Valuation model of new start-up companies: Lithuanian case/Naujai isteigtu imoniu vertinimo metodai: Lietuvos atvejis.
Stankeviciene, Jelena ; Zinyte, Santaute
1. Introduction
Nowadays a huge number of new ventures are emerging. The problem is
that new entrepreneurs typically have a great idea which could be
transformed into business, but do not have any capital, or their budget
is very limited. The only way to get financing and experienced advice is
from the external sources.
Just before financing, new venture must always be evaluated by
investors whether is it worth to invest or not. It is very hard to
evaluate the new firm, as most of the models and methods are based on
the accounting information, however, new firms usually do not have such
information. They also do not have any tangible wealth, therefore it
becomes impossible to evaluate them. There is a lack of evaluation
models which could take into account other data rather than accounting.
The model, proposed in this article, evaluates new firms from
relative investor's perspective and considers both their financial
performance and overall attraction. It is based on a multi-criteria
decision strategy using the SAW method and its advantages to combine,
find relations and evaluate both qualitative and quantitative criteria.
Proposed model is based on the main concept of multi-criteria evaluation
methods--the integration of the criteria values and weights into a
single magnitude.
In this paper the general SAW model framework is adopted to suit
specifically new venture firms. The model could be used by any simple
individual investor having information available to the public to
evaluate the new firm's performance in near future and make the
decision on his own. The model was applied to two different Lithuanian
new venture capital companies.
The actuality of the research appeals for the reason that there are
no appropriate methodologies to evaluate the optimal new start-up
company according to individual investor's and owner's of the
firm preferences.
It is not quite clear what criteria are the most important and
should be considered when choosing. Though, it is difficult to find
effective methodology that would allow an investor to evaluate a new
firm without knowing the accounting information. Particularly in
Lithuania, where the concept of funding as external source of finance is
not yet complete and the investment culture is not as advanced.
The main goal of the paper is to propose the new venture evaluating
model, test it empirically and illustrate how to choose the most
suitable company for individual investor to invest.
The main tasks of the research are:
1. To reveal the main funding possibilities for new ventures.
2. To indentify the main factors influencing the value of new
ventures.
3. To adopt the multi-criteria decision method based on SAW into
start-up valuation process.
4. To test the model applicability and to evaluate two Lithuanian
newly established companies.
The model is applied using 6 criteria groups dividing them into 22
sub-criteria and creating 2 alternatives to new Lithuanian companies.
2. Previous research
The term "entrepreneur" originated in French economics in
the 17th century and indicated someone who shifts economic resources out
of an area of lower and into an area of higher productivity and greater
yield (Carpenter II 2009). This conventional view suggests the primary
function of an entrepreneur in starting new profit-seeking business
ventures, especially ones involving financial risk.
The equity is the most important problem to solve for almost all
entrepreneurs. More often an entrepreneur has got an interesting idea
which should be transformed into business idea. To realize it--he needs
money.
The key areas, which confirm an objective financial position of the
venture and the entrepreneur's attitude toward the venture's
funds, are capital and cash flows. Small ventures with strong capital
support are much more likely to succeed than those that are capital
deficient (Brzozowska 2008). A satisfactory capital to company's
needs gives the venture appropriate flexibility to decide about further
growth, investments and market. It also allows the management team to
concentrate on running business rather than seek and create various ways
to achieve financing.
To have a clear view of new venture, all stages which are involved
in the development of new firms shall be described. New venture involves
several stages, different from each other, completing finally a
venture's life cycle. Not every venture should come over each
stage, and the length of certain stages is different in the case of a
sector, and a stage of sector's life cycle, strategy and
possibilities of its execution in competitive surroundings and
management capabilities. In practice there are two main stages of
venture development:
--early stage, with seed, start-up, and early stage development
phases,
--expansion stage.
The first is the seed stage when a concept has still to be
developed and proven. The second is the start-up phase when products or
services are developed and initial marketing takes place. The
third--early stage development--a firm is producing but often
unprofitably. At the stage of expansion a firm achieves a mature level
and might go public in a short time. Depending on the stage of
development various sources of finance can be involved (Brzozowska
2008). Sources of finance and stages are presented in Figure 1.
