I've conducted a CBC Analysis and implemented a conditional pricing table. I had different prices "low", "middle" and "high" for the "private label" and "brand", so overall 6 different prices shown to the respondents.

Now, I did a Logit and HB estimation and chose to change the attribute coding for price to linear coding and took the average prices for each attribute level (low, middle, high) as value.

I know that I must take into account, that the "brand" was, on average, shown with a higher price. So, since I got a negative brand utility, I can say that the private label was preferred and the respondent was, on average, not willing to pay the higher price for the brand. Am I correct?

Additionally, I want to calculate the Willingness-to-pay for my attributes. I took the simplest way and calculated: -1*(attribute coefficient/price coefficient) (I know that there are better (more correct) ways to calculate WTP, but for my purposes, this way is sufficient). When I do that for the brand coefficient, I get a negative WTP for brand (since the brand utility is negative too).

Since the brand product was on average 0.13$ more expensive than the private lable, should I add that amount to my WTP?

So, for example, my average WTP for brand is -0.05$. I would normally say that the average respondent would only buy the brand if it's 0.05$ cheaper than the private label. But since the brand is 0.13$ more expensive, can I take that into account and say the "adjusted" WTP for the brand product is: -0.05$ + 0.13$ = 0.08$ ?

Thank you very much for your help!

So if i have brand utility of -0.15 and private label utility of 0.15, I take the difference which is 0.30 and divide it by the price utility (-5.25), which is linear coded, to get a WTP in $.

When I do that I get a negative $ value for the brand (-0.057$). So how do I account for the higher brand price (on average 0.13$ higher), which was shown to the respondent with the conditional pricing?