  The design and pricing of services are two of the most important decisions
faced by any intermodal transport operator. The key success factor lies in the
ability of meeting the needs of the shippers. Therefore, making full use of the
available information about the demand helps to come up with good design and
pricing decisions. With this in mind, we propose a Choice-Driven approach,
incorporating advanced choice models directly into a Service Network Design and
Pricing problem. We evaluate this approach considering three different mode
choice models: one deterministic with 4 attributes (cost, time, frequency and
accessibility); and two stochastic also accounting for unobserved attributes
and shippers heterogeneity respectively. To reduce the computational time for
the stochastic instances, we propose a predetermination heuristic. These models
are compared to a benchmark, where shippers are solely cost-minimizers. Results
show that the operator profits can be significantly improved, even with the
deterministic version. The two stochastic versions further increase the
realized profits, but considering heterogeneity allows a better estimation of
the demand.