[FIGURE 1 OMITTED]
Young entrepreneurs are defined by their fresh, exciting ideas and
passionate drive to succeed. Most, however, lack money--and the
experience and connections to turn their concepts into viable
businesses. Consequently they need some help from external sources.
However, an entrepreneur is not always able to borrow as much as needed
because of the imperfect enforceability of borrowing contracts.
Consequently the output of the firm will depend on the assets level of
the owner (Fernandez-Villaverde et al. 2003).
In academic literature, there are two types of capital determined:
debt financing (money for the interest) and equity financing (invested
capital in exchange of part ownership). Source of debt financing covers
commercial banks, commercial finance companies, leasing companies, state
and local Government Lending Programs, trade credit and Consortiums.
Meanwhile sources of equity capital cover: private investors,
institutional venture capital firms, mergers and acquisitions, strategic
investor and corporate venture capitalists and overseas investors
(Snieska, Venckuviene 2010).
Moreover, some different sources (Klein 2010; Mace et al. 2010;
Snieska, Venckuviene 2010) suggest several funding options for the
start-ups, all of them are explained more in detail in Table 1.
Academic studies of the interaction between firms and their sources
of capital always focus on a single source of capital. Separate streams
of literature have emerged in bank finance, lease finance, venture
capital finance, private individual investor finance, supplier finance,
etc. In theoretical work, the need to focus on one (or in exceptional
cases, two) external capital source is directly attributable to
theoretical tractability. In empirical work, the focus on one or two
capital sources is largely attributable to data availability, since
data-sets are typically derived from investors, particularly in the case
of non-publicly traded businesses (Cosh et al. 2009).
Talking about the case of Lithuania, here small and medium sized
enterprises account for 99.4% of total active companies (Snieska,
Venckuviene 2010). However, Lithuanian business is pretty conservative
and venture capital market is not necessary for applying of innovation.
And companies with foreign capital in all sectors in Lithuania focus
more on the new innovative products and services market possibilities
than Lithuanian companies do.
Early stage business in Lithuania could be financed from several
sources. Here several financing sources will be briefly presented
available for early stage business in the context of Lithuania. There
are also two ways to get capital financed: debt and equity financing. As
a result, very similar system of aforementioned institutions operating
abroad is in Lithuania as well. Those sources of financing might be
Internal source of financing, Bootstrapping, State support, State
guarantee institution INVEGA, National support programme, Local
municipalities, Bank loans, EU Structural funds, Microcredits and
Private investors (Business Angels). All of them were described in Table
1 above.
To sum up, there are some peculiarities of venture capital market
in Lithuania (Snieska, Venckuviene 2010):
1. Venture capital market in Lithuania is emerging.
2. A huge role is played by EU initiatives in fostering venture
capital market.
3. The privatisation processes which started after independence was
regained, spurred first venture capital activities in Lithuania.
4. No register of venture capital activities exists, this cause the
lack of information for business about the possibilities of venture
capital.
5. Most investments by venture capital funds were made in medium
and large companies with long history of performance.
Determining the economic valuation of a company is one of the most
challenging and important discussions an entrepreneur can have with
investors. Research that provides operational guidance on such economic
valuation, is, however, lacking and little work is available on the
valuation of venture capital investments. Furthermore, some venture
capitalists maintain that: "the truth about valuing a start-up is
that it's often a guess" (Ge et al. 2005). Certainly, both
academic researchers and venture capitalists are increasingly
recognizing the importance of both sound theoretical and practical
contributions to this emerging research area.
How to evaluate accurately a firm is traditionally a financial
economics topic and most extant valuation methods are based on
accounting information. According to financial economics theory, the
economic value of any investment is the sum of the present value of its
future cash flows. Such an economic valuation depends on the ability of
the enterprise to generate future cash flows and investors'
assessments of, and attitudes towards, the risk of these future cash
flows. As Venture Capitalists typically finance growth, the main problem
is capturing the economic value of the growth opportunities being
financed. This usually involves specifying and estimating future growth
rates in some underlying value driving variable such as free cash flows.
