This paper extends tour-based mode choice model, which mainly includes individual trip level interactions, to include
linked travel modes of consecutive trips of an individual. Travel modes of consecutive trip made by an individual in a
household have strong dependency or co-relation because individuals try to maintain their travel modes or use a few
combinations of modes for current and subsequent trips. Traditionally, tour based mode choice models involved nested
logit models derived from expert knowledge. There are limitations associated with this approach. Logit models assumes
i) specific model structure (linear utility model) in advance; and, ii) it holds across an entire historical observations.
These assumptions about the predefined model may be representative of reality, however these rules or heuristics
for tour based mode choice should ideally be derived from the survey data rather than based on expert knowledge/
judgment. Therefore, in this paper, we propose a novel data-driven methodology to address the issues identified in tour
based mode choice. The proposed methodology is tested using the Household Travel Survey (HTS) data of Sydney
metropolitan area and its performances are compared with the state-of-the-art approaches in this area
