This book brings together frontier research in transportation and travel behaviour on the formulation and estimation of models of bounded rationality to analyse and predict various facets underlying daily activity-travel behaviour. Key behavioural principles and mechanisms relate to simplifying decision complexity by ignoring particular attributes, developing context and task-dependent mental representations, deriving decision heuristics, adding emotional aspects to cognitive assessments of choice options, regret-minimization, semi-compensatory decision rules based on mental effort and risk perception, learning and adaptation, satisfying decision rules and prospect theoretic approaches. The book is important reading for transportation researchers and professionals who are interested in the latest developments in transport demand forecasting. It offers historical reviews of the development of models of bounded rationality in this field of research, and a variety of new concepts and modelling approaches that should be inspirational to both new and experienced researchers in this field of research and application.

As mobile technologies become ever more pervasive in modern society, users find increasingly innovative methods to take advantage of the newest developments and mobile devices. Data mining, in particular, has seen a vast shift as a result of wireless technologies. Mobile Technologies for Active-Travel Data Collection and Analysis concentrates on one particular and fast-growing application of mobile technologies: data acquisition for the tourism industry. This critical reference source will provide travel agents, visitors, and hosts with the most advanced data mining methods, empirical research findings, and computational analysis techniques necessary to compete effectively in the global tourism industry.