DCF (discounted cash flow) valuation methods for Venture Capital
investments involve estimating future cash flows, their growth rates,
and a horizon terminal value representing the enterprise's value at
the Venture Capitalists exit (Goldenberg, D. H., Goldenberg, M. D.
2009).
The corporate finance literature reports four valuation methods
most commonly used in start-up valuation: discounted cash flow, earnings
multiple, net asset, and venture capital method. However, as it is
discussed below, none of these approaches is fully satisfactory for new
entrepreneurial firms.
A fundamental assumption underlying these financial valuation
methods is that there is an efficient capital market for the ownership
of the firm. This assumption may be workable for the public capital
market, as legal rules are in place, which regulate public firms to
release all material information to the market and private information
is not as common. Traded in a competitive market, the ownership of these
firms is also highly liquid. The venture capital market is doubtfully an
inefficient market and quite different in several aspects from the
public capital market (Ge et al. 2005):
1. Venture capitalists invest in private and new ventures. New
ventures have a short operating history, and as a result accounting
information is limited, making the new venture's future cash flows
difficult to calculate.
2. The law does not require that private firms report any financial
or management information. Such information is difficult to collect and
to verify. Therefore, the information asymmetry between entrepreneur and
potential investors is typically high.
3. Due to regulation the tradability of shareholdings in these
firms is low. Thus, there is not a ready market for these new
entrepreneurial firms.
4. Most of the assets of these entrepreneurial firms are intangible
and highly firm specific.
In order to evaluate a new company, usually the accounting data
should be taken, but when the company is new it is impossible to
evaluate, as accounting data is not available yet. Then other factors
should be taken into consideration. Thus, savvy venture capitalists
should take these key factors into consideration when evaluating a new
venture. It was founded empirically (Ge et al. 2005) that venture
capitalists typically valuate a new venture higher if: (1) the new
venture is in an industry with higher product differentiation and faster
growth; (2) the founder(s) has top management experience and start-up
experiences before founding the current venture; (3) the new venture was
founded by a team of founders rather than a solo founder and, major
management functions are covered by a complete management team; and (4)
the new venture has external partners.
Therefore, an integrative framework from strategic management
theories was developed to investigate how factors identified in the
research literature that are important to firm-level performance may
affect the economic valuation of a new venture when the new venture
seeks equity financing from venture capitalists. That integrative
framework suggests that firm resources, external ties, and market
opportunities jointly influence firm-level profitability, which can
serve as the fundamental basis for the economic valuation of a new
venture. Recently, scholars have drawn on network literature to
highlight the importance of external resources available to the firm
through its networks. The strategic network perspective avers that the
embeddedness of firms in networks of external relationships with other
organizations holds significant implications for firm performance
(Zaheer, Bell 2005).
3. Theoretical framework of the study
An integrative strategic management framework and indicators from
venture capital firm definition will be used in the proposed model.
Literature depicts that work has been explored on various aspects of
quality evaluation and performance appraisal in various service sectors.
However, it should be noted that service quality differs from product
quality. Product quality can be estimated by some quantitative
attributes which can be measured and the extent of quality of the
product can be estimated. While in case of evaluating quality of a
service sector as a whole or evaluating quality of an individual, most
of the attributes become qualitative (Datta et al. 2009). When valuing
new firms in emerging industries, investors are likely to turn their
attention to secondary sources of information to help identify
qualitative differences across firms (Sanders, Boivie 2003). In this
case, new companies have both quantitative and qualitative criteria. So
in order to create a model, six main criteria groups are analysed. As
these criteria are multidimensional and work in different directions,
there is a need to apply methods which can connect all criteria to one
descriptive measure. Multi-criteria evaluation methods are exactly these
measures which can analyse those criteria (Ginevicius 2007).
