• Internal Code :
  • Subject Code : INF30004
  • University : Swinburne University of Technology
  • Subject Name : Business Intelligence Analysis

Crowd Computing Project

Introduction

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,

Literature Review

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).

Hypothesis of The Study

  1. The null hypothesis: There is no 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 highest reward pledges

  1. The null hypothesis: There is no 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

  1. The null hypothesis: There is no 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 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 The Study

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

.186a

.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

.000b

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 t-value 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

.008a

.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

.168b

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 t-value 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

.191a

.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

.000b

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

Discussion and Conclusion

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 warm-glow giving, The economic journal, (1990) 464 477.

Beier, K. Wagner, Crowdfunding between Social Media and E-Commerce: Online Communication, Online Relationships and

Fundraising Success on Crowdfunding Platforms, in: Discussion Papers on Economics and Entrepreneurial Management 03/2014, (2014).

Burkett, Crowdfunding Exemption-Online 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 crowd-funded markets, Information Systems Research, 24(3) (2013) 499-519.

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Business Intelligence Assignment Help

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