Dr Gabrielle Lin

Demand analysis is a core foundation in economics, which underlies all the decisions of both private and public economic agents. As a human- and business-intensive industry, tourism encompasses tremendous economic activities, whose demand plays a crucial role in determining corporate profitability and informing government taxation and welfare provision and exerts comprehensive impacts on an economy. Previous research rests on microeconomic demand theory in neoclassical economics to establish the quantitative framework for tourism demand analysis, where theoretical deficiencies and practical limitations are observed especially in terms of estimating dynamic elasticity over the full price range and modeling disaggregate demand data to capture the heterogeneity of consumption behavior across individuals and consumption contexts.

From a behavioral economics perspective, this thesis aims to model consumer demand at the disaggregate level to explore the effects of individual differences and contextual variables on the demand for a particular tourism product by introducing the behavioral economic demand framework to tourism research and proposing more advanced behavioral economic demand models to improve the original framework. The overall research design contains three sequential studies to apply the behavioral economic demand models into the estimation of tourism demand with the complete shape of the demand curve being depicted, to incorporate substitute price into the demand models, and to integrate both monetary cost and time cost into the demand models. The effect of contextual variables will be examined by framing different consumption scenarios in the experimental research, while the effect of individual differences will be investigated by grouping the demand data of individual participants according to various socio-demographic variables.

This thesis will contribute to the theoretical research on economic demand analysis by filling in the gaps in current tourism demand estimation regarding the parameterization of the dynamics of elasticity along the demand curve and the remarkably flexible regression method to estimate demand at the disaggregate level as well as by improving the existing univariate behavioral economic demand models into multivariate variants to render them more comprehensive and adaptive in delineating the consumption of different products. The research findings will also provide significant practical implications from the managerial perspective, especially in terms of pricing and marketing strategies which are informed by the complete demand curve with optimal pricing point and the comparisons of tourism demand across different consumers in different contexts.