Multi-criteria decision making (MCDM) is applied to preferable decisions
among available classified alternatives by multiple attributes. So MCDM
is one of the most widely used decision methodology in project selection
problems (Simanauskas, Sidlauskas 2006). The MCDM is a method that
follows the analysis of several unrelated criteria, simultaneously. In
this method economic, environmental, social and technological factors
are considered for the selection of the project and for making the
choice sustainable (Bakshi, Sarkar 2011; Tamosiuniene et al. 2007).
Multi-criteria analysis is capable of dealing with the multiple
dimensions of evaluation problems. Multi-criteria decision-making
methods intuition is closely related to the way humans have always been
making decisions. Consequently, despite the diversity of multi-criteria
decision-making methods approaches, methods and techniques, the basic
ideas of multi-criteria decision-making methods are very simple: a
finite or infinite set of actions (alternatives, solutions, courses of
action ...), at least two criteria, and, obviously, at least one
decisionmaker. Given these basic elements, multi-criteria
decision-making methods are an activity which helps making decisions
mainly in terms of choosing, ranking or sorting the actions (Turskis et
al. 2009).
Each of the available quantitative methods of multi-criteria
evaluation has some unusual features and individual logic reflecting the
specific characteristics of the alternatives compared. Using several
multi-criteria methods simultaneously allows us to identify some stable
alternatives rated similarly by various techniques. However, numerous
calculations have also shown different ranks of a certain number of
alternatives, though the variations are slight (Ustinovichius et al.
2007). In this paper, SAW method will be used to create the valuation
model.
SAW (Simple Additive Weighting) is the oldest, typical, one of the
simplest, most widely known and practically used method (Ginevicius et
al. 2008; Ginevicius, Podvezko 2008b; Podvezko 2011). The method was
summarized by MacCrimmon. The criterion of the method [S.sub.j] clearly
demonstrates the main concept of multi-criteria evaluation methods--the
integration of the criteria values and weights into a single magnitude
(Ginevicius, Podvezko 2009). This is also reflected in its name.
The sum [S.sub.j] of the weighted normalized values of all the
criteria is calculated for the j-th object:
[S.sub.j] = [m.summation over (i=1)][[omega].sub.i][[??].sub.ij].
(1)
Where [[omega].sub.i] is weight of the i-th criterion [[??].sub.ij]
is normalized i-th criterion's value for j-th object; i = 1, ...,
m; j = 1, ..., n; m is the number of the criteria used, n--is the number
of the objects (alternatives) compared (Ginevicius, Podvezko 2006;
Andriusaitiene et al. 2008; Ginevicius 2008).
The largest value of the criterion [S.sub.j] corresponds to the
best alternative (Ginevicius, Podvezko 2008a). The alternatives compared
should be ranked in the decreasing order of the calculated values of the
criterion [S.sub.j].
Adopting the SAW method in the new venture evaluation process some
steps should be made:
1. Weights are given for each criterion as the importance of
attribute.
2. A value (score) is given for each alternative by criteria
assessment.
3. When there is already normalized matrix, every member of that
matrix is multiplied by its weight and summed with other members of the
alternative (line).
4. The alternative with the highest score is chosen.
Model consists of three stages and some stages consist of some
steps. First stage is for choosing criterion, second uses SAW to weight
the evaluative criteria and the last, third stage gives the optimal
newly established firm to fund for investor.
4. Application of valuation model to Lithuanian new startup
companies
All criteria were defined and grouped in smaller groups of
sub-criteria. This was made in order to have a more specific and
detailed valuation of criteria. Moreover, this structure will help to
create a better valuation model as firstly experts will evaluate all
sub-criteria. After that all subcriteria will be combined into criteria
groups with global weights and those criteria groups will be used in the
model to choose the most optimal start-up company to invest in.
When the criteria are given, the criteria weights can be
determined. They can be calculated by various methods. In any case, the
expert estimates are considered. This process is very subjective, so it
depends on various conditions, such as qualification of experts, number
of criteria and giving weights (Ginevicius 2006). This estimation of
criteria weights was made by six various experts. Three experts were
chosen from different companies' top management and three top
employees were chosen from Lithuanian banks. The results of their
evaluation are shown in Table 2.
