Validez y Confiabilidad

Sub-RQ 2.2 was as follows: Is there a statistically significant relationship between SMEs’ reliance on crowdfunding and SMEs’ reliance on start-up funding?

4.3.2.1 Start-up funding, all years

The regression of crowdfunding on start-up funding was statistically insignificant, F(1, 998) = 2.560, p = .1099. The regression of crowdfunding on start-up funding had an effect size of 0.026, indicating that roughly 2.6% of the variation in crowdfunding could be explained by variation in start-up funding. The regression equation for the relationship between crowdfunding and start-up funding was as follows:

Crowdfunding % = (Start-up funding %)(-0.018) + 4.229

Thus, every additional percentage a company’s total finding from start-up funding reduced crowdfunding by roughly a tenth of a percent. The results of adding technology company status to the regression of crowdfunding on start-up funding are presented in Table 30 below, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (9.66) (7.52) _cons 5.465*** 2.787*** (14.42) 1.techtype 3.534*** (.) 0.techtype 0 (-3.15) (0.78) seed -0.0923** 0.0142 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 144 Table 30: Regression of Crowdfunding in Startup Funding, No Covariate & Tech Covariate Models (Source: Author)

Thus, technology companies received 3.261% more of their funding as crowdfunding, but the effect of being a technology company on outsourcing did not change start-up funding as a statistically insignificant predictor of crowdfunding as a % of total funding. The adjusted coefficient of determination of the regression of crowdfunding on start-up funding was 0.1099, but this regression did not meet the assumption of heteroskedasticity of errors through the Breusch-Pagan / Cook-Weisberg test, χ2 = 21310, p < .001. However, the same results were obtained through a RSE regression, so the findings reported above are statistically reliable.

4.3.2.2 Start-up funding, 2008

The regression of crowdfunding on start-up funding in 2008 was statistically insignificant, F(1, 98) = 2.330, p = .1302. The regression of crowdfunding on start-up funding in 2008 had an effect size of 0.0232, indicating that roughly 2.3% of the variation in crowdfunding in 2008 could be explained by variation in start-up funding in 2008. The regression equation for the relationship between crowdfunding and start-up funding in 2008 was as follows:

Crowdfunding %, 2008 = (Start-up funding %, 2008)(-0.030) + 4.360

Thus, every additional percentage a company’s total finding from start-up funding in 2008 reduced crowdfunding received in 2008 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2008 on start-up funding in 2008 are presented in Table 31, which also includes the results of the original regression..

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 1000 1000 (21.06) (15.36) _cons 4.230*** 2.927*** (17.57) 1.techtype 3.261*** (.) 0.techtype 0 (-1.60) (1.64) su -0.0184 0.0168 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 145 Table 31: Regression of Crowdfunding in 2008 on Startup Funding in 2008, Tech Covariate (Source: Author)

Thus, technology companies received 3.036% more of their funding as crowdfunding in 2008, but the effect of being a technology company on outsourcing did not change start-up funding in 2008 as a statistically significant predictor of crowdfunding as a % of total funding in 2008.

4.3.2.3 Start-up funding, 2009.

The regression of crowdfunding on start-up funding in 2009 was statistically insignificant, F(1, 98) = 0.080, p = .7779. The regression of crowdfunding on start-up funding in 2009 had an effect size of 0.0008, indicating that very little of the variation in crowdfunding in 2009 could be explained by variation in start-up funding in 2009. The regression equation for the relationship between crowdfunding and start-up funding in 2009 was as follows:

Crowdfunding %, 2009 = (Start-up funding %, 2009)(0.010) + 4.086

Thus, every additional percentage a company’s total finding from start-up funding in 2009-increased crowdfunding received in 2009 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2009 on start-up funding in 2009 are presented in Table 32, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (12.64) (13.57) _cons 4.361*** 3.009*** (14.00) 1.techtype 3.036*** (.) 0.techtype 0 (-1.53) (0.53) su -0.0309 0.00641 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 146 Table 32: Regression of Crowdfunding in 2009 on Start-up Funding in 2009, Tech Covariate (Source: Author)

Thus, technology companies received 3.065% more of their funding as crowdfunding in 2009, but the effect of being a technology company on outsourcing did not change start-up funding in 2009 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2009.

