%), fish farming (6%), and industry (6%) (Lund
and Freeston, 2001).
During the last decade, a number of countries have incentivized individual
house owners to install and mainly use ground source heat pumps. Governments have
stimulated further use of geothermal energy by setting up financial incentive schemes,
as the heat pumps reduce the need for peak power and thus replace new electric
generating capacity. The USA was the leader with about 400,000 heat pump units
(about 4800 MWt) and energy production of 3300 GWh/y in 1999 (Lund and Boyd,
2000).
The U.S. still leads the world in online geothermal energy capacity and is one of
the main countries that will increase its capacity, according to a report by the U.S.
Geothermal Energy Association. California and Nevada are the leading states in
developing geothermal energy, and make up almost 97 percent of currently active
geothermal power capacity (GEA, 2010).
−Insert Figure 3 about here−
2.1.5 Biofuels-Biomass Energy
Agriculture and forest products industry provide food, feed, fiber, and a broad
range of necessary products in everyday life like packaging, clothing, and 11
communications. However, biomass is also a source of a large variety of chemicals and
materials, and of electricity and fuels. About 60% of the needed process energy in
pulp, paper, and forest products is provided by biomass combustion.
Today’s corn refinery industry produces a wide range of products including
starch-based ethanol fuels for transportation. The biomass industry can produce
supplementary amounts of ethanol by fermenting some by-product sugar streams
(Chum and Overend, 2001).
Industrial biomass use is primarily of residues of agriculture (leftover material
from crops, such as the stalks, leaves, and husks of corn plants), forest products
operations (chips and sawdust from lumber mills, dead trees, and tree branches) or
urban and industrial residues. Additional crop residues could be collected for product
or energy purposes; increases in supply would have to come from crops particularly
planted for these purposes (Chum and Overend, 2001).
Biomass is a complex resource that can be processed in many ways leading to a
variety of products such as ethanol, an oxygenate that can also be used as a fuel
additive and many others. Removal of carbon from fossil fuels is a way to increase
energy consumption without increasing carbon consumption in a carbon-constrained
world while decarbonizes fossil fuels prior to use in energy production is likely to be
less costly than attempting to abstract CO2 from dispersed sources (Chum and
Overend, 2001).
2.2 Public Policies Enforcing the Cleantech Development in the U.S.A
“The nation that leads the world in creating new energy sources will be the nation that
leads the 21st Century global economy.”
-Barack Obama-
In order to stimulate the development and encourage assimilation of clean
technologies, governments have attempted to promote their positive advantages and
eliminate the barriers (relative advantages of end-of-pipe technology, nature of
regulation, time-scale, and lack of knowledge) (Hooper and Jerkins, 1995).
12
A number of policy priorities, such as environmental regulation, economic
incentives, economic indicators, technology policies, dissemination of information on
clean technologies, corporate leadership and education have been occupied to
encourage 'social, economic, political and cultural milieus' favorably disposed towards
the development and dispersion of clean technologies (Hooper and Jerkins, 1995).
US energy policy was directed toward providing sufficient supplies of clean,
inexpensive energy in support of long-term economic growth and strategic security
from the years of father’s Bush administration. To provide a consistent framework for
US policy, a national energy strategy has been developed (Moore, 1990). While the
Clinton administration failed to achieve what it wanted and planned in pushing for
action on climate change, George W. Bush’s promises to regulate the carbon emissions
of power producers in the United States vanished only two months after entering
office in the beginning of 2001 (Harris, 2009).
The White House recognized the opportunities as well as the threats that the
2008’s economic recession has brought. A valuable opportunity was to direct serious
money to the sustainable energy sector addressing the climate changes and reducing
the green house emissions. The 2009 American Recovery and Reinvestment Act (ARRA)
financial investment and stimulus package includes over US$70bn for renewables
technologies, transportation and energy conservation activities (DOE).
The US Treasury and Department of Energy (DOE) reported that they accept
applications for payments in lieu of tax credits from firms that establish renewable
energy facilities. The expectations of the two departments range too high and they
anticipate that the “advanced energy manufacturing tax credit will result in more than
US$3bn of stimulus spread over hundreds of wind, solar, biomass and other renewable
energy plants”. The DOE’s Small Business Innovation Research and Small Business
Technology Transfer programmes funds are intended for small businesses while the
Build America Bond (BAB) programme provides an alternative way for states to raise
money for capital expenditure and operations (Marsh, 2010).
Bright examples of proactive operations in the individual state level are the
increased growth rates of wind power capacity in Texas and in California the
implementation of “The California Climate Action Plan”, “The California Solar
13
Initiative”, “The Sunrise Powerlink” transmission scheme and other state programmes.
Several other states have similarly affiliated the green energy cause.
The U.S.A already has a sizeable presence in renewable energy development.
Particularly, last year the renewables accounted over 10% of the country’s
domestically energy production, including 300 GW of hydroelectric power. By mid
2009, installed US wind power capacity reached 29,440 MW putting the sector of wind
energy in the vanguard of the renewable energy revolution (Marsh, 2010).
The 2009’s American Clean Energy and Security (ACES) Act, widely known as
the Waxman-Markey Climate Bill, is another proof of commitment at high political
level. Significantly, the ACES promotes a Renewable Electricity Standard (RES) that
targets for a quarter of the nation’s electricity to be derived from renewable sources
by 2025. Federal and state provisions aimed at creating clean energy jobs, reducing
energy consumption and greenhouse gas emissions, include creation of a Clean Energy
Deployment Administration which would manage loan guarantees for new low-carbon
energy programmes and help private investors’ initiatives. The bill also calls carbon
capture and storage, smart grid and electric vehicles as targets for federal support
(Marsh, 2010).
3. The Venture Capital Industry
“The myth is that venture capitalists invest in good people and good ideas. The reality
is that they invest in good industries”
-Bob Zider-
3.1 Definition and Characteristics of the Venture Capital
Venture Capital (VC) is a specific type of investment and can be typically
defined as investment by professional investors of long-term, risk equity finance in
new firms where the primary reward is eventual capital gain (Wright and Robbie,
1998). Bovaird (1990) noted that VC is equity-linked investments in young, privately
held companies from emerging industries where the investor is often active as a
director, an advisor, or even a manager of the firm.
14
VC can be also seen as a professionally managed pool of capital that is invested
in equity-linked securities of private ventures at different stages in their development
(Sahlman, 1990). Each stage is in general tied to a momentous development in the
company, such as completion of design, pilot production, first profitability,
introduction of a second product, or an initial public offering (Plummer, 1987;
Kozmetsky et al., 1985). Depending on the stage of the investee company’s
development, VC is called different names (Randjelovic, 2001). The different stages of
financing are described by Bovaird (1990) and they are the following: seed capital,
start-up capital, early stage capital, second round finance, expansion capital and
mezzanine finance.
Venture capitalists are actively involved in the management of the ventures
they fund, usually as members of the board of directors and maintaining significant
economic rights in addition to their ownership rights. The prevailing organizational
structure in the industry is the limited partnership, with the venture capitalists acting
as general partners and the outside investors as limited partners (Sahlman, 1990).