The method's simple added weighting may use
'classical' normalization (Ginevicius, Podvezko 2008b). The
values of the criterion [S.sub.j] of the method range from 0 to 1 (not
taking the ultimate values) for all the alternatives considered, while
the sum of the criterion values is equal to unity allowing for graphical
(geometrical) interpretation of the method.
For further calculations it is needed to calculate the global
weight of each criterion. This is useful not only for the calculations
but also in order to see the most important criteria on the whole. The
global weights are calculated very simply. For example, Owner's
profile will be calculated getting simple arithmetic average from
sub-criteria of Owner's profile. All other global weights of each
criteria group will be got in the same way. The results of each global
criterion are given in Table 3 below. These results will be used in the
valuation model in order to find out which one of the companies is more
optimal to invest. The most important criteria are Market Opportunities
and External Ties. The least important is Investment Period.
Selecting optimal newly established firm to fund for investor is
based on the evaluation of two companies by scores. These two different
companies are from different sectors. The first company is in innovative
product sector with unique product in the industry oriented to local and
foreign markets, while another is in services sector with restaurants
and oriented to only local market. Moreover, both companies have good
relations with external partners. Further, Company 2 has already started
to get profit, whereas Company 1 has just been established and has no
profit.
Having the descriptions of the companies, it is possible to
evaluate criteria of companies by scores. In other words, criteria
matrix should be normalised. As input data for calculation is the
criteria and their values of importance, the matrix should be normalised
according to these conditions by evaluating the values of criteria in
the interval from 1 to 5, where:
1. Negative value of criteria (decreasing value of criteria).
2. Insufficient value of criteria (remaining the same).
3. Medium value of criteria (medium increasing).
4. Sufficient value of criteria (sufficient increasing).
5. High value of criteria (high increasing).
It is difficult to normalise the values of criteria. Experience
shows that the major problem is encountered when the part of the
criteria has a negative value. The normalisation is possible when all
the criteria, all values are positive (Podvezko 2011).
The numbers of normalised values of alternatives are presented in
Table 4. Also, codes of global criteria are mentioned.
The calculation of aggregated values was made from the numbers
using the formula (1). The usage of the formula is very simple. The
value of criterion of one company is multiplied by global weight of that
criterion. After all, values are summed and the aggregated value is got.
The results can be seen in Table 5.
Based on the data presented, a few conclusions can be drawn. First
of all it is assumed to use the alternative 1 for the valuation model of
optimal newly established company. This alternative is chosen because
its aggregated value 1.1515 is higher than the second value 0.8710.
The main factors of the chosen alternative are the higher product
differentiation in an industry, the higher demand growth rate of an
industry; it is innovative, entrepreneurial, very risky, promising and
perspective venture. Also, this company is very young and
growthoriented. These factors are the most important during crisis
period as many companies do not get enough profits, so to be different
and unique is good.
For the analysis 6 criteria and 22 sub-criteria were chosen and 2
alternatives created. They consist of various dimensions and change in
various directions. This means that the situation is getting better when
some of their values are growing, on the other hand, when the values of
some other criteria are decreasing, the situation is worsening.
Quantitative evaluation of these complex phenomena was successfully
performed by multi-criteria evaluation method. It was applied when the
values and weights of all the criteria were calculated. The overall
conclusion from evaluation of those two alternatives shows not very wide
dispersion, so it can be assumed that the criteria and criteria weights
are chosen correctly and the aggregated value sum of 1.15 shows that
alternative 1 is better to choose for a decision considering the
investment idea in some new companies.
5. Discussion
This study provides an evaluation criterion and evaluation
framework for determining the optimal new ventures to invest for
different investors with different goals. In order to evaluate a new
company in this way, a new valuation model was proposed using the
multi-criteria valuation method--simple additive weighting. The model
suggests that venture capital investors should not only focus on
traditional financial criteria but also on their given conditions and
parameters of the company. According to the received results the model
works properly and helps for venture capitalists to choose the best
optimal company to fund. For Lithuanian venture capital market in case
of implementation, the proposed model might be of practical utility.
