Previous research, based on microeconomic demand theory from neoclassical economics, has established a quantitative framework for modeling tourism and hospitality demand. This framework, while insightful, has theoretical deficiencies and practical limitations. These include challenges in estimating dynamic elasticity across the full price range and in modeling disaggregate demand data. The latter is necessary to accurately capture the heterogeneous demand curves that vary across different consumers and contexts. 

This thesis introduces a behavioral economic demand framework to tourism research, which offers several advantages over the neoclassical framework. It broadens the definition of price and demand to include non-monetary costs and valued entities, accounts for dynamic elasticity along the entire demand curve, and constructs complete demand curves to identify optimal pricing points. This framework allows for detailed micro-level analysis, revealing significant variability across different consumers and contexts. It incorporates behavioral heterogeneity by considering individual differences and environmental factors, leading to more accurate predictions of consumer behavior. These insights inform more effective pricing, marketing, and crisis management strategies, addressing many limitations of neoclassical models.

The thesis is structured in manuscript format, encompassing three sequential studies. The empirical studies within this thesis are contextualized specifically in the lodging sector, demonstrating the application of this novel methodology.

The first study offers a critical reflection on current issues in tourism demand modeling, examining both microeconomic demand theory and econometric demand models. It introduces and adapts the behavioral economic demand framework to the tourism context, developing a new conceptual model for disaggregate level tourism demand modeling.

The second study serves as an empirical application of the conceptual model proposed in the first study. It constructs disaggregate demand curves for three hotel types (economy, midscale and upscale) using a behavioral economic demand model. This study reveals the heterogeneity of demand curves across various consumer demographics (including gender, age, income, preference and risk tolerance) and different contexts (such as normal situations versus pandemic situations).

The third study delves into the application of the behavioral economic demand framework in analyzing product interactions. It constructs both alone-price and own-price demand curves for three hotel types (economy, midscale and upscale), as well as cross-price demand curves for sharing accommodation in relation to hotel pricing. This aims to quantify the dual-directional substitutive relationship between hotels and sharing accommodation. Additionally, it explores the varying degrees of substitutability between different customer groups (segmented by gender, age and preference) and travel companion scenarios (traveling alone versus traveling with friends).

This thesis is the first to introduce the behavioral economic demand framework into tourism research. It offers an innovative theoretical framework for understanding and analyzing demand curves, advancing the interpretation of elasticity with a focus on the dynamic nature of elasticity along the demand curve. This approach elevates tourism demand modeling to a more comprehensive and micro-oriented level. Utilizing behavioral economic demand models to construct complete demand curves enables researchers to gain a thorough understanding of the interplay between price, demand and revenue. This level of insight has not been achieved by most econometric modeling studies. Moreover, the complete demand curves serve as a functional tool for analyzing substitutive and complementary relationships between products. The methodology also provides flexibility in collecting and processing disaggregate demand data. This thesis demonstrates that modeling tourism demand at the disaggregate level can reveal many more details about demand that have been overlooked by previous demand modeling practices.

The research findings have multiple implications for managerial decision-making. The complete demand curve indicates the optimal pricing point for maximizing business revenue. It also highlights variations in this optimal pricing point across different consumer groups and consumption scenarios. Furthermore, disaggregate demand curves can aid businesses in developing differentiated sales strategies tailored to various customer segments, as well as in devising appropriate responses to health crises. Additionally, a thorough investigation of the substitution between different hotel types and sharing accommodation can inform effective competition strategies for each type of lodging establishment.