Experimental Design with Constraints
Posted: Thu Feb 19, 2026 9:44 pm
In some stated choice experiments, certain alternatives may systematically outperform others on some attributes (e.g., travel time reliability, travel time), while being worse on others (e.g., cost, frequency). For example, a bullet train service may always be faster and more reliable than a conventional train, but also more expensive.
In this case, is it better to use constraints in experimental design or select attribute levels in a way that one alternative has always superior levels in one attribute and inferior levels of another attribute compared to a reference alternative?
For instance, one possible experimental design involves a choice between the current option and an alternative that is cheaper but has equal or worse levels of service:
Another experimental design involves the current option and an alternative that is more expensive but offers better levels of service:
Alternatively, should these two cases be combined into a single experiment with three alternatives: the current option, a premium alternative (higher cost but better service), and a discount alternative (lower cost but inferior service)? From a design and modeling perspective, which approach is preferable: separate experiments reflecting asymmetric trade-offs, or a single combined experiment that presents both types of alternatives simultaneously?
In this case, is it better to use constraints in experimental design or select attribute levels in a way that one alternative has always superior levels in one attribute and inferior levels of another attribute compared to a reference alternative?
For instance, one possible experimental design involves a choice between the current option and an alternative that is cheaper but has equal or worse levels of service:
Code: Select all
Design
? This game involves choice between the current option and an alternative that is Cheaper but with lower or equal level-of-service in the rest of the attributes
? Cost is in Euros per shipment
? Transit time is in days
? Magnitude of delay in days
? Frequency is in number of weekly departures
;alts = alt1, alt2
;rows = 12
;eff = (mnl,d)
;model:
U(alt1) = b_cost[-0.00347] * cost.ref[700] + b_time[-0.357] * time.ref[4] + b_delay[-0.107] * delay.ref[2] + b_freq[0.255] * frequency.ref[3]/
U(alt2) = b_cost * cost.piv[-25%,-15%,-10%] + b_time * time.piv[1,2,3] + b_delay * delay.piv[-2%,-5%,-10%] + b_freq * frequency.piv[-2,-1,0]
$Code: Select all
Design
? This game involves choice between the current option and an alternative that involves a higher cost but offers better conditions for the other attributes considered
? Transit time is in days
? Magnitude of delay in days
? Frequency is in number of weekly departures
;alts = alt1, alt2
;rows = 12
;eff = (mnl,d)
;model:
U(alt1) = b_cost[-0.00347] * cost.ref[700] + b_time[-0.357] * time.ref[4] + b_delay[-0.107] * delay.ref[2] + b_freq[0.255] * frequency.ref[3]/
U(alt2) = b_cost * cost.piv[5%,10%,20%] + b_time * time.piv[-2,-1,0] + b_delay * delay.piv[0%,5%,7%] + b_freq * frequency.piv[-1,0,1]
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