Such kind of evaluation has never been made as all the previous
researchers were concentrating on evaluating companies through the
accounting data perspective. Thus, it is hard to compare this study with
the previous research. The received results of the research could be
improved further by analysing more criteria in the description of
Portfolio of Company's profile which could give more accurate
results. Moreover, it might be recommended to use more combinations of
other methods of multi-criteria evaluation to normalise the criteria
used and to pool the alternatives of various companies. The results from
the implementation with more multicriteria methods might show stronger
and more effective results from different perspectives.
6. Conclusions
Before financing, new venture must always be evaluated by investors
whether it is worth to invest or not. It is very hard to evaluate the
new firm, as most of the methods in literature are made according to the
accounting information, however, new firms usually do not have such
information. They also do not have any tangible wealth.
As there is a lack of valuation models for new venture firms, the
valuation model for new ventures was proposed in this paper. In order to
create such a model, the multi-criteria valuation method simple additive
weighting (SAW) was used. In comparison with other models, this SAW
model is effective, as different criteria can be chosen by different
investor according to his personal preferences. This method was used by
simulating the possible alternative target values and taking economic
situation in Lithuania for two companies into consideration. The
survival of company can be successful only with an accurate view and
prediction of the future.
For model creation in analysis 6 criteria and 22 sub-criteria were
chosen and 2 alternatives created. They consist of various dimensions
and change in various directions. Quantitative evaluation of these
complex phenomena was successfully performed by multi-criteria
evaluation method. It was applied when the values and weights of all the
criteria were calculated. Simple additive weighting method has worked
properly and proved that it was the right method to apply in the model.
The results of this method helped to choose the most optimal company to
invest in. It can be concluded that the created model can be extensively
applied for evaluating and selecting most optimal newly established
company. The overall conclusion from evaluation of those two
alternatives shows not very wide dispersion, so it can be assumed that
the criteria and criteria weights are chosen correctly and the
aggregated value sum of 1.1515 shows that alternative 1 is best to
choose for a decision considering the investment idea in some new
companies.
This study provides an evaluation criterion and evaluation
framework for determining the optimal new ventures to invest for
different investors with different goals. The model suggests that
venture capital investors should not only focus on traditional financial
criteria but also on their given conditions and parameters of the
company. For Lithuanian venture capital market in case of
implementation, the proposed model might be of practical utility. The
proved evaluation model can evaluate the optimal new venture firm for
individual investor.
Finally, results which were got could be improved further by
analysing more criteria in the description of Portfolio of
Company's profile which could give more accurate results. It might
be recommended to use more combinations of other methods of
multicriteria evaluation to normalise the criteria used and to pool the
alternatives of various companies. The results from the implementation
with more multi-criteria methods might show stronger and more effective
results from different perspectives.
http://dx.doi.org/ 10.3846/btp.2011.39
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Jelena Stankeviciene (1), Santaute Zinyte (2)
Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223
Vilnius, Lithuania
E-mails: (1) jelena.stankeviciene@vgtu.lt (corresponding author);
(2) santaute.zinyte@gmail.com
Received 26 November 2010; accepted 26 February 2011
Jelena STANKEVICIENE. PhD, is currently working as an Assoc. Prof.
in the Department of Finance Engineering at Vilnius Gediminas Technical
University (Lithuania), where she is also the dean of the Faculty of
Business Management. Her main research topics include assets and
liability management, regulation of financial institution, financial
management for value creation, value engineering.
Santaute ZINYTE. Graduated from Vilnius Gediminas Technical
University (Lithuania), following her Master of Science in Banking and
Finance at Ghent University (Belgium). Her latest research is concerned
with management of financial institutions, valuation models, fund
rising.
Jelena Stankeviciene (1), Santaute Zinyte (2)
Vilniaus Gedimino technikos universitetas, Sauletekio al. 11,
LT-10223 Vilnius, Lithuania
El. pastas: (1) jelena.stankeviciene@vgtu.lt; (2)
santaute.zinyte@gmail.com
Received 26 November 2010; accepted 26 February 2011
Table 1. Sources of financing (Compounded from sources: Ivanov, Xie
2010; Klein 2010; Mace et al. 2010; Snieska, Venckuviene 2010; Crowd
Funding 2011; Crowd Source Capital 2011; What is a Business
Incubator? 2011; Business Incubators 2011;
Invega 2011)
Self-funding or Initial capital sources are savings, credit
Internal source of cards, home-equity loans and other. At the
financing early stage families, friends or founder
generally funds the entrepreneurial firms.
