Surveying citizen preferences on transportation modes when commuting is a major issue
in urban transport planning. Most of the current methods approach the problem through
the attributes of choices thus forecasting the demand indirectly. This paper aims
to analyze a survey of commuting students and university staff by two direct preference
models: the Analytic Hierarchy Process and the Best-Worst Method. Both techniques
are based on pairwise comparisons; consequently, the commuting transport alternatives
can be directly compared with each other, and the results are comparable, too. However,
the two methods differ in the number and the nature of comparisons and in the consistency
check, thus they can be regarded as competitors. A real-world case study on commuting
student groups provides a better understanding of the proposed methodology. As a result,
it can be stated that despite their low utilization in the transportation field, both
the Analytic Hierarchy Process and the Best-Worst Method are applicable to mode choice
preference surveys, and they produce comprehensive final outcomes. Therefore, the
well-known tools of mode choice can be extended by Multi-Criteria-Decision-Making
techniques to increase the efficiency of transport demand prediction. The extension
is beneficial to avoid the bias of other methods in converting attribute evaluations
to real mode choice decision, as both models, especially the Best-Worst approach,
requires less cost and time than the mainstream techniques.
