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Study On The Differences Of Time And Space And The Influencing Factors Of Tourism Poverty Alleviation Efficiency In The Three Gorges Reservoir Area

Posted on:2020-05-18Degree:MasterType:Thesis
Country:ChinaCandidate:H YangFull Text:PDF
GTID:2439330572484469Subject:Tourism Management
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As a high value-added "smoke-free industry",the tourism industry has achieved fruitful results in numerous tourism poverty alleviation practice bases at home and abroad.Based on the special natural geographical environment and economic development level of the Three Gorges reservoir area,the practice of poverty alleviation in tourism has achieved initial results in the reservoir area,but its research on poverty alleviation efficiency needs to be further studied.Using data envelopment analysis(DEA)to calculate the absolute economic efficiency of tourism poverty alleviation in the Three Gorges reservoir area from 2011 to 2016,and combining absolute economic efficiency with the Manquist index to calculate the poverty alleviation efficiency of each district and county relative to the previous year.That is called the relative efficiency.Taking the median value of absolute efficiency and the relative efficiency as a two-dimensional index,all districts and counties are classified according to data performance,which are potential districts,development districts,mature districts,and recession districts.According to the characteristics of the four classifications,the corresponding development mode is proposed.Finally,the ARCGIS software is used to visualize the data performance of each district and county.The study found that: potential districts and counties should adopt the industrial borrowing development model,development districts and counties should adopt the tourism industry strategic alliance development model,mature districts and counties should adopt the government-enterprise cooperation model,and recession districts and counties should adopt the point-support model.From the perspective of pure output efficiency or input-output efficiency,the efficiency of tourism poverty alleviation in the Three Gorges reservoir area will be graded,and there will be three tourism development highlands in Chongqing main city,Wanzhou district and Yiling district.The overall tourism poverty alleviation efficiency has developed rapidly with the passage of time.By comparing the distribution pattern of comprehensive tourism efficiency in the reservoir area in 2011,2014 and 2016,it is found that the spatial distribution pattern is based on the tourism group of Chongqing main city,Wanzhou district and Yiling district.The development trend is low in the middle and continues to be stable.The study further establishes a spatial econometric regression model for tourism development in the reservoir area,and measures the impact mechanism of per capita GDP,tourism number,comprehensive tourism revenue,proportion of tertiary industry service sector,and fiscal expenditure on tourism poverty alleviation efficiency.The results show that per capita GDP,tertiary industry share,and fiscal expenditure have a positive impact on tourism poverty alleviation efficiency.Among them,per capita GDP has the greatest impact,tourism comprehensive income,and tourism population have a negative impact on tourism poverty alleviation efficiency.The reason is that although the tourism development in the reservoir area has obtained some foundations,the problems of the tourism products and service brands exposed by the overall industry are not strong,the high value-added industries are few,the regional cooperation needs to be strengthened,and the poverty alleviation orientation is not clear enough.In order to change the situation,deepen the potential of regional resources,increase marketing efforts,actively guide community participation,and make full use of national policies to carry out cross-regional cooperation will be the focus of tourism development in the current and future reservoir areas.
Keywords/Search Tags:Three Gorges reservoir area, tourism poverty alleviation efficiency, data envelopment analysis, ARCGIS, spatial regression model
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