方法对比

	Destination Competitiveness Index	Destination Choice Experiment
领域	Tourism Recreation	Tourism
方法族	MCDM	Regression model
起源年份	2003	2000
提出者	J. R. Brent Ritchie & Geoffrey I. Crouch	Jordan Louviere, David Hensher & Joffre Swait; applied to destinations by Twan Huybers
类型	Multi-attribute composite index of destination competitiveness	Stated-choice discrete-choice model of destination attribute trade-offs
开创性文献	Ritchie, J. R. B., & Crouch, G. I. (2003). The Competitive Destination: A Sustainable Tourism Perspective. Wallingford, UK: CABI Publishing. ISBN: 9780851996646	Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated Choice Methods: Analysis and Applications. Cambridge University Press. ISBN: 9780521788304
别名	Ritchie-Crouch Competitiveness Model, Tourism Destination Competitiveness Index, Crouch-Ritchie Competitiveness Framework	Destination Discrete Choice Experiment, Holiday Destination Choice Modelling, Stated-Choice Destination Selection, Destination Attribute Choice Analysis
相关	3	4
摘要	The Destination Competitiveness Index operationalizes the Ritchie-Crouch model, the most influential conceptual framework for understanding why some tourism destinations outperform others. Crouch and Ritchie argued in 1999, and elaborated in their 2003 book The Competitive Destination, that a destination's ability to attract visitors and deliver lasting prosperity depends on a structured set of determinants: core resources and attractors, supporting factors and resources, destination management, destination policy and planning, and qualifying and amplifying determinants that set the ceiling on what is achievable. The index turns this framework into a multi-attribute composite: each destination is scored on attributes within each determinant, the attributes are weighted by importance, and the weighted scores are aggregated into an overall competitiveness score that can be benchmarked against rival destinations to reveal where advantage is won or lost.	A destination choice experiment is a stated-preference technique that asks travellers to choose among experimentally designed hypothetical destinations, each described by a bundle of attributes such as price, travel distance, climate, the type and quality of attractions, and crowding. Grounded in random-utility theory and the stated-choice toolkit codified by Louviere, Hensher and Swait (2000), the method estimates a discrete-choice model that recovers the implicit weight travellers place on each attribute, the trade-offs they are willing to make, and the marginal willingness to pay for improvements. Huybers (2003) applied this framework to short-break holiday destination choices, showing how designed choice tasks reveal which destination features actually drive selection. Because the attributes are manipulated by design rather than merely observed, the experiment isolates the causal effect of each feature on choice in a way that revealed-preference travel data cannot.