










































AGORA International Journal of Economical Sciences, http://univagora.ro/jour/index.php/aijes 

ISSN 2067-3310, E-ISSN 2067-7669 

Vol. 18, No. 2 (2024), pp. 375-386 

 

375 

 

VALUATION MODEL OF CROWDFUNDING CAMPAIGNS 

APPLYING SIMPLE ADDITIVE WEIGHTING METHOD 

 

S. VENSLAVIENĖ, J. KARTAŠOVA 

 

Santautė Venslavienė¹, Jekaterina Kartašova² 

¹ ² Vilnius University Business School, Lithuania  

¹ https://orcid.org/0000-0002-4432-6753, E-mail: santaute.venslaviene@vm.vu.lt 

² https://orcid.org/0000-0003-3774-1817, E-mail: jekaterina.kartasova@vm.vu.lt   

 

Abstract: Every investor has some difficulties when investing into crowdfunding campaigns, 

as it is not clear how to evaluate specific crowdfunding campaign or what success factors to 

choose. The aim of this study is to propose the crowdfunding campaign assessment model, test 

it empirically and illustrate how to select the most appropriate crowdfunding campaign for 

individual investor to invest. Multi-criteria methods, used in the evaluation process, enable to 

get objective answers about the effectiveness of the optimal crowdfunding campaign 

comprehensively by presenting some generalized indicators and considering both quantitative 

and qualitative data. The obtained empirical results comparing two crowdfunding campaigns 

show that the proposed method could be used for evaluating complex processes of the optimal 

crowdfunding investments, and could be adapted for various situations. 

Keywords: crowdfunding, crowdfunding campaign, valuation model, multi-criteria decision 

method, simple additive weighting 

 

INTRODUCTION 

The crowdfunding industry increased significantly after the 2008 global financial crisis, 

as the typical financial system, especially the banking sector, was no longer trusted. Since then, 

crowdfunding has thrived globally (Jalal et al., 2024). Crowdfunding, being one of the key 

applications of Fintech that may disrupt traditional financial intermediation, is an emerging 

financing alternative form that connects those who can invest money directly with those who 

need financing for a specific project (Pandey et al., 2024; Wan et al., 2023). It is an internet-

based way for companies, organizations or individuals to raise money through either donations 

or investments from multiple individuals (Hussain et al., 2023). The basic principle of 

crowdfunding is therefore to pool money from a group of individuals instead of professional 

parties (Mora-Cruz & Palos-Sanchez, 2023). The definitions of crowdfunding might be 

different, but they summarize the following key components: 1) raise funds in minor amounts; 

2) many-to-many platform and 3) use of digital technology (Hussain et al., 2023; Mora-Cruz 

& Palos-Sanchez, 2023). 

These days many crowdfunding campaigns are emerging. Due to the high variety of 

crowdfunding campaigns, it is very difficult to select the right one. In order to select the most 

wanted campaign, the crowdfunding campaigns must be evaluated whether it is worth to invest 

or not. It is very difficult to assess the crowdfunding campaign, as most campaigns are from 

https://orcid.org/0000-0002-4432-6753
mailto:santaute.venslaviene@vm.vu.lt
https://orcid.org/0000-0003-3774-1817
mailto:jekaterina.kartasova@vm.vu.lt


VALUATION MODEL OF CROWDFUNDING CAMPAIGNS APPLYING SIMPLE 

ADDITIVE WEIGHTING METHOD 

376 

 

new companies which still do not have much accounting information or any tangible wealth. 

Also, there are not many specific success factors of crowdfunding campaigns to look. 

The proposed model identifies the success factors and evaluates new campaigns from 

investor’s perspective and reflects both their financial performance and overall attraction. This 

model is based on a multi-criteria decision weighting methodology and to be more precise – 

Simple Additive Weighting (SAW) method. The main benefits of this method are 1) ability to 

combine; 2) find relations; 3) evaluate both quantitative and qualitative criteria. This model 

follows main concept of all multi-criteria evaluation methods – it integrates the criteria values 

and weights into a single magnitude. 

