| Under the background of information globalization and the rapid development of tourism,the spatial and temporal distribution of tourism flow as well as its forecast have become a hot spot in the field of tourism.In recent years,the domestic tourism industry has developed more rapidly,which has brought a continuous growth of passenger traffic in most of domestic scenic spots.The tourism flow of partial tourist attractions even exceeds their maximum bearing capacity during some legal holidays.Based on this situation,it's important to research out a most scientific method to precisely predict the amount of tourists in scenic spots so that we can avoid the destruction of the scenic environment.Nanjing is one of the “National Smart Traveling Cities Alliance” that was established in May 2011,and it is also one of the cities as the first batch of “National Smart Traveling Pilot Cities”,which was announced by the National Tourism Administration.In 2015,Nanjing was awarded the “Smart Travel City of the Year” award at the China Tourism Conference,and the Nanjing Tourism Commission was honored as the Provincial “Tourism + Internet”demonstration unit.In 2016,Nanjing won the title of “Excellent Internet + Tourism City” in China.The development of Nanjing's smart tourism is at the forefront of the province and even the country.Therefore,this article takes Nanjing as an example for research.Based on the Nanjing smart tourism big data monitoring platform,this article studies the tourism flow of Nanjing from two perspectives of time and space.In terms of temporal diffusion,the distribution patterns of tourist flows are studied on the five time scales which are “Year”,“Season”,“Month”,“Week”,and “Day”;and in terms of spatial diffusion,the source of tourists and the best toutist routes are studied by taking the preferred routes as a starting point,and then the relevant conclusions can provide targeted guidance of the optimization of tourism spatial structure in the same case area,tourism marketing,and line design.On the basis of the foregoing,this article takes the overall tourists group in Nanjing as the research object,using the Baidu index of related keywords and the Granger causality test method to analyze the actual tourist quantity in Nanjing each day and it's corresponding Baidu index,and then establishes an autoregressive moving average model to predict tourist quantity inNanjing each day.Based on this model,opportunely and accurately management decisions for Nanjing scenic spots can be provided,especially during legal holidays.Based on the above research,this article draws the following conclusion: The yearly temporal distribution of Nanjing's travel flow generally showed the characteristics of “double peaks and multiple peaks”;and the seasonal index showed a stable dynamic change;and the monthly changes were obvious,showing a series of small Sawtooth;and distinctive "warm-tail" feature can be seen during the week;and daily distribution was spoon mode.When speaking of spatial distribution,the farther source area is,the less tourists there are.The concentration level in scenic spots is negatively correlated with the length of holidays,and contrarily with the range of attractions of source area.Tourist quantity can leap during traditional and characteristic festivals.The popular scenic spots is still the main force constituting the tourist route,with the urban area as the core,reaching the Southeastern region as a long and thin “inverted triangle”.The tourism resource in the North is scarce so that the tourist routes are basically not expanding to the north.In terms of forecasting,this article constructed a model which can forecast the daily total tourist volume in Nanjing,especially during holidays,in order to avoid a blowout.It is hoped that scholars can more fully consider the influencing factors of the spatial and temporal proliferation of tourism flows and establish more accurate forecast models to obtain more accurate forecast results. |
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