Particularly, VC managers operate as financial intermediaries between institutions that
seek outlets for their investment (investors) and institutions, which search for
investment funds (investees). In addition, venture capitalists are professional asset
managers that act as representatives of the venture capital institutions (such as banks,
asset management companies, independent companies, etc) (Randjelovic, 2001). For
better understanding of the structure of venture capital industry, the following figure
shows basic links and relations among venture capital players.
−Insert Figure 4 about here−
According to Gompers and Lerner (1998), VC organizations finance high-risk,
potentially high-reward projects, purchasing equity stakes while the firms remain
privately held. Cumming and MacIntosh (2001) define them as financial intermediaries
that are in essence a kind of specialized mutual fund who receive capital contributions
from institutional investors, particularly pension funds.
All the above mentioned definitions of the VC capture some of the particular
characteristics of VC, but none of them includes the complete set of distinguishing
15
features for VC. Perhaps, one of the most complete and descriptive definitions in the
literature about VC, the one that is adopted in this paper, is the one that describes VC
as a type of financial capital provision, which is invested in high-risk ventures and
which offers the possibility of significant gains to compensate for the risks involved in
such investments (Reid, 1998).
VC begins with investors who invest in a VC fund (Randjelovic et al., 2003).
According to Sahlman (1997) “investors, of course, are looking for business in which
management can buy low, sell high, collect early, and pay late”. This is the key driving
force for investors who look for appropriate investee companies and thus they put
pressure on VC managers to find these companies. Tyebjee and Bruno (1984), in their
empirical research, emphasized that VC firms’ investment decisions are based on the
market attractiveness, product differentiation, managerial capabilities and competitive
threats, trying to reduce the high risk involved in the investment procedure.
This process ends with providing funding to attractive companies (investee
companies) and receiving equity shares in return (Randjelovic et al., 2003). The
involvement of VC is completed with the exiting procedure (i.e. selling the received
equity shares to the stock market) which can take from one to five years from the
initial point of the funding. Post-investments actions, such as financial statement
monitoring, business strategy advice and overall monitoring of the investee company
can guarantee the successful exit of the VC (Van Osnabrugge and Robinson, 2000).
3.1.1 Human Capital and Venture Capital Investments
A large number of studies on the investment process of VCs, which mainly focus
on the criteria VCs, employ to make their investment (Zopounidis, 1994), offer a
number of important insights into the VC decision process. According to Franke et al.
(2006), the results of these studies are interpreted as direct evidence on the long-term
success factors of new firms. The human capital of founding entrepreneurs has started
featuring in studies of investors’ decision criteria (MacMillan et al., 1985; Muzyka et
al., 1996; Baum and Silverman, 2004; Gimmon and Levie, 2010). Even though financial
capital has been the prime perspective for assessment, the importance of human
16
capital and the nature of entrepreneurial teams have been added to the VC literature
(Dubini, 1989; Gimmon and Levie, 2010), aiming to deal with the problem of selecting
the winners from the losers (Riquelme and Rickards, 1992). The competence-based
view of the literature contends that higher human capital founders start more
successful firms that is there is a direct positive effect of founders' human capital on
firm growth (Colombo and Grilli, 2009).
Becker (1975) underlined the distinction often made in the literature between
the generic and specific components of human capital. Generic human capital relates
to the wide-ranging knowledge acquired by entrepreneurs through educational
attainment and past professional experience (Colombo and Grilli, 2005). Prior
managerial and work experience combined with high educational attainment has
significant positive effects for realizing venture success (Watson et al., 2003).
Reflecting the vital role of individuals and founding teams, wide-ranging surveys
have focused on their strengths and weaknesses. In these researches, variables such as
educational attainment, prior work and managerial experience, and family background
have frequently been used as proxies of capability (Cooper et al, 1994). Recent
scholars and policy makers become aware of the importance of the educational system
for entrepreneurship (Reynolds et al., 1999). Particularly, in the empirical growth
literature education is positively related to the level of economic growth (Krueger and
Lindahl, 2001) specifying growth as a function of the initial level of education. The
educational level creates awareness of alternative career choices and broadens the
horizon of individuals, equipping them with cognitive tools and enabling them to
perceive and develop entrepreneurial capabilities and opportunities (Reynolds et al.,
1999).
As far as the managerial competencies concerned, Goslin and Barge (1986)
have suggested that the management team of one company has a greater impact on
the venture capitalists’ selection process than any product and market consideration.
Furthermore, the strategic management literature has focused on the availability of
management know-how as a predictor of venture success. Cooper et al. (1994)
reported that managerial experience might positively affect the firm performance as
17
experienced individuals can adopt more promising strategies or superior management
methods.
3.1.2 How Venture Capital Investments Influence Firm Growth
The rationale that VC spurs innovation in the United States has been the key
factor for governments around the world that have been eager to duplicate the
success of the accelerating U.S VC industry (Kortum and Lerner, 2000). Hellman and
Puri (2000), provide empirical evidence that VC financing is influential to new
innovative ventures. More specifically, they contend that innovative firms are more
likely to obtain VC funds while obtaining VC is directly related to faster time to market
in the case of innovative activities. Another crucial finding of their empirical research is
that VC backed firms have significant increases in patenting. Consistent with this, Engel
and Keilbach (2007) after testing a number of German VC funded firms they confirmed
that VC backed firms have a higher number of patent applications while they have
significantly high growth rates.
Additionally, early researches in new product development (NPD) have
emphasized on the positive association between new product strategy and venture
success (Booz et al., 1982; Dwyer, 1990). According to Black and Gilson (1998),
“venture capital is investments by specialized venture capital organizations in high-
growth, high-risk, often high-technology firms that need capital to finance product
development or growth”. Furthermore, venture capitals are associated with a faster
time to market (Hellmann and Puri, 2000). The ten-year life spans of venture
partnerships lead to pressure on companies to commercialize products quickly after
obtaining venture financing (Kortum and Lerner, 2000).
Another key aspect of firm growth is the networking capability of firms. Social
capital theory emphasizes on interpersonal relations because these relations provide
an axial person with access to external resources embedded in the relationship (Burt,
1997). According to Gemünden et al. (1996), a firm's networking capability helps
generate new resource configurations through resource integration, reconfiguration
and generation (Chen et. al., 2009). The strategic networks help firms develop
capabilities which are a growth pattern (Niederkofler, 1991).
18
VC firms supplement the capital financing with access to their accumulated
experience and expertise, networks and reputation (Moore and Wüstenhagen, 2004).
Particularly, it is claimed that VC firms bring a value-added network to the funded
venture.
According to the stages of VC investing that Plummer (1987) suggested, rapid
expansion of manufacturing facilities requires VC capital. Miller (1963) contended that
one venture considered to be successful of when the technology proposed has been
adapted, new facilities have been developed or familiarity with the new markets has
developed.
3.2 The History of the Venture Capital Industry and the Transition from the “dot com” to the Cleantech Industry
The VC industry is a rather recent phenomenon which draws its origins in the
U.S.A and is generally considered to have begun after the Second World War with the
formation of American Research and Development in 1946 (Rind, 1981). AR&D was the
first venture organization open to public investment and was the sole financier of
Digital Equipment Corporation, turning a $70,000 investment into $490 million market
value (Liles, 1977).
