The application of random regret minimization on commuter's mode choice behaviour: Model-Fit comparisons with Rum-Modelling (case: comparison between Matsuyama and Yogyakarta)

Modelling the mode choice behaviours of travellers is a key to design effective transport management policies, particularly in shifting travellers to public transport. Abundant studies have analysed the impact of level of services on mode choice preferences through its Random Utility Maximization (RUM), but the possibility of minimalize the regret have been overlooked. This paper will discusses the possibility of using generalised Random Regret Minimization (G-RRM) model on choosing transportation modes. The study is performed in two cities for comparison: Jogjakarta in Indonesia and Matsuyama in Japan. A stated preference (SP) survey isconducted, in which respondents choose Bike or Bus under hypothetical situations. As the result of RUM revealed that travellers prefer the transportation mode with more ensuring level of service. While an empirical proof of concept, the G-RRM model is estimated on a stated mode choice dataset, and its outcomes are compared with RUM and RRM counterparts