4.3.2.4 Start-up funding, 2010

The regression of crowdfunding on start-up funding in 2010 was statistically significant, F(1, 98) = 4.190, p = .0433. The regression of crowdfunding on start-up funding in 2010 had an effect size of 0.0410, indicating that roughly 4% of the variation in crowdfunding in 2010 could be explained by variation in start-up funding in 2010. The regression equation for the relationship between crowdfunding and start-up funding in 2010 was as follows:

Crowdfunding %, 2010 = (Start-up funding %, 2010)(-0.037) + 4.181

Thus, every additional percentage a company’s total finding from start-up funding in 2010 reduced crowdfunding received in 2010 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2010 on start-up funding in 2010 are presented in Table 33, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (6.24) (5.39) _cons 4.086*** 3.460*** (3.60) 1.techtype 2.165*** (.) 0.techtype 0 (0.28) (0.53) su 0.0109 0.0192 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 147 Table 33: Regression of Crowdfunding in 2010 on Start-up Funding in 2010, Tech Covariate (Source: Author)

Thus, technology companies received 2.902% more of their funding as crowdfunding in 2010, but the effect of being a technology company on outsourcing did not change start-up funding in 2010 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2010.

4.3.2.5 Start-up funding, 2011

The regression of crowdfunding on start-up funding in 2011 was statistically insignificant, F(1, 98) = 0.290, p = .5893. The regression of crowdfunding on start-up funding in 2011 had an effect size of 0.003, indicating that roughly 0.3% of the variation in crowdfunding in 2011 could be explained by variation in start-up funding in 2011. The regression equation for the relationship between crowdfunding and start-up funding in 2011 was as follows:

Crowdfunding %, 2011 = (Start-up funding %, 2011)(-0.038) + 4.897

Thus, every additional percentage a company’s total finding from start-up funding in 2011 reduced crowdfunding received in 2011 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2011 on start-up funding in 2011 are presented in Table 34, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (12.56) (13.78) _cons 4.182*** 3.021*** (13.16) 1.techtype 2.902*** (.) 0.techtype 0 (-2.05) (-0.05) su -0.0376* -0.000579 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 148 Table 34: Regression of Crowdfunding in 2011 on Startup Funding in 2011, Tech Covariate (Source: Author)

Thus, technology companies received 5.638% more of their funding as crowdfunding in 2011, but the effect of being a technology company on outsourcing did not change start-up funding in 2011 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2011.

4.3.2.6 Start-up funding, 2012

The regression of crowdfunding on start-up funding in 2012 was statistically significant, F(1, 98) = 4.450, p = .0374. The regression of crowdfunding on start-up funding in 2012 had an effect size of 0.0434, indicating that roughly 4.3% of the variation in crowdfunding in 2012 could be explained by variation in start-up funding in 2012. The regression equation for the relationship between crowdfunding and start-up funding in 2012 was as follows:

Crowdfunding %, 2012 = (Startup funding %, 2012)(-0.051) + 4.664

Thus, every additional percentage a company’s total finding from start-up funding in 2012 reduced crowdfunding received in 2012 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2012 on start-up funding in 2012 are presented in Table 35, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (3.85) (1.91) _cons 4.898*** 2.470 (4.38) 1.techtype 5.638*** (.) 0.techtype 0 (-0.54) (0.57) su -0.0387 0.0388 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 149 Table 35: Regression of Crowdfunding in 2012 on Start-up Funding in 2012, Tech Covariate (Source: Author)

Thus, technology companies received 3.326% more of their funding as crowdfunding in 2012, and the effect of being a technology company on outsourcing was strong enough to displace start-up funding in 2012 as a statistically significant predictor of crowdfunding as a % of total funding in 2012.

4.3.2.7 Start-up funding, 2013

The regression of crowdfunding on start-up funding in 2013 was statistically insignificant, F(1, 98) = 1.310, p = .2552. The regression of crowdfunding on start-up funding in 2013 had an effect size of 0.0132, indicating that roughly 1% of the variation in crowdfunding in 2013 could be explained by variation in start-up funding in 2013. The regression equation for the relationship between crowdfunding and start-up funding in 2013 was as follows:

Crowdfunding %, 2013 = (Start-up funding %, 2013)(-0.019) + 3.972

Thus, every additional percentage a company’s total finding from start-up funding in 2013 reduced crowdfunding received in 2013 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2013 on start-up funding in 2013 are presented in Table 36, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (11.77) (12.94) _cons 4.664*** 3.304*** (13.51) 1.techtype 3.326*** (.) 0.techtype 0 (-2.11) (-1.33) su -0.0514* -0.0194 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 150 Table 36: Regression of Crowdfunding in 2013 on Start-up Funding in 2013, Tech Covariate (Source: Author)

Thus, technology companies received 2.348% more of their funding as crowdfunding in 2013, but the effect of being a technology company on outsourcing did not change start-up funding in 2013 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2013.

