Setting cost levels in Ngene

[mattw]

Hello, thank you for offering this forum. It has been some time since I have used Ngene and on behalf of my study team I wanted to post a question on a national survey we are working on. There are 3 attributes besides cost, the 1st is a negative on utility with 3 levels, the 2nd is a positive on utility also with 3 levels, the 3rd is also positive and is binary. From focus group pretests we have set priors on these so that their influence on utility is approximately equal. We have also set cost levels such that the middle cost level would approximately balance the maximum improvement offered. We borrowed some syntax from the stormwater demo project in Ngene.

We have 4 questions related to this design:
1) Is there any guidance on how to set cost levels other than offering a decent spread above and below the level that would exactly offset a "maximum" policy change? I have heard the lowest cost should be attractive to most respondents and the highest cost should deter almost everyone, but wondering if there are other factors practitioners use, including deciding on the total number of cost levels to offer. More levels seems like it would be easier to avoid dominance problems.
2) The below script does not run. However if I change "tax[24,56..] below to "tax[0,56,... ], in other words just replace 24 with 0, it does run. However I do not plan to offer policyA at zero cost. So I am wondering if there is another problem with my script that I am not understanding, please advise if anyone recognizes a problem here. I am trying to get the script to run without the need to add a 0 cost option for PolicyA.
3) The choice experiment is fairly sparse, and I am wondering if 32 runs is overly high (8 blocks 4 questions each). More runs means more statistical variability but also more dominance problems, are there rules of thumb here?
4) I was interested in the "s" efficiency option because it seemed it would have a more direct interpretation than "d" efficiency, such as to sample size but the "s" measure of 0.95, I am not sure if it has a direct interpretation.

Thanks much for any advice! -Matt

design
;alts = (policyA, sq)
;rows = 32
;block = 8
;eff = (mnl,s)
;alg = mfedorov(candidates = 68)
;require:
sq.HAB_area = 100, sq.OE = 0, sq.HAB_info = 0, sq.tax = 0
;model:
U(policyA) = b_HAB_area[-0.2] * HAB_area[100,50,0] ? sqmi of HAB area
+ b_OE[0.1] * OE[0,50,100] ? sqmi of high qual habitat
+ b_HAB_info[10] * HAB_info[0,1] ? 0 = low (base), 1 = high
+ b_tax[-0.1] * tax[24,56,112,173,240] ? 0, 68, 127, 173, 246 annual tax ($)
/
U(sq) = b_sq[0]
+ b_HAB_area * HAB_area
+ b_OE * OE
+ b_HAB_info * HAB_info
+ b_tax * tax
$