The general Simple Additive Weighting model framework is adopted to fit specifically 

crowdfunding campaigns. This model can be used by any individual investor having chosen 

the proposed criteria to evaluate the crowdfunding campaigns and make investment decisions 

for the most exciting campaigns. For application purposes, two different campaigns were 

discussed in the evaluation model. 

The main goal of the paper is to propose the crowdfunding campaign assessment model, 

test it empirically and illustrate how to select the most appropriate crowdfunding campaign for 

individual investor to invest. Three tasks were developed: 

1) To identify the main success factors that influence the value of crowdfunding 

campaigns. 

2) To adopt the multi-criteria decision method based on SAW into crowdfunding 

campaign valuation process. 

3) To test the model applicability and to evaluate two crowdfunding campaigns. 

The paper is organized as follows: first, the literature review of financing crowdfunding 

campaigns and their success factors was conducted. Second, the applied methodology is 

described. Finally, the results, discussion, limitations and conclusions are discussed.  

 

1. Literature review 

1.1. Financing Crowdfunding Campaigns 

An ecosystem of crowdfunding consists of three groups: the platform, campaign owners 

and backers. The dominant point of every crowdfunding ecosystem is a platform. A platform 

is a technologically supported solution used to link supply (those who provide funds) and 

demand (those who are seeking for funds). The supply side consists of lenders, investors, 

backers and donors. The demand side consists of individuals and various organizations that 

seek for financial support (Jenik et al., 2017; Kumar et al., 2024). Crowdfunding has become 

very novel and popular financing application worldwide (Huang et al., 2023; Liang et al., 

2019). First studies that emphasised crowdfunding platforms, compared the decision-making 

process of equity crowdfunding with new venture capital funding (Hagedorn & Pinkwart, 2016; 

Löher, 2017).  

However, there is not enough knowledge about the crowdfunding success targets should 

be evaluated. Additionally, studies on campaign success factors and investment criteria in 

equity crowdfunding is rare. On the other hand, knowledge of the crowdfunding success factors 

is required in order to better understand the dynamics of crowdfunding and its campaign 

success rates (Fan-Osuala et al., 2018). While the number of crowdfunding campaigns is 



Santautė VENSLAVIENĖ, Jekaterina KARTAŠOVA 

377 

 

increasing, it is essential to understand what motivates people to fund these campaigns. The 

success of crowdfunding campaigns is influenced by various factors, including social capital 

theory (Butticè et al., 2017; Colombo et al., 2015; Skirnevskiy et al., 2017), signal theory 

(Ahlers et al., 2015; Courtney et al., 2017), the herding effect (Mohammadi & Shafi, 2018), 

and local bias (Mendes-Da-Silva et al., 2016). Therefore, success factors for crowdfunding 

campaigns will be discussed from traditional funding, venture capital and business angels 

theories. Moreover, crowdfunding can be comparable with traditional e-commerce transactions 

(Ahlers et al., 2015). 

 

1.2. Success Factors for Crowdfunding Campaigns 

Success factors for crowdfunding campaigns were taken from crowdfunding, venture 

capital and business angel theory and e-commerce literature. Most combinations of success 

factors were adapted from other study (Venslavienė et al., 2021) and are given in the table 1. 

According to the existing literature of crowdfunding theory, success factors are splitted into 4 

categories: campaign characteristics, networks, understandability and quality signals 

(Cumming et al., 2020; Ferreira & Pereira, 2018). Those 4 categories included other sub-

factors, in total counting 15 success factors from crowdfunding theory. While discussing 

Venture Capital and Business Angels theory, there were found 6 success factors (Huang et al., 

2023; Liu et al., 2023; Zhu et al., 2023). Finally, from e-commerce theory, there were found 

three main factor groups related with risk, including 10 related risks. To summarize, 6 global 

factor groups including 24 success factors affect crowdfunding campaigns. 

