Maria Kamargianni

Investigating factors affecting consumers’ electric vehicle (EV) purchasing behaviour. By defining consumers’ preference factors, targeted corporate marketing and government policies can be developed to accelerate diffusion of EV.

Quantifying factors affecting mode choice behaviour in developing countries and explore the ways and the potentials of promoting bike sharing and car sharing schemes via examining the past, the present and future mobility opportunities

Mobility as a Service is a new concept for people’s mobility. The aim of this project is to investigate and model consumers demand for purchasing and using MaaS, as well as its potential impact on private vehicle ownership.

Taking advantage of open data and APIs, a methodology is developed to incorporate transport operators’ APIs and other open data sources into smartphone-based travel survey tools..

Developing methodologies for deriving individuals travel patterns via big data. The patterns are analysed based on several socio-economic characteristics, built environment characteristics/urban form, transport mode used, time of the day, happiness, weather conditions etc., while scenarios are constructed for the implications of mobility patterns on energy consumption.

A novel analysis framework for the spatial aspects of car travel, measured by vehicle miles travelled (VMT), extended to include a variable decomposition approach that captures potential asymmetries and hysteresis in a spatial setting.