Use indirectly related RP data in SP model
Posted: 20 Mar 2024, 15:50
Dear Prof. Hess and Team,
I have conducted a Stated Choice Experiment for the willigness-to-subscribe / willigness-to-pay for a subscription service.
The choice was between 3 plans with different characteristics and prices or the opt-out option.
I have estimated a nested-logit model showing a way too high willigness-to-pay. I would strongly assume this is due to the hypothetical bias.
As I already imagined this might happen, I have included an second experiment in the survey to get (kind of) revealed preference data. In particular, the participants were asked to select a voucher for the subscription service or a lower cash amount as a reward for taking the survey. (With a 10% chance of actually getting this reward.)
The first choice was beween a 30$ voucher and 1$ cash, which was increased in 5$ increments until cash was selected or 30$ in cash was reached.
A substential part of the sample actually selected very low cash amounts despite previously stating their willigness to subscribe for a rather high price.
I am now thinking if there is a sensible way to include this data into my SP model to correct the willingness to pay.
However, in contrast to typical approaches of combining RP and SP data (e.g. Buckell & Hess, 2019) I cannot directly use the cash/voucher price attribute, as it has been a different setting.
Do you have any ideas what might be suitable direction or do you have a paper in mind that could be helpful? My current idea would go into the direction of scaling the price parameter in the SP model, but I am a bit stuck on how to do this.
I have conducted a Stated Choice Experiment for the willigness-to-subscribe / willigness-to-pay for a subscription service.
The choice was between 3 plans with different characteristics and prices or the opt-out option.
I have estimated a nested-logit model showing a way too high willigness-to-pay. I would strongly assume this is due to the hypothetical bias.
As I already imagined this might happen, I have included an second experiment in the survey to get (kind of) revealed preference data. In particular, the participants were asked to select a voucher for the subscription service or a lower cash amount as a reward for taking the survey. (With a 10% chance of actually getting this reward.)
The first choice was beween a 30$ voucher and 1$ cash, which was increased in 5$ increments until cash was selected or 30$ in cash was reached.
A substential part of the sample actually selected very low cash amounts despite previously stating their willigness to subscribe for a rather high price.
I am now thinking if there is a sensible way to include this data into my SP model to correct the willingness to pay.
However, in contrast to typical approaches of combining RP and SP data (e.g. Buckell & Hess, 2019) I cannot directly use the cash/voucher price attribute, as it has been a different setting.
Do you have any ideas what might be suitable direction or do you have a paper in mind that could be helpful? My current idea would go into the direction of scaling the price parameter in the SP model, but I am a bit stuck on how to do this.