This week's topic is Customer Choice Logit Models. The table below comes from a modified version of the Office Star data

Here is some information about the context:

In December 2018, OfficeStar conducts a survey to understand how their people in their target segment perceive their expensiveness, convenience, service quality, and variety of choice. Then, they track whether or not a respondent of that survey purchased anything from the OfficeStar stores in next 12 months (i.e., the entire year of 2019).

In January 2020, they bring their their dataset to you and ask you help them run a logit analysis.

The variables in this dataset are:

1) Choice (0/1): This variable is coded as 1 if a survey respondent purchased anything from the OfficeStar in 2019

2) Expensiveness: How a survey respondent rated the perceived expensiveness of OfficeStar (7-point scale from 1: not expensive at all to 7: very expensive)

3) Convenience: How a survey respondent rated the perceived convenience of OfficeStar (7-point scale from 1: not convenient at all to 7: very convenient)

4) Service quality: How a survey respondent rated the perceived service quality of OfficeStar (7-point scale from 1: very low service quality to 7: very high service quality)

5) Variety of Choice: How a survey respondent rated the perceived variety of choice in OfficeStar stores (7-point scale from 1: very low variety of choice to 7: very high variety of choice)

Using Enginius, you ran a logit model and find the results below.

How would you interpret these results?:

Parameters Standard deviations P-values Intercept -0.9346 1.011 0.3551 expensiveness -0.5622 0.286 0.0493 convenience 0.0677 0.261 0.7953 service quality 0.0316 0.310 0.9190 'variety of choice 0.2927 0.180 0.1044