The industry has helped create many successful companies, including Apple
Computer, Intel, Federal Express, People Express, Microsoft, Sun Microsystems, Digital
Equipment, Compaq Computer, Tandem and Genentech. Each of these colossal
companies received VC in its early stage and later went public (Sahlman, 1990).
The 1950s saw several new companies from a number of industries founded
with government R&D contracting as their major business while in the late 1950s and
early 1960s, a number of organizations was formed by large groups leaving the major
data processing companies. Many new groups entered the VC field in the 1960s and
1970s. The decline of the public market for new actions in 1970, followed by its
downfall in 1974 and 1975, ravaged most of the new entities.
The industry has been reinvigorated since 1977 for several reasons, including:
capital gains tax reduction, improved liquidity from changes, attractive acquisition
19
prices for small technological companies, and a revitalized public market for high-
growth companies (Rind, 1981).
While the general tendency has been one of increasing VC investments with
growth in this class of investments from $1.46 billion in 1980 to $27.7 billion in 2007, it
is also clear that growth in VC investments has not been gradually increasing over this
period (Dooley, 2008). Figure 1 shows total U.S. VC investments over the period 1980-
2007.
−Insert Figure 5 about here−
Over the time period 1980-2007, the majority (anywhere between 60-90%) of
the U.S. VC investments in a given year was absorbed by key industrial sectors such as
communications equipment, computer hardware, computer software, biotechnology,
medical devices and “internet-specific” (Dooley, 2008).
In many years since 1980, some of these sectors individually accounted for 20%
or more of all VC spending. Priorities accorded to these sectors shifted as the
marketplace moved on to what was seen as the next high growth prospect (Dooley,
2008). During the early 1980s, U.S. VC investments in the energy/industrial sector
accounted for more than 20% of all VC investments due to the high energy prices; the
two major global oil crises (1970s and 2003-2004) as well as repeated high level
statements from the U.S. government on the need to reduce U.S. dependence on
imported energy and significant commitments of government and private sector
funding for the development of new energy technologies drove the trend towards
cleantech sector (Dooley, 2008).
By the early 1990s, energy/industrial VC investments were attracting less than
3% of all U.S. investments and by 2000 these investments accounted for only 1% of the
$119 billion invested that year by the U.S. VC industry; half of the funding in this peak
year was for “internet specific” investments (Dooley, 2008).
The new cross cutting accounting of U.S. VC investments the so called cleantech
sector captured the attention the sequent years. Data for cleantech investments from
1995-2007 are presented in Figure 6. The U.S. investments in the cleantech industry
intimately follow the pattern seen in the more specific energy/industrial category. In
1995, cleantech VC investments were less than $100 million and accounted for 1% of
20
all U.S. VC. The scenery changed and by 2007, cleantech accounted for approximately
$2.4 billion and slightly more than 8% of all venture capital investments.
−Insert Figure 6 about here−
The very difficult fundraising environment, in part created by recent economic
stress, resulted to a decrease in new commitments to VC funds in the United States in
2009. The total VC investments declined this year to $15.4 billion from their post-
bubble record level $36.1 billion in 2007. However, most of the decrease reflects the
contraction of the U.S. VC industry that began after the technology bubble burst in
2000 (NVCA, 2010). Block and Sandnder (2009) argued that a financial crisis can have a
strong, exogenous affect on VC activities, which consequently can lead to a severe
‘funding gap’ in the financing of technological development and innovation.
4. Hypotheses
In this session it is presented the literature supporting the hypotheses and the
hypotheses themselves which aim to give explicit answers of the influence of the VC in
the development of the cleantech industry.
4.1 Individual Characteristics of Founders Influencing Venture Capitalists’ Investment
Human capital, consisted of work experience, education, and other skills and
perspectives that increase knowledge accumulation and business astuteness, is an
important characteristic of entrepreneurial capability (Sexton and Upton, 1985) and is
beginning to surface, as an equal with financial capital, in predicting venture
performance (Cooper et al., 1994; Pennings et al., 1998).
In general, VC investors focus on specific industries and develop context-
specific screening capabilities that allow them to judge the hidden quality of
entrepreneurial projects and the entrepreneurial talent of the proponents better than
any other investors (Chan, 1983; Amit et al., 1998). The main role of VC investors lie in
acting as a “scout”, the human capital characteristics of founders that drive firm
21
growth will also attract VC investments (Baum and Silverman, 2004). Early surveys
provided evidence that the general management competencies and the industry-
specific experience of firms' founders are central selection criteria for VC investors
(Tyebjee and Bruno, 1984; MacMillan et al., 1985, 1987; Muzyka et al., 1996; Sheperd
et al., 2000).
In addition, once a firm obtains VC financing the financial constraints that
impede growth are removed. Therefore, the human capital characteristics of founders
that enhance growth should have a greater positive effect if firms receive VC funds
(Watson et al., 2003).
Endorsing the results of the US DOE for the trend of VC firms to cleantech
industry in the latest years and the belief that VC firms’ investments are often in
emerging industries (Cohen and Levinthal, 1990); it is assumed that the transition of
VC financing from the consumer web to the cleantech industry is driven also by the
managerial competencies of the founders. Therefore, the following hypothesis is
formed:
H1: Founders of cleantech firms are more likely to have superior managerial
experience than founders from consumer web industry when firms are VC backed.
Researchers have suggested that investors may seek other signals of quality,
apart from the managerial experience (Hall and Hofer, 1993). According to both
Spence (1974) and Becker (1993), degrees and education certificates in general,
convey information about differences in abilities, persistence and other valuable
attributes of individuals. Maidique (1986) found that VCs considered founders with
advanced degrees from high quality institutions to affect the success of their
companies. Consistent with this, Engel and Keilbach (2007), after testing a large sample
of privately held young German companies, concluded that the education of founders
crucially influences the likelihood of receiving VC.
Additionally, investment in high status individuals may have a self-fulfilling, or
‘Matthew’ effect (Merton, 1968; Podolny, 1993; Podolny and Stuart, 1995). This high
status attracts resources which then increases the likelihood of success.
22
However, a study of Chandler and Jansen (1992), suggests that it is not the
amount of education that makes a difference, but the type of education. The
interviews’ results indicated that the most successful founders also evaluated
themselves highly on their technical skills. They believe that they were specialists in
their fields.
In most studies, education has served as a proxy for entrepreneurial skills and
abilities (Barringer et al., 2005). For example, Sapienza and Grimm (1997), argued that
search skills, foresight, imagination, and computational and communication skills are
enhanced through college education. In addition, concrete forms of knowledge-
intensive education, such as engineering, computer science, and biochemistry, provide
the receivers of education an advantage if they run a firm that is related to their area
of expertise.
Applying the literature in favor of the cleantech industry, the following
hypothesis is introduced:
H2: Highly educated founders of cleantech firms are more likely that they
attended relevant studies than founders of the consumer web industry when firms are
VC backed.
