方法对比

	Recreation Demand Travel Cost Model	Destination Choice Experiment
领域	Tourism Economics	Tourism
方法族	Regression model	Regression model
起源年份	1966	2000
提出者	Harold Hotelling (concept); Marion Clawson & Jack Knetsch (operationalization)	Jordan Louviere, David Hensher & Joffre Swait; applied to destinations by Twan Huybers
类型	Revealed-preference demand model for recreation site valuation	Stated-choice discrete-choice model of destination attribute trade-offs
开创性文献	Clawson, M., & Knetsch, J. L. (1966). Economics of Outdoor Recreation. Baltimore: Johns Hopkins Press for Resources for the Future. ISBN: 9780801801211	Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated Choice Methods: Analysis and Applications. Cambridge University Press. ISBN: 9780521788304
别名	Recreation Demand Estimation, Zonal Travel Cost Model, Individual Travel Cost Model, Clawson-Knetsch Method	Destination Discrete Choice Experiment, Holiday Destination Choice Modelling, Stated-Choice Destination Selection, Destination Attribute Choice Analysis
相关	3	4
摘要	The recreation demand travel cost model values a recreation site — a national park, beach, lake, or heritage attraction — by exploiting the fact that visitors reveal how much the experience is worth to them through the cost they incur to get there. Although most such sites charge little or no entry fee, people from farther away must spend more on distance, time, and expenses, and they visit less often as a result. By relating visit frequency to travel cost across visitors or origin zones, the analyst traces out a demand curve for the site and recovers the consumer surplus that visitors enjoy — a money measure of the site's recreational use value. The approach was made operational by Marion Clawson and Jack Knetsch in Economics of Outdoor Recreation (1966), building on Harold Hotelling's earlier insight, and it remains the workhorse revealed-preference method for nonmarket recreation valuation.	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.