Comparative mode choice analysis of university staff commuting travel preferences

Abstract

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.

McDm Approaches for Evaluating Urban and Public Transportation Systems: A Short Review of Recent Studies

“…Regarding a similar problem,Yaliniz et al (2022) presented an approach based on AHP and ANP to deal with a P&R evaluation problem. There are some other studies used AHP in hybrid approaches including AHP-GIS(Saplıoğlu, Aydın 2018), AHP-TOPSIS(Öztürk 2021), AHP-WASPAS(Aydin et al 2022;Tumsekcali et al 2021), AHP-BWM(Moslem et al 2022), BWM-AHP-MOORA(Çelikbilek et al 2022) and AHP-PROMETHEE (Oubahman, Duleba 2022).…”