 

Table 1. Success factors for crowdfunding campaigns found in the literature 

Theory 
Global Success 

Factor 
Codes Success factor Codes 

Description 

C
ro

w
d

fu
n

d
in

g
 t

h
eo

ry
 

Campaign 

characteristics 
C1 

Campaign 

duration 
SC11 

duration of the project campaign 

Funding target SC12 
minimum sum needed to launch the 

project 

Min. Investment SC13 
minimum amount to invest to 

participate in the project campaign 

Provision of 

financials 
SC14 

financial forecasts/projections, early 

financial statements 

Number of early 

backers 
SC15 

number of investors who invest before 

the campaign is launched 

Capital raised SC16 total capital raised for one project 

Number of 

investors 
SC17 

actual number of investors investing in 

the same project 

Networks C2 

Social media 

networks 
SC21 

the followers’ social network of the 

project owner 

Private networks SC22 
family and friends who support the 

project 

Understandability C3 

Understandability SC31 
is it oriented to business (B2B) or 

customer (B2C) 

Information 

about risk 
SC32 

if the crowdfunding campaign is giving 

information about the risk 



VALUATION MODEL OF CROWDFUNDING CAMPAIGNS APPLYING SIMPLE 

ADDITIVE WEIGHTING METHOD 

378 

 

Environment 

commitments 
SC33 

if the crowdfunding campaign is 

committed to the environment 

Quality signals C4 

Updates SC41 how often updates are sent to audience 

Spelling mistakes SC42 
are there any spelling errors in the 

campaign text 

Video SC43 
is there a descriptive video about the 

campaign/product 

V
en

tu
re

 C
ap

it
al

 a
n

d
 B

u
si

n
es

s 
A

n
g

el
s 

Company ratings C5 

Team rating SC51 

industry expertise 

educational background 

Experience 

the balance between team members’ 

skill sets 

perceived motivation, drive, passion, 

commitment, honesty 

Markets rating SC52 
attainable market that determines the 

company’s growth potential. 

Concept rating SC53 

how well the product fits the target 

market 

relevance of the end customer’s 

problem 

how well the company addresses the 

problem compared to other alternatives 

value of the solution to the customer 

Scalability rating SC54 
it is easy to scale up the solution to the 

entire target market. 

Terms rating SC55 

valuation 

whether the targeted funding amount is 

sufficient to lift the company to the 

next level 

Stage rating SC56 

progress of the company on its 

development path 

remaining gap to the target state 

status of the product 

status of market validation 

existence of paying customers 

E
-c

o
m

m
er

ce
 t

h
eo

ry
 

Risk C6 

Risks associated 

with the project 
SC61 

product risk/funding object risk 

Social risk 

psychological risk 

post-funding risk/ repayment risk 

Risks associated 

with the project 

initiator 

SC62 

project initiator risk/owner risk/seller 

risk 

time risk/convenience risk 

delivery risk 

Risks associated 

with the 

intermediary 

SC63 

intermediary risk/privacy risk 

financial risk 

performance risk/operating risk 

Source: Adapted from (Venslavienė et al., 2021) 

These success factors should be used in evaluation model for crowdfunding campaigns. 

 



Santautė VENSLAVIENĖ, Jekaterina KARTAŠOVA 

379 

 

2. Methodology 

When assessing crowdfunding campaigns, investors usually do not have full 

information and have to turn their attention to secondary sources of information to help find 

out qualitative differences among crowdfunding campaigns. Thus, usually crowdfunding 

campaigns have both quantitative and qualitative success factors. Therefore, in order to create 

a model, six main factor groups were analyzed. Since these success factors are 

multidimensional, there is a need to apply methods that can link all criteria to one descriptive 

measure. Multi-criteria evaluation methods are the ones which can analyze those factors 

(Barretta et al., 2023; Hashemi et al., 2022; Khan et al., 2022). Multi-criteria decision making 

(MCDM) is applied to preferable decisions among available classified alternatives by multiple 

attributes (Taherdoost & Madanchian, 2023; Zavadskas et al., 2022). Multi-criteria desicion 

method is a method that does the analysis of several unrelated criteria. In this method 

environmental, economic, technological and social factors are discussed for the choice of the 

project and for making the choice sustainable (Alvarez et al., 2021).  