4.2 Firm-specific Characteristics-Indicators of Development
In the area of cleaner production technologies, preventative, proactive and
process-integrated approaches have a preference over those that are alleviative,
reactive and end-of-pipe or conventional. It has gradually become accepted that a
product orientated approach may be even more attractive than a process orientated
one, regarding the maximization of the potential of cleaner production (Van Weenen,
1995).
Hegarty and Hoffman (1990) argued that successful environmental new
product development needs to be underpinned by an environmental product strategy
that is explicitly defined, and penetrated in the overall strategy of the firm. Early
researchers in new product development (NPD) have found a positive association
23
between new product strategy and success and have contended that it is crucial to
identifying product and market opportunities (Booz et al., 1982; Dwyer, 1990).
According to Black and Gilson (1998), “venture capital is investments by
specialized venture capital organizations in high-growth, high-risk, often high-
technology firms that need capital to finance product development or growth”.
Furthermore, venture capitals are associated with a faster time to market (Hellmann
and Puri, 2000). The ten-year life spans of venture partnerships lead to pressure on
companies to commercialize products quickly after obtaining venture financing
(Kortum and Lerner, 2000).
Considering that cleantech became the third-largest North American venture
capital investment category (11 percent of all venture investments), behind software
and biotechnology (Stack et al., 2007).and the implementation of product strategy by
VC firms the following hypothesis in introduced:
H3: Cleantech firms are more likely to introduce a new product/service after the
VC financing than firms from the consumer web industry
Schumpeter (1934) defined innovation as new products, new methods of
production, new sources of supply, the exploitation of new markets and new ways to
organize business. Furthermore, Edquist (2005) refers to innovation as technologically
novel or improved material goods, intangible services or ways of producing goods and
services. Cleaner technologies and production methods are acknowledged as a form of
innovation, since they imply technological, organizational and institutional changes to
the knowledge base of existing conventional energy production systems (Foxon and
Pearson, 2008; Kuehr, 2007).
A broad range of theoretical and descriptive literature of firm growth
emphasizes the vital role innovation plays for firms wishing to expand (Coad and Rao,
2008). Investments in product innovation are the single most popular strategy for
expansion, a finding which holds across various industries (Hay and Kamshad, 1994).
Creation of innovative young firms is an important source of innovation and
growth. The existence of a sophisticated VC industry is a key factor behind America’s
24
ability to encourage and sustain technological innovation and growth. The argument
that VC makes firms grow faster, create more value and wealth and generate more
employment that other start-ups is empirically supported. According to Kortum and
Lerner (2000), VC backed firms are more innovative and produce more valuable
patents. Consistent with this, Gompers and Lerner (2001) considered that VC
investments can be directly related with the increase in innovation growth rates and
commercial applications.
Venture capital, innovation and entrepreneurs are rationally interrelated.
Kortum and Lerner (1998) analyzed 20 industries over a three-decade period and
found that ‘the amount of venture capital activity in an industry significantly increases
its rate of patenting’ and that VC may have a larger influence on innovation than
corporate R&D programmes.
Considering the existing literature for innovation in the cleantech industry the
following hypothesis is formatted:
H4: Cleantech companies are more likely to be innovative after the VC launch
than firms from the consumer web industry.
The networking capability of ventures also attracts a lot of attention from
researchers (Gemünden et al., 1996; Shane & Stuart, 2002). Networking capability
defined as the capacity of firms to recognize, establish, coordinate and develop
relationships with different players in the market. Social capital theory emphasizes on
interpersonal relations because these relations provide an axial person with access to
external resources embedded in the relationship (Burt, 1997). A firm's networking
capability also helps generate new resource configurations as the firm can integrate its
own resources (Gemünden et al., 1996) with those of other firms for further
development through resource integration, reconfiguration and generation (Chen et.
al., 2009).
Valuable strategic networks help firms develop technological capabilities which
are admittedly a growth pattern. Ventures with strong networking capability have
access to more partnership opportunities. These companies tend to depend on
25
contractual relationships with large firms to make products with technologies that are
transferred from the vendor to meet the vendor's precise requirements (Niederkofler,
1991). In addition to capital, VC firms generally provide access to their accumulated
experience and expertise, networks and reputation (Moore and Wüstenhagen, 2004).
Particularly, it is claimed that VC firms which invest in energy, either as a primary
activity or as a line of business, bring a value-added network to the funded venture.
Based on the arguments outlined above, the following hypothesis is proposed:
H5: Cleantech firms are more likely to have established networks after the VC
financing than firms from the consumer web industry.
Miller (1963) suggested that the success of one business may not come until
the technology proposed has been adapted, new facilities have been developed or
familiarity with the new markets has developed.
A large number of firms borrow directly from a commercial bank to build a new
plant or facility or buy new equipment. However, the lack of substantial tangible
assets, the uncertain future and an extensive period of losses prior to earning money
are the major constraints to bank loans. Gompers and Lerner (2001) claimed that VC is
the only source of capital that could help firms to overcome these financial constraints
when they need outside financing to fund their projects. According to the stages of VC
investing that Plummer (1987) suggested, rapid expansion of manufacturing facilities
requires VC capital.
The following hypothesis is introduced based on the fact that cleantech firms
require larger amounts of VC financing to establish their facilities due to the newness
of the industry and the expensive infrastructure and materials:
H6: Cleantech firms are more likely to build new plants or new facilities in USA
after the VC financing than firms from the consumer web industry.
26
5. Data and Operationalization
The CrunchBase is the free database of TechCrunch with startup companies and
information on people and technology which develops every day because of the
valuable assistance of all users of the community of TechCrunch. In CrunchBase, so far
have been registered more than 20,000 people, 10,000 businesses and 1.000 Venture
Capitals. The bulk of the content is added by the community since CrunchBase has
similar features with Wikipedia. When there is an important deal or there is some
important information for a person or a startup and refers to a site, then anyone can
add this to CrunchBase in order to make accessible valuable information to everyone
(TechCrunch).
5.1 Descriptive Statistics
The final dataset used in the present empirical analysis originate from the
CrunchBase raw database (January 2010) including 32.397 companies out of which
13.889 US companies, 18 industry categories and 3.646 financial organizations. The
sample used includes 236 companies from the consumer web industry and equal
number of firms from the cleantech industry out of the large pool of data.
Each entity had to match a number of criteria in order to be included in the set
fulfilling the purposes of the analysis. Firstly, in order to make the comparison
between these two industries which admittedly captured the attention of the VC
industry the last decade only firms with category code cleantech and web were
included in the sample. Also, the companies’ headquarters should be in the U.S.A, they
should have received VC funds at least in one stage (VC backed) and they should have
internet presence that is being "present" and visible on the internet so that other
people can find information about them. After a detailed research, a sample group of
472 US, VC backed and internet present companies has been formed.
The final dataset consist of quantitative data, obtained from the CrunchBase,
and qualitative information, transformed into quantitative data, which were acquired
27
from each company’s website. Table 2 provides detailed information for the
descriptive of the key variables.
−Insert Table 2 about here−
5.2 Measures
The following sessions provide descriptive explanation for the variables used in
the analysis while providing comprehensive information for their construction. Table 3
illustrates the description and construction of the key variables on a detailed level.
