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This project examine the importance of crowd funding though determining the relationship between the average amount per pledger as the dependent variables and the independent variables the number of pledges, the total count of pledges, and the number of comments counts. The crowd funding is a raising of fund from the community though the online platforms. It’s therefore important for crowd funding to ensure that its able to attract many people in the funding platform. The main objective of this project is to investigate if there exist a significant relationship between the average amount per pledger and the factors that can attract many people like the comments counts, the number of pledges, and the total count of pledges,
The past studies found that for any fund raising to be successful for any business there is need to attract many financials and potential financial. The study also found that it is a very big challenge for small business ventures to be in a position to raise fund for their capital using the traditional ways of funding ( Burkett, 2011). Different researcher found that crowd funding has significantly simplified the process of fund raising among the small scale business enterprises who were an able to raise funding from traditional method of fund raising. The crowd funding has also served a means of advertisement for the IT industries as well as the capital seeking and capital giving companies. The ability to raise fund through crowd funding lies solely on the power to bring the crowd together and the ability of the crowd to generate the crowd capital.
Therefore communication is a strong element in the realization of the crowd funding (Burtch Ghose, Wattal, 2013). The integration of IT in the crowd funding make its easy to be able to reach large crowd which can be able to generate the money required for the fund raising. Different research have been conducted to access the success rate of the crowd funding platform which found that crowd participation is a key factor in the realization of successful crowd fund raising. Other studies focused on the measure of success of crowd funds realized from the crowd fund raiser platform as a clear measure of success (Agrawal catalini, 2011).
Therefore the total amount of money that is raised by the crowd funding is a true measure of the success of crowd funding. Many studies have determined several ways in which crowd funding can be realized; some of those methods are reward, pledges, equity based, donations, and lending method (Andreoni 1990). Therefore it was found that different crowd funding method differ from one another due to the method of funding approach selected to be used. That type of crowd funding that can be able to attract large crowd of participants or users is likely to realize the highest amount of money raised (Beier Wanger, 2014).
The Alternative hypothesis: There is significant relationship between the average amount of rewards and the highest reward pledges
The Alternative hypothesis: There is significant relationship between the average amount of rewards and the number of pledges
The Alternative hypothesis: There is significant relationship between the average amount of rewards and the number of pledges, the total count of pledges, and the number of comments counts
The results of objective one
From the analysis below we are interested in determining if there is significant relationship between the average amount of pledge reward and the highest amount of pledges rewarded. From the analysis it was observed that the value of coefficient of determination was 0.035 which implied that the regression model can account for 3.5% of the variability on the average amount of rewards contributed by the highest pledge rewarded.
Model Summary 

Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
Change Statistics 

R Square Change 
F Change 
df1 
df2 
Sig. F Change 

1 
.186^{a} 
.035 
.035 
102.75097 
.035 
1024.516 
1 
28445 
.000 
The results in the table below show if there is significant relationship between the average amount of pledge rewards and the highest amount of pledges. From the analysis, it was observed that the f value was 1024.517 with a p value of 0.000 which was less than 0.05 significant level. This means that the highest pledge rewards influenced that average amount per pledge.
ANOVA 

Model 
Sum of Squares 
df 
Mean Square 
F 
Sig. 

1 
Regression 
10816594.589 
1 
10816594.589 
1024.516 
.000^{b} 
Residual 
300315550.149 
28445 
10557.762 

Total 
311132144.738 
28446 
From the analysis of the coefficient of the simple regression model, it was observed that the coefficient of the highest pledge rewards was 0.006 with a standard error of 0.000. The coefficient of highest pledge reward had a tvalue of 32.008 with a p value of 0.000 which was less than 0.05 significant level. This means that there is sufficient evidence to conclude that the highest pledge rewards statistically influences the average amount per pledger.
Coefficients 

Model 
Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 

B 
Std. Error 
Beta 

1 
(Constant) 
53.710 
.752 
71.421 
.000 

highest_pledge_reward_$ 
.006 
.000 
.186 
32.008 
.000 
Residuals Statistics 

Minimum 
Maximum 
Mean 
Std. Deviation 
N 

Predicted Value 
53.7161 
117.2972 
67.8221 
19.50000 
28447 
Residual 
118.29716 
4887.70264 
.00000 
102.74917 
28447 
Std. Predicted Value 
.723 
2.537 
.000 
1.000 
28447 
Std. Residual 
1.151 
47.568 
.000 
1.000 
28447 
The test for relationship between the average amount per pledge and the number of pledges
From the analysis below we are interested in determining if there is significant relationship between the average amount of pledge reward and the number of pledges. From the analysis it was observed that the value of coefficient of determination was 0.000064 which implied that the regression model can account for 0.0064% of the variability on the average amount of rewards contributed by the number of pledge.
Model Summary 

Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
Change Statistics 

R Square Change 
F Change 
df1 
df2 
Sig. F Change 

1 
.008^{a} 
.000 
.000 
104.58152 
.000 
1.900 
1 
28445 
.168 
The results in the table below show if there is significant relationship between the average amount of pledge rewards and the number of pledges. From the analysis, it was observed that the f value was 1.90 with a p value of 0.168 which was greater than 0.05 significant level. This means that the number of pledges does not influenced that average amount per pledge.
ANOVA 

Model 
Sum of Squares 
df 
Mean Square 
F 
Sig. 