In this paper, Simple Additive Weighting method, one of MCDM methods, will be used 

to create valuation model. SAW method is the oldest, one of the simplest, widely known and 

practically used (Amalia & Alita, 2023; Kelen et al., 2023; Rusidah et al., 2023; Sinaga & 

Riandari, 2020). The criterion of the method Sj clearly demonstrates the main concept of multi-

criteria evaluation methods – the integration of the criteria values and weights into a single 

magnitude (Amalia & Alita, 2023; Sinaga & Riandari, 2020). The sum Sj of the weighted 

normalized values of all the criteria is calculated for the j-th object: 

𝑆𝑗 = ∑ 𝜔𝑖𝑟𝑖𝑗,
𝑚
𝑖=1                                 

(1) 

Where ωi is weight of the i-th criterion rij 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. 

The largest value of criterion Sj corresponds on the best alternative (Rajagukguk et al., 

2022). All the compared alternatives must be ranked in the decreasing order of the calculated 

values of the criterion Sj. 

Adopting the SAW method in the crowdfunding campaign evaluation process several 

steps should be done: 

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 

4) The alternative with the highest score is selected. 

Model consists of three stages. First, choose criteria. Second, use SAW to weight the 

evaluative criteria and the last, third stage gives the optimal crowdfunding campaign to fund 

for investor. 

 

3. Application of valuation model crowdfunding campaigns 

In order to have more specific and detailed valuation of factors, all factors were defined 

and grouped in smaller groups of sub-factors. Also, this way is easier for experts to evaluate 



VALUATION MODEL OF CROWDFUNDING CAMPAIGNS APPLYING SIMPLE 

ADDITIVE WEIGHTING METHOD 

380 

 

factors more precisely. After the expert evaluation, all sub-factors should be combined into 

factor groups with global weights and those factor groups will be used in the model to choose 

the most optimal crowdfunding campaign to invest in. 

When all factors are set, the factor weights can be found. Here expert estimates are 

chosen. This estimation is very subjective, therefore five professionals with experience in 

investing into crowdfunding platforms were chosen. Three of them constantly invest into 

crowdfunding campaigns, while the other two are the owners of crowdfunding campaigns. The 

results of expert evaluations are given in table 2. 

 

Table 2. Expert estimation of factor weights 

No Success factor Codes 1 2 3 4 5 Total Weights 

1 Campaign duration SC11 8 3 2 4 1 18 0.036 

2 Funding target SC12 4 4 3 3 1 15 0.030 

3 Min. Investment SC13 10 5 3 2 1 21 0.042 

4 Provision of financials SC14 3 3 2 3 5 16 0.032 

5 Number of early backers SC15 0 4 4 2 8 18 0.036 

6 Capital raised SC16 0 3 5 4 7 19 0.038 

7 Number of investors SC17 0 3 3 2 6 14 0.028 

8 Social media networks SC21 3 2 4 3 2 14 0.028 

9 Private networks SC22 3 2 20 9 6 40 0.080 

10 Understandability SC31 6 4 5 3 1 19 0.038 

11 Information about risk SC32 10 3 1 2 4 20 0.040 

12 Environment commitments SC33 5 2 1 3 3 14 0.028 

13 Updates SC41 3 2 1 2 4 12 0.024 

14 Spelling mistakes SC42 5 3 1 2 3 14 0.028 

15 Video SC43 0 4 1 3 5 13 0.026 

16 Team rating SC51 7 5 10 6 4 32 0.064 

17 Markets rating SC52 5 3 2 3 4 17 0.034 

18 Concept rating SC53 3 7 10 6 4 30 0.060 

19 Scalability rating SC54 0 3 4 3 5 15 0.030 

20 Terms rating SC55 0 5 4 3 2 14 0.028 

21 Stage rating SC56 0 5 4 3 2 14 0.028 

22 Risks associated with the project SC61 10 10 4 8 8 40 0.080 

23 Risks associated with the project 

initiator 

SC62 5 8 3 11 5 32 0.064 

24 Risks associated with the 

intermediary 

SC63 10 7 3 10 9 39 0.078 

  Total 100 100 100 100 100 500 1.000 

 

