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- W4313893399 abstract "This paper investigates the future U.S. demand for streamlined space tourism by showing the missions and factors impacting traveler choices with machine learning. Space tourism is growing and is expected to become available to the masses soon. While private companies need to better understand the demand for space tourism to customize their services, transportation agencies require guidance to support fund management related to commercial space exploration. This work analyzes the three most prominent missions for streamlined space tourism (i.e., suborbital, orbital, and space tourism around the moon) and their selection determinants (i.e., price, safety, training, number of passengers, take-off locations, among other decision-maker factors). A stated preference experiment is constructed to collect data that is analyzed using machine learning. Results provide valuable insights into the mixed opinions of Americans with respect to space tourism, their mission preferences, and risk considerations." @default.
- W4313893399 created "2023-01-10" @default.
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- W4313893399 date "2023-03-01" @default.
- W4313893399 modified "2023-10-16" @default.
- W4313893399 title "Missions and factors determining the demand for affordable mass space tourism in the United States: A machine learning approach" @default.
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- W4313893399 doi "https://doi.org/10.1016/j.actaastro.2023.01.006" @default.
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