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The Tourism Flow Space-Time Distribution’s Characteristics And Regulation Guilin As An Example

Posted on:2017-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiuFull Text:PDF
GTID:2309330485999877Subject:Tourism Management
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Tourism time distribution flow mainly is shown in its tourism seasonality, and tourist flow space and time distribution overlay, intensifying the seasonal tourism. Irregular time distribution prompts the tourism peak seasons and off-seasons, tourism spatial distribution will have the destinations divided into "hot spots" and "cold spots" areas. In hot season, tourist flow increases into most "hot spots", off-season tourist flow decreases and "cold spots" decrease more, which directly causes the hot spots more popular, and the off-season spot less popular, and restricts the development of the tourism industry.In this paper, we introduces Guilin tourism time-distribution flow made a quantitative study, with the help of X-12-ARIMA model, it concludes that the existence and stability of the tourism flow time, based on the research of the seasonal factors, and finds that the Guilin tourism time-distribution flow inhomogeneity is very significant, mainly the April-May month each year, and July-October period is the tourist season, and the other months are off-season. Next we are based on social network theory, using Ucinet software and the spatial distribution characteristics of Guilin tourism flow made a quantitative study, whose tourist flow is significant uneven, and performance as a certain space accumulation characteristic. This kind of tourism flow space accumulation and uneven distribution of time, exacerbate the seasonal tourism. In order to further reveal the effects of seasonality, through takes empirical researches on perception of tourism stakeholders for tourism flow space-time distribution inhomogeneity influences. Respectively for residents and visitors, it has found that seasonal tourism flow has had effects on social, economic, social, cultural, social services, such as ecological environment, and the capacity of the scenic spot, which has both positive effects, and negative ones.At last, based on the above section of tourist space-time flow distribution inhomogeneity, combining with tourism stakeholders perception analysis on tourism flow space-time distribution, and from the perspectives of tourist demand, tourism supply process and reengineering process, puts forward control countermeasures. Chapter 7 relates to research conclusion and research prospects.
Keywords/Search Tags:tourism flow space-time distribution, X-12-ARIMA model, social network theory, Tourism seasonality
PDF Full Text Request
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