−Insert Table 3 about here−
A correlation is a measure of a linear relationship between variables.
Considerable caution must be taken when interpreting correlation coefficients because
they give no indication of the direction of causality. Table 4a illustrates the correlation
matrix of key variables while Table 4b provides with the significance levels of the
correlation of each variable.
-Insert Table 4a and Table 4b about here-
5.2.1 Dependent Variable
The variable clean_web acts as the dependent variable of the analysis. The
binary dependent variable is composed of firms from the consumer web industry and
the cleantech industry and takes value 1 for those who categorized as cleantech and
value 0 when a firm’s category code in the CrunchBase original database is web. In
addition, the dummy variable is filtered for those companies from both groups that
have their headquarters in the U.S.A, they are VC backed and they have internet
presence.
5.2.2 Independent Variables
The binary variable manageskills captures entrepreneurs that they have
managerial knowledge, skills and experience required to run a business. The variable
takes value 1 if the individuals’ past managerial experience exceeded 10 years before
starting the business and value 0 if founders from both industries had no managerial
28
experience or less than 10 years. The dummy variable was constructed after a detailed
research of the founders’ biographies. It is crucial to mention that the variable refers
to founders that hold positions in the management team of their companies and
relates to the first hypothesis.
Moreover, the dummy variable higheducation refers to the founders’ education
attainment and it is related to the second hypothesis. It takes value 1 for those who
obtained a secondary degree, have post secondary education attainment or graduate
experience and value 0 for those who have no education experience or some
secondary studies.
Furthermore, the binary variable theoreticalbackground was constructed to
depict the relevance of the theoretical background of the founders with their
operational expertise. The dummy variable takes value 1 for those founders that are
highly educated while they run a firm that is related to their area of expertise and
value 0 for those who have not. The dummy variable relates to the hypothesis 2.
The dummy variable newproduct, which was constructed from the qualitative
data gathered from the companies’ websites, distinguishes those firms that introduced
a new product or service after the VC funding (value 1) from those who have not (value
0). Newproduct relates to hypothesis 3.
One of the major indicators that have been used for innovation analysis is the
data on patent applications, grants and citations (Smith, 2005). The innovative
activities of every firm included in the dataset are captured by the patent applications,
grants and citations recorded to the United States Patent and Trademark Office
(U.S.P.T.O). The dummy variable inno_active relates to hypotheses 4 and takes value 1
for those companies that hold a patent, grant or citation or applied for one and value 0
for those who have not after the VC financing.
In addition, the author constructed a dummy variable capturing the network of
the firms created after the VC financing. The dummy variable partnership was
constructed to categorize the firms that established a network after the VC launch and
those who have not and relates to hypothesis 5. The binary variable takes value 1 for
the companies from both industries that contracted with suppliers, customers or even
with the VC firm after the VC funding and value 0 for those who have not.
29
The dummy variable newfacilities, constructed by the information provided in
the internet websites of the firms, distinguishes those entities that built a new facility,
office or expanded their existing facilities in the U.S.A from those who have not after
the VC launch and takes value 1 for the expanded ones and value 0 for the others. The
dummy variable relates to hypothesis 6.
5.2.3 Control Variables
A number of dummy variables included in the regression analysis that control
for the amount raised by the funded firms (lnraised_amount), the founded year of the
firms (founded_post98), the companies’ customers (customers_) and the funded year
of the firms (funded_post04) included in the survey. However, these control variables
are not of primary research interest.
5.3 Methodology
In Statistics, the type of predictive model that can be used when the target
variable is a categorical variable with two categories, e.g. live/die, female/male etc, is
the logistic regression model. In this paper the dependent variable (clean_web) has a
binary outcome (value 0: consumer web industry and value 1: cleantech industry) and
therefore the logistic regression was used.
In a logistic regression, instead of predicting the value of a variable Y from a
predictor variable X1 or several explanatory variables, Xn, the model predicts the
probability of Y occurring given the values of X1, …, Xn (Field, 2005). Then the logistic
regression of Y on X1, …, Xn estimates parameter values for β0, β1, …, βn (coefficients or
weights attached to each predictor) via maximum likelihood method of the following
equation:
Logit (P )=log ¿
Multicollinearity exists when there is a strong correlation between two or more
predictors in a regression model. Perfect collinearity poses a serious problem, because
it becomes impossible to obtain unique estimates of the regression coefficients (i.e.,
the coefficients are interchangeable).
30
Furthermore, univariate analysis or independent samples t-test is used when
you want to compare the means of a normally distributed interval dependent variable
for two independent groups. The Mann-Whitney-Wilcoxon test (also called the Mann-
Whitney U, the Wilcoxon-Mann-Whitney and the Wilcoxon rank sum test) is an
alternative to the between-subjects, or groups, ttest.
6. Results and Discussion
The following sessions provide the results of the regression analysis and the
theoretical literature supporting them. Table 5 illustrates the results of the regression
model and table 6a and 6b the results of the univariate analysis respectively.
−Insert Table 5 and Tables 6a and 6b about here−
Particularly, the estimated coefficients of the regression analysis show that VC
backed cleantech firms are founded by individuals with high managerial experience
and skills. This result provides support to hypothesis 1. Furthermore, the univariate
analysis results suggest that there is a statistically significant difference between the
underlying distributions of the high educated founders with relevant theoretical
background scores of cleantech firms and the scores of web businesses. The result
indicates that not only managerial experience counts but also high and relevant with
their expertise educational attainment of the founders. VC backed cleantech firms are
run by highly educated entrepreneurs whose studies “equipped” them with specific
knowledge to start and operate a business in the sector.
However, econometric results do not support hypothesis 3 that imply that
cleantech firms have introduced a new product/service after the VC financing. More
specific, the coefficient is significant and negative when testing for new product
development. On the other hand, cleantech firms funded by VCs found to be more
innovative than web businesses. Hence, VC backed cleantech firms are more likely to
have more patents, patent applications, and patent citations than web ventures.
Additionally, VC funded cleantech firms found to have established networks and
31
contractual partnerships with their suppliers, customers and other firms that
supplement the operational performance of one company.
The insignificant coefficient in the case of the variable newfacilities show that
VC backed cleantech firms have not built new facilities or expanded their existing ones
in the U.S.A after the financing. Therefore, hypothesis 6 is not supported.
Each result is comprehensively discussed in a separate paragraph.
6.1 Individual Covariates
Empirical evidence support hypothesis 1 which stated that founders of
cleantech firms are more likely to have superior managerial experience and skills. The
regression results indicate that founders of cleantech firms have more managerial
experience and skills than founders of web firms.
Several studies inspired by the competence-based perspective (e.g. Cooper and
Bruno, 1977; Feeser and Willard, 1990; Colombo and Grilli, 2005a), emphasizing capital
market imperfections, suggest that founders with greater human capital have access
to abundant financial resources and therefore are able to overcome the financial
constraints that otherwise impede firms’ growth (Colombo and Grilli, 2005).