Bootstrapping It refers to "non-traditional funding of a
company using series of interim techniques and
sources to move from one company stage to
another". From the point view of entrepreneur,
it is a creative way to allocate financial
resources for interim period.
Microfinance An emerging phenomenon that opens access to
capital for individuals previously shut out
from financial services. The most common
micro-financing instrument is micro-credit,
which is the issuance of small, unsecured loans
to individuals or groups for the purpose of
starting or expanding businesses.
Networking Young entrepreneurs who want to deal with their
lack of experience and contacts can join
numerous business organisations and get their
ideas in front of potential capital sources.
People can meet there business angels, venture
capitalists, attorneys, accountants, and
marketing experts. Almost every country has
such organisation or venture capital
association. Venture capital investments,
Business angels and venture capital investors
will be discussed separately and more widely
later in this thesis.
Commercial banks Usually an entrepreneur cannot get loans from
the bank or other financial institutions when
he has just an idea, because he cannot prove
his credit worthiness. Only later, in other
stages of development of the firm, the bank
suggests various loans and investment funds for
new entrepreneurs.
Crowd-funding An approach to raise the capital required for a
(sometimes called new project or enterprise by appealing to large
crowd-financing) numbers of ordinary people for small donations.
It describes collective cooperation, attention
and trust by people.
Business incubators Projects which are designed to help new
businesses develop and successfully launch,
helping them to survive and grow during the
start-up period when they are most vulnerable.
The goal of business incubators is to produce
healthy knowledge-based firms that create jobs
and wealth, strengthen the economy,
commercialize new technologies and refresh
communities.
State support State support for the ventures can be twofold:
direct and indirect (refers to various public
services like consultancy, establishment of
business incubators and Science and technology
parks etc.).
State guarantee The company was established to promote the
institution INVEGA financing of new business as well as its
(in Lithuania) development in Lithuania. The company issues
guarantees for micro-credit as well as for
loans to small and medium sized enterprises.
INVEGA provides guarantee part of SMEs' loan
(up to 80%) for banks and compensates up to 50%
of interest on guaranteed loan.
Local municipalities Almost all municipalities have programmes for
developing favourable environment for SMEs. The
programmes vary across the municipalities, but
forms of support can cover for example,
compensation of interest rates as well as
compensation of asset and facilities leasing,
education programmes for entrepreneurs and many
other.
EU Structural funds The main priorities of EU structural support
for the period 2007-2013 are three: 1)
productive human resources for knowledge
society; 2) competitive economy; 3) life
quality and cohesion.
