Smart mobility has become increasingly prevalent nowadays, and new travel modes have been emerging in this process. The entry of these new modes not only fosters diversity of transport systems, but also would lead to changes of the characteristics of the transport system itself. This may induce changes in individual travel behaviour. For example, some people would shift to a new mode from other existing modes, while other individuals might be induced to make additional travel which would not be made if the new mode is not available. Some unique underlying characteristics may also drive these changes in travel behaviour. For instance, while some individuals are resistant to change, others may be prone to adopt novel options. This necessitates the investigation of the impact of variety-seeking on how people make choices when new modes are involved. Secondly, while choices are relatively stable for some individuals, others may have stronger tendencies to vary their choices more frequently over choice occasions. Exploration into this characteristic is needed to facilitate better understanding of people's consecutive choices over time. Thirdly, a new mode is usually associated with some new attributes with which individuals may be less familiar. This entails obtaining more knowledge of the role that attributes play in choice making for travel behaviour researchers. This thesis aims at examining mode choice behaviour at an individual level and uncovering travel demand through empirical analyses. Contributions are made to accounting for the three unique underlying characteristics in behaviour as mentioned above, which enhance understanding of the determinants behind mode choices and heterogeneity in preferences in the context of the introduction of new modes. This thesis exclusively uses stated preference (SP) data, as SP data can be used for preference elicitation in hypothetical scenarios, whereas it is much more difficult to collect revealed preference data when new modes have not yet been launched or have only existed in the market for a short period. This research relies on discrete choice modelling (DCM), which is a well-established econometric method for analysing individual choice behaviour and aggregate demand. DCM enables the accommodation of complex heterogeneity in preferences both across individuals and within individuals, and to achieve greater behavioural realism in delineating decision-making. The integrated choice and latent variable (ICLV) model is adopted in different manners, illustrating that the incorporation of latent variables is not confined to investigating the impact of unobserved psychological factors (e.g. variety-seeking) in choices or in class allocation, but could be extended for the purpose of combining stated choice (SC) data with other alternative SP data, e.g. best-worst scaling (BWS) data. The research findings are as expected. The study in the context of HSR (high-speed rail)-air intermodality suggests that people with stronger variety-seeking tendencies are more likely to adopt the new mode introduced. The same finding has been discovered in the second study that applies to the context where a hypothetical air taxi service is involved, which further shows that stronger variety-seeking tendencies can also lead to more unstable preferences across choices. The third study that synthesises traditional SC data and additional BWS data demonstrates the correlation between these different types of collection methods, illustrates that attributes play a relatively consistent - though not one-to-one - role across different methods, and enables the exploration of behavioural information per individual to a greater extent. In general, this thesis contributes to deeper understanding of mode choice behaviour in the context of the introduction of new modes. That is, the investigation into the impact of various level-of-service attributes provides empirical evidence for transport practitioners in willingness-to-pay evaluation. Moreover, the research indicates that while variety-seekers are more likely to be attracted to adopt a new mode at an early stage, they might in the meantime have less consistency in using the new mode. Thus, policy makers could expect an initial uptake of the new mode in the population, but it does not necessarily mean that people would keep on using the new mode over time. Furthermore, this research shows that when confronting the introduction of a new mode characterised with new attributes, an applicable approach for policy makers to improve the understanding of trade-offs and forecast of travel demand would be jointly using alternative preference elicitation methods together with the traditional SC survey.
