TABLE 3.
Results Of Regression Analysis. Citation Per Patent As The
Dependent Variable. Unstandardized Regression Coefficients
Reported; Standard Errors Shown In Parentheses. MODEL
| 1 | 2 | 3 | |
| Intercep | 2044.4* | 2494.06 | 2775.8 |
| t | * | ** | ** |
| (340.9) | (375.8) | (447.8) | |
| R&D age | -0.015 | ||
| (0.02) | |||
| N R&D | -0.69** | -0.75* | |
| (0.26) | (0.30) | ||
| Ln rd | -0.083 | 0.95 | 1.36 |
| (0.54) | (0.60) | (0.68) | |
| Founding | -1.03** | -1.26** | - |
| 1.40** | |||
| (0.18) | (0.19) | (0.23) | |
| R2 | 0.448 | 0.533 | 0.559 |
| Adj. R2 | 0.51 | ||
| # p < 0.1 | * p < 0.05, | ** p < 0.01 | (two tailed tests) |
Table 4 provides tests for the hypotheses 3 and 4. These hypotheses have startup growth as the dependent variable, and propose a positive relationship between collaboration and startup growth. Controlling for R&D expenditures, we find that the age of technology partners is positively related with startup growth (model 3). Hypothesis 4 is thus supported. However, the number of R&D partners (hypothesis 4) fails to remain significant in model 6, but is still in the right direction (positive).
Overall, the results provide moderate and in some cases strong support for the hypothesis of the dual role of technological collaboration. Whereas the number of partners, and their average industry tenure is positively related with startup growth and total innovative output, the effect is negative on radical innovation outcomes.
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