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題名:觀光文獻發展軌跡與台灣觀光產業之探討
作者:李靜貞
作者(外文):Ching-Chen Lee
校院名稱:元智大學
系所名稱:管理學院博士班
指導教授:盧煜煬
學位類別:博士
出版日期:2017
主題關鍵詞:觀光需求預測觀光目的地選擇永續觀光發展主路徑分析集群分析tourism demand forecastingtourism destination choicesustainable tourism developmentmain path analysisedge-betweenness clustering
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本研究首先以Scopus資料庫中1953年到2014年之11,063篇觀光相關論文為範疇,運用主路徑分析與edge-betweenness clustering方法,探討其知識發展軌跡與研究主題。主路徑分析乃利用文獻引用網絡關係產生之龐大引證網路,找出主要知識擴散路徑以及關鍵學術文獻。Edge-betweenness clustering方法則將引證網絡分門別類,以發掘主要研究議題。本研究共找出六大研究主題,包含觀光目的地選擇、永續觀光發展、遺產觀光的真實性、觀光需求預測、觀光對氣候變遷影響及醫療觀光。其中觀光需求預測研究主題與台灣觀光發展最有關連,接著進一步以來台觀光前五大來源國家或地區(中國大陸、香港澳門、日本、韓國及美國)為研究對象,探討影響來台觀光人數關鍵之預測變數。最後,依據所得之預測模型預估未來五大來源國家或地區來台觀光人數。
This study retrieves 11,063 tourism relevant articles from Scopus database and applies main path analysis and edge-betweenness clustering technique to identifying the knowledge development trajectory and the major research themes in tourism. The time span of data ranges from 1953 to 2014. A citation network of the relevant articles is built and then two methods are applied on the network. First, the main path analysis is used to identify the knowledge diffusion path and the important articles. Second, the edge-betweenness clustering technique is applied to grouping and finding the major research themes. Six research themes are identified: tourism destination choice, sustainable tourism development, authenticity of heritage tourism, tourism demand forecasting, the impact of tourism on climate change, and medical tourism. Among them, tourism demand forecasting is the most relevant to Taiwan’s tourism development. This study uses the major inbound tourists from Mainland china , Hong Kong and Macaw, Japan, Korea and United States to build the tourism demand forecasting model. Final, the forecasting model is applied to estimate future inbound tourists from five main countries or regions in Taiwan.
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