Consequently, firms established by individuals with superior human capital enjoy
greater growth because of their exceptional managerial capabilities (Colombo and
Grilli, 2005).
Supplementary findings by Colombo and Grilli (2009) clearly demonstrate that
“firms founded by individuals with selected human capital characteristics can leverage
the distinctive capabilities associated with the knowledge and skills of their founders to
grow larger”. Therefore founders' human capital has a direct positive effect on firm
growth (Colombo and Grilli, 2009) as there is an advantage in already knowing how to
set up and manage a firm (Colombo and Grilli, 2005).
The empirical results of this study confirm the evidence provided by previous
empirical studies that VC investments are attracted by the perceived management
competence of firms' founding team, proxied here by the presence in the founding
entrepreneurial team of one or more individuals with prior managerial experience. In
32
our sample, relevant measure of human capital such as managerial experience and
skills were found to be a key factor of receiving VC financing for the cleantech firms
which yields greater growth rates according to the growth literature. The high
uncertainty embedded in the renewables sector could be overcome by high
managerial competencies. Prior managerial experience and skills could leverage the
difficulties and high risks when operating a new firm in an uncertain sector. Specific
know how and realized managerial strategies aiming to predict and avoid market
inconsistencies could be incorporated in the strategic decisions of one firm in order to
help it grow faster.
Hypothesis 2 claimed that founders of cleantech firms that received VC funds
are more likely to have high educational attainment and start a business relevant to
their educational expertise than founders of firms from the consumer web industry. To
test the hypothesis univariate analysis (ttest) was conducted. The findings of the
univariate analysis support the assumption that founders of cleantech firms have high
educational level and attained relevant theoretical studies with the field they operate.
A possible explanation could be that the knowledge base and the analytical and
problem solving skills obtained by education provide individuals with the core
competencies to more effectively deal with the demands of entrepreneurship (Watson
et al., 2003).
Colombo and Grilli (2009) stated that “integration and coordination of the
knowledge possessed by “specialists” are more effective if they are members of the
founding team”. Individuals with higher educational attainment, superior work
experience, especially in the same sector as the new firm (i.e. industry-specific human
capital), and distinguished entrepreneur-specific human capital, are likely to have
better entrepreneurial judgment and more specific knowledge than other individuals.
Hence, they are in a better position to appropriate neglected business opportunities
and take adequate and efficient strategic decisions critical for the success of the new
firm.
According to a survey conducted by Chandler and Jansen (1992), having a
bachelor’s degree in business is related to firm profitability. However, they concluded
33
that is the type of education that makes the difference. In their survey the most
successful founders perceived themselves highly on their technical skills acquired by
their studies. Their expertise in their fields made them confident to use specialized
tools and procedures to produce high-quality products and services. This could also be
the explanation of the present study. Highly educated individuals with expertise in the
cleantech field such as environmental science and technology could be more confident
about their technical skills to start a business rather than an individual who hold a
computer science degree.
Considering the high technical environment of the cleantech industry firms
which requires specific forms of knowledge-intensive education, founders with
educational expertise in this area have an outstanding advantage (Sapienza and
Grimm, 1997).
6.2 Firm Covariates
Hypothesis 3 claimed that the likelihood of introducing a new product after the
VC investment is bigger for cleantech firms than for web ventures. This hypothesis,
however, is not supported by the empirical evidence. Actually, the findings of the
econometric analysis show that firms from the consumer web industry are more likely
to introduce a new product/service after the VC financing.
Sadorsky (2010) categorizes renewable energy companies and contends that
are partially closer to technology companies than energy companies. Renewable
energy companies are using or introducing new technology to increase energy
efficiency or lower the costs of providing existing and new renewable sources of
energy and products. However, uncertainty about future demand, technological, and
competitive conditions hinder firms' decisions about new product introductions.
The result of the present study is consistent with several studies which
underlined the negative relationship between new product development and high
market uncertainties (Badgett et al., 2002; Chatterjee and Sugita, 1990; Gatignon and
Xuereb, 1997).
Uncertainty about future demand and technological conditions could be a
possible explanation for the results of the present empirical study. Although cleantech
34
firms can use sufficient strategies to reduce such uncertainties or there is almost
always significant uncertainty remaining at the time of new product introduction that
gets resolved only after the new product is introduced. Another possible explanation
could be the high fixed production costs of the cleantech products and services.
Despite the fact that the firms included in the survey are VC backed the high
uncertainty of the renewable sector impedes the introduction of new products.
Furthermore, a number of barriers that have prevented penetration of
Renewable Energy Technologies (RET) have been identified in the existing literature.
These include cost-effectiveness, technical barriers, and market barriers such as
inconsistent pricing structures, institutional, political and regulatory barriers, and social
and environmental barriers (Painuly, 2001).
Another possible explanation could be the necessity to transform the
technology into early market-driven, market-ready products including prototypes
specific to initial markets that requires significant time and money. Finally, to meet
user needs, a product may require certification (e.g., through the UL [Underwriters
Laboratories] process) consistent with industry practices (Murphy et al., 2007).
The empirical evidence supports the hypothesis 4, which stated that cleantech
firms are more likely to be innovative than businesses from the consumer web industry
after the VC financing. In the present study the innovativeness is measured by the
patents, patent applications and patent citations recorded in the U.S.P.T.O. for the
products and/or services introduced by the companies included in the survey.
VC backed firms show a significantly larger number of patent applications;
however they do so even before the involvement of the VC. After a venture capitalist
invests, the number of patent applications by venture-funded firms is still large (Engel
and Keilbach, 2007). A study published by Kortum and Lerner (1998) looked at twenty
industries over a thirty-year period of time and found that “the amount of venture
capital activity in an industry significantly increases its rate of patenting” and that VC
may have a superior influence on innovation than corporate R&D programs. The VC
can provide or withhold investment funding for the relatively high risk but often
35
revolutionary and innovative R&D that can lead to the introduction in markets of new
cost-effective sustainable energy technologies (Moore and Wüstenhagen, 2004).
Another key factor that leads innovation in clean technologies is the growing
political emphasis on sustainable economic development. U.S federal initiatives
fostering clean technologies such as the 2009’s American Recovery and Reinvestment
Act (ARRA) stimulus package or state-level policies (e.g. “The Regional Greenhouse Gas
Initiative”, “The California Solar Initiative “The Sunrise Powerlink” etc.) could further
explain the high level of innovativeness in the industry. According to Harris et.al
(1993), states and local governments have often been the innovators in emerging
areas of public policy. State energy initiatives have been expanded to energy RD&D, a
part of a trend towards investing in technology innovation, focused on end-use
efficiency, renewable resources and sustainable economic development goals.
At this point it is crucial to state that VC funded cleantech firms are more
innovative than web ventures even though the results of the econometric analysis
showed that they are less likely to introduce a new product/service after the VC
financing. This contradictory result could be explained by the tendency of non
patenting strategies of web businesses for their products. For example, e-commerce
business using a patent to protect its revolutionary engine will have to publicly disclose
information on it; in this way, the company will provide valuable information which
can be easily mimicked by competitors.
Hypothesis 5 stated that cleantech firms are more likely to establish networks
after the VC financing than consumer web ventures. The regression results provide
support for this hypothesis.
