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.