Simple additive weighting method uses the typical normalization. The values of the 

criterion Sj of the method range from 0 to 1 for all the alternatives considered, while the sum 

of the criterion values is equal to unity allowing for graphical (geometrical) interpretation of 

the method. 



Santautė VENSLAVIENĖ, Jekaterina KARTAŠOVA 

381 

 

The global weights of each criterion should be estimated for further calculations. The 

global weights will show the most important factors from the whole group. The global weights 

are calculated in a very simple way – by finding simple arithmetic average from each sub-

factor group. The results of global weights are found in table 3. The results shall be used in the 

valuation model to get which one of crowdfunding campaigns is more attractive to invest. The 

most important factors are related with Risk and with Networks, while the least important are 

quality signals. 

 

Table 3. Global weights of each factor group 

Global Success 

Factor 
Codes Success factor Codes 

Total Weights 

Global 

weights 

Campaign 

characteristics 
C1 

        0.0346 

   Campaign duration SC11 18 0.036  

   Funding target SC12 15 0.030  

   Min. Investment SC13 21 0.042  

   Provision of financials SC14 16 0.032  

   Number of early backers SC15 18 0.036  

   Capital raised SC16 19 0.038  

  Number of investors SC17 14 0.028  

Networks C2         0.054 

  Social media networks SC21 14 0.028  

   Private networks SC22 40 0.080  

Understandability C3         0.0353 

  Understandability SC31 19 0.038  

  Information about risk SC32 20 0.040  

  Environment commitments SC33 14 0.028  

Quality signals C4         0.0260 

   Updates SC41 12 0.024  

   Spelling mistakes SC42 14 0.028  

   Video SC43 13 0.026  

Company ratings C5         0.0407 

   Team rating SC51 32 0.064  

   Markets rating SC52 17 0.034  

   Concept rating SC53 30 0.060  

   Scalability rating SC54 15 0.030  

   Terms rating SC55 14 0.028  

  Stage rating SC56 14 0.028  

Risk C6         0.0740 

  Risks associated with the project SC61 40 0.080  

  

Risks associated with the project 

initiator 
SC62 

32 0.064  

  

Risks associated with the 

intermediary 
SC63 

39 0.078  



VALUATION MODEL OF CROWDFUNDING CAMPAIGNS APPLYING SIMPLE 

ADDITIVE WEIGHTING METHOD 

382 

 

The next step is to find out the most attractive crowdfunding campaign to invest in. 

There were analyzed two different crowdfunding campaigns from different sectors. The first 

crowdfunding campaign is in real estate and oriented to both foreign and local markets, while 

the second is innovative with unique product in the industry, but oriented only to local market. 

Moreover, both already have some early investors. Further, Crowdfunding Campaign 1 is 

considered to be on lower risk, while Crowdfunding Campaign 2 is the opposite – very risky. 

With proper descriptions of the crowdfunding campaigns, it is likely to assess 

crowdfunding campaigns by scores. In other words, the factor matrix should be normalised. As 

input data for calculation are the factors and their values of importance, the matrix should be 

normalised according to these conditions by evaluating the values of factors in the interval 

from 1 to 5, where: 

1) Negative value of factors (decreasing value of factors). 

2) Insufficient value of factors (remaining the same). 

3) Medium value of factors (medium increasing). 

4) Sufficient value of factors (sufficient increasing). 