One of the major features of VC firms is the allowance of a value-added
network to the funded firms (Moore and Wüstenhagen, 2004). Once they have
invested in a company, VCs might activate their networks (e.g. head hunters, patent
lawyers, investment bankers, etc.) to help the company succeed (Gorman and
Sahlman, 1989; Sahlman, 1990). Hochberg et al., (2007) contend that VCs presumably
have better-quality relationships and thus enjoy more influential network positions
than others, implying differences in clout, investment opportunities, and access to
36
information, etc. VCs bring a network of contacts with experienced infrastructure
providers (such as accounting firms, law firms, and executive search firms) and
potential professional managers that increase the likelihood of higher average growth
rates of the VC backed firms (Davila et al., 2003).
The results of the empirical analysis indicate that firms of the cleantech
industry exploit the network provided by the VC firms and they eventually contract
with suppliers, customers, law firms etc. establishing their own network and using
these partnerships to share technologies and get access to further valuable resources,
such as distribution channels and customer bases (Baucus et al., 1996). In a sector with
high demand and technological uncertainty such as the cleantech a network could
soften the high risks. Contracting with suppliers, customers etc could eliminate the
uncertainties as market base and technological knowledge are already realized and
transferred to the new firm. A network provided by an established firm, like a VC firm
or an incumbent supplier in the energy sector, could be described as a bridge for new
cleantech firms to general information for the sector, specific technological
knowledge, penetrating strategies and eventually to the wide market.
The last hypothesis of this survey note that cleantech firms are more likely to
build a new facility or new plants in USA after the VC financing than firms from the
consumer web industry. However, this hypothesis is not supported by the empirical
analysis since the variable newfacilities is not significant. After controlling for
multicollinearity it is explicit that the problem of the insignificance is not that. One
possible explanation for this could be that the majority of the companies included in
the survey have been already operating in the market and have built their main
manufacturing facilities or have already established their offices before the VC
financing. Due to lack of information provided in the companies’ websites was not
feasible to clearly state if the facilities have been built before or after the VC
investment.
37
7. Conclusion and Further Research
Environmental concerns, climate change and increasing oil prices are the main
driving factors towards renewable resources of energy generation while greater use of
renewable resources and renewable energy systems and energy efficiency provides
economic benefits while at the same time protecting the economy from political and
economic risks (Wei et al, 2010). Governments around the world have realized the
emerging sustainability challenges and have already started to design policy
mechanisms aimed to support market introduction of sustainable energy technologies
(Moore and Wüstenhagen, 2004).
While governments’ policies target societal added value VCs look for
investments that create private value. Compiling information about VC investments in
sustainable energy is not a straightforward task, since not only data on VC investment
is generally not publicly available but also as energy is an emerging VC category,
energy arrangements are often not accurately identified in the statistics (Wüstenhagen
and Teppo, 2006).
This paper makes a contribution to the scarce amount of research regarding the
influence of the VC on the growth of the cleantech industry in the U.S.A. The present
study investigates not only the theoretical framework of both renewable energy
market and VC industry in the U.S.A but also analyzes empirically the effect of involving
of VCs in the emerging sector of renewable energy.
The paper empirically tests some hypotheses about the role of the venture
capitalists in the growth of US cleantech firms. Most hypotheses about the (short
term) positive impact of venture capital can be confirmed on the basis of the results of
a descriptive analysis and the use of econometric analysis tools. Particularly, it was
found that US cleantech firms receiving VC achieve significantly higher growth rates as
they are more innovative and they are more likely to establish networks than
consumer-web businesses. The human capital of cleantech firms is another factor
contributing to the growth of the industry. Managerial experience and relevant
theoretical background was found to be significant and positive related to the
38
development of cleantech firms. According to the social-based literature, VC investors
identify and finally invest in ventures owned by experienced and highly educated
founders; characteristics that can guarantee the success of one company.
In accordance with the predictions, venture capitalists are more able to push
the firms to a faster and higher growth. Venture capitalists are more profit oriented
and thus mainly interested in fast growing sectors in order to realize their expected
revenues in a short time. The positive impact shown is supposed to make a
contribution to the increasing adoption of VC finance as a financial resource for
cleantech firms.
The paper is concluded with some thoughts about limitations of this study,
which can be the starting point for further research on the emerging energy VC
market.
Firstly, due to lack of information it was not feasible to differentiate two
plausible paths: New VC funds with an energy sector allocation might be raised, or
existing generalist VC funds (or those with a different sector specialization) might
extend their line of business to making energy investments. Secondly, the topic of
government involvement in sustainable energy VC would also deserve future research.
Government policies to induce sustainable innovation should be informed about VC
activity. VCs could leverage policy efforts for sustainable energy if these policies are
carefully designed. Finally, measuring innovation with patents data implies weakness
as they are indicator of invention rather than innovation while many non-patented
inventions and innovations are missing (Smith, 2005; Kleinknecht et al., 2002).
An interesting question for further studies especially in the emerging sector of
the renewables is whether venture-backed firms achieve a sustainable medium and
long-term growth and whether results are the same if non-surviving firms are included
in the survey.