4.3.2.8 Start-up funding, 2014

The regression of crowdfunding on start-up funding in 2014 was statistically insignificant, F(1, 98) = 0.100, p = .7569. The regression of crowdfunding on start-up funding in 2014 had an effect size of 0.001, indicating that roughly a tenth of 1% of the variation in crowdfunding in 2014 could be explained by variation in start-up funding in 2014. The regression equation for the relationship between crowdfunding and start-up funding in 2014 was as follows:

Crowdfunding %, 2014 = (Start-up funding %, 2014)(0.015) + 3.786

Thus, every additional percentage a company’s total finding from start-up funding in 2014-increased crowdfunding received in 2014 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2014 on start-up funding in 2014 are presented in Table 37, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (12.55) (11.54) _cons 3.972*** 2.831*** (10.35) 1.techtype 2.348*** (.) 0.techtype 0 (-1.14) (1.31) su -0.0191 0.0158 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 151 Table 37: Regression of Crowdfunding in 2014 on Start-up Funding in 2014, Tech Covariate (Source: Author)

Thus, technology companies received 4.235% more of their funding as crowdfunding in 2014, but the effect of being a technology company on outsourcing did not change start-up funding in 2014 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2014.

4.3.2.9 Start-up funding, 2015

The regression of crowdfunding on start-up funding in 2015 was statistically insignificant, F(1, 98) = 1.120, p = .2935. The regression of crowdfunding on start-up funding in 2015 had an effect size of 0.011, indicating that roughly 1% of the variation in crowdfunding in 2015 could be explained by variation in start-up funding in 2015. The regression equation for the relationship between crowdfunding and start-up funding in 2015 was as follows:

Crowdfunding %, 2015 = (Start-up funding %, 2015)(-0.030) + 4.512

Thus, every additional percentage a company’s total finding from start-up funding in 2015 reduced crowdfunding received in 2015 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2015 on start-up funding in 2015 are presented in Table 38, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (4.36) (3.48) _cons 3.787*** 2.787*** (5.08) 1.techtype 4.235*** (.) 0.techtype 0 (0.31) (0.44) su 0.0157 0.0202 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 152 Table 38: Regression of Crowdfunding in 2015 on Start-up Funding in 2015, Tech Covariate (Source: Author)

Thus, technology companies received 3.344% more of their funding as crowdfunding in 2015, but the effect of being a technology company on outsourcing did not change start-up funding in 2015 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2015.

4.3.2.10 Start-up funding, 2016

The regression of crowdfunding on start-up funding in 2016 was statistically insignificant, F(1, 98) = 0.130, p = .7146. The regression of crowdfunding on start-up funding in 2016 had an effect size of 0.001, indicating that roughly a tenth of 1% of the variation in crowdfunding in 2016 could be explained by variation in start-up funding in 2016. The regression equation for the relationship between crowdfunding and start-up funding in 2016 was as follows:

Crowdfunding %, 2016 = (Startup funding %, 2016)(0.013) + 3.822

Thus, every additional percentage a company’s total finding from start-up funding in 2016-increased crowdfunding received in 2016 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2016 on start-up funding in 2016 are presented in Table 39, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (8.88) (7.15) _cons 4.513*** 2.946*** (9.13) 1.techtype 3.344*** (.) 0.techtype 0 (-1.06) (0.60) su -0.0306 0.0132 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 153 Table 39: Regression of Crowdfunding in 2016 on Start-up Funding in 2016, Tech Covariate (Source: Author)

Thus, technology companies received 2.558% more of their funding as crowdfunding in 2016, but the effect of being a technology company on outsourcing did not change start-up funding in 2016 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2016.

4.3.2.11 Start-up funding, 2017

The regression of crowdfunding on start-up funding in 2017 was statistically insignificant, F(1, 98) = 0.110, p = .7442. The regression of crowdfunding on start-up funding in 2017 had an effect size of 0.001, indicating that roughly a tenth of 1% of the variation in crowdfunding in 2017 could be explained by variation in start-up funding in 2017. The regression equation for the relationship between crowdfunding and start-up funding in 2017 was as follows:

Crowdfunding %, 2017 = (Start-up funding %, 2017)(-0.007) + 3.861

Thus, every additional percentage a company’s total finding from start-up funding in 2017 reduced crowdfunding received in 2017 by roughly the amount indicated above. The results of adding technology company status to the regression of crowdfunding in 2017 on start-up funding in 2017 are presented in Table 40, which also includes the results of the original regression.

* p<0.05, ** p<0.01, *** p<0.001 t statistics in parentheses N 100 100 (5.70) (3.13) _cons 3.822*** 2.337** (3.71) 1.techtype 2.558*** (.) 0.techtype 0 (0.37) (1.80) su 0.0135 0.0679 cfund cfund (1) (2)

Ph.D. Research - Doctoral Research Programme in Business Page 154 Table 40: Regression of Crowdfunding in 2017 on Start-up Funding in 2017, Tech Covariate (Source: Author)

Thus, technology companies received 3.462% more of their funding as crowdfunding in 2017, but the effect of being a technology company on outsourcing did not change start-up funding in 2017 as a statistically insignificant predictor of crowdfunding as a % of total funding in 2017.