5) High value of criteria (high increasing). 

The normalized values of alternatives are provided in table 4. The estimation of 

aggregated values was done by applying the formula (1). The final results are presented in table 

5. Based on the results, it is possible to draw some conclusions. As the optimal alternative, it 

should be selected the second crowdfunding campaign since its aggregated value is 1.0303 that 

is higher than the first crowdfunding campaign with aggregated value of 0.7982. 

 

Table 4. Global Normalized values for Crowdfunding campaigns 

Global Success Factor Codes Crowdfunding Campaign 1 Crowdfunding Campaign 2 

Campaign characteristics C1 5 4 

Networks C2 3 4 

Understandability C3 4 3 

Quality signals C4 2 3 

Company ratings C5 3 3 

Risk C6 2 5 

 

Table 5. Crowdfunding campaign value calculation using SAW method 

Global Success 

Factor 
Codes 

Crowdfunding 

Campaign 1 

Crowdfunding 

Campaign 2 Global weights 

Value of 

Crowdfunding 

Campaign 1 

Value of 

Crowdfunding 

Campaign 2 

Campaign 

characteristics 
C1 

5 4 0.0346 0.1729 0.1383 

Networks C2 3 4 0.0540 0.1620 0.2160 

Understandability C3 4 3 0.0353 0.1413 0.1060 

Quality signals C4 2 3 0.0260 0.0520 0.0780 

Company ratings C5 3 3 0.0407 0.1220 0.1220 

Risk C6 2 5 0.0740 0.1480 0.3700 

Aggregated value 0.7982 1.0303 

 



Santautė VENSLAVIENĖ, Jekaterina KARTAŠOVA 

383 

 

For this analysis six factor groups and 24 sub-factors were selected and 2 alternatives 

created. Multi-criteria evaluation method was applied to perform quantitative evaluation on 

these success factors. First, all values and weights of all factors were estimated and then they 

were applied to evaluation model. The overall conclusion from evaluation of those two 

alternatives shows not very wide dispersion, so it can be assumed that the factors and factor 

weights are selected correctly and the aggregated value sum of 1.0303 shows that alternative 2 

is more attractive to choose for a decision considering the investment idea in some 

crowdfunding campaigns.  

 

DISCUSSION 

This paper provides the estimation framework to determine the optimal crowdfunding 

campaigns to invest. A new valuation model was proposed applying simple additive weighting 

methods which is part of multi-criteria evaluation method. The model suggests that 

crowdfunding investors should focus not only on traditional financial factors but also on their 

given parameters and conditions. The model works properly and helps for investors to decide 

on the best crowdfunding campaign. Moreover, it might be recommended to select more 

success factors or to use more combinations of other methods of multi-criteria evaluation to 

normalise the factors used and to pool the alternatives of various crowdfunding campaigns. 

The results from the implementation with more multi-criteria methods might show stronger 

and more effective results from different perspectives. 

 

CONCLUSIONS  

Before investing into new crowdfunding campaigns, investors must evaluate whether it 

is worth to invest or not. It is quite difficult to evaluate crowdfunding campaigns as most of 

them are very new in the market and there is little financial data.  

The valuation model to assess crowdfunding campaigns was proposed in this paper. Moreover, 

the multi-criteria valuation method simple additive weighting was applied. Comparing with 

other models, simple additive weighting is effective, as different factors can be chosen by 

different investor according to his personal preferences.  

For this analysis six factor groups and 24 sub-factors were selected and 2 alternatives created. 

Multi-criteria evaluation method was applied to perform quantitative evaluation on these 

success factors. First, all values and weights of all factors were estimated and then they were 

applied to evaluation model. 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 crowdfunding campaign to invest in. It can be concluded that the 

created model can be extensively applied for evaluating and selecting most optimal 

crowdfunding campaign. The overall conclusion from evaluation of those two alternatives 

shows not very wide dispersion, so it can be assumed that the factors and factor weights are 

selected correctly.  

 



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