39
Appendices
Figure 1
Annual Cumulative Solar Capacity in USA
S
ource: SEIA US Solar Industry Year in Review 2009
Figure 2Total Wind Power Capacity in USA (Annual and Cumulative)
Source: AWEA 2010
40
Figure 3 41
Geothermal Power Capacity on lineApril 2010
Installed capacity (MW): nominal nameplate capacity Running capacity (MW): gross capacity of plant in operation
Source: GEA 2010
Figure 4The Venture Capital Structure
Source: Randjelovic et al., 2003Figure 5
42
Total U.S. Venture Capital Investments in All Fields: 1980-2007 (Millions of constant 2005 U.S. dollars)
Figure 6
U.S. Venture Capital Investments in CleanTech: 1995-2007(millions of constant 2005 U.S. dollars)
Source: Dooley, 2008
43
Table 2Descriptive Statistics of Key Variables
N Minimum Maximum Mean Std. Deviation Skewness Kurtosis
clean_web 937 0 1 0.436 0.496 0.256 1.066
manageskills 813 0 1 0.781 0.414 -1.359 2.848
higheducation 937 0 1 0.725 0.447 -1.006 2.012
theoreticalbackground 932 0 1 0.492 0.500 0.030 1.001
newproduct 937 0 1 0.762 0.426 -1.230 2.514
inno_active 937 0 1 0.528 0.499 -0.113 1.013
partnership 907 0 1 0.834 0.373 -1.791 4.206
consumers_ 937 0 1 0.661 0.474 -0.678 1.460
newfacilities 935 0 1 0.327 0.469 0.736 1.542
lnraised_amount 859 9.392662 20.09778 15.631 1.461 -0.449 4.593
founded_post98 937 0 1 0.955 0.207 -4.400 20.356
funded_post04 937 0 1 0.943 0.231 -3.839 15.739*The number of the observations (N) appears to be greater than the total number of firms included in the survey due to duplication resulting from the multiple funding rounds of some firms
44
Table 3
Detailed description of variables
Type of variableName of variable
included in regression
Description of variable and
transformation made
Dependent
variableclean_web
The dependent variable was constructed
to distinguish firms included in the
cleantech industry from those from
consumer web industry and takes value 0
for the firms of the consumer web
industry and value 1 for those from
cleantech industry
Independent
variablemanageskills
This dummy variable is constructed to
distinguish those founders, from both
industries, that have managerial
entrepreneurial experience from those
who have not before founding their
company and takes value 0 for founders
that have not past managerial experience
or up to 5 years before they introduced
their companies and value 1 for those that
have managerial experience more than 10
years
higheducation
This dummy variable is constructed to
capture the educational attainment of the
founders and takes value 0 for those that
are not educated or they have some
secondary educational experience and
value 1 for those that they have attended
university and hold a bachelor, master or
PhD degree
45
theoreticalbackground
This dummy variable is constructed to
distinguish those founders, from both
industries, that have high educational
attainment relevant to their expertise
area from those who have not and takes
value 0 for highly educated founders that
have not the necessary theoretical
background to start a business and value
1 for those that have
newproduct
This dummy variable is constructed to
distinguish those firms, from both
industries, that introduced a new
product/service after the VC launch from
those who have not and takes value 0 for
companies that have not introduced a
new product/service and value 1 for those
that have introduced a new
product/service after the VC launch
Inno_active
This dummy variable is constructed to
distinguish those firms, from both
industries, that hold a patent or a patent
citation or applied for a patent in the
USPTO after the VC launch from those
who have not and takes value 0 for
companies that do not hold a patent or
patent citation or applied for a patent and
value 1 for those that have after the VC
launch
46
partnership
This dummy variable is constructed to
distinguish those firms, from both
industries, that have an established
network with their suppliers, customers or
they have contracted with other
companies after the VC launch from those
who have not and takes value 0 for
companies that have not established
networks and value 1 for those that have
obtained after the VC launch
newfacilities
This dummy variable is constructed to
distinguish those firms, from both
industries, that built a new facility or
expanded their existing facilities in the
U.S.A after the VC launch from those who
have not and takes value 0 for companies
that have not built or expanded their
facilities and value 1 for those that have
after the VC launch
Control
Variablepost98
This dummy variable is constructed to
distinguish those firms, from both
industries, that have been founded before
or after 1998 and takes value for those
founded before 1998 and value 1 for
those companies that have been founded
after 1998
47
funded_post04
This dummy variable is constructed to
capture the funded year of the firms, from
both industries and takes value 0 for those
firms that have been funded before 2004
and value 1 for those funded after 2004
lnraised_amount
This variable was constructed from the
original data and captures the amount
raised by the VC from the companies from
both industries
consumers_
This dummy variable distinguishes the
customers of the companies, from both
industries, included in the survey. It takes
value 0 when the customers are end
consumers (b2c) and value 1 when
customers are other businesses (b2b)
48
Table 4a
Correlation Matrix of Key Variables
Variable 1 2 3 4 5 6 7 8 9 10
1.clean_web 1.0000
2.manageskills 0.0312** 1.0000
3.newproduct -0.0640* -0.0884* 1.0000
4.inno_active 0.0945* -0.1053 0.2902 1.0000
5.partnership 0.0792* -0.0740* 0.1323 0.1338 1.0000
6.consumers_ 0.1809 -0.0202** 0.0652* 0.1083 0.0109** 1.0000
7.newfacilities 0.0696* 0.0046*** 0.0427** 0.1279 0.0895* -0.0141** 1.0000
8.lnraised_amount 0.2921 0.0259**0.0046*** 0.1278 0.0837* 0.0838* 0.2067 1.0000
9.founded_post98 0.0139** -0.1000 -0.0363** -0.1220 0.0025*** -0.0354** -0.1239 -0.0614* 1.0000
10.funded_post04 0.1689 0.063*5 -0.0501* -0.0093*** 0.0065*** -0.0096*** -0.0163** 0.0349** 0.1926 1.0000
49
Table 4b
Matrix of Significance Level of each Correlation
Variable 1 2 3 4 5 6 7 8 9 10
1.clean_web 1.0000
2.manage_exp 0.3749 1.0000
3.newproduct 0.0503 0.0117 1.0000
4.inno_active 0.0038 0.0026 0.0000 1.0000
5.partnership 0.0170 0.0375 0.0001 0.0001 1.0000
6.consumers_ 0.0000 0.5657 0.0460 0.0009 0.7439 1.0000
7.newfacilities 0.0334 0.8958 0.1922 0.0001 0.0071 0.6671 1.0000
8.lnraised_amount 0.0000 0.4818 0.8931 0.0002 0.0158 0.0140 0.0000 1.0000
9.founded_post98 0.6717 0.0043 0.2672 0.0002 0.9405 0.2784 0.0001 0.0722 1.0000
10.funded_post04 0.0000 0.0706 0.1258 0.7770 0.8440 0.7684 0.6184 0.3063 0.0000 1.0000
50
Table 5
Logit model Estimations on VC backed US cleantech firms
Coefficients P>|z|Individual Covariates
manageskills 0.350573** 0.091
Firm Covariates
newproduct-
0.4420235** 0.032inno_active 0.4111249** 0.021partnership 0.4158513* 0.076
new facilities 0.0961109 0.608
Control Variables
customers_ 1.0787*** 0.000founded_post98 1.585695** 0.021funded_post04 1.301446** 0.01
lnraised_amount 0.425646*** 0.000
Model DiagnosticsN 718LL -412.7836
Prob > x2 0.000 * Denotes significance at 90% level ** Denotes significance at 95% level*** Denotes significance at 99% levelThe number of the observations (N) appears to be greater than
the total number of firms included in the survey due to duplication resulting from the multiple funding rounds of some firms
51
Table 6a
Univariate analysis estimations of highly educated founders with relevant theoretical background on VC backed US cleantech firms
Two sample ttest with equal variances
Group Observations Mean Stand. Error Stand. Deviation 95% Coef. Interval0 277 0.8808664 0.0194992 0.3245319 0.8424803 0.91925251 182 0.9945055 0.0054945 0.0741429 0.983664 1.005347
combined 459 0.9259259 0.0122374 0.2621772 0.9018775 0.9499743difference -0.1136391 0.0244731 0.1617329 -0.0655452
difference=mean(0)-mean(1) t=-4.6435 degrees of freedom=457
H0 :diff=0
Ha :diff<0Pr (T<t)=0.0000***
Ha :diff!=0Pr (|T|>|t|)=0.0000
Ha :diff>0Pr (T>t)=1.0000
Table 6bTwo-sample Wilcoxon rank-sum (Mann-Whitney) test
clean_web Observations Rank sum Expected
0 277 60845.5 63710
1 182 44724.5 41860
combined 459 105570 105570
Unadjusted Variance 1932536.67
Adjustment for ties -1.53E+06
Adjusted Variance 397643.18
Null Hypothesis: higheducation if theoreticalbackground==1(clean_web==0) = higheducation(clean_web==1)
z=-4.543
Prob>|z|=0.0000***
52
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