Compare methods

	Tourism Product Conjoint Analysis	Destination Choice Experiment
Field	Tourism	Tourism
Family	Regression model	Regression model
Year of origin	1978	2000
Originator	Paul Green & V. Srinivasan (conjoint analysis); applied to tourism products	Jordan Louviere, David Hensher & Joffre Swait; applied to destinations by Twan Huybers
Type	Decompositional part-worth model of multi-attribute travel-product preference	Stated-choice discrete-choice model of destination attribute trade-offs
Seminal source	Green, P. E., & Srinivasan, V. (1978). Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research, 5(2), 103-123.	Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated Choice Methods: Analysis and Applications. Cambridge University Press. ISBN: 9780521788304
Aliases	Travel Package Conjoint Analysis, Tourism Product Profile Analysis, Holiday Package Part-Worth Estimation, Tourism Attribute Decompositional Preference Analysis	Destination Discrete Choice Experiment, Holiday Destination Choice Modelling, Stated-Choice Destination Selection, Destination Attribute Choice Analysis
Related	4	4
Summary	Tourism product conjoint analysis is a decompositional preference-measurement technique that breaks travellers' overall judgments of holiday packages into the separate contributions, or part-worths, of each package attribute. Building on the conjoint framework articulated by Green and Srinivasan (1978), the method presents respondents with whole travel-package profiles, each combining levels of attributes such as price, trip duration, board basis, accommodation class and included activities, and asks them to rate or rank the packages. From these holistic evaluations it statistically recovers how much each attribute level adds to or subtracts from preference, and how important each attribute is overall. Unlike choice-based methods that model selection among alternatives, traditional ratings-based conjoint treats preference as a quantity to be decomposed, making it a natural tool for designing and optimising tourism products and bundles.	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.