摘要：Traveling during off-peak season can mean cheaper flights, cheaper hotels, and the chance to see a destination at a less frenetic time of year. To alleviate the congestion of roads and tourist attractions, a better demand management plan is needed to guide tourists to avoid travel during holidays. This study takes holiday tourists’ peak travel avoidance behavior as the research object, and a Nested Logit (NL) model of travel time and destination joint decisions was established based on Utility Maximization Theory. Model calibration and elastic analysis were carried out using Revealed Preference/Stated Preference (RP/SP) survey data. Results show that tourist attributes such as the number of tourists traveling together, travel companion, duration of the visit, the number of previous visits, tourism motivation, type of tourist attraction, quality grade of tourist attraction, and degree of congestion significantly influence destination decisions. Travel scope, travel duration, age, and other factors significantly influence travel time decisions. The traffic congestion around tourist attractions, holiday admission ticket prices, and non-holiday admission ticket prices significantly influence travel time and destination decisions. Holiday admission ticket price increases have a strong impact on the decision to change the travel destination, while non-holiday admission ticket discounts have a weak impact on travel time decision behavior. The findings of this study offer a theoretical basis for holiday travel management and tourism management. It is practical and significant to reasonably guide tourists to travel during the off-peak season and to understand the travel needs and characteristics of holiday tourists, thus adjusting the distribution of holiday tourist flow.
