How to compute willingness to pay based on different types of surveys

Question

Good evening,

I am trying to design a survey using JMP, and my objective is then to use JMP to compute the customers' Willingness to pay based on the answers.

The aim is to evaluate the price customers would be willing to pay for different services. For example, let's say that the customers want to rent a house for a few days, the final objective is to know how much more they would be willing to pay to add Wi-Fi (with different speeds), laundry service (with different options), ...

After reading a few papers, I came up with different types of questions. However, I am not sure of how to compute Willingness to pay with the answers.

Examples of types of questions : (the prices would change with the respondents, being "attributes" for the services)

1) How likely would you be to purchase high-speed Wi-Fi at $7/day ?

- Very likely - Likely - Neutral - Not very likely - Not likely at all

Then I could attribute a score (1-5) to each answer, and try to compute the utility of the service based on that ? Do you have an idea of how I could do that ?

2) Would you rather purchase...

- Low-speed Wi-Fi at $3/day - High-speed Wi-Fi at $7/day - None ($0)

I think it is the closest to the "Choice surveys" offered by JMP. It allows to compute WTP using the Choice analysis, and choosing the "None" answer as a baseline.

3) You just rented a house for a day. You have now a budget of $25. Which items would you spend it on ? (multi-choice)

- Laundry service ($15) - High speed Wi-Fi ($8) - ... - Nothing ($0)

This should also allow to compute Willingness to pay, right ? How could I do that with JMP ?

My other ideas feel less relevant.

I feel that most of my questions do not really fit in the cases provided by JMP. What do you think ?

Thank you for your time,

Have a nice day !

AB

dale_lehman · Answer

I don't see this as a JMP question (although someone else might have something to suggest).  To get price elasticity estimates, you will need a variety of prices and the number of respondents that are, or are not, willing to pay those prices.  As we have discussed, the issue really surround eliminating bias from the responses.  That is difficult enough, but I am more concerned about the difficulty of eliciting accurate responses - what incentive do people have to respond accurately (how do they even know what is accurate for themselves)?  The only suggestion I have is to make sure you pretest whatever survey design you come up with.  Perhaps even use a focus group after an initial survey with a small group of respondents.

akb3 · Answer

Hi dale_lehman,

Thank you for taking the time to answer my question, and sorry for the late reply. I am mostly concerned about the treatment of data afterwards, using JMP or not (since does not seem to be really adapted to the question). I have read a lot of articles about the shape of questions, and how to avoid anchoring and that kind of things. But before starting to ask the questions, I would like to have a plan to analyze data, and be sure that with the answers to my survey I can come up with WTP and price elasticity, basically. Do you have an idea of a process in JMP that would allow me to do it for the sample of questions I posted ?

Thank you,

AB

dale_lehman · Answer

I have not kept up with the literature, so I really recommend doing a thorough literature search.  Environmental economists have probably done the most sophisticated survey modeling and testing in this area.  From what I do recall, if you are going to ask questions along the lines of "would you be willing to pay $7 to get....?" you need t randomize the amount of money - and then you need to obtain a sufficient sample size to make reasonable inferences from.  Another approach is to pose a series of binary choices;  "would you prefer bundle X (e.g., $x + wifi vs. $y without wifi) or bundle Y?"  I've been critical of those surveys in the past - they remind me of going to the optometrist and constantly being asked which view is clearer - and often not being able to tell.  Notably, in that case, the choices are presented repeatedly to protect against mistakes - something that owuld be hard to do in a survey.  One other approach I am aware of is to present a WTP scale with a wide range and ask people to place a mark that best represents their max WTP.  The scale may produce anchoring, so you should at least vary the end points of the scale a bit to see if it influences the responses.