1 
Regression 
20785.056 
1 
20785.056 
1.900 
.168^{b} 
Residual 
311111359.682 
28445 
10937.295 

Total 
311132144.738 
28446 
From the analysis of the coefficient of the simple regression model, it was observed that the coefficient of the number of pledge was 0.001 with a standard error of 0.001. The coefficient of number of pledge reward had a tvalue of 1.379 with a p value of 0.168 which was less than 0.05 significant level. This means that there is sufficient evidence to conclude that the number of pledge does not statistically influences the average amount per pledger.
Coefficients 

Model 
Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 

B 
Std. Error 
Beta 

1 
(Constant) 
67.721 
.624 
108.458 
.000 

number_of_pledgers 
.001 
.001 
.008 
1.379 
.168 
Residuals Statistics 

Minimum 
Maximum 
Mean 
Std. Deviation 
N 

Predicted Value 
67.7209 
137.3131 
67.8221 
.85480 
28447 
Residual 
75.05315 
4937.27783 
.00000 
104.57969 
28447 
Std. Predicted Value 
.118 
81.295 
.000 
1.000 
28447 
Std. Residual 
.718 
47.210 
.000 
1.000 
28447 
The test for significant relationship between the average amount of rewards and the number of pledges, the total count of pledges, and the number of comments counts
The table below give the analysis of the relationship between the average amount of rewards as the dependent variable and the number of pledges, the total count of pledges, and the number of comments counts as the independent variables. From the analysis, it was observed that the value of R squared coefficient of determination was 0.036 which implies that the linear regression model can account for 3.6% variability of the average amount of rewards due to the independent variables.
Model Summary 

Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
Change Statistics 

R Square Change 
F Change 
df1 
df2 
Sig. F Change 

1 
.191^{a} 
.036 
.036 
102.66997 
.036 
268.508 
4 
28442 
.000 
The results in the table below show if there is significant relationship between the average amount of pledge rewards and the number of pledges, the total count of pledges, and the number of comments counts. From the analysis, it was observed that the f value was equal to 268.508 with a p value of 0.000 which was significantly less than 0.05 significant level. This means that the the number of pledges, the total count of pledges, and the number of comments counts influenced that average amount per pledge.
ANOVA 

Model 
Sum of Squares 
df 
Mean Square 
F 
Sig. 

1 
Regression 
11321505.063 
4 
2830376.266 
268.508 
.000^{b} 
Residual 
299810639.675 
28442 
10541.124 

Total 
311132144.738 
28446 
The table below show the analysis of the coefficient of independent variables. From the analysis of the results, it was observed that the number of pledges had a coeffient of 0.003 with a standard error of 0.001. The coefficient of the number of pledges had a t value of 4.263 with a p value of 0.000 which was less than 0.05 significant level. This means that there is significant evidence that the number of pledgers statistically influence the average amount per pledger. The analysis of the results also indicate that the coefficient of the comments counts was 0.005 with a standard error of 0.001.
The coefficient of comments count had a t value of 4.186 with a p value of 0.000 which was less than 0.05 significant level. This means that the number of comments influences that average amount per pledger since the p value was significantly less than 0.05. The analysis of the results also indicate that the coefficient of the highest pledge rewards was 0.006 with a standard error of 0.000. The coefficient of highest pledge rewards had a t value of 27.149 with a p value of 0.000 which was less than 0.05 significant level. This means that the highest pledge rewards influences that average amount per pledger since the p value was significantly less than 0.05.
From the analysis of the results also indicate that the coefficient of the total count of pledge levels was 0.699 with a standard error of 0.128. The coefficient of total count of pledge levels had a t value of 5.446 with a p value of 0.000 which was less than 0.05 significant level. This means that the total count of pledge levels influences that average amount per pledger since the p value was significantly less than 0.05.
Coefficients 

Model 
Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 

B 
Std. Error 
Beta 

1 
(Constant) 
48.551 
1.234 
39.343 
.000 

number_of_pledgers 
.003 
.001 
.036 
4.263 
.000 

comments_count 
.005 
.001 
.035 
4.186 
.000 

highest_pledge_reward_$ 
.006 
.000 
.173 
27.149 
.000 

total_count_of_pledge_levels 
.699 
.128 
.035 
5.446 
.000 
Residuals Statistics 

Minimum 
Maximum 
Mean 
Std. Deviation 
N 

Predicted Value 
97.8326 
247.6833 
67.8221 
19.94993 
28447 
Residual 
164.55669 
4893.79590 
.00000 
102.66276 
28447 
Std. Predicted Value 
8.304 
9.016 
.000 
1.000 
28447 
Std. Residual 
1.603 
47.665 
.000 
1.000 
28447 
From the analysis, it was concluded that the number of pledgers significantly influences the average amount per pledger. This means that the number of pledger determine the rate of success of crowd funding. The results also conclude that the comments counts influences the amount per pledger. The means that the comment counts determine the rate of success of the crowd funding. The analysis also conclude that the highest pledge reward and the total count of pledge levels influences the amount per pledger. This means that the highest pledge reward and the total count of pledge levels determine the level of success of the crowd funding.
References
A.K. Agrawal, C. Catalini, A. Goldfarb, The geography of crowdfunding, in, (National Bureau of Economic Research, 2011).
Andreoni, Impure altruism and donations to public goods: a theory of warmglow giving, The economic journal, (1990) 464 477.
Beier, K. Wagner, Crowdfunding between Social Media and ECommerce: Online Communication, Online Relationships and
Fundraising Success on Crowdfunding Platforms, in: Discussion Papers on Economics and Entrepreneurial Management 03/2014, (2014).
Burkett, Crowdfunding ExemptionOnline Investment Crowdfunding and US Secrutiies Regulation, A, Transactions: Tenn. J.
Bus. L., 13(2011) 63.
Burtch, A. Ghose, S. Wattal, An empirical examination of the antecedents and consequences of contribution patterns in crowdfunded markets, Information Systems Research, 24(3) (2013) 499519.
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