基于网络游记的旅游流时空特征分析

Analysis of the spatio-temporal characteristics of tourism flows based on online travelogues

网络游记蕴含了丰富的游客出行信息,为旅游流研究提供了新的视角。本文采集2016~2020年马蜂窝游记数据,从旅游流量、日均出行距离、目的地的空间分布视角,分析旅游流时空变化规律。结果发现:(1)旅游流存在节假日、休息日效应,节假日、休息日的流量普遍高于工作日,4到10月为旅游旺季,11月至次年3月为旅游淡季,法定节假日假期均出现旅游流高峰;季度尺度是导致旅游流波动的主导因素。(2)出行距离也存在休息日效应,休息日的日均出行距离普遍低于工作日;随着出行距离增加,旅游流量逐渐衰减,衰减过程为幂律性衰减。(3)目的地分布存在季节性变化规律,旅游淡季以经济发展水平较高或旅游资源丰富的城市为主,在旅游旺季旅游流逐渐向其他区域扩散。

Online travelogues contain a wealth of information on tourists′travel,providing a new perspective for tourism flow research.This paper collects data from 2016~2020 from Ma Hive travelogues and analyzes the spatial and temporal change patterns of tourism flows from the perspective of tourism flows,average daily travel distance and spatial distribution of destinations.The results found that:(1)There is a holiday and rest day effect on travel flows,with flows generally higher on holidays and rest days than on weekdays.Meanwhile,the peak travel season is from April to October,and the low season from November to next March,with peaks in travel flows on all statutory holidays and vacations;the quarterly scale is the dominant factor leading to fluctuations in travel flows.(2)Travel distance also has a rest day effect,with the average daily travel distance on rest days generally lower than that on weekdays;as travel distance increases,tourism flows gradually decay,with the decay process being a power-law decay.(3)There is a seasonal pattern of change in the distribution of destinations,dominated by cities with higher levels of economic development or rich tourism resources in the low season,and tourism flows gradually spreading to other regions in the high season.