運用自動內容分析技術探析觀光與旅遊領域研究主題與趨勢

Applying Automatic Content Analysis to Identify Research Themes and Trends in the Tourism and Travel Fields

原友蘭(Yulan Yuan) ； 曾元顯(Yuen-Hsien Tseng) ； 何昶鴛(Chaang-Iuan Ho)

《戶外遊憩研究》 32卷1期 (2019/03) Pp. 1-32

https://doi.org/10.6130/JORS.201903_32(1).0001

摘要

研究的基礎立基於掌握研究議題與趨勢。承此，本文使用自動內容分析工具（CATAR），以書目對分析法，多階層主題凝聚（Clustering）技術，分析16本觀光與旅遊領域期刊之文章，目的在瞭解1997到2016年間之研究主題與各主題發展趨勢。研究結果顯示20年間所發表的6867篇研究文獻，可歸納為七大主題；依序為觀光客、在地人與地方，生態旅遊與永續發展，觀光產業結構與市場剖析，目的地經營管理，觀光經濟與政策，組織效能與公民參與，分享經濟與科技應用。從主題發表量的變化可見研究主題的變化，以及研究主題裂解出更多的分枝。值得注意的是「觀光客、在地人與地方的關係與互動」持續吸引學者們的投入。研究結果亦顯示觀光與旅遊領域知識的創新與建構受到少數關鍵文獻的影響。

關鍵字

書目對分析法 ； 文字探勘 ； 觀光與旅遊研究趨勢

並列摘要

This paper analyzes tourism research trends based on more than 6000 papers from 16 journals between 1997 and 2016 using bibliographic coupling and citation methods. Unlike previous studies based on expert opinion and manual calculations, this study adopts a content mining tool to process a large volume of data so as to obtain relatively objective research topics and their trends. The result provides an overview of the research during the past 20 years for further study or for teaching reference. This study shows that the research topics become diversified as the world changes. New topics emerge with the advent of new technology and novel management in society. Mobile technology and the rise of the co-sharing economy are the two salient examples. In the future, climate change, artificial intelligence, unmanned vehicles, and big data will attract significant attention and become the major research topics in tourism. It is worth noting that Topic 1, Tourists, Locals, and Places, accounts for 90.6% and has continuously drawn scholars' attention over the past 20 years. The shifts in research focus suggest that the interests of tourism scholars change along with contemporary events, such as technology development, new business models, international incidents, or environmental changes, all of which have an influence on research trends. The analytical result also revealed the creation of tourism knowledge derived from a few groups of key articles.

並列關鍵字

Bibliographic coupling analysis ； Text mining ； Tourism and travel research trend

參考文獻

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