Table 2. Estimation of criteria weights
No. Criteria Codes 1 2 3 4 5
1 The founder of new SC11 0 0 6 6 10
business venture has
previous top management
experiences
2 The founder of new SC12 1 0 5 2 10
venture has previous
start-up experiences
3 New venture's founder has
relevant industry SC13 1 0 5 6 10
experience before
founding the business
venture
4 New business ventures are SC14 0 0 5 4 0
founded by a team rather
than by one founder
5 New business ventures are SC15 10 1 4 2 10
with a functionally
complete management team
6 The owner of the company SC16 0 0 3 2 0
is male or female
7 There is larger size of SC21 10 14 5 3 10
the new venture "ego
network"
8 The new venture has SC22 5 0 7 7 10
external partners
9 There is higher product SC31 15 18 2 5 1
differentiation in an
industry
10 There is higher demand SC32 15 18 5 3 1
growth rate of an
industry
11 Investment period: Medium SC41 5 0 3 6 0
5 to 7 years
12 Investment period: Long SC42 2 0 3 1 0
term up to 12 years
13 Equity linked investment SC51 3 0 4 6 0
14 Debt or mixed forms of SC52 5 0 5 3 5
financing
15 Innovative / SC61 5 1 5 7 10
Entrepreneurial firms
16 Risky SC62 5 0 6 8 3
17 Promising /perspective SC63 5 10 5 6 10
venture
18 Young company SC64 0 0 5 3 0
19 Growth-oriented venture SC65 10 14 4 5 10
20 Private company SC66 0 1 4 6 0
21 Unquoted in stock market SC67 0 5 2 2 0
22 Future profit, future SC68 3 18 7 7 0
wealth, future cash flows
Total 100 100 100 100 100
No. 6 Total Weights
1 8 30 0.0500
2 8 26 0.0433
3
8 30 0.0500
4 5 14 0.0233
5 9 36 0.0600
6 1 6 0.0100
7 5 47 0.0783
8 7 36 0.0600
9 3 44 0.0733
10 5 47 0.0783
11 1 15 0.0250
12 5 11 0.0183
13 3 16 0.0267
14 1 19 0.0317
15 5 33 0.0550
16 1 23 0.0383
17 5 41 0.0683
18 1 9 0.0150
19 5 48 0.0800
20 1 12 0.0200
21 6 15 0.0250
22 7 42 0.0700
100 600 1.0000
Table 3. Global weights of each criterion
Global
Criteria Codes Sub-Criteria
Owner's C1
profile
The founder of new business venture has
previous top management experiences
The founder of new venture has previous
start-up experiences
New venture's founder has relevant industry
experience before founding the business
venture
New business ventures are founded by a team
rather than by one founder
New business ventures are with a functionally
complete management team
The owner of the company is male or female
External C2
ties
There is larger size of the new venture "ego
network"
The new venture has external partners
Market C3
Opportunities
There is higher product differentiation in an
industry
There is higher demand growth rate of an
industry
Investment C4
period
Medium 5 to 7 years
Long term up to 12 years
Financing C5
model
Equity linked investment
Debt or mixed forms of financing
Portfolio C6
Company's
profile
Innovative / Entrepreneurial firms
Risky
Promising / perspective venture
Young company
Growth-oriented venture
Private company
Unquoted in stock market
Future profit, future wealth, future cash
flows
Total
Global Global
Criteria Codes Total Weights weights
Owner's 0.0394
profile
SC11 30 0.0500
SC12 26 0.0433
SC13 30 0.0500
SC14 14 0.0233
SC15 36 0.0600
SC16 6 0.0100
External 0.0692
ties
SC21 47 0.0783
SC22 36 0.0600
Market 0.0758
Opportunities
SC31 44 0.0733
SC32 47 0.0783
Investment 0.0217
period
SC41 15 0.0250
SC42 11 0.0183
Financing 0.0292
model
SC51 16 0.0267
SC52 19 0.0317
Portfolio 0.0465
Company's
profile
SC61 33 0.0550
SC62 23 0.0383
SC63 41 0.0683
SC64 9 0.0150
SC65 48 0.0800
SC66 12 0.0200
SC67 15 0.0250
SC68 42 0.0700
600 1.0000
Table 4. Normalised values of Companies
Global Criteria Codes Company 1 Company 2
Owner's profile C1 3 5
External ties C2 4 4
Market Opportunities C3 5 2
Investment period C4 4 3
Financing model C5 2 3
Portfolio of Company's profile C6 5 2
Table 5. Calculating the values of companies using SAW method
Global Criteria Codes Company 1 Company 2
Owner's profile C1 3 5
External ties C2 4 4
Market Opportunities C3 5 2
Investment period C4 4 3
Financing model C5 2 3
Portfolio of Company's profile C6 5 2
Aggregated value
Value of Value of
Global Criteria Weights Company 1 Company 2
Owner's profile 0.0394 0.1183 0.1972
External ties 0.0692 0.2767 0.2767
Market Opportunities 0.0758 0.3792 0.1517
Investment period 0.0217 0.0867 0.0650
Financing model 0.0292 0.0583 0.0875
Portfolio of Company's profile 0.0465 0.2323 0.0929
Aggregated value 1.1515 0.8710
