For this paper, we have varied the parameter of the model as follows and computed ten instances of each.

1. Bundle discount from 0% to 50% (in increments of 10).

1. Mean WTP pricing or 100 random iterations.

1. Normal and lognormal distribution of customer WTP.

1. Correlation between basic WTP for the two products of 0, ±0.2, ±0.5 or ±0.8.

1. Mean basic WTP for the two products was either 10 for both of them or 5 for the first and 15 for the second.

1. Standard deviation of the mean basic WTP was always 2 for the first product and either 2 or 4 for the second product.

In total, this produced 6 720 solutions of the model and each for 1000 customers. This sample data allows us to look at a number of interesting questions.

df.query('Lognormal == 1', inplace = False)['TotalRevenue'].describe()

df = pd.read_excel('20190718_outputs.xlsx')

df.query('Lognormal == 1', inplace = False)['TotalRevenue'].describe()