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Table 11 Results from OLS regression

From: Network effects in two-sided markets: why a 50/50 user split is not necessarily revenue optimal

Independent variables

Dependent variable: DailyRevenuePerUser

Model 1

Model 2

Final model 3

User split

 ShareOfWomen

334.2746***

312.4332***

346.8351***

 ShareOfWomenSquared

−468.437***

−428.2298***

−479.6163***

Platform parameters

 PlatformLifetime

 

0.00136***

0.00159***

 Update1

 

0.06716

0.29307***

 Update2

 

0.13269*

−0.27801***

 Update3

 

−0.25703***

−0.17709**

 Update4

 

−0.36184***

−0.14882

 Update5

 

−0.5221***

−0.70081***

 Update6

 

0.29947***

−0.05956

 Update7

 

−0.68634***

−0.53678***

 Update8

 

0.33535**

0.40668**

 Update9

 

0.53921***

0.69158***

 Update10

 

0.21367

0.36379*

Seasonal parameters

 TVevent1

  

0.38896*

 TVevent2

  

−0.07567

 Winter

  

−0.08448

 Spring

  

0.49053***

 Summer

  

0.24884***

Constant

−56.39442***

−58.46802***

−65.29321***

F

162.70

347.90

258.91

Number of observations

1005,275

1005,275

1005,275

R 2

0.0002

0.0034

0.0035

Optimum (highest revenue dep. on share of women)

35.7 %

36.5 %

36.2 %

  1. Dependent variable: DailyRevenuePerUser (in eurocent)
  2. * Significant at the 10 % level
  3. ** Significant at the 5 % level
